Links to Exploration step
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Discovery and comparative profiling of microRNAs in a sweet orange red-flesh mutant and its wild type</title><author><name sortKey="Xu, Qiang" sort="Xu, Qiang" uniqKey="Xu Q" first="Qiang" last="Xu">Qiang Xu</name><affiliation><nlm:aff id="I1">Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Liu, Yuanlong" sort="Liu, Yuanlong" uniqKey="Liu Y" first="Yuanlong" last="Liu">Yuanlong Liu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Zhu, Andan" sort="Zhu, Andan" uniqKey="Zhu A" first="Andan" last="Zhu">Andan Zhu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Wu, Xiaomeng" sort="Wu, Xiaomeng" uniqKey="Wu X" first="Xiaomeng" last="Wu">Xiaomeng Wu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Ye, Junli" sort="Ye, Junli" uniqKey="Ye J" first="Junli" last="Ye">Junli Ye</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Yu, Keqin" sort="Yu, Keqin" uniqKey="Yu K" first="Keqin" last="Yu">Keqin Yu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Guo, Wenwu" sort="Guo, Wenwu" uniqKey="Guo W" first="Wenwu" last="Guo">Wenwu Guo</name><affiliation><nlm:aff id="I1">Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Deng, Xiuxin" sort="Deng, Xiuxin" uniqKey="Deng X" first="Xiuxin" last="Deng">Xiuxin Deng</name><affiliation><nlm:aff id="I1">Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">20398412</idno><idno type="pmc">2864249</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2864249</idno><idno type="RBID">PMC:2864249</idno><idno type="doi">10.1186/1471-2164-11-246</idno><date when="2010">2010</date><idno type="wicri:Area/Pmc/Corpus">000E12</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Discovery and comparative profiling of microRNAs in a sweet orange red-flesh mutant and its wild type</title><author><name sortKey="Xu, Qiang" sort="Xu, Qiang" uniqKey="Xu Q" first="Qiang" last="Xu">Qiang Xu</name><affiliation><nlm:aff id="I1">Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Liu, Yuanlong" sort="Liu, Yuanlong" uniqKey="Liu Y" first="Yuanlong" last="Liu">Yuanlong Liu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Zhu, Andan" sort="Zhu, Andan" uniqKey="Zhu A" first="Andan" last="Zhu">Andan Zhu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Wu, Xiaomeng" sort="Wu, Xiaomeng" uniqKey="Wu X" first="Xiaomeng" last="Wu">Xiaomeng Wu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Ye, Junli" sort="Ye, Junli" uniqKey="Ye J" first="Junli" last="Ye">Junli Ye</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Yu, Keqin" sort="Yu, Keqin" uniqKey="Yu K" first="Keqin" last="Yu">Keqin Yu</name><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Guo, Wenwu" sort="Guo, Wenwu" uniqKey="Guo W" first="Wenwu" last="Guo">Wenwu Guo</name><affiliation><nlm:aff id="I1">Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author><author><name sortKey="Deng, Xiuxin" sort="Deng, Xiuxin" uniqKey="Deng X" first="Xiuxin" last="Deng">Xiuxin Deng</name><affiliation><nlm:aff id="I1">Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</nlm:aff></affiliation></author></analytic><series><title level="j">BMC Genomics</title><idno type="eISSN">1471-2164</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Red-flesh fruit is absent from common sweet orange varieties, but is more preferred by consumers due to its visual attraction and nutritional properties. Our previous researches on a spontaneous red-flesh mutant revealed that the trait is caused by lycopene accumulation and is regulated by both transcriptional and post-transcriptional mechanisms. However, the knowledge on post-transcriptional regulation of lycopene accumulation in fruits is rather limited so far.</p></sec><sec><title>Results</title><p>We used Illumina sequencing method to identify and quantitatively profile small RNAs on the red-flesh sweet orange mutant and its wild type. We identified 85 known miRNAs belonging to 48 families from sweet orange. Comparative profiling revealed that 51 known miRNAs exhibited significant expression differences between mutant (MT) and wild type (WT). We also identified 12 novel miRNAs by the presence of mature miRNAs and corresponding miRNA*s in the sRNA libraries. Comparative analysis showed that 9 novel miRNAs are differentially expressed between WT and MT. Target predictions of the 60 differential miRNAs resulted 418 target genes in sweet orange. GO and KEGG annotation revealed that high ranked miRNA-target genes are those implicated in transcription regulation, protein modification and photosynthesis. The expression profiles of target genes involved in carotenogenesis and photosynthesis were further confirmed to be complementary to the profiles of corresponding miRNAs in WT and MT.</p></sec><sec><title>Conclusion</title><p>This study comparatively characterized the miRNAomes between the red-flesh mutant and the wild type, the results lay a foundation for unraveling the miRNA-mediated molecular processes that regulate lycopene accumulation in the sweet orange red-flesh mutant.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Spiegel Roy, P" uniqKey="Spiegel Roy P">P Spiegel-Roy</name></author><author><name sortKey="Goldschmidt, Ee" uniqKey="Goldschmidt E">EE Goldschmidt</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Jayaprakasha, Gk" uniqKey="Jayaprakasha G">GK Jayaprakasha</name></author><author><name sortKey="Patil, Bs" uniqKey="Patil B">BS Patil</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bartley, Ge" uniqKey="Bartley G">GE Bartley</name></author><author><name sortKey="Scolnik, Pa" uniqKey="Scolnik P">PA Scolnik</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rouseff, R" uniqKey="Rouseff R">R Rouseff</name></author><author><name sortKey="Raley, L" uniqKey="Raley L">L Raley</name></author><author><name sortKey="Hofsommer, Hj" uniqKey="Hofsommer H">HJ Hofsommer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lee, Hs" uniqKey="Lee H">HS Lee</name></author><author><name sortKey="Castle, Ws" uniqKey="Castle W">WS Castle</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Xu, Cj" uniqKey="Xu C">CJ Xu</name></author><author><name sortKey="Fraser, Pd" uniqKey="Fraser P">PD Fraser</name></author><author><name sortKey="Wang, Wj" uniqKey="Wang W">WJ Wang</name></author><author><name sortKey="Bramley, Pm" uniqKey="Bramley P">PM Bramley</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kato, M" uniqKey="Kato M">M Kato</name></author><author><name sortKey="Ikoma, Y" uniqKey="Ikoma Y">Y Ikoma</name></author><author><name sortKey="Matsumoto, H" uniqKey="Matsumoto H">H Matsumoto</name></author><author><name sortKey="Sugiura, M" uniqKey="Sugiura M">M Sugiura</name></author><author><name sortKey="Hyodo, H" uniqKey="Hyodo H">H Hyodo</name></author><author><name sortKey="Yano, M" uniqKey="Yano M">M Yano</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Schwarz, S" uniqKey="Schwarz S">S Schwarz</name></author><author><name sortKey="Obermuller Jevic, Uc" uniqKey="Obermuller Jevic U">UC Obermuller-Jevic</name></author><author><name sortKey="Hellmis, E" uniqKey="Hellmis E">E Hellmis</name></author><author><name sortKey="Koch, W" uniqKey="Koch W">W Koch</name></author><author><name sortKey="Jacobi, G" uniqKey="Jacobi G">G Jacobi</name></author><author><name sortKey="Biesalski, Hk" uniqKey="Biesalski H">HK Biesalski</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Monselise, Sp" uniqKey="Monselise S">SP Monselise</name></author><author><name sortKey="Halevy, Ah" uniqKey="Halevy A">AH Halevy</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Saunt, J" uniqKey="Saunt J">J Saunt</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Liu, Q" uniqKey="Liu Q">Q Liu</name></author><author><name sortKey="Xu, J" uniqKey="Xu J">J Xu</name></author><author><name sortKey="Liu, Yz" uniqKey="Liu Y">YZ Liu</name></author><author><name sortKey="Zhao, Xl" uniqKey="Zhao X">XL Zhao</name></author><author><name sortKey="Deng, Xx" uniqKey="Deng X">XX Deng</name></author><author><name sortKey="Guo, Ll" uniqKey="Guo L">LL Guo</name></author><author><name sortKey="Gu, Jq" uniqKey="Gu J">JQ Gu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Liu, Q" uniqKey="Liu Q">Q Liu</name></author><author><name sortKey="Zhu, A" uniqKey="Zhu A">A Zhu</name></author><author><name sortKey="Chai, Lj" uniqKey="Chai L">LJ Chai</name></author><author><name sortKey="Zhou, Wj" uniqKey="Zhou W">WJ Zhou</name></author><author><name sortKey="Yu, Kq" uniqKey="Yu K">KQ Yu</name></author><author><name sortKey="Ding, J" uniqKey="Ding J">J Ding</name></author><author><name sortKey="Xu, J" uniqKey="Xu J">J Xu</name></author><author><name sortKey="Deng, Xx" uniqKey="Deng X">XX Deng</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Xu, Q" uniqKey="Xu Q">Q Xu</name></author><author><name sortKey="Yu, Kq" uniqKey="Yu K">KQ Yu</name></author><author><name sortKey="Zhu, Ad" uniqKey="Zhu A">AD Zhu</name></author><author><name sortKey="Ye, Jl" uniqKey="Ye J">JL Ye</name></author><author><name sortKey="Liu, Q" uniqKey="Liu Q">Q Liu</name></author><author><name sortKey="Zhang, Jc" uniqKey="Zhang J">JC Zhang</name></author><author><name sortKey="Deng, X" uniqKey="Deng X">X Deng</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pan, Zy" uniqKey="Pan Z">ZY Pan</name></author><author><name sortKey="Liu, Q" uniqKey="Liu Q">Q Liu</name></author><author><name sortKey="Yun, Z" uniqKey="Yun Z">Z Yun</name></author><author><name sortKey="Guan, R" uniqKey="Guan R">R Guan</name></author><author><name sortKey="Zeng, Wf" uniqKey="Zeng W">WF Zeng</name></author><author><name sortKey="Xu, Q" uniqKey="Xu Q">Q Xu</name></author><author><name sortKey="Deng, Xx" uniqKey="Deng X">XX Deng</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Welsch, R" uniqKey="Welsch R">R Welsch</name></author><author><name sortKey="Maass, D" uniqKey="Maass D">D Maass</name></author><author><name sortKey="Voegel, T" uniqKey="Voegel T">T Voegel</name></author><author><name sortKey="Dellapenna, D" uniqKey="Dellapenna D">D Dellapenna</name></author><author><name sortKey="Beyer, P" uniqKey="Beyer P">P Beyer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Vaucheret, H" uniqKey="Vaucheret H">H Vaucheret</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Jones Rhoades, Mw" uniqKey="Jones Rhoades M">MW Jones-Rhoades</name></author><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sunkar, R" uniqKey="Sunkar R">R Sunkar</name></author><author><name sortKey="Zhu, Jk" uniqKey="Zhu J">JK Zhu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lu, S" uniqKey="Lu S">S Lu</name></author><author><name sortKey="Sun, Yh" uniqKey="Sun Y">YH Sun</name></author><author><name sortKey="Shi, R" uniqKey="Shi R">R Shi</name></author><author><name sortKey="Clark, C" uniqKey="Clark C">C Clark</name></author><author><name sortKey="Li, L" uniqKey="Li L">L Li</name></author><author><name sortKey="Chiang, Vl" uniqKey="Chiang V">VL Chiang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Mallory, Ac" uniqKey="Mallory A">AC Mallory</name></author><author><name sortKey="Vaucheret, H" uniqKey="Vaucheret H">H Vaucheret</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Aung, K" uniqKey="Aung K">K Aung</name></author><author><name sortKey="Lin, Si" uniqKey="Lin S">SI Lin</name></author><author><name sortKey="Wu, Cc" uniqKey="Wu C">CC Wu</name></author><author><name sortKey="Huang, Yt" uniqKey="Huang Y">YT Huang</name></author><author><name sortKey="Su, Cl" uniqKey="Su C">CL Su</name></author><author><name sortKey="Chiou, Tj" uniqKey="Chiou T">TJ Chiou</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Moxon, S" uniqKey="Moxon S">S Moxon</name></author><author><name sortKey="Jing, R" uniqKey="Jing R">R Jing</name></author><author><name sortKey="Szittya, G" uniqKey="Szittya G">G Szittya</name></author><author><name sortKey="Schwach, F" uniqKey="Schwach F">F Schwach</name></author><author><name sortKey="Rusholme Pilcher, Rl" uniqKey="Rusholme Pilcher R">RL Rusholme Pilcher</name></author><author><name sortKey="Moulton, V" uniqKey="Moulton V">V Moulton</name></author><author><name sortKey="Dalmay, T" uniqKey="Dalmay T">T Dalmay</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pant, Bd" uniqKey="Pant B">BD Pant</name></author><author><name sortKey="Musialak Lange, M" uniqKey="Musialak Lange M">M Musialak-Lange</name></author><author><name sortKey="Nuc, P" uniqKey="Nuc P">P Nuc</name></author><author><name sortKey="May, P" uniqKey="May P">P May</name></author><author><name sortKey="Buhtz, A" uniqKey="Buhtz A">A Buhtz</name></author><author><name sortKey="Kehr, J" uniqKey="Kehr J">J Kehr</name></author><author><name sortKey="Walther, D" uniqKey="Walther D">D Walther</name></author><author><name sortKey="Scheible, Wr" uniqKey="Scheible W">WR Scheible</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ramachandran, V" uniqKey="Ramachandran V">V Ramachandran</name></author><author><name sortKey="Chen, X" uniqKey="Chen X">X Chen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Llave, C" uniqKey="Llave C">C Llave</name></author><author><name sortKey="Kasschau, Kd" uniqKey="Kasschau K">KD Kasschau</name></author><author><name sortKey="Rector, Ma" uniqKey="Rector M">MA Rector</name></author><author><name sortKey="Carrington, Jc" uniqKey="Carrington J">JC Carrington</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lindow, M" uniqKey="Lindow M">M Lindow</name></author><author><name sortKey="Krogh, A" uniqKey="Krogh A">A Krogh</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rajagopalan, R" uniqKey="Rajagopalan R">R Rajagopalan</name></author><author><name sortKey="Vaucheret, H" uniqKey="Vaucheret H">H Vaucheret</name></author><author><name sortKey="Trejo, J" uniqKey="Trejo J">J Trejo</name></author><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Jones Rhoades, Mw" uniqKey="Jones Rhoades M">MW Jones-Rhoades</name></author><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author><author><name sortKey="Bartel, B" uniqKey="Bartel B">B Bartel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wang, Jf" uniqKey="Wang J">JF Wang</name></author><author><name sortKey="Zhou, H" uniqKey="Zhou H">H Zhou</name></author><author><name sortKey="Chen, Yq" uniqKey="Chen Y">YQ Chen</name></author><author><name sortKey="Luo, Qj" uniqKey="Luo Q">QJ Luo</name></author><author><name sortKey="Qu, Lh" uniqKey="Qu L">LH Qu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sunkar, R" uniqKey="Sunkar R">R Sunkar</name></author><author><name sortKey="Girke, T" uniqKey="Girke T">T Girke</name></author><author><name sortKey="Jain, Pk" uniqKey="Jain P">PK Jain</name></author><author><name sortKey="Zhu, Jk" uniqKey="Zhu J">JK Zhu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bonnet, E" uniqKey="Bonnet E">E Bonnet</name></author><author><name sortKey="Wuyts, J" uniqKey="Wuyts J">J Wuyts</name></author><author><name sortKey="Rouze, P" uniqKey="Rouze P">P Rouze</name></author><author><name sortKey="Peer, Y Van De" uniqKey="Peer Y">Y Van de Peer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Adai, A" uniqKey="Adai A">A Adai</name></author><author><name sortKey="Johnson, C" uniqKey="Johnson C">C Johnson</name></author><author><name sortKey="Mlotshwa, S" uniqKey="Mlotshwa S">S Mlotshwa</name></author><author><name sortKey="Archer Evans, S" uniqKey="Archer Evans S">S Archer-Evans</name></author><author><name sortKey="Manocha, V" uniqKey="Manocha V">V Manocha</name></author><author><name sortKey="Vance, V" uniqKey="Vance V">V Vance</name></author><author><name sortKey="Sundaresan, V" uniqKey="Sundaresan V">V Sundaresan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zhang, Bh" uniqKey="Zhang B">BH Zhang</name></author><author><name sortKey="Pan, Xp" uniqKey="Pan X">XP Pan</name></author><author><name sortKey="Wang, Ql" uniqKey="Wang Q">QL Wang</name></author><author><name sortKey="Cobb, Gp" uniqKey="Cobb G">GP Cobb</name></author><author><name sortKey="Anderson, Ta" uniqKey="Anderson T">TA Anderson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gleave, Ap" uniqKey="Gleave A">AP Gleave</name></author><author><name sortKey="Ampomah Dwamena, C" uniqKey="Ampomah Dwamena C">C Ampomah-Dwamena</name></author><author><name sortKey="Berthold, S" uniqKey="Berthold S">S Berthold</name></author><author><name sortKey="Dejnoprat, S" uniqKey="Dejnoprat S">S Dejnoprat</name></author><author><name sortKey="Karunairetnam, S" uniqKey="Karunairetnam S">S Karunairetnam</name></author><author><name sortKey="Nain, B" uniqKey="Nain B">B Nain</name></author><author><name sortKey="Wang, Y Y" uniqKey="Wang Y">Y-Y Wang</name></author><author><name sortKey="Crowhurst, Rn" uniqKey="Crowhurst R">RN Crowhurst</name></author><author><name sortKey="Macdiarmid, Rm" uniqKey="Macdiarmid R">RM MacDiarmid</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Song, C" uniqKey="Song C">C Song</name></author><author><name sortKey="Fang, J" uniqKey="Fang J">J Fang</name></author><author><name sortKey="Li, X" uniqKey="Li X">X Li</name></author><author><name sortKey="Liu, H" uniqKey="Liu H">H Liu</name></author><author><name sortKey="Thomas Chao, C" uniqKey="Thomas Chao C">C Thomas Chao</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Morin, Rd" uniqKey="Morin R">RD Morin</name></author><author><name sortKey="Aksay, G" uniqKey="Aksay G">G Aksay</name></author><author><name sortKey="Dolgosheina, E" uniqKey="Dolgosheina E">E Dolgosheina</name></author><author><name sortKey="Ebhardt, Ha" uniqKey="Ebhardt H">HA Ebhardt</name></author><author><name sortKey="Magrini, V" uniqKey="Magrini V">V Magrini</name></author><author><name sortKey="Mardis, Er" uniqKey="Mardis E">ER Mardis</name></author><author><name sortKey="Sahinalp, Sc" uniqKey="Sahinalp S">SC Sahinalp</name></author><author><name sortKey="Unrau, Pj" uniqKey="Unrau P">PJ Unrau</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lu, C" uniqKey="Lu C">C Lu</name></author><author><name sortKey="Tej, Ss" uniqKey="Tej S">SS Tej</name></author><author><name sortKey="Luo, S" uniqKey="Luo S">S Luo</name></author><author><name sortKey="Haudenschild, Cd" uniqKey="Haudenschild C">CD Haudenschild</name></author><author><name sortKey="Meyers, Bc" uniqKey="Meyers B">BC Meyers</name></author><author><name sortKey="Green, Pj" uniqKey="Green P">PJ Green</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lu, C" uniqKey="Lu C">C Lu</name></author><author><name sortKey="Kulkarni, K" uniqKey="Kulkarni K">K Kulkarni</name></author><author><name sortKey="Souret, Ff" uniqKey="Souret F">FF Souret</name></author><author><name sortKey="Muthuvalliappan, R" uniqKey="Muthuvalliappan R">R MuthuValliappan</name></author><author><name sortKey="Tej, Ss" uniqKey="Tej S">SS Tej</name></author><author><name sortKey="Poethig, Rs" uniqKey="Poethig R">RS Poethig</name></author><author><name sortKey="Henderson, Ir" uniqKey="Henderson I">IR Henderson</name></author><author><name sortKey="Jacobsen, Se" uniqKey="Jacobsen S">SE Jacobsen</name></author><author><name sortKey="Wang, W" uniqKey="Wang W">W Wang</name></author><author><name sortKey="Green, Pj" uniqKey="Green P">PJ Green</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fahlgren, N" uniqKey="Fahlgren N">N Fahlgren</name></author><author><name sortKey="Howell, Md" uniqKey="Howell M">MD Howell</name></author><author><name sortKey="Kasschau, Kd" uniqKey="Kasschau K">KD Kasschau</name></author><author><name sortKey="Chapman, Ej" uniqKey="Chapman E">EJ Chapman</name></author><author><name sortKey="Sullivan, Cm" uniqKey="Sullivan C">CM Sullivan</name></author><author><name sortKey="Cumbie, Js" uniqKey="Cumbie J">JS Cumbie</name></author><author><name sortKey="Givan, Sa" uniqKey="Givan S">SA Givan</name></author><author><name sortKey="Law, Tf" uniqKey="Law T">TF Law</name></author><author><name sortKey="Grant, Sr" uniqKey="Grant S">SR Grant</name></author><author><name sortKey="Dangl, Jl" uniqKey="Dangl J">JL Dangl</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Nobuta, K" uniqKey="Nobuta K">K Nobuta</name></author><author><name sortKey="Venu, Rc" uniqKey="Venu R">RC Venu</name></author><author><name sortKey="Lu, C" uniqKey="Lu C">C Lu</name></author><author><name sortKey="Belo, A" uniqKey="Belo A">A Belo</name></author><author><name sortKey="Vemaraju, K" uniqKey="Vemaraju K">K Vemaraju</name></author><author><name sortKey="Kulkarni, K" uniqKey="Kulkarni K">K Kulkarni</name></author><author><name sortKey="Wang, W" uniqKey="Wang W">W Wang</name></author><author><name sortKey="Pillay, M" uniqKey="Pillay M">M Pillay</name></author><author><name sortKey="Green, Pj" uniqKey="Green P">PJ Green</name></author><author><name sortKey="Wang, Gl" uniqKey="Wang G">GL Wang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lu, C" uniqKey="Lu C">C Lu</name></author><author><name sortKey="Jeong, Dh" uniqKey="Jeong D">DH Jeong</name></author><author><name sortKey="Kulkarni, K" uniqKey="Kulkarni K">K Kulkarni</name></author><author><name sortKey="Pillay, M" uniqKey="Pillay M">M Pillay</name></author><author><name sortKey="Nobuta, K" uniqKey="Nobuta K">K Nobuta</name></author><author><name sortKey="German, R" uniqKey="German R">R German</name></author><author><name sortKey="Thatcher, Sr" uniqKey="Thatcher S">SR Thatcher</name></author><author><name sortKey="Maher, C" uniqKey="Maher C">C Maher</name></author><author><name sortKey="Zhang, L" uniqKey="Zhang L">L Zhang</name></author><author><name sortKey="Ware, D" uniqKey="Ware D">D Ware</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sunkar, R" uniqKey="Sunkar R">R Sunkar</name></author><author><name sortKey="Zhou, X" uniqKey="Zhou X">X Zhou</name></author><author><name sortKey="Zheng, Y" uniqKey="Zheng Y">Y Zheng</name></author><author><name sortKey="Zhang, W" uniqKey="Zhang W">W Zhang</name></author><author><name sortKey="Zhu, Jk" uniqKey="Zhu J">JK Zhu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Xue, Lj" uniqKey="Xue L">LJ Xue</name></author><author><name sortKey="Zhang, Jj" uniqKey="Zhang J">JJ Zhang</name></author><author><name sortKey="Xue, Hw" uniqKey="Xue H">HW Xue</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Axtell, Mj" uniqKey="Axtell M">MJ Axtell</name></author><author><name sortKey="Snyder, Ja" uniqKey="Snyder J">JA Snyder</name></author><author><name sortKey="Bartell, Dp" uniqKey="Bartell D">DP Bartell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Barakat, A" uniqKey="Barakat A">A Barakat</name></author><author><name sortKey="Wall, K" uniqKey="Wall K">K Wall</name></author><author><name sortKey="Leebens Mack, J" uniqKey="Leebens Mack J">J Leebens-Mack</name></author><author><name sortKey="Wang, Yj" uniqKey="Wang Y">YJ Wang</name></author><author><name sortKey="Carlson, Je" uniqKey="Carlson J">JE Carlson</name></author><author><name sortKey="Depamphilis, Cw" uniqKey="Depamphilis C">CW dePamphilis</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Barakat, A" uniqKey="Barakat A">A Barakat</name></author><author><name sortKey="Wall, Pk" uniqKey="Wall P">PK Wall</name></author><author><name sortKey="Diloreto, S" uniqKey="Diloreto S">S Diloreto</name></author><author><name sortKey="Depamphilis, Cw" uniqKey="Depamphilis C">CW Depamphilis</name></author><author><name sortKey="Carlson, Je" uniqKey="Carlson J">JE Carlson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Molnar, A" uniqKey="Molnar A">A Molnar</name></author><author><name sortKey="Schwach, F" uniqKey="Schwach F">F Schwach</name></author><author><name sortKey="Studholme, Dj" uniqKey="Studholme D">DJ Studholme</name></author><author><name sortKey="Thuenemann, Ec" uniqKey="Thuenemann E">EC Thuenemann</name></author><author><name sortKey="Baulcombe, Dc" uniqKey="Baulcombe D">DC Baulcombe</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yao, Y" uniqKey="Yao Y">Y Yao</name></author><author><name sortKey="Guo, G" uniqKey="Guo G">G Guo</name></author><author><name sortKey="Ni, Z" uniqKey="Ni Z">Z Ni</name></author><author><name sortKey="Sunkar, R" uniqKey="Sunkar R">R Sunkar</name></author><author><name sortKey="Du, J" uniqKey="Du J">J Du</name></author><author><name sortKey="Zhu, Jk" uniqKey="Zhu J">JK Zhu</name></author><author><name sortKey="Sun, Q" uniqKey="Sun Q">Q Sun</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Qiu, D" uniqKey="Qiu D">D Qiu</name></author><author><name sortKey="Pan, X" uniqKey="Pan X">X Pan</name></author><author><name sortKey="Wilson, Iw" uniqKey="Wilson I">IW Wilson</name></author><author><name sortKey="Li, F" uniqKey="Li F">F Li</name></author><author><name sortKey="Liu, M" uniqKey="Liu M">M Liu</name></author><author><name sortKey="Teng, W" uniqKey="Teng W">W Teng</name></author><author><name sortKey="Zhang, B" uniqKey="Zhang B">B Zhang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Meyers, Bc" uniqKey="Meyers B">BC Meyers</name></author><author><name sortKey="Axtell, Mj" uniqKey="Axtell M">MJ Axtell</name></author><author><name sortKey="Bartel, B" uniqKey="Bartel B">B Bartel</name></author><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author><author><name sortKey="Baulcombe, D" uniqKey="Baulcombe D">D Baulcombe</name></author><author><name sortKey="Bowman, Jl" uniqKey="Bowman J">JL Bowman</name></author><author><name sortKey="Cao, X" uniqKey="Cao X">X Cao</name></author><author><name sortKey="Carrington, Jc" uniqKey="Carrington J">JC Carrington</name></author><author><name sortKey="Chen, X" uniqKey="Chen X">X Chen</name></author><author><name sortKey="Green, Pj" uniqKey="Green P">PJ Green</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ambros, V" uniqKey="Ambros V">V Ambros</name></author><author><name sortKey="Bartel, B" uniqKey="Bartel B">B Bartel</name></author><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author><author><name sortKey="Burge, Cb" uniqKey="Burge C">CB Burge</name></author><author><name sortKey="Carrington, Jc" uniqKey="Carrington J">JC Carrington</name></author><author><name sortKey="Chen, Xm" uniqKey="Chen X">XM Chen</name></author><author><name sortKey="Dreyfuss, G" uniqKey="Dreyfuss G">G Dreyfuss</name></author><author><name sortKey="Eddy, Sr" uniqKey="Eddy S">SR Eddy</name></author><author><name sortKey="Griffiths Jones, S" uniqKey="Griffiths Jones S">S Griffiths-Jones</name></author><author><name sortKey="Marshall, M" uniqKey="Marshall M">M Marshall</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chen, C" uniqKey="Chen C">C Chen</name></author><author><name sortKey="Ridzon, Da" uniqKey="Ridzon D">DA Ridzon</name></author><author><name sortKey="Broomer, Aj" uniqKey="Broomer A">AJ Broomer</name></author><author><name sortKey="Zhou, Z" uniqKey="Zhou Z">Z Zhou</name></author><author><name sortKey="Lee, Dh" uniqKey="Lee D">DH Lee</name></author><author><name sortKey="Nguyen, Jt" uniqKey="Nguyen J">JT Nguyen</name></author><author><name sortKey="Barbisin, M" uniqKey="Barbisin M">M Barbisin</name></author><author><name sortKey="Xu, Nl" uniqKey="Xu N">NL Xu</name></author><author><name sortKey="Mahuvakar, Vr" uniqKey="Mahuvakar V">VR Mahuvakar</name></author><author><name sortKey="Andersen, Mr" uniqKey="Andersen M">MR Andersen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Varkonyi Gasic, E" uniqKey="Varkonyi Gasic E">E Varkonyi-Gasic</name></author><author><name sortKey="Wu, R" uniqKey="Wu R">R Wu</name></author><author><name sortKey="Wood, M" uniqKey="Wood M">M Wood</name></author><author><name sortKey="Walton, Ef" uniqKey="Walton E">EF Walton</name></author><author><name sortKey="Hellens, Rp" uniqKey="Hellens R">RP Hellens</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Feng, J" uniqKey="Feng J">J Feng</name></author><author><name sortKey="Wang, K" uniqKey="Wang K">K Wang</name></author><author><name sortKey="Liu, X" uniqKey="Liu X">X Liu</name></author><author><name sortKey="Chen, S" uniqKey="Chen S">S Chen</name></author><author><name sortKey="Chen, J" uniqKey="Chen J">J Chen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zhang, Y" uniqKey="Zhang Y">Y Zhang</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ossowski, S" uniqKey="Ossowski S">S Ossowski</name></author><author><name sortKey="Schwab, R" uniqKey="Schwab R">R Schwab</name></author><author><name sortKey="Weigel, D" uniqKey="Weigel D">D Weigel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Moxon, S" uniqKey="Moxon S">S Moxon</name></author><author><name sortKey="Schwach, F" uniqKey="Schwach F">F Schwach</name></author><author><name sortKey="Dalmay, T" uniqKey="Dalmay T">T Dalmay</name></author><author><name sortKey="Maclean, D" uniqKey="Maclean D">D Maclean</name></author><author><name sortKey="Studholme, Dj" uniqKey="Studholme D">DJ Studholme</name></author><author><name sortKey="Moulton, V" uniqKey="Moulton V">V Moulton</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zuker, M" uniqKey="Zuker M">M Zuker</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Carra, A" uniqKey="Carra A">A Carra</name></author><author><name sortKey="Mica, E" uniqKey="Mica E">E Mica</name></author><author><name sortKey="Gambino, G" uniqKey="Gambino G">G Gambino</name></author><author><name sortKey="Pindo, M" uniqKey="Pindo M">M Pindo</name></author><author><name sortKey="Moser, C" uniqKey="Moser C">C Moser</name></author><author><name sortKey="Pe, Me" uniqKey="Pe M">ME Pe</name></author><author><name sortKey="Schubert, A" uniqKey="Schubert A">A Schubert</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Arazi, T" uniqKey="Arazi T">T Arazi</name></author><author><name sortKey="Talmor Neiman, M" uniqKey="Talmor Neiman M">M Talmor-Neiman</name></author><author><name sortKey="Stav, R" uniqKey="Stav R">R Stav</name></author><author><name sortKey="Riese, M" uniqKey="Riese M">M Riese</name></author><author><name sortKey="Huijser, P" uniqKey="Huijser P">P Huijser</name></author><author><name sortKey="Baulcombe, Dc" uniqKey="Baulcombe D">DC Baulcombe</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Luo, Qj" uniqKey="Luo Q">QJ Luo</name></author><author><name sortKey="Samanta, Mp" uniqKey="Samanta M">MP Samanta</name></author><author><name sortKey="Koksal, F" uniqKey="Koksal F">F Koksal</name></author><author><name sortKey="Janda, J" uniqKey="Janda J">J Janda</name></author><author><name sortKey="Galbraith, Dw" uniqKey="Galbraith D">DW Galbraith</name></author><author><name sortKey="Richardson, Cr" uniqKey="Richardson C">CR Richardson</name></author><author><name sortKey="Ou Yang, F" uniqKey="Ou Yang F">F Ou-Yang</name></author><author><name sortKey="Rock, Cd" uniqKey="Rock C">CD Rock</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Morin, Rd" uniqKey="Morin R">RD Morin</name></author><author><name sortKey="O Connor, Md" uniqKey="O Connor M">MD O'Connor</name></author><author><name sortKey="Griffith, M" uniqKey="Griffith M">M Griffith</name></author><author><name sortKey="Kuchenbauer, F" uniqKey="Kuchenbauer F">F Kuchenbauer</name></author><author><name sortKey="Delaney, A" uniqKey="Delaney A">A Delaney</name></author><author><name sortKey="Prabhu, Al" uniqKey="Prabhu A">AL Prabhu</name></author><author><name sortKey="Zhao, Y" uniqKey="Zhao Y">Y Zhao</name></author><author><name sortKey="Mcdonald, H" uniqKey="Mcdonald H">H McDonald</name></author><author><name sortKey="Zeng, T" uniqKey="Zeng T">T Zeng</name></author><author><name sortKey="Hirst, M" uniqKey="Hirst M">M Hirst</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hobert, O" uniqKey="Hobert O">O Hobert</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Henderson, Ir" uniqKey="Henderson I">IR Henderson</name></author><author><name sortKey="Zhang, X" uniqKey="Zhang X">X Zhang</name></author><author><name sortKey="Lu, C" uniqKey="Lu C">C Lu</name></author><author><name sortKey="Johnson, L" uniqKey="Johnson L">L Johnson</name></author><author><name sortKey="Meyers, Bc" uniqKey="Meyers B">BC Meyers</name></author><author><name sortKey="Green, Pj" uniqKey="Green P">PJ Green</name></author><author><name sortKey="Jacobsen, Se" uniqKey="Jacobsen S">SE Jacobsen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zhang, B" uniqKey="Zhang B">B Zhang</name></author><author><name sortKey="Pan, X" uniqKey="Pan X">X Pan</name></author><author><name sortKey="Cannon, Ch" uniqKey="Cannon C">CH Cannon</name></author><author><name sortKey="Cobb, Gp" uniqKey="Cobb G">GP Cobb</name></author><author><name sortKey="Anderson, Ta" uniqKey="Anderson T">TA Anderson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sunkar, R" uniqKey="Sunkar R">R Sunkar</name></author><author><name sortKey="Jagadeeswaran, G" uniqKey="Jagadeeswaran G">G Jagadeeswaran</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Voinnet, O" uniqKey="Voinnet O">O Voinnet</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Axtell, Mj" uniqKey="Axtell M">MJ Axtell</name></author><author><name sortKey="Jan, C" uniqKey="Jan C">C Jan</name></author><author><name sortKey="Rajagopalan, R" uniqKey="Rajagopalan R">R Rajagopalan</name></author><author><name sortKey="Bartel, Dp" uniqKey="Bartel D">DP Bartel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ronemus, M" uniqKey="Ronemus M">M Ronemus</name></author><author><name sortKey="Vaughn, Mw" uniqKey="Vaughn M">MW Vaughn</name></author><author><name sortKey="Martienssen, Ra" uniqKey="Martienssen R">RA Martienssen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Allen, E" uniqKey="Allen E">E Allen</name></author><author><name sortKey="Xie, Zx" uniqKey="Xie Z">ZX Xie</name></author><author><name sortKey="Gustafson, Am" uniqKey="Gustafson A">AM Gustafson</name></author><author><name sortKey="Carrington, Jc" uniqKey="Carrington J">JC Carrington</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="He, Y" uniqKey="He Y">Y He</name></author><author><name sortKey="Vogelstein, B" uniqKey="Vogelstein B">B Vogelstein</name></author><author><name sortKey="Velculescu, Ve" uniqKey="Velculescu V">VE Velculescu</name></author><author><name sortKey="Papadopoulos, N" uniqKey="Papadopoulos N">N Papadopoulos</name></author><author><name sortKey="Kinzler, Kw" uniqKey="Kinzler K">KW Kinzler</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kolotilin, I" uniqKey="Kolotilin I">I Kolotilin</name></author><author><name sortKey="Koltai, H" uniqKey="Koltai H">H Koltai</name></author><author><name sortKey="Tadmor, Y" uniqKey="Tadmor Y">Y Tadmor</name></author><author><name sortKey="Bar Or, C" uniqKey="Bar Or C">C Bar-Or</name></author><author><name sortKey="Reuveni, M" uniqKey="Reuveni M">M Reuveni</name></author><author><name sortKey="Meir, A" uniqKey="Meir A">A Meir</name></author><author><name sortKey="Nahon, S" uniqKey="Nahon S">S Nahon</name></author><author><name sortKey="Shlomo, H" uniqKey="Shlomo H">H Shlomo</name></author><author><name sortKey="Chen, L" uniqKey="Chen L">L Chen</name></author><author><name sortKey="Levin, I" uniqKey="Levin I">I Levin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Liu, Y" uniqKey="Liu Y">Y Liu</name></author><author><name sortKey="Liu, Q" uniqKey="Liu Q">Q Liu</name></author><author><name sortKey="Tao, N" uniqKey="Tao N">N Tao</name></author><author><name sortKey="Deng, X" uniqKey="Deng X">X Deng</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Griffiths Jones, S" uniqKey="Griffiths Jones S">S Griffiths-Jones</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kal, Aj" uniqKey="Kal A">AJ Kal</name></author><author><name sortKey="Van Zonneveld, Aj" uniqKey="Van Zonneveld A">AJ van Zonneveld</name></author><author><name sortKey="Benes, V" uniqKey="Benes V">V Benes</name></author><author><name sortKey="Berg, M Van Den" uniqKey="Berg M">M van den Berg</name></author><author><name sortKey="Koerkamp, Mg" uniqKey="Koerkamp M">MG Koerkamp</name></author><author><name sortKey="Albermann, K" uniqKey="Albermann K">K Albermann</name></author><author><name sortKey="Strack, N" uniqKey="Strack N">N Strack</name></author><author><name sortKey="Ruijter, Jm" uniqKey="Ruijter J">JM Ruijter</name></author><author><name sortKey="Richter, A" uniqKey="Richter A">A Richter</name></author><author><name sortKey="Dujon, B" uniqKey="Dujon B">B Dujon</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Schmid, R" uniqKey="Schmid R">R Schmid</name></author><author><name sortKey="Blaxter, Ml" uniqKey="Blaxter M">ML Blaxter</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ashburner, M" uniqKey="Ashburner M">M Ashburner</name></author><author><name sortKey="Ball, Ca" uniqKey="Ball C">CA Ball</name></author><author><name sortKey="Blake, Ja" uniqKey="Blake J">JA Blake</name></author><author><name sortKey="Botstein, D" uniqKey="Botstein D">D Botstein</name></author><author><name sortKey="Butler, H" uniqKey="Butler H">H Butler</name></author><author><name sortKey="Cherry, Jm" uniqKey="Cherry J">JM Cherry</name></author><author><name sortKey="Davis, Ap" uniqKey="Davis A">AP Davis</name></author><author><name sortKey="Dolinski, K" uniqKey="Dolinski K">K Dolinski</name></author><author><name sortKey="Dwight, Ss" uniqKey="Dwight S">SS Dwight</name></author><author><name sortKey="Eppig, Jt" uniqKey="Eppig J">JT Eppig</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kanehisa, M" uniqKey="Kanehisa M">M Kanehisa</name></author><author><name sortKey="Goto, S" uniqKey="Goto S">S Goto</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Genomics</journal-id><journal-title-group><journal-title>BMC Genomics</journal-title></journal-title-group><issn pub-type="epub">1471-2164</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">20398412</article-id><article-id pub-id-type="pmc">2864249</article-id><article-id pub-id-type="publisher-id">1471-2164-11-246</article-id><article-id pub-id-type="doi">10.1186/1471-2164-11-246</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>Discovery and comparative profiling of microRNAs in a sweet orange red-flesh mutant and its wild type</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Xu</surname><given-names>Qiang</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><email>xuqiang@mail.hzau.edu.cn</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Liu</surname><given-names>Yuanlong</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>whitepig1989@163.com</email></contrib><contrib contrib-type="author" id="A3"><name><surname>Zhu</surname><given-names>Andan</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>anand233@webmail.hzau.edu.cn</email></contrib><contrib contrib-type="author" id="A4"><name><surname>Wu</surname><given-names>Xiaomeng</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>eam@webmail.hzau.edu.cn</email></contrib><contrib contrib-type="author" id="A5"><name><surname>Ye</surname><given-names>Junli</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>yejunli@webmail.hzau.edu.cn</email></contrib><contrib contrib-type="author" id="A6"><name><surname>Yu</surname><given-names>Keqin</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>yukeqin@webmail.hzau.edu.cn</email></contrib><contrib contrib-type="author" id="A7"><name><surname>Guo</surname><given-names>Wenwu</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><email>guoww@mail.hzau.edu.cn</email></contrib><contrib contrib-type="author" corresp="yes" id="A8"><name><surname>Deng</surname><given-names>Xiuxin</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><email>xxdeng@mail.hzau.edu.cn</email></contrib></contrib-group><aff id="I1"><label>1</label>Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China</aff><aff id="I2"><label>2</label>National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China</aff><pub-date pub-type="collection"><year>2010</year></pub-date><pub-date pub-type="epub"><day>17</day><month>4</month><year>2010</year></pub-date><volume>11</volume><fpage>246</fpage><lpage>246</lpage><history><date date-type="received"><day>10</day><month>11</month><year>2009</year></date><date date-type="accepted"><day>17</day><month>4</month><year>2010</year></date></history><permissions><copyright-statement>Copyright ©2010 Xu et al; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2010</copyright-year><copyright-holder>Xu et al; licensee BioMed Central Ltd.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0">http://creativecommons.org/licenses/by/2.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1471-2164/11/246"></self-uri><abstract><sec><title>Background</title><p>Red-flesh fruit is absent from common sweet orange varieties, but is more preferred by consumers due to its visual attraction and nutritional properties. Our previous researches on a spontaneous red-flesh mutant revealed that the trait is caused by lycopene accumulation and is regulated by both transcriptional and post-transcriptional mechanisms. However, the knowledge on post-transcriptional regulation of lycopene accumulation in fruits is rather limited so far.</p></sec><sec><title>Results</title><p>We used Illumina sequencing method to identify and quantitatively profile small RNAs on the red-flesh sweet orange mutant and its wild type. We identified 85 known miRNAs belonging to 48 families from sweet orange. Comparative profiling revealed that 51 known miRNAs exhibited significant expression differences between mutant (MT) and wild type (WT). We also identified 12 novel miRNAs by the presence of mature miRNAs and corresponding miRNA*s in the sRNA libraries. Comparative analysis showed that 9 novel miRNAs are differentially expressed between WT and MT. Target predictions of the 60 differential miRNAs resulted 418 target genes in sweet orange. GO and KEGG annotation revealed that high ranked miRNA-target genes are those implicated in transcription regulation, protein modification and photosynthesis. The expression profiles of target genes involved in carotenogenesis and photosynthesis were further confirmed to be complementary to the profiles of corresponding miRNAs in WT and MT.</p></sec><sec><title>Conclusion</title><p>This study comparatively characterized the miRNAomes between the red-flesh mutant and the wild type, the results lay a foundation for unraveling the miRNA-mediated molecular processes that regulate lycopene accumulation in the sweet orange red-flesh mutant.</p></sec></abstract></article-meta></front><body><sec><title>Background</title><p>Sweet orange (<italic>Citrus sinensis </italic>[L.] Osbeck), one of the most important fruit crops worldwide, is responsible for 75% of citrus production used both as fresh fruit and processed juice [<xref ref-type="bibr" rid="B1">1</xref>]. Orange fruit is believed to contain many phytochemicals which are beneficial to human health [<xref ref-type="bibr" rid="B2">2</xref>]. Carotenoids are a group of the health-promoting products which may serve as antioxidants, vitamin A precursors, and cancer-preventing effectors [<xref ref-type="bibr" rid="B3">3</xref>]. Orange fruit is reported with more than 115 species of carotenoids [<xref ref-type="bibr" rid="B4">4</xref>], but lycopene are absent from common varieties [<xref ref-type="bibr" rid="B5">5</xref>-<xref ref-type="bibr" rid="B7">7</xref>]. Interest in lycopene metabolism and regulation is growing rapidly because a variety of epidemiological trials have suggested that higher intake of lycopene-containing fruits or foods are associated with decreased cardiovascular disease and prostate cancer risks [<xref ref-type="bibr" rid="B8">8</xref>]. So far, three sweet orange mutants with lycopene accumulation in the fruits were reported: Shara [<xref ref-type="bibr" rid="B9">9</xref>], Cara Cara [<xref ref-type="bibr" rid="B10">10</xref>] and the recently reported 'Hong Anliu' [<xref ref-type="bibr" rid="B11">11</xref>]. 'Hong Anliu' is a spontaneous bud mutant from its wild type 'Anliu' sweet orange. We found that lycopene in the 'Hong Anliu' mutant was 1000-fold higher than that in its wild type fruits, and in juice sacs the lycopene accumulation was coincided with increased expression of upstream carotenogenic genes and reduced expression of downstream genes [<xref ref-type="bibr" rid="B11">11</xref>]. Thereafter, transcriptional study including cDNA microarray in combination with suppression subtraction hybridization (SSH) was used to investigate gene expression changes in the mutant, and a total of 267 differentially expressed genes were detected [<xref ref-type="bibr" rid="B12">12</xref>]. More recently, massively parallel signature sequencing was applied to decipher the transcriptome changes between WT and MT; and the results indicated that partial impairment of lycopene downstream flux are critical for the formation of lycopene accumulation trait in the mutant [<xref ref-type="bibr" rid="B13">13</xref>]. Meanwhile, comparative proteomic analyses were performed between the mutant and its wild type. And the proteomic data, when considered in combination with transcriptional data, suggest that post-transcriptional regulations are involved in shaping the red-flesh trait of the orange mutant [<xref ref-type="bibr" rid="B14">14</xref>]. However, it remains largely unknown what kind of post-transcriptional mechanism was involved in the red-flesh mutant. So far, one interesting case has been reported in Arabidopsis where miRNA was proposed to regulate the expression of APETALA2 transcription factor (designated as RAP2.2) in controlling a key carotenoids biosynthesis gene (phytoene synthase gene) [<xref ref-type="bibr" rid="B15">15</xref>]. But to date, very little is known about miRNAs or miRNA-mediated molecular processes that regulate lycopene accumulation in plant fruits.</p><p>Small RNAs (sRNAs) are emerging as important regulators of biological processes on post-transcriptional level in most eukaryotes [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>]. In plants, sRNAs are involved in a variety of activities that are essential for genome stability, development, and adaptive responses to biotic and abiotic stresses [<xref ref-type="bibr" rid="B16">16</xref>-<xref ref-type="bibr" rid="B21">21</xref>]. There is still increasing data for the implication of sRNAs in the regulation of other biological processes [<xref ref-type="bibr" rid="B22">22</xref>-<xref ref-type="bibr" rid="B24">24</xref>].</p><p>Based on difference of biogenesis and action, sRNAs have been mainly grouped into two categories, microRNA (miRNA) and short interfering RNA (siRNA) [<xref ref-type="bibr" rid="B21">21</xref>]. miRNAs distinguish from siRNAs by their biogenesis. miRNAs are cleaved from stem-loop precursor molecules that derive from single-stranded RNAs, while siRNAs are generated from double-strand RNA precursors [<xref ref-type="bibr" rid="B25">25</xref>]. In plants, miRNA regulates gene expression mostly on post-transcription level [<xref ref-type="bibr" rid="B17">17</xref>]. The majority of the miRNAs initially isolated from model plant <italic>Arabidopsis thaliana </italic>was found to be evolutionarily conserved across plant species [<xref ref-type="bibr" rid="B26">26</xref>]. Later, many researches suggested that the miRNA repertoire of plant species comprises a set of non-conserved miRNAs besides the conserved ones [<xref ref-type="bibr" rid="B27">27</xref>-<xref ref-type="bibr" rid="B29">29</xref>]. To date, 1894 miRNA sequences have been identified from 24 plant species, as revealed from miRNA registry database (miRBase v13.0; <ext-link ext-link-type="uri" xlink:href="http://microrna.sanger.ac.uk">http://microrna.sanger.ac.uk</ext-link>). However, no citrus miRNAs have been found in this database so far.</p><p>Plant miRNAs have been identified mostly by two strategies: traditional Sanger sequencing of the small RNA libraries as for Arabidopsis [<xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B26">26</xref>], rice [<xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref>], and poplar [<xref ref-type="bibr" rid="B20">20</xref>]; and computational prediction of conserved miRNAs by searching for homologous sequences using EST or genomic sequences [<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B32">32</xref>-<xref ref-type="bibr" rid="B36">36</xref>]. However, the computation-based approach is mostly limited to the discovery of conserved miRNAs; and the small-scale traditional sequencing approach identified mainly conserved miRNAs, as suggested by Morin et al. [<xref ref-type="bibr" rid="B37">37</xref>] and Moxon et al. [<xref ref-type="bibr" rid="B23">23</xref>]. Recently developed high-throughput sequencing technology has allowed the discovery of several non-conserved or lowly expressed miRNAs as well as quantification of the expression of miRNAs. This strategy has been successfully applied to both model plants [<xref ref-type="bibr" rid="B28">28</xref>,<xref ref-type="bibr" rid="B38">38</xref>-<xref ref-type="bibr" rid="B44">44</xref>], and non-model plants [<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B37">37</xref>,<xref ref-type="bibr" rid="B45">45</xref>-<xref ref-type="bibr" rid="B50">50</xref>].</p><p>The criteria for miRNAs characterization and annotation in plants have been advanced since plants have relatively large and complex sRNA populations within which miRNAs are often a minority [<xref ref-type="bibr" rid="B51">51</xref>]. The minimum criteria include biogenesis criterion that miRNA precursors can be folded into stem-loop structure, and expression criterion that mature miRNAs should be detected by northern blotting, qRT-PCR or sequencing [<xref ref-type="bibr" rid="B52">52</xref>]. Proof of biogenesis requires data of the cloning or detection of miRNA* sequences, which is complementary to miRNA sequences in the precursor molecule [<xref ref-type="bibr" rid="B29">29</xref>,<xref ref-type="bibr" rid="B51">51</xref>]. Expression detection can also be done by recently developed qRT-PCR-based methods [<xref ref-type="bibr" rid="B53">53</xref>,<xref ref-type="bibr" rid="B54">54</xref>], where each miRNA is reverse-transcribed from total RNA using a specific stem-loop primer, followed by PCR amplification and detection. This method is believed to be a powerful alternative for sensitive, rapid, and cost-effective detection of miRNA [<xref ref-type="bibr" rid="B24">24</xref>,<xref ref-type="bibr" rid="B55">55</xref>]. Target prediction can be an ancillary criterion for miRNA annotation. Sequence complementarity between miRNAs and their target genes is very high in plants, which has made the search for plant miRNA target genes a straightforward process [<xref ref-type="bibr" rid="B18">18</xref>]. A number of prediction algorithms are available publicly for plant miRNA target prediction, such as miRU [<xref ref-type="bibr" rid="B56">56</xref>], WMD3 [<xref ref-type="bibr" rid="B57">57</xref>], and UEA plant sRNA toolkit [<xref ref-type="bibr" rid="B58">58</xref>].</p><p>Here we described the deep sequencing of sRNAs from a red-flesh sweet orange mutant and its wild type. Comparative profiling of the sRNA transcriptome between wild type and mutant revealed a set of 51 known and 9 novel miRNAs showing significant expression changes. The annotation of the potential targets of differential miRNAs indicated that high ranked genes are that implicated in biological processes including carotenoid biosynthesis, transcription regulation, and photosynthesis.</p></sec><sec><title>Results</title><sec><title>Sequencing and annotation of sweet orange small RNAs</title><p>Our previous studies showed that the stage of 170 days after flowering (DAF) is the critical stage for the phenotype of color break and global gene expression changes during fruit development in the mutant (Figure <xref ref-type="fig" rid="F1">1</xref>) [<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B13">13</xref>]. In this study, sRNA libraries were generated from fruit pulps of 'Anliu' sweet orange (wild type, WT) and its red-flesh mutant (MT) 'Hong Anliu' at 170 DAF stage. Deep sequencing of small RNA libraries yielded 4,987,484 and 7,163,041 unfiltered sequence reads for WT and MT, respectively. The raw sRNA data were submitted to Gene Expression Omnibus (GEO) under accession no. GSE18207. After discarding low quality sequences containing ambiguous nucleotides, sequences shorter than 18 nucleotides, and sequences counts below 3 in both libraries, 1,790,395 (WT) and 3,345,746 (MT) reliable sequences were remained for analysis. These sequences represented 202,965 and 320,443 unique sRNA sequences in WT and MT, respectively. The distribution of unique sRNA length is summarized in Figure <xref ref-type="fig" rid="F2">2</xref>. The overall distribution pattern was similar between WT and MT, i.e. the majority of sRNAs (approximately 95%) were 21-24 nt in length with 24-nt sRNA as the major peak.</p><fig id="F1" position="float"><label>Figure 1</label><caption><p><bold>Fruit development of the red-flesh mutant 'Hong anliu' sweet orange (MT) and its wild type (WT)</bold>. The schematic presentation shows the strategy of transcriptional analysis by the Massive Parallel Signature Sequencing (previously) and post-transcriptional analysis by sRNA sequencing (this study) on the MT and WT. DAF stands for Days After Flowering.</p></caption><graphic xlink:href="1471-2164-11-246-1"></graphic></fig><fig id="F2" position="float"><label>Figure 2</label><caption><p><bold>Length distribution of sweet orange small RNA</bold>.</p></caption><graphic xlink:href="1471-2164-11-246-2"></graphic></fig><p>The unique sRNAs were further classified into different RNA categories (Table <xref ref-type="table" rid="T1">1</xref>). Analysis showed that 10.8% (WT) and 9.9% (MT) of the unique sRNAs matched the <italic>Citrus sinensis </italic>unigenes (dataset from TIGR, the institute for genomic research). Detailed information was shown in Additional file <xref ref-type="supplementary-material" rid="S1">1</xref> and <xref ref-type="supplementary-material" rid="S2">2</xref>. Further analysis using the sRNA sequences searching against Rfam database revealed that 1.7%, and 1.5% of the sequences for WT and MT, respectively, matched noncoding RNAs including rRNA, tRNA, snRNA and snoRNAs (Additional file <xref ref-type="supplementary-material" rid="S3">3</xref> and <xref ref-type="supplementary-material" rid="S4">4</xref>). Searching the remaining sRNAs from WT and MT against miRBase v13.0 identified 0.4% and 0.3% of the unique sequences matched known miRNAs, which account 3.7% and 3.1% of the total sRNAs, respectively (Table <xref ref-type="table" rid="T1">1</xref>).</p><table-wrap id="T1" position="float"><label>Table 1</label><caption><p>Summary of sRNAs sequences from WT and MT sweet orange</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left">Category</th><th align="left" colspan="2">Distinct signatures</th><th align="left" colspan="2">Total signatures</th><th align="center" colspan="2">Mean frequencies</th></tr></thead><tbody><tr><td></td><td align="center"><bold>WT</bold></td><td align="center"><bold>MT</bold></td><td align="left"><bold>WT</bold></td><td align="left"><bold>MT</bold></td><td align="center"><bold>WT</bold></td><td align="center"><bold>MT</bold></td></tr><tr><td align="left">matching protein-coding gene</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td align="left"> sense</td><td align="center">13811 (6.80%)</td><td align="center">18142 (5.66%)</td><td align="left">244819 (13.67%)</td><td align="left">346569 (10.36%)</td><td align="center">17.73</td><td align="center">19.10</td></tr><tr><td align="left"> antisense</td><td align="center">8281 (4.08)</td><td align="center">10651 (3.32%)</td><td align="left">120749 (6.74%)</td><td align="left">162839 (4.87%)</td><td align="center">14.58</td><td align="center">15.29</td></tr><tr><td align="left">non-protein-coding RNAs</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td align="left"> snoRNA</td><td align="center">13 (0.01%)</td><td align="center">14 (0.01%)</td><td align="left">471 (0.03%)</td><td align="left">149 (0.01%)</td><td align="center">36.23</td><td align="center">10.64</td></tr><tr><td align="left"> snRNA</td><td align="center">39 (0.02%)</td><td align="center">104 (0.03%)</td><td align="left">261 (0.01%)</td><td align="left">859 (0.03%)</td><td align="center">6.69</td><td align="center">8.26</td></tr><tr><td align="left"> tRNA</td><td align="center">647 (0.32%)</td><td align="center">1301 (0.41%)</td><td align="left">21932 (1.22%)</td><td align="left">73778 (2.21%)</td><td align="center">33.90</td><td align="center">56.71</td></tr><tr><td align="left"> rRNA</td><td align="center">2747 (1.35%)</td><td align="center">3772 (1.18%)</td><td align="left">59535 (3.33%)</td><td align="left">99252 (2.97%)</td><td align="center">21.67</td><td align="center">26.31</td></tr><tr><td align="left">miRNAs</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td align="left"> known</td><td align="center">667 (0.33%)</td><td align="center">802 (0.25%)</td><td align="left">61993 (3.46%)</td><td align="left">87455 (2.61%)</td><td align="center">92.94</td><td align="center">109.05</td></tr><tr><td align="left"> novel</td><td align="center">83 (0.04%)</td><td align="center">111 (0.03%)</td><td align="left">4084 (0.23%)</td><td align="left">11463 (0.34%)</td><td align="center">49.20</td><td align="center">103.27</td></tr><tr><td align="left">other sRNAs</td><td align="center">176677 (87.05%)</td><td align="center">285546 (89.11%)</td><td align="left">1276551 (71.30%)</td><td align="left">2563382 (76.62%)</td><td align="center">7.23</td><td align="center">8.98</td></tr><tr><td align="left">total</td><td align="center">202965 (100%)</td><td align="center">320443 (100%)</td><td align="left">1790395 (100%)</td><td align="left">3345746 (100%)</td><td align="center">8.82</td><td align="center">10.44</td></tr></tbody></table></table-wrap></sec><sec><title>Known miRNAs</title><p>We identified 85 miRNAs, belonging to 48 familes, in sweet orange by BLAST against the miRBase v13.0 using our combined (WT and MT) sRNA sequences (Additional file <xref ref-type="supplementary-material" rid="S5">5</xref>). The potential conserved miRNAs were used for BLASTN against sweet orange unigene dataset to search precursor sequences (Detail in Methods). Since the orange genome is largely unknown, we used orange unigene dataset (from TIGR, the institute for genomic research) and 1.2× coverage sequence of sweet orange (from NCBI) to predict RNA secondary structures. The sequences of perfect match with sRNA sequences were used for fold-back structure prediction by Mfold program [<xref ref-type="bibr" rid="B59">59</xref>]. The miRNA-containing fold-back structures were shown in Additional file <xref ref-type="supplementary-material" rid="S6">6</xref>.</p><p>To compare the miRNA abundance in different libraries, the count of each miRNA was normalized to transcripts per million (TPM). In the WT sRNA library, miR168, miR172 and miR156 were the most overrepresented families, with the abundance at 8,927, 4,754 and 3,566 TPM, respectively. These three miRNA families also frequently represented in MT sRNA library, but the difference is that the miR172 abundance ranked third (3,330 TPM) after miR156 (4,397 TPM) and miR168 (8,437 TPM) in the library. It is interesting that in both libraries miR168 was the most frequent miRNA which constituted nearly 32% of the miRNA transcriptome of sweet orange.</p><p>The 48 miRNA families from sweet orange were compared with those from 11 other plant species (Figure <xref ref-type="fig" rid="F3">3</xref>). Generally, the orange miRNAs had corresponding homolog in at least one plant species; one miRNA miR1061 only has homolog in phylogenetically distant species <italic>Physcomitrella</italic>. Moreover, miR1169 and miR1171 were extraordinary that they only have homolog genes in <italic>Chlamydomonas </italic>which belongs to protista kingdom. These data suggest that some orange miRNAs are ancient. Sweet orange was phylogenetically close to Arabidopsis which have 187 miRNA genes in miRBase v13.0 database; comparison between them showed that 28 miRNA familes were conserved between them. When comparing with the 140 miRNA genes from another fruit crop grapevine, 23 of them were conserved between sweet orange and grapevine (Figure <xref ref-type="fig" rid="F3">3</xref>).</p><fig id="F3" position="float"><label>Figure 3</label><caption><p><bold>Known miRNAs from sweet orange (<italic>Citrus sinensis</italic>), designated as csi on the first column, and their homologs in other plant species</bold>. The picture is modified from Axtell et al. [<xref ref-type="bibr" rid="B45">45</xref>]. Scale 0, miRNA only predicted; scale 1, miRNA sequenced; scale 2, miRNA/miRNA* accumulation detected; scale 3, miRNA detected by small RNA blot or qRT-PCR; scale 4, miRNAs with validated targets. The general information is based on miRBase 13.0 statistics. Abbreviations: ath, <italic>Arabidopsis thaliana</italic>; bna, <italic>Brassica napus</italic>; csi, <italic>Citrus sinensis</italic>; eca, <italic>Eschscholzia californica</italic>; mtr, <italic>Medicago truncatula</italic>; osa, <italic>Oryza sativa</italic>; pta, <italic>Pinus taeda</italic>; ptc, <italic>Populus trichocarpa</italic>; ppt, <italic>Physcomitrella patens</italic>; sly; <italic>Solanum lycopersicum</italic>; vvi, <italic>Vitis vinifera</italic>; zma, <italic>Zea mays</italic>. Some of the data is renewed with information from publications including Arabidopsis [<xref ref-type="bibr" rid="B24">24</xref>,<xref ref-type="bibr" rid="B62">62</xref>], California poppy [<xref ref-type="bibr" rid="B46">46</xref>], grape [<xref ref-type="bibr" rid="B60">60</xref>], rice [<xref ref-type="bibr" rid="B44">44</xref>], and tomato [<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B55">55</xref>].</p></caption><graphic xlink:href="1471-2164-11-246-3"></graphic></fig><p>Putative targets of miRNAs were determined using publicly available algorithms including miRU [<xref ref-type="bibr" rid="B56">56</xref>] and WMD3 [<xref ref-type="bibr" rid="B57">57</xref>]. Of the 85 known miRNAs, 82 had putative targets, with the exception of miR167a, miR845b, and miR1520c (Additional file <xref ref-type="supplementary-material" rid="S7">7</xref>). Many putative targets are transcription factors and homologs of known miRNA target genes in other plant species, such as SBP for miR156, NAC for miR164, bZIP for miR166, AP2 for miR172 and F-box for miR394. One occasional case in grapevine [<xref ref-type="bibr" rid="B60">60</xref>] was also observed in sweet orange: csi-miR535 was predicted to target <italic>squamosa promoter-binding protein-like </italic>(<italic>SPL</italic>) gene while not target to a brassinosteroid signaling regulator as that firstly reported in moss [<xref ref-type="bibr" rid="B61">61</xref>].</p></sec><sec><title>Novel miRNAs</title><p>After excluding the rRNA, tRNA, snRNA, snoRNAs and known miRNAs, the remained sRNA sequences were used to BLAST search on orange unigenes and 1.2× coverage sequence of sweet orange (from NCBI); and secondary structure prediction were done for each locus using the criteria described by Jones-Rhoades et al. [<xref ref-type="bibr" rid="B29">29</xref>]. This analysis revealed that 21 sRNA sequences were perfectly matched ESTs and could be folded into stem-loop structures (Additional file <xref ref-type="supplementary-material" rid="S8">8</xref>). Search of complementary miRNA* sequences showed that 12 of the 21 candidate miRNAs were detected (Table <xref ref-type="table" rid="T2">2</xref> and Additional file <xref ref-type="supplementary-material" rid="S8">8</xref>). Based on the criteria of loci with stem-loop structure producing sequenced mature miRNA and miRNA* species as described in Meyers et al. [<xref ref-type="bibr" rid="B51">51</xref>], these 12 sequences were considered as novel miRNAs.</p><table-wrap id="T2" position="float"><label>Table 2</label><caption><p>Potential novel miRNA genes from sweet orange</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left">miRNA ID</th><th align="center">Sequences (5'-3')</th><th align="center">WT count<sup>a</sup></th><th align="center">MT count<sup>a</sup></th><th align="center">Fold change</th><th align="center">Precursor Unigene ID</th><th align="center">Start, end</th><th align="center">miRNA star</th></tr></thead><tbody><tr><td align="left">csi-novel-01</td><td align="left">UUUUUCGGCAACAUGAUUUCU</td><td align="center">2.8</td><td align="center">0.0</td><td></td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY671768">EY671768</ext-link></td><td align="center">607, 764</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-02</td><td align="left">UGGAGGCAGCGGUUCAUCGAUC</td><td align="center">4.5</td><td align="center">3.3</td><td align="center">1.4</td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY681703">EY681703</ext-link></td><td align="center">286,417</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-03</td><td align="left">UAGAUAAAGAUGAGAGAAAAA</td><td align="center">220.1</td><td align="center">1248.5</td><td align="center">5.7</td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY683731">EY683731</ext-link></td><td align="center">19,166</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-04</td><td align="left">UUCAAGAAAUCUGUGGGAAG</td><td align="center">8.9</td><td align="center">0.0</td><td></td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY714194">EY714194</ext-link></td><td align="center">255, 397</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-05</td><td align="left">UGAAGGGCCUUUCUAGAGCAC</td><td align="center">90.5</td><td align="center">29.6</td><td align="center">3.1</td><td align="center"><ext-link ext-link-type="gen" xlink:href="CN182895">CN182895</ext-link></td><td align="center">123, 285</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-06</td><td align="left">UUCCCUAGUCCCCCUAUUCCUA</td><td align="center">11.2</td><td align="center">1.5</td><td align="center">7.5</td><td align="center"><ext-link ext-link-type="gen" xlink:href="CX051199">CX051199</ext-link></td><td align="center">168, 263</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-07</td><td align="left">GGAAUGUUGUCUGGCUCGAGG</td><td align="center">12.3</td><td align="center">4.8</td><td align="center">2.6</td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY672989">EY672989</ext-link></td><td align="center">141, 318</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-08</td><td align="left">AGUGGGAGCGUGGGGUAAGAAG</td><td align="center">287.1</td><td align="center">369.1</td><td align="center">1.3</td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY676411">EY676411</ext-link></td><td align="center">137, 282</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-09</td><td align="left">UUGAGUUCUGCAAGCCGUCGA</td><td align="center">0.0</td><td align="center">2.7</td><td></td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY712260">EY712260</ext-link></td><td align="center">398, 498</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-10</td><td align="left">AGGUCAUCUUGCAGCUUCAAU</td><td align="center">27.9</td><td align="center">4.5</td><td align="center">6.2</td><td align="center"><ext-link ext-link-type="gen" xlink:href="EY739655">EY739655</ext-link></td><td align="center">272, 634</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-11</td><td align="left">UGGACAGAGAAAUCACGGUCA</td><td align="center">591.5</td><td align="center">132.7</td><td align="center">4.5</td><td align="center"><ext-link ext-link-type="gen" xlink:href="TC19570">TC19570</ext-link></td><td align="center">105, 191</td><td align="center">Yes</td></tr><tr><td align="left">csi-novel-12</td><td align="left">GCAGCGUCCUCAAGAUUCACA</td><td align="center">15.1</td><td align="center">4.5</td><td align="center">3.4</td><td align="center"><ext-link ext-link-type="gen" xlink:href="TC23189">TC23189</ext-link></td><td align="center">300, 444</td><td align="center">Yes</td></tr></tbody></table><table-wrap-foot><p><sup>a </sup>count was normalized as transcripts per million (TPM).</p></table-wrap-foot></table-wrap><p>All the 12 novel miRNAs had a predicted target in at least one orange EST sequence (Additional file <xref ref-type="supplementary-material" rid="S9">9</xref>). Putative targets of four miRNAs were transcription factors, including NAC for csi-novel-01 and csi-novel-11, AUX/IAA TF for csi-novel-03 and YABBY for csi-novel-10. It is notable that one miRNA potentially target disease resistance genes, i.e. csi-novel-06 predicted to target on serine/threonine kinase gene.</p><p>To confirm the expression of the novel miRNAs, we analyzed the expression of all the 12 novel miRNAs using stem-loop qRT-PCR. All the genes could be detected by qRT-PCR (Figure <xref ref-type="fig" rid="F4">4A</xref>). Of the 12 novel miRNAs, 8 genes showed similar expression pattern to that revealed from sequencing data of the sRNA libraries. The electrophoresis of the qRT-PCR products confirmed the size and expression of these novel miRNAs (Figure <xref ref-type="fig" rid="F4">4C</xref>). Moreover, we analyzed the expression of three miRNA*s (csi-novel-03, -05, -06); and results showed that two miRNA*s had different expression pattern from those of corresponding mature miRNAs (Figure <xref ref-type="fig" rid="F4">4A</xref>).</p><fig id="F4" position="float"><label>Figure 4</label><caption><p><bold>Expression confirmation of citrus miRNAs derived from high throughput sequencing</bold>. (A). novel miRNAs expression detected by stem-loop qRT-PCR; (B) differentially expressed known miRNAss expression detected by stem-loop qRT-PCR; (C) electrophoresis of the stem-loop PCR products. Each primer has been used for the PCR amplifications on two samples, mutant and wild type.</p></caption><graphic xlink:href="1471-2164-11-246-4"></graphic></fig></sec><sec><title>miRNA-targets associated small RNAs</title><p>To compare the frequency of small RNAs located in miRNA-target genes with other genes, we mined the unique small RNAs (sRNAs) that matched perfectly to miRNA-target genes in sense or antisense strands according to Luo et al. [<xref ref-type="bibr" rid="B62">62</xref>]. Target prediction of the 85 known and 12 novel miRNAs produced a total of 555 miRNA-target genes. Then all the 555 miRNA-target genes were searched against the unigenes on which sRNAs were mapped. This analysis in WT showed that 13,811 sRNAs in sense and 8,281 sRNAs in antisense were mapped perfectly on orange unigenes (Table <xref ref-type="table" rid="T1">1</xref>; Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>). Of the mapped unigenes in WT, 76 were miRNA-target genes: 21 of them produced sRNAs in sense strand, 11 in antisense and 44 in both sense and antisense (Table <xref ref-type="table" rid="T3">3</xref>). For MT sample, 18,142 and 10,651 sRNAs were mapped in sense and antisense, respectively (Table <xref ref-type="table" rid="T1">1</xref>; Additional file <xref ref-type="supplementary-material" rid="S2">2</xref>). Similar analysis revealed that 97 miRNA-target genes match sRNAs perfectly, with 20 in sense strand, 27 in antisense and 50 in both strand (Table <xref ref-type="table" rid="T3">3</xref>; detail in Additional file <xref ref-type="supplementary-material" rid="S10">10</xref>). This study showed that 13.7% and 17.5% of the miRNA-target genes in WT and MT could be the precursors of sRNAs. The high frequency of miRNA-targets associated sRNAs suggests that miRNA-target genes are hotspots for generation of sRNAs.</p><table-wrap id="T3" position="float"><label>Table 3</label><caption><p>Summary of small RNAs generated from miRNA-target genes</p></caption><table frame="hsides" rules="groups"><thead><tr><th></th><th align="center">Producing sense small RNAs</th><th align="center">Producing antisense small RNAs</th><th align="center">Overlap between sense and antisense</th><th align="center">Total<break></break>sense or antisense</th></tr></thead><tbody><tr><td align="center">WT miRNA target genes<sup>a</sup></td><td align="center">65 (11.7%)</td><td align="center">55 (9.9%)</td><td align="center">44 (7.9%)</td><td align="center">76 (13.7%)</td></tr><tr><td align="center">MT miRNA<break></break>target genes<sup>a</sup></td><td align="center">70 (12.6%)</td><td align="center">77 (13.9%)</td><td align="center">50 (9.0%)</td><td align="center">97 (17.5%)</td></tr></tbody></table><table-wrap-foot><p><sup>a </sup>All the 555 miRNA-target genes were used for analysis, detailed gene ID see in Additional file <xref ref-type="supplementary-material" rid="S10">10</xref>.</p></table-wrap-foot></table-wrap></sec><sec><title>Differentially expressed miRNAs between WT and MT</title><p>The frequency of each miRNAs in the small RNA library could serve as an index for the estimation of the relative expression abundance of miRNAs. To investigate the expression change of miRNAs between WT and MT, the abundance of each miRNA was normalized as transcripts per million (TPM). A total of 51 known miRNA genes and 9 novel miRNAs were up- or down-regulated significantly at 0.01 level based on Z-score statistics (Table <xref ref-type="table" rid="T2">2</xref> and Additional file <xref ref-type="supplementary-material" rid="S5">5</xref>). Among these 60 differentially expressed genes, 52 miRNAs showed a two-fold or greater (ratio > 2 or < 0.5) expression difference between MT and WT. Table <xref ref-type="table" rid="T4">4</xref> summarized the 20 miRNAs with the most significant expression changes between WT and MT.</p><table-wrap id="T4" position="float"><label>Table 4</label><caption><p>Top 20 differentially expressed miRNAs between WT and MT</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="center">miRNA</th><th align="center">Sequence</th><th align="center">WT count<sup>a</sup></th><th align="center">MT count<sup>a</sup></th><th align="center">Fold change</th><th align="right">p-value</th></tr></thead><tbody><tr><td align="left" colspan="6"><bold>Higher expression in MT</bold></td></tr><tr><td align="left">csi-miR479</td><td align="left">UGUGAUAUUGGUUCGGCUCAUC</td><td align="center">1341.6</td><td align="center">1921.5</td><td align="center">1.9</td><td align="right">0</td></tr><tr><td align="left">csi-miR156a</td><td align="left">UGACAGAAGAGAGUGAGCAC</td><td align="center">856.2</td><td align="center">1656.1</td><td align="center">2.6</td><td align="right">0</td></tr><tr><td align="left">csi-miR167a</td><td align="left">UGAAGCUGCCAGCAUGAUCUA</td><td align="center">759.6</td><td align="center">1967.3</td><td align="center">21.6</td><td align="right">0</td></tr><tr><td align="left">csi-miR171b</td><td align="left">CGAGCCGAAUCAAUAUCACUC</td><td align="center">28.5</td><td align="center">615.4</td><td align="center">4.5</td><td align="right">0</td></tr><tr><td align="left">csi-novel-08</td><td align="left">UAGAUAAAGAUGAGAGAAAAA</td><td align="center">220.1</td><td align="center">1248.5</td><td align="center">1.5</td><td align="right">0</td></tr><tr><td align="left">csi-miR166j</td><td align="left">UCUCGGACCAGGCUUCAUUCC</td><td align="center">1682.9</td><td align="center">2078.5</td><td align="center">3.1</td><td align="right">2.85E-22</td></tr><tr><td align="left" colspan="6"><bold>Lower expression in MT</bold></td></tr><tr><td align="left">csi-miR482a</td><td align="left">UCUUCCCUAUGCCUCCCAUUCC</td><td align="center">103.9</td><td align="center">4.2</td><td align="center">15.6</td><td align="right">0</td></tr><tr><td align="left">csi-miR162a</td><td align="left">UCGAUAAACCUCUGCAUCCAG</td><td align="center">401.0</td><td align="center">25.7</td><td align="center">12.4</td><td align="right">0</td></tr><tr><td align="left">csi-miR159a</td><td align="left">UUUGGAUUGAAGGGAGCUCUA</td><td align="center">307.8</td><td align="center">24.8</td><td align="center">3.5</td><td align="right">0</td></tr><tr><td align="left">csi-miR390a</td><td align="left">AAGCUCAGGAGGGAUAGCGCC</td><td align="center">822.2</td><td align="center">235.8</td><td align="center">2.5</td><td align="right">0</td></tr><tr><td align="left">csi-miR164a</td><td align="left">UGGAGAAGCAGGGCACGUGCA</td><td align="center">1894.0</td><td align="center">749.0</td><td align="center">1.6</td><td align="right">0</td></tr><tr><td align="left">csi-miR167d</td><td align="left">UGAAGCUGCCAGCAUGAUCUGA</td><td align="center">1362.3</td><td align="center">825.8</td><td align="center">1.4</td><td align="right">0</td></tr><tr><td align="left">csi-miR172a</td><td align="left">AGAAUCUUGAUGAUGCUGCAU</td><td align="center">4688.4</td><td align="center">3299.7</td><td align="center">1.4</td><td align="right">0</td></tr><tr><td align="left">csi-novel-11</td><td align="left">UGGACAGAGAAAUCACGGUCA</td><td align="center">591.5</td><td align="center">132.7</td><td align="center">5.7</td><td align="right">0</td></tr><tr><td align="left">csi-miR156b</td><td align="left">CUGACAGAAGACAGUGAGCAC</td><td align="center">41.3</td><td align="center">1.8</td><td align="center">2.5</td><td align="right">2.86E-27</td></tr><tr><td align="left">csi-miR473a</td><td align="left">ACUCUCCCUCAAGGGCUUCGC</td><td align="center">168.1</td><td align="center">68.1</td><td align="center">1.2</td><td align="right">2.01E-26</td></tr><tr><td align="left">csi-novel-03</td><td align="left">UGAAGGGCCUUUCUAGAGCAC</td><td align="center">90.5</td><td align="center">29.6</td><td align="center">8.1</td><td align="right">2.87E-20</td></tr><tr><td align="left">csi-miR399a</td><td align="left">UGCCAAAGGAGAAUUGCCCUG</td><td align="center">36.3</td><td align="center">4.5</td><td align="center">13.8</td><td align="right">3.14E-18</td></tr><tr><td align="left">csi-miR482c</td><td align="left">UCUUGCCCACCCCUCCCAUUCC</td><td align="center">29.0</td><td align="center">2.1</td><td align="center">15.6</td><td align="right">8.98E-18</td></tr><tr><td align="left">Csi-miR164d</td><td align="left">UGGAGAAGCAGGGCACGUGCU</td><td align="center">49.1</td><td align="center">11.1</td><td align="center">4.4</td><td align="right">7.6E-17</td></tr></tbody></table><table-wrap-foot><p><sup>a </sup>count was normalized as transcripts per million (TPM).</p></table-wrap-foot></table-wrap><p>To confirm the expression difference of the miRNA, we analyzed the expression of 21 known miRNA genes using stem-loop qRT-PCR in addition to the 12 novel miRNA genes described earlier. The expression level of each gene in the MT and WT was compared with its abundance from the sequencing data of the sRNA library. Results showed that among the 33 miRNAs, 18 known miRNAs and 8 novel miRNAs have the same expression pattern in WT and MT as that from sequencing data (Figure <xref ref-type="fig" rid="F4">4B</xref>).</p></sec><sec><title>Annotation of potential targets of differentially expressed miRNAs</title><p>Functional annotations were further performed to investigate which processes are differentially regulated by miRNAs in the mutant. A total of 418 potential target genes were predicted based on the 60 differentially expressed miRNAs in sweet orange (Additional file <xref ref-type="supplementary-material" rid="S11">11</xref>). Interestingly, the potential targets included two important carotenogenic genes, i.e. geranylgeranyl pyrophosphate synthase (GGPS) gene which targeted by csi-miR167 and lycopene β-cyclase (LYCb) gene which targeted by csi-miR1857. To evaluate the potential functions of these miRNA-target genes, gene ontology (GO) categories were assigned to the putative targets of the 60 differentially expressed miRNA genes according to the method described by Morin et al. [<xref ref-type="bibr" rid="B63">63</xref>]. Figure <xref ref-type="fig" rid="F5">5</xref> summarized the categorization of miRNA-target genes according to the cellular component, molecular function, and biological process. Based on molecular function, the genes were finally classified into 13 categories, as shown in Figure <xref ref-type="fig" rid="F5">5B</xref>; the most three over-represented GO terms are metal ion binding, nucleic acid binding, and transcription factor activity. Categories based on biological processes revealed that the miRNA-target genes were related to 17 biological processes; the most three frequent terms are regulation of transcription, signal transduction, protein modification (Figure <xref ref-type="fig" rid="F5">5C</xref>). Moreover, GO representations from this study were compared with that based on all the public unigenes from sweet orange in TIGR gene index database <ext-link ext-link-type="uri" xlink:href="http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/GO_browser.pl?species=Orange&gi_dir=csgi">http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/GO_browser.pl?species=Orange&gi_dir=csgi</ext-link>; the analysis revealed that the striking differences lies in the high percentage of nucleus, plastid and chloroplast for cellular component, and overpresentation of regulation of transcription, protein modification and photosynthesis for biological process in this study.</p><fig id="F5" position="float"><label>Figure 5</label><caption><p><bold>Gene ontology categories of the predicted target genes of the 60 differential miRNAs</bold>. Categorization of miRNA-target genes was performed according to the cellular component (A), molecular function (B), and biological process (C).</p></caption><graphic xlink:href="1471-2164-11-246-5"></graphic></fig><p>The biological interpretation of the target genes of differential miRNAs was further completed using KEGG pathway analysis. A total of 15 different metabolic pathways were found (Table <xref ref-type="table" rid="T5">5</xref>), of which some were consistent with biological processes that already revealed by GO analysis. The most represented pathways included carbon fixation (8 enzymes represented), fatty acid metabolism (5), flavonoid biosynthesis (6), terpenoid biosynthesis (3), and ubiquitin mediated proteolysis (3).</p><table-wrap id="T5" position="float"><label>Table 5</label><caption><p>List of the important KEGG pathways more than 3 miRNA-target genes affiliated</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left">KEGG<sup>a </sup>pathway</th><th align="left">Genes<sup>b</sup></th><th align="left">Gene ID</th><th align="left">Best E-value</th></tr></thead><tbody><tr><td align="left">Benzoate degradation</td><td align="left">5</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY732960">EY732960</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY732985">EY732985</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY748192">EY748192</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18796">TC18796</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC9807">TC9807</ext-link></td><td align="left">1.00E-125</td></tr><tr><td align="left">Carbon fixation</td><td align="left">8</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY665527">EY665527</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY667061">EY667061</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC11997">TC11997</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC13950">TC13950</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC17473">TC17473</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC24400">TC24400</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY722705">EY722705</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC11997">TC11997</ext-link></td><td align="left">1.00E-128</td></tr><tr><td align="left">Ethylbenzene degradation</td><td align="left">5</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY732960">EY732960</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY732985">EY732985</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY748192">EY748192</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18796">TC18796</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC9807">TC9807</ext-link></td><td align="left">1.00E-156</td></tr><tr><td align="left">Fatty acid metabolism</td><td align="left">5</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY732960">EY732960</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY732985">EY732985</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY748192">EY748192</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18796">TC18796</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC9807">TC9807</ext-link></td><td align="left">1.00E-156</td></tr><tr><td align="left">Flavonoid biosynthesis</td><td align="left">6</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY697662">EY697662</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY742573">EY742573</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC14650">TC14650</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC3846">TC3846</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC14650">TC14650</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC3846">TC3846</ext-link></td><td align="left">6.00E-93</td></tr><tr><td align="left">Geraniol degradation</td><td align="left">5</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY732960">EY732960</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY732985">EY732985</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY748192">EY748192</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18796">TC18796</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC9807">TC9807</ext-link></td><td align="left">1.00E-156</td></tr><tr><td align="left">Glyoxylate and dicarboxylate metabolism</td><td align="left">3</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY667061">EY667061</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY708354">EY708354</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY722705">EY722705</ext-link></td><td align="left">2.00E-86</td></tr><tr><td align="left">Linolenic acid metabolism</td><td align="left">5</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY732960">EY732960</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY732985">EY732985</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY748192">EY748192</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18796">TC18796</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC9807">TC9807</ext-link></td><td align="left">1.00E-122</td></tr><tr><td align="left">Methane metabolism</td><td align="left">3</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY697129">EY697129</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY724821">EY724821</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC20228">TC20228</ext-link></td><td align="left">1.00E-68</td></tr><tr><td align="left">Pentose phosphate pathway</td><td align="left">3</td><td align="left"><ext-link ext-link-type="gen" xlink:href="TC13950">TC13950</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC17473">TC17473</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC15377">TC15377</ext-link></td><td align="left">5.00E-58</td></tr><tr><td align="left">Phenylalanine metabolism</td><td align="left">4</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY664657">EY664657</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY697129">EY697129</ext-link>, <ext-link ext-link-type="gen" xlink:href="NP13097244">NP13097244</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC20228">TC20228</ext-link></td><td align="left">1.00E-167</td></tr><tr><td align="left">Photosynthesis - antenna proteins</td><td align="left">5</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY672715">EY672715</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY682256">EY682256</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY701112">EY701112</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY701374">EY701374</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY756276">EY756276</ext-link></td><td align="left">1.00E-102</td></tr><tr><td align="left">Ribosome</td><td align="left">3</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY681302">EY681302</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY752996">EY752996</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18634">TC18634</ext-link></td><td align="left">2.00E-91</td></tr><tr><td align="left">Terpenoid biosynthesis</td><td align="left">3</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY730974">EY730974</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC363">TC363</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY752486">EY752486</ext-link></td><td align="left">6.00E-84</td></tr><tr><td align="left">Ubiquitin mediated proteolysis</td><td align="left">3</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY656660">EY656660</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY665372">EY665372</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY752038">EY752038</ext-link></td><td align="left">2.00E-83</td></tr><tr><td align="left">Valine leucine and isoleucine degradation</td><td align="left">6</td><td align="left"><ext-link ext-link-type="gen" xlink:href="EY732985">EY732985</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY732960">EY732960</ext-link>, <ext-link ext-link-type="gen" xlink:href="EY748192">EY748192</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC18796">TC18796</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC9807">TC9807</ext-link>, <ext-link ext-link-type="gen" xlink:href="TC5927">TC5927</ext-link></td><td align="left">1.00E-156</td></tr></tbody></table><table-wrap-foot><p><sup>a</sup>KEGG = Kyoto Encyclopedia of Genes and Genomes.</p><p><sup>b</sup>The putative target genes of miRNA genes which differentially expressed significant at 0.05 level between the mutant and wild type</p></table-wrap-foot></table-wrap><p>High ranked target genes of the differentially expressed miRNAs were those implicated in three biological processes including regulation of transcription, protein modification and photosynthesis. It is easy to understand the high frequency of terms 'regulation of transcription' and 'protein modification' since miRNA are involved in diverse regulatory events [<xref ref-type="bibr" rid="B64">64</xref>]. However, the biological process of photosynthesis needs to be verified. Moreover, two carotenogenic genes were also predicted to be targeted by miRNAs. We further analyzed one gene involved in the carbon fixation (miR319a and putative target phosphoenolpyruvate carboxylase [TC11997]) and another gene involved in carotenoid biosynthesis (miR1857 and putative target lycopene β-cyclase [LYCb]). The results showed that the expression profiles of miRNAs are complementary to the profiles of their target genes (Figure <xref ref-type="fig" rid="F6">6</xref>), implied the possible roles of miRNAs in regulation of the biological processes that involved in shaping the mutant trait in sweet orange.</p><fig id="F6" position="float"><label>Figure 6</label><caption><p><bold>The model for the biological processes possibly regulated by miRNAs in the red-flesh mutant of sweet orange</bold>. The pathway was modified based on Xu et al. (2009) [<xref ref-type="bibr" rid="B13">13</xref>]. The two biological processes, the carotenogenesis and photosynthesis, were high ranked processes that differential miRNA target genes involved in by gene ontology analysis. The data of photosynthetic rate were extracted from our previous in situ photosynthesis analysis [<xref ref-type="bibr" rid="B13">13</xref>]. The expression profiles of miRNA319 and miR1857 are complementary to the profiles of the corresponding miRNA-target genes (phosphoenolpyruvate carboxylase [TC11997]) and lycopene β-cyclase [LYCb]), implied the possible roles of these miRNAs in regulation the biological processes on posttranscriptional way.</p></caption><graphic xlink:href="1471-2164-11-246-6"></graphic></fig></sec></sec><sec><title>Discussion</title><p>We have characterized the small RNA transcriptome in a red-flesh mutant that with abnormal pattern of lycopene accumulation and its wild type. With deep sequencing strategy by Illumina platform, it provides us not only large number of conserved miRNAs but also novel miRNAs. To the author's knowledge, this is the first report of cloning and characterization of large scale sRNAs and identification of novel miRNAs from sweet orange. A total of 5 and 7 million sRNAs were obtained from WT and MT, respectively; and the size distribution of small RNAs (Figure <xref ref-type="fig" rid="F2">2</xref>) is quite similar to those published from phylogenetically close plant species such as Arabidopsis [<xref ref-type="bibr" rid="B65">65</xref>], with the total percentage of 21-24 nt sRNAs being more than 90% and percentage of 24 nt sRNAs over 50%. This suggests that the Illumina sequencing data of sRNA libraries was reliable.</p><sec><title>miRNAome in sweet orange</title><p>In this study, 85 conserved miRNAs belonging 48 families as well as 12 novel miRNA families were identified in sweet orange. The miRNAs cloned in this study were compared with those from previously reported citrus miRNAs [<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B66">66</xref>,<xref ref-type="bibr" rid="B67">67</xref>], of them four sweet orange miRNAs were not overlap with this study. These results suggest that at least 101 miRNAs exist in the miRNA transcriptome (miRNAome) of sweet orange. We believe that this is a conservative estimate since only fruit samples were used in this study. The miRNA species in wild type and mutant was different, i.e. 69 miRNAs were detected in WT sample while 66 miRNAs were in MT sample. Moreover, the expression levels of each miRNA varied greatly within the transcriptome, i.e. in MT the abundance ranged from 0.9 TPM for csi-miR1858 to 8437 TPM for csi-miR168. All these data implied that miRNAome, as small RNA transcriptome [<xref ref-type="bibr" rid="B38">38</xref>], is distinct and complex though miRNA sequences are believed to be conserved across different plant families [<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B29">29</xref>,<xref ref-type="bibr" rid="B68">68</xref>].</p><p>Take a broader view on the small RNA transcriptome of sweet orange, we noticed that the size distribution pattern of sRNAs from sweet orange (the total percentage of 21-24 nt sRNAs > 90% with 24 nt sRNAs > 50%) is quite similar to Arabidopsis as described earlier [<xref ref-type="bibr" rid="B65">65</xref>]; however, the distribution pattern is strikingly different from that in <italic>Pinus contorta</italic>, a conifer species [<xref ref-type="bibr" rid="B37">37</xref>] where 24-nt RNAs was less frequently (2.5%) and 21-nt RNAs were more abundant (> 50%). The striking difference also existed when compare the sweet orange small RNA transcriptome with another gymnosperm plant species, Chinese yew (<italic>Taxus chinensis</italic>) [<xref ref-type="bibr" rid="B50">50</xref>]. When compared with monocot species rice, the difference is less severe but still exists, i.e. in rice 24-nt sRNAs has the highest percentage (approximately 20%) followed by the 21-nt sRNAs (approximately 10%) [<xref ref-type="bibr" rid="B37">37</xref>]. These analyses indicated that the small RNA transcriptome is complicated across plant species and can be significantly different between phylogenetically-distant plant families.</p><p>A total of 12 novel miRNAs were identified from sweet orange, as evidenced from the biogenesis characteristics of miRNAs including the stem-loop structure of the pre-miRNAs (Additional file <xref ref-type="supplementary-material" rid="S8">8</xref>) and sequencing of the miRNA* in the libraries. The expression of all the 12 miRNAs was also detected by qRT-PCR analyses. Additional qRT-PCR analyses of miRNA*s revealed that some miRNA* species can accumulated at certain levels in fruits; moreover, the expression pattern of miRNA*s in WT and MT fruits can be different from that of miRNAs. For example, csi-novel-05 has lower expression in MT (30 TPM) than in WT (90 TPM) as confirmed by qRT-PCR analysis; in contrast, csi-novel-05* has higher expression in MT (50 TPM) than in WT (26 TPM) which was also confirmed by qRT-PCR. The differential accumulation of miRNAs and miRNA*s may be due to the different activities of key enzyme in the sRNA-pathway, as shown in rice that the differential expression of AGO genes in different tissues might cause the change of miRNA*s abundance [<xref ref-type="bibr" rid="B44">44</xref>].</p></sec><sec><title>miRNA-targets are hot spots for generating sRNAs</title><p>The relationship of sRNA genes and the miRNA target genes is one of the hot topics in the phenomenon of "miRNA-associated transitivity" [<xref ref-type="bibr" rid="B69">69</xref>-<xref ref-type="bibr" rid="B71">71</xref>]. In this study, 13.7% (WT) and 17.5% (MT) of the miRNA putative target genes generated sRNAs. This data implied that miRNA target gene could be hot spots for generating sRNAs. Moreover, high percentage of antisense sRNAs was associated with the miRNA-target genes, with 11.7% and 12.6% for WT and MT, respectively. The antisense sRNAs/transcripts can function in post-transcriptional gene silencing [<xref ref-type="bibr" rid="B62">62</xref>,<xref ref-type="bibr" rid="B72">72</xref>]. The post-transcriptional gene silencing is mainly caused by formation of dsRNA duplexes; this could be supported from the observation that 75% of the antisense sRNAs have their cognate sense transcripts in WT and 64% happens in MT sample in this study.</p></sec><sec><title>miRNAs in plant fruits</title><p>Up to now, miRNA identification in fruits using a cloning approach is rare except in tomato [<xref ref-type="bibr" rid="B23">23</xref>] and grape [<xref ref-type="bibr" rid="B60">60</xref>]. In this study, cloning from sweet orange fruit led to the identification of 48 conserved miRNA families. Analysis of them revealed that 6 miRNA families are expressed in fruits of the three plant species; but they are not fruit-specific. Furthermore, the comparison between the two fruit crops (85 miRNAs from sweet orange and 140 miRNAs from grapevine) showed that 8 miRNA families are expressed in fruits of both crops, and only miR535 is specific to the two species. These analyses suggested that expression and function of fruit-specific miRNAs across plant species is lacking, and miRNAs involved in fruit ripening may overlap with that function in other organs, or the same miRNAs in different organs may have different functions.</p></sec><sec><title>miRNAs possibly involved in the regulation of lycopene accumulation in the sweet orange red-flesh mutant</title><p>The characterization and comparative profiling of entire sets of small RNAs (Small RNA transcriptome), especially the microRNA transcriptome, lays the foundation to unravel the complex miRNA-mediated regulatory networks controlling lycopene accumulation in the red-flesh sweet orange mutant. In this study, a number of miRNAs have been identified to be differentially expressed between 'Anliu' sweet orange (WT) and its red-flesh mutant (MT). Compared with WT, 16 known miRNA genes and one novel miRNA genes were expressed exclusively in MT. On the other hand, we found 19 known miRNAs and two novel miRNAs were WT-specific. Moreover, a total of 51 known miRNAs and 9 novel miRNAs were found to exhibit significant expression changes between MT and WT.</p><p>Target prediction of these differential miRNAs could provide information on the biological processes regulated by miRNA. Putative targets were predicted by psRNATarget (the updated version of miRU) [<xref ref-type="bibr" rid="B56">56</xref>] and web miRNA designer (WMD3) [<xref ref-type="bibr" rid="B57">57</xref>]. This strategy was also used in Arabidopsis for the identification of nutrient-responsive miRNAs and their potential targets [<xref ref-type="bibr" rid="B24">24</xref>], though further direct validation is necessary to elucidate the true in-vivo targets. However, the annotations of these potential miRNA target genes did provide an alternate view of gene regulation of the red-flesh trait formation in MT (Additional file <xref ref-type="supplementary-material" rid="S11">11</xref>). We found that three groups of predicted miRNA-target genes are most possibly involved in the mutant trait formation of lycopene accumulation. The first interesting observation is that two potential targets (EY752486 by csi-miR167 and TC5 by csi-miR1857) are the key enzymes of the carotenoid biosynthesis pathway (Additional file <xref ref-type="supplementary-material" rid="S11">11</xref>). They encode geranylgeranyl pyrophosphate synthase (GGPS), a key enzyme for the production of prerequisite molecules for carotenoids accumulation, and lycopene β-cyclase (LYCb), a rate-limiting enzyme in the conversion of lycopene to downstream cyclic carotenes. The expression of LYCb and csi-miR1857 also indicated possible interaction between them because of the complementary expression profile (Figure <xref ref-type="fig" rid="F6">6</xref>). And we also detected the GGPS gene expression, but failed due to the incorrect sequence information in the current public database. The second interesting target genes are APETALA2 (AP2) transcription factors, including EY726563 by csi-novel-03, and TC7810 by csi-miR172a. In Arabidopsis, one AP2 protein (designated as RAP2.2) has been experimentally validated to interact with phytoene synthase (PSY) gene, which encodes a rate-limiting enzyme for the synthesis of carotenoids. The RAP2.2 gene was also believed to be regulated by miRNA because of the large discrepancy between mRNA and protein levels in the overexpression lines [<xref ref-type="bibr" rid="B15">15</xref>]. The data from this study also supported the proposition, and indicated that RAP2.2 (encoded by TC7810 gene in this study) is a potential target of miRNA172a in sweet orange. The third group of target genes is those involved in photosynthesis or carbon fixation (Table <xref ref-type="table" rid="T5">5</xref>). The potential target genes associated with photosynthesis fits well with the GO results with large number of genes that are located in chloroplast or plastid. Moreover, our photosynthesis-related gene expression analysis and in situ detection of the photosynthetic rate confirmed that photosynthesis in MT is stronger than that in WT (Figure <xref ref-type="fig" rid="F6">6</xref>). The result is quite consistent with our gas chromatographic analyses that the sugars in juice sacs are higher in MT than in WT [<xref ref-type="bibr" rid="B11">11</xref>]. Tomato <italic>hp-2 </italic>mutant which manifested with increased carotenoids, primarily lycopene, showed that genes related with photosynthesis are consistently up-regulated throughout fruit ripening [<xref ref-type="bibr" rid="B73">73</xref>]. All these evidences implied the important role of photosynthesis in the accumulation of lycopene. Taken together, the annotation of the potential targets of differentially expressed miRNA genes between WT and MT indicated that several miRNA-directed biological processes including carotenoid biosynthesis, transcription regulation, and photosynthesis may be important for the regulation of lycopene accumulation in the sweet orange red-flesh mutant.</p></sec></sec><sec><title>Conclusions</title><p>Our study provides a large scale cloning and characterization of miRNAs in sweet orange. The interpretation of the small RNA data uncovered a total of 85 known and 12 novel miRNAs. Meanwhile, comparative profiling of these miRNAs between a spontaneous red-flesh mutant and its wild type revealed that 51 known and 9 novel miRNAs are differentially expressed. Target prediction of the 60 differential miRNAs indicated that two key genes of the carotenoid biosynthesis, geranylgeranyl pyrophosphate synthase (GGPS) and lycopene β-cyclase (LYCb), are under miRNA regulation. Functional annotation of the 418 target genes of differential miRNA revealed that high ranked biological processes are transcription regulation, protein modification and photosynthesis. The expression of miRNAs and target genes involved in photosynthesis and carotenogenesis were further confirmed. Taken together, this study provides new insight into the miRNAome and possible miRNA-directed molecular processes that regulate lycopene accumulation in the red-flesh sweet orange mutant.</p></sec><sec sec-type="methods"><title>Methods</title><sec><title>Plant materials and RNA preparation</title><p>The red-flesh mutant 'Hong Anliu' and the wild type 'Anliu' sweet orange (<italic>Citrus sinensis </italic>L. Osbeck), cultivated at the Institute of Citrus Research located in Guilin, Guangxi Province, China, were used as materials. The mutant 'Hong Anliu' sweet orange (MT) is a spontaneous bud mutation of wild type 'Anliu' sweet orange (WT); and they are with isogenic background as revealed from our previous physiological traits and molecular marker evaluations [<xref ref-type="bibr" rid="B11">11</xref>]. Same sampling strategy as previously published [<xref ref-type="bibr" rid="B13">13</xref>] was employed. Fruit samples were harvested at 170 days after flowering (DAF) that is the critical stage for the flesh color transition. Three different trees were used, and 10 representative fruits from each tree were collected. All samples were separated into peel and pulp, immediately frozen in liquid nitrogen and kept at -80°C until use. Total RNA was extracted according to Liu et al. [<xref ref-type="bibr" rid="B74">74</xref>].</p></sec><sec><title>Small RNA library construction and sequencing</title><p>Small RNA library construction and sequencing was performed as described by Yao et al. [<xref ref-type="bibr" rid="B49">49</xref>]. Briefly, small RNAs with 16-30 nt in length were isolated from the total RNA of WT and MT samples by size fractionation with 15% Tris-borate-EDTA urea polyacrylamide gel (TBU). After extraction from the gel, sRNA was dephosphorylatd by alkaline phosphatase (New England Biolabs Inc.). Then the small RNAs were ligated sequentially to 5' and 3' RNA/DNA chimeric oligonucleotide adaptors (Illumina). The ligation products were purified from 10% TBE urea polyacrylamide gel. Reverse transcription was performed with the ligated sRNAs as templates. The obtained cDNAs were sequenced using the Illumina 1 G Genome Analyzer by Beijing Genomics Institute (BGI) (Shenzhen, China).</p></sec><sec><title>Small RNA annotation and microRNA identification</title><p>Small RNA sequences were extracted from raw reads matching both the last 7 nt of the 5'-adaptor and the first 7 nt of the 3'-adaptor as described by Moxon et al. [<xref ref-type="bibr" rid="B23">23</xref>]. After trimming off the adaptors, sequences between 18 and 30 bp in length and reads more than 3 were used to search the Rfam database <ext-link ext-link-type="uri" xlink:href="http://www.sanger.ac.uk/Software/Rfam">http://www.sanger.ac.uk/Software/Rfam</ext-link> by BLASTN analysis to discard rRNA, tRNA, snRNA, and snoRNA. The remaining sequences were compared to known plant miRNAs from miRBase v13.0 [<xref ref-type="bibr" rid="B75">75</xref>] using BLASTN algorithm to search conserved miRNAs. Sequences in our libraries with identical or with four or fewer mismatches to currently known miRNAs from other plant species were regarded as potential conserved miRNAs. The potential miRNA sequences were used for BLASTN search against sweet orange unigene dataset and 1.2× coverage sequence of sweet orange (from NCBI), the perfectly matched sequences were used for fold-back structure prediction by Mfold program [<xref ref-type="bibr" rid="B59">59</xref>].</p><p>To identify non-conserved miRNAs from sweet orange, the remained sRNAs were used for BLASTN search against sweet orange ESTs from TIGR gene index database <ext-link ext-link-type="uri" xlink:href="http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/GO_browser.pl?species=Orange&gi_dir=csgi">http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/GO_browser.pl?species=Orange&gi_dir=csgi</ext-link> and 1.2× coverage sequence of sweet orange (from NCBI), since the sweet orange genome is not fully sequenced. The sequences of perfect match with sRNA sequences were used for fold-back structure prediction by Mfold program [<xref ref-type="bibr" rid="B59">59</xref>]. The sRNAs that have stem-loop precursors were regarded as putative non-conserved miRNAs. Furthermore, we searched miRNA* sequences (complementary to miRNA in the precursor molecule) in the sRNA libraries. Only those with miRNA-miRNA* duplexes were regarded as novel miRNAs.</p><p>Significance level of the difference of miRNA frequency and abundance between WT and MT was analyzed using Z-score method according to Kal et al. [<xref ref-type="bibr" rid="B76">76</xref>]. The significance of differentially expressed miRNAs were set at the <italic>p </italic>value < 0.01.</p></sec><sec><title>miRNA expression confirmation by stem-loop qRT-PCR</title><p>The detection of miRNA expression was performed using stem-loop qRT-PCR method according to Chen et al. [<xref ref-type="bibr" rid="B53">53</xref>] and Varkonyi-Gasic et al. [<xref ref-type="bibr" rid="B54">54</xref>]. Stem-loop primers for reverse transcription and primers for quantitative PCR were list in Additional file <xref ref-type="supplementary-material" rid="S12">12</xref>. Total RNA was reverse-transcribed using SuperScript III Reverse Transcriptase (Invitrogen, US) by a pulse reverse transcription program [<xref ref-type="bibr" rid="B54">54</xref>]. Real-time quantitative PCR (qPCR) was performed on the ABI 7500 Real Time System (PE Applied Biosystems, Foster City, CA, USA) using <italic>actin </italic>gene as endogenous control according to Liu et al. [<xref ref-type="bibr" rid="B11">11</xref>]. Briefly, the primers for miRNAs and <italic>actin </italic>were diluted in the SYBER GREEN PCR Master Mix (PE Applied Biosystems) and 20 μl of the reaction mix was added to each well. Reactions were performed by an initial incubation at 50°C for 2 min and at 95°C for 1 min, and then cycled at 95°C for 15 s and 60°C for 1 min for 40 cycles. Output data was generated by the instrument on-board software Sequence Detector Version 1.3.1 (PE Applied Biosystems). The electrophoresis of the PCR products was performed on 3% agarose gel for 1 hr under 70 V voltage. The marker contained two fragments, 50 and 60 bp in length, the sequences information was: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCCGATG and CGGCGAAGATTGAAGTGAAGGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTTCCGA respectively.</p></sec><sec><title>Target prediction of miRNAs</title><p>Target prediction of miRNAs from sweet orange was performed based on methods described by Pant et al. [<xref ref-type="bibr" rid="B24">24</xref>]. Two publicly available algorithms, miRU [<xref ref-type="bibr" rid="B56">56</xref>] and WMD3 [<xref ref-type="bibr" rid="B57">57</xref>] were used in the prediction. The sweet orange EST sequences from TIGR database as described earlier were used to predict the targets. The hybridization energy of each miRNA-predicted target duplex (ΔG) was determined from WMD3 output.</p></sec><sec><title>Functional assignments of the potential targets of differentially expressed miRNAs</title><p>To investigate biological processes possibly regulated by miRNAs, assignments of putative functions to potential target genes of differentially expressed miRNAs were performed using annot8r program, which was run locally to BLAST against a reference database that stores UniProt entries, their associated Gene Ontology (GO), Enzyme Commission (EC) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotations [<xref ref-type="bibr" rid="B77">77</xref>]. The GO categorization results were expressed as three independent hierarchies for biological process, cellular component, and molecular function [<xref ref-type="bibr" rid="B78">78</xref>]. The biological interpretation of the potential targets was further completed by assigning to metabolic pathways using KEGG [<xref ref-type="bibr" rid="B79">79</xref>].</p></sec><sec><title>The expression detection of two microRNAs target genes</title><p>The expression levels of one carotenoid biosynthesis gene (lycopene β-cyclase, LYCb) and one carbon fixation-related gene (phosphoenolpyruvate carboxylase, TC11997) were determined on the ABI 7500 Real Time System (PE Applied Biosystems, Foster City, CA, USA) using <italic>actin </italic>gene as endogenous control according to Liu et al. [<xref ref-type="bibr" rid="B11">11</xref>]. The primers are as following: TC11997: forward, GAGATGGTGCAGGCCAAGTT and reverse GTTGAGGAGGTCGCATGGTT; LYCb: forward, GGCTATATGGTGGCAAGGACTT and reverse, CAGAATTGAGGCTTCGAACGA. The data of in situ rates of photosynthesis in the mutant and the wildtype were extracted from our previous data [<xref ref-type="bibr" rid="B13">13</xref>].</p></sec></sec><sec><title>Data access</title><p>The small RNA sequence data from this study have been submitted to Gene Expression Omnibus (GEO) under accession No. GSE18207 at website: <ext-link ext-link-type="uri" xlink:href="http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=bvcnfememqckehi&acc=GSE18207">http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=bvcnfememqckehi&acc=GSE18207</ext-link></p></sec><sec><title>Abbreviations</title><p>AGO: ARGONAUTE; AP2: APETEAL2; bZIP: Basic zipper; DAF: Days after flowering; GO: Gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; miRNA: microRNA; NAC: NAM, ATAF, and CUC; PEPC: phosphoenolpyruvate carboxylase; rRNA: Ribosomal RNA; Rubisco: Ribulose-1,5-bisphosphate carboxylase oxygenase; SBP: Squamosa promoter-binding protein; snRNA: Small nuclear RNA; snoRNA: Small nucleolar RNA; sRNA: small RNA; siRNA: short interfering RNA; TPM: Transcripts per million; tRNA: transfer RNA.</p></sec><sec><title>Authors' contributions</title><p>QX, YLL, ADZ and KQY are responsible for generating the sRNA data and for interpretation of the results. YLL and JLY carried out qRT-PCR experiments. QX drafted the manuscript. XMW and WWG participated in research design and statistical analyses. XXD proposed and supervised the research. All authors read and approved the final manuscript.</p></sec><sec sec-type="supplementary-material"><title>Supplementary Material</title><supplementary-material content-type="local-data" id="S1"><caption><title>Additional file 1</title><p><bold>WT-derived sRNAs from coding RNA</bold>. This file contains the information of WT-derived sRNAs which were mapped on protein-coding EST genes from sweet orange (<italic>Citrus sinensis</italic>).</p></caption><media xlink:href="1471-2164-11-246-S1.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S2"><caption><title>Additional file 2</title><p><bold>MT-derived sRNAs from coding RNA</bold>. This file contains the information of MT-derived sRNAs which were mapped on protein-coding EST genes from sweet orange (<italic>Citrus sinensis</italic>).</p></caption><media xlink:href="1471-2164-11-246-S2.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S3"><caption><title>Additional file 3</title><p><bold>WT-derived sRNAs from non-coding RNA</bold>. The file lists WT-derived sRNAs which were mapped on non-protein coding RNAs (tRNA, snRNA, snoRNA and rRNA).</p></caption><media xlink:href="1471-2164-11-246-S3.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S4"><caption><title>Additional file 4</title><p><bold>MT-derived sRNAs from non-coding RNA</bold>. The file lists MT-derived sRNAs which were mapped on non-protein coding RNAs (tRNA, snRNA, snoRNA and rRNA).</p></caption><media xlink:href="1471-2164-11-246-S4.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S5"><caption><title>Additional file 5</title><p><bold>Known citrus miRNAs</bold>. Known citrus miRNAs and their expression in WT and MT sweet oranges.</p></caption><media xlink:href="1471-2164-11-246-S5.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S6"><caption><title>Additional file 6</title><p><bold>Fold-back structures for known miRNA from sweet orange (<italic>Citrus sinensis</italic>)</bold>. Precursor sequences for known miRNAs from sweet orange were shown in black letters with miRNA and miRNA* (The sequence complementary to miRNA in the fold-back structure) sequences highlighted in yellow and pink, respectively. Precursor secondary structures and dG value were produced using the mfold software <ext-link ext-link-type="uri" xlink:href="http://mfold.bioinfo.rpi.edu/">http://mfold.bioinfo.rpi.edu/</ext-link>.</p></caption><media xlink:href="1471-2164-11-246-S6.PDF" mimetype="application" mime-subtype="pdf"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S7"><caption><title>Additional file 7</title><p><bold>Target prediction of citrus known miRNAs</bold>. This file contains the predicted target genes for known miRNA genes in sweet orange.</p></caption><media xlink:href="1471-2164-11-246-S7.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S8"><caption><title>Additional file 8</title><p><bold>Fold-back structures for novel miRNAs from sweet orange (<italic>Citrus sinensis</italic>)</bold>. Precursor sequences for novel miRNA from sweet orange were shown in black letters with miRNA and miRNA* (The sequence complementary to miRNA in the fold-back structure) sequences highlighted in yellow and pink, respectively. Precursor secondary structures and dG value were produced using the mfold software <ext-link ext-link-type="uri" xlink:href="http://mfold.bioinfo.rpi.edu/">http://mfold.bioinfo.rpi.edu/</ext-link>.</p></caption><media xlink:href="1471-2164-11-246-S8.PDF" mimetype="application" mime-subtype="pdf"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S9"><caption><title>Additional file 9</title><p><bold>Target prediction of citrus novel miRNAs</bold>. This file contains the predicted target genes for novel miRNA genes in sweet orange.</p></caption><media xlink:href="1471-2164-11-246-S9.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S10"><caption><title>Additional file 10</title><p><bold>miRNA target genes are hotspots for generation small RNAs</bold>. This file contains the information of citrus sRNA loci located in miRNA-target genes in both sense and antisense way.</p></caption><media xlink:href="1471-2164-11-246-S10.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S11"><caption><title>Additional file 11</title><p><bold>The computational annotation of target genes of differential miRNA genes</bold>. This file shows the annotation information of citrus miRNA-target genes; the annotation was performed using arbidopsis homologous gene and Uniprot database.</p></caption><media xlink:href="1471-2164-11-246-S11.XLS" mimetype="application" mime-subtype="vnd.ms-excel"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S12"><caption><title>Additional file 12</title><p><bold>The primer sequence information</bold>. This file lists the primers used for miRNA expression detection by stem-loop qRT-PCR.</p></caption><media xlink:href="1471-2164-11-246-S12.PDF" mimetype="application" mime-subtype="pdf"><caption><p>Click here for file</p></caption></media></supplementary-material></sec></body><back><sec><title>Acknowledgements</title><p>We thank Dr. Hanhui Kuang from Huazhong Agricultural University (China) for their helpful suggestions on this study. This work was supported by the Natural Science Foundation of China (NSFC Nos. 30921002, 30830078 and 30800745), Specialized Research Fund for the Doctoral Program of Ministry of Education of China (No.200805041024), and Hubei Provincial Natural Science Foundation (2008CDB083).</p></sec><ref-list><ref id="B1"><mixed-citation publication-type="book"><name><surname>Spiegel-Roy</surname><given-names>P</given-names></name><name><surname>Goldschmidt</surname><given-names>EE</given-names></name><source>Biology of Citrus</source><year>1996</year><publisher-name>Cambridge, UK: Cambridge University Press</publisher-name></mixed-citation></ref><ref id="B2"><mixed-citation publication-type="journal"><name><surname>Jayaprakasha</surname><given-names>GK</given-names></name><name><surname>Patil</surname><given-names>BS</given-names></name><article-title>In vitro evaluation of the antioxidant activities in fruit extracts from citron and blood orange</article-title><source>Food Chem</source><year>2007</year><volume>101</volume><fpage>410</fpage><lpage>418</lpage><pub-id pub-id-type="doi">10.1016/j.foodchem.2005.12.038</pub-id></mixed-citation></ref><ref id="B3"><mixed-citation publication-type="journal"><name><surname>Bartley</surname><given-names>GE</given-names></name><name><surname>Scolnik</surname><given-names>PA</given-names></name><article-title>Plant carotenoids: pigments for photoprotection, visual attraction, and human health</article-title><source>Plant Cell</source><year>1995</year><volume>7</volume><fpage>1027</fpage><lpage>1038</lpage><pub-id pub-id-type="doi">10.1105/tpc.7.7.1027</pub-id><pub-id pub-id-type="pmid">7640523</pub-id></mixed-citation></ref><ref id="B4"><mixed-citation publication-type="journal"><name><surname>Rouseff</surname><given-names>R</given-names></name><name><surname>Raley</surname><given-names>L</given-names></name><name><surname>Hofsommer</surname><given-names>HJ</given-names></name><article-title>Application of diode array detection with a C-30 reversed phase column for the separation and identification of saponified orange juice carotenoids</article-title><source>J Agric Food Chem</source><year>1996</year><volume>44</volume><fpage>2176</fpage><lpage>2181</lpage><pub-id pub-id-type="doi">10.1021/jf950631q</pub-id></mixed-citation></ref><ref id="B5"><mixed-citation publication-type="journal"><name><surname>Lee</surname><given-names>HS</given-names></name><name><surname>Castle</surname><given-names>WS</given-names></name><article-title>Seasonal changes of carotenoid pigments and color in Hamlin, Earlygold, and budd blood orange juices</article-title><source>J Agric Food Chem</source><year>2001</year><volume>49</volume><fpage>877</fpage><lpage>882</lpage><pub-id pub-id-type="doi">10.1021/jf000654r</pub-id><pub-id pub-id-type="pmid">11262044</pub-id></mixed-citation></ref><ref id="B6"><mixed-citation publication-type="journal"><name><surname>Xu</surname><given-names>CJ</given-names></name><name><surname>Fraser</surname><given-names>PD</given-names></name><name><surname>Wang</surname><given-names>WJ</given-names></name><name><surname>Bramley</surname><given-names>PM</given-names></name><article-title>Differences in the carotenoid content of ordinary citrus and lycopene-accumulating mutants</article-title><source>J Agric Food Chem</source><year>2006</year><volume>54</volume><fpage>5474</fpage><lpage>5481</lpage><pub-id pub-id-type="doi">10.1021/jf060702t</pub-id><pub-id pub-id-type="pmid">16848534</pub-id></mixed-citation></ref><ref id="B7"><mixed-citation publication-type="journal"><name><surname>Kato</surname><given-names>M</given-names></name><name><surname>Ikoma</surname><given-names>Y</given-names></name><name><surname>Matsumoto</surname><given-names>H</given-names></name><name><surname>Sugiura</surname><given-names>M</given-names></name><name><surname>Hyodo</surname><given-names>H</given-names></name><name><surname>Yano</surname><given-names>M</given-names></name><article-title>Accumulation of carotenoids and expression of carotenoid biosynthetic genes during maturation in citrus fruit</article-title><source>Plant Physiol</source><year>2004</year><volume>134</volume><fpage>824</fpage><lpage>837</lpage><pub-id pub-id-type="doi">10.1104/pp.103.031104</pub-id><pub-id pub-id-type="pmid">14739348</pub-id></mixed-citation></ref><ref id="B8"><mixed-citation publication-type="journal"><name><surname>Schwarz</surname><given-names>S</given-names></name><name><surname>Obermuller-Jevic</surname><given-names>UC</given-names></name><name><surname>Hellmis</surname><given-names>E</given-names></name><name><surname>Koch</surname><given-names>W</given-names></name><name><surname>Jacobi</surname><given-names>G</given-names></name><name><surname>Biesalski</surname><given-names>HK</given-names></name><article-title>Lycopene inhibits disease progression in patients with benign prostate hyperplasia</article-title><source>J Nutr</source><year>2008</year><volume>138</volume><fpage>49</fpage><lpage>53</lpage><pub-id pub-id-type="pmid">18156403</pub-id></mixed-citation></ref><ref id="B9"><mixed-citation publication-type="journal"><name><surname>Monselise</surname><given-names>SP</given-names></name><name><surname>Halevy</surname><given-names>AH</given-names></name><article-title>Detection of lycopene in pink orange fruit</article-title><source>Science</source><year>1961</year><volume>133</volume><fpage>1478</fpage><pub-id pub-id-type="doi">10.1126/science.133.3463.1478</pub-id><pub-id pub-id-type="pmid">13772077</pub-id></mixed-citation></ref><ref id="B10"><mixed-citation publication-type="book"><name><surname>Saunt</surname><given-names>J</given-names></name><source>Citrus Varieties of the World</source><year>2000</year><publisher-name>Norwich, England: Sinclair International Ltd</publisher-name></mixed-citation></ref><ref id="B11"><mixed-citation publication-type="journal"><name><surname>Liu</surname><given-names>Q</given-names></name><name><surname>Xu</surname><given-names>J</given-names></name><name><surname>Liu</surname><given-names>YZ</given-names></name><name><surname>Zhao</surname><given-names>XL</given-names></name><name><surname>Deng</surname><given-names>XX</given-names></name><name><surname>Guo</surname><given-names>LL</given-names></name><name><surname>Gu</surname><given-names>JQ</given-names></name><article-title>A novel bud mutation that confers abnormal patterns of lycopene accumulation in sweet orange fruit (<italic>Citrus sinensis </italic>L. Osbeck)</article-title><source>J Exp Bot</source><year>2007</year><volume>58</volume><fpage>4161</fpage><lpage>4171</lpage><pub-id pub-id-type="doi">10.1093/jxb/erm273</pub-id><pub-id pub-id-type="pmid">18182424</pub-id></mixed-citation></ref><ref id="B12"><mixed-citation publication-type="journal"><name><surname>Liu</surname><given-names>Q</given-names></name><name><surname>Zhu</surname><given-names>A</given-names></name><name><surname>Chai</surname><given-names>LJ</given-names></name><name><surname>Zhou</surname><given-names>WJ</given-names></name><name><surname>Yu</surname><given-names>KQ</given-names></name><name><surname>Ding</surname><given-names>J</given-names></name><name><surname>Xu</surname><given-names>J</given-names></name><name><surname>Deng</surname><given-names>XX</given-names></name><article-title>Transcriptome analysis of a spontaneous mutant in sweet orange [<italic>Citrus sinensis </italic>(L.) Osbeck] during fruit development</article-title><source>J Exp Bot</source><year>2009</year><volume>60</volume><fpage>801</fpage><lpage>813</lpage><pub-id pub-id-type="doi">10.1093/jxb/ern329</pub-id><pub-id pub-id-type="pmid">19218315</pub-id></mixed-citation></ref><ref id="B13"><mixed-citation publication-type="journal"><name><surname>Xu</surname><given-names>Q</given-names></name><name><surname>Yu</surname><given-names>KQ</given-names></name><name><surname>Zhu</surname><given-names>AD</given-names></name><name><surname>Ye</surname><given-names>JL</given-names></name><name><surname>Liu</surname><given-names>Q</given-names></name><name><surname>Zhang</surname><given-names>JC</given-names></name><name><surname>Deng</surname><given-names>X</given-names></name><article-title>Comparative transcripts profiling reveals new insight into molecular processes regulating lycopene accumulation in a sweet orange (<italic>Citrus sinensis</italic>) red-flesh mutant</article-title><source>BMC Genomics</source><year>2009</year><volume>10</volume><fpage>540</fpage><pub-id pub-id-type="doi">10.1186/1471-2164-10-540</pub-id><pub-id pub-id-type="pmid">19922663</pub-id></mixed-citation></ref><ref id="B14"><mixed-citation publication-type="journal"><name><surname>Pan</surname><given-names>ZY</given-names></name><name><surname>Liu</surname><given-names>Q</given-names></name><name><surname>Yun</surname><given-names>Z</given-names></name><name><surname>Guan</surname><given-names>R</given-names></name><name><surname>Zeng</surname><given-names>WF</given-names></name><name><surname>Xu</surname><given-names>Q</given-names></name><name><surname>Deng</surname><given-names>XX</given-names></name><article-title>Comparative proteomics of a lycopene-accumulating mutant reveals the important role of oxidative stress on carotenogenesis in sweet orange (<italic>Citrus sinensis </italic>[L.] Osbeck)</article-title><source>Proteomics</source><year>2009</year><volume>9</volume><fpage>5455</fpage><lpage>5470</lpage><pub-id pub-id-type="doi">10.1002/pmic.200900092</pub-id><pub-id pub-id-type="pmid">19834898</pub-id></mixed-citation></ref><ref id="B15"><mixed-citation publication-type="journal"><name><surname>Welsch</surname><given-names>R</given-names></name><name><surname>Maass</surname><given-names>D</given-names></name><name><surname>Voegel</surname><given-names>T</given-names></name><name><surname>Dellapenna</surname><given-names>D</given-names></name><name><surname>Beyer</surname><given-names>P</given-names></name><article-title>Transcription factor RAP2.2 and its interacting partner SINAT2: stable elements in the carotenogenesis of Arabidopsis leaves</article-title><source>Plant Physiol</source><year>2007</year><volume>145</volume><fpage>1073</fpage><lpage>1085</lpage><pub-id pub-id-type="doi">10.1104/pp.107.104828</pub-id><pub-id pub-id-type="pmid">17873090</pub-id></mixed-citation></ref><ref id="B16"><mixed-citation publication-type="journal"><name><surname>Bartel</surname><given-names>DP</given-names></name><article-title>MicroRNAs: target recognition and regulatory functions</article-title><source>Cell</source><year>2009</year><volume>136</volume><fpage>215</fpage><lpage>233</lpage><pub-id pub-id-type="doi">10.1016/j.cell.2009.01.002</pub-id><pub-id pub-id-type="pmid">19167326</pub-id></mixed-citation></ref><ref id="B17"><mixed-citation publication-type="journal"><name><surname>Vaucheret</surname><given-names>H</given-names></name><article-title>Post-transcriptional small RNA pathways in plants: mechanisms and regulations</article-title><source>Genes Dev</source><year>2006</year><volume>20</volume><fpage>759</fpage><lpage>771</lpage><pub-id pub-id-type="doi">10.1101/gad.1410506</pub-id><pub-id pub-id-type="pmid">16600909</pub-id></mixed-citation></ref><ref id="B18"><mixed-citation publication-type="journal"><name><surname>Jones-Rhoades</surname><given-names>MW</given-names></name><name><surname>Bartel</surname><given-names>DP</given-names></name><article-title>Computational identification of plant MicroRNAs and their targets, including a stress-induced miRNA</article-title><source>Mol Cell</source><year>2004</year><volume>14</volume><fpage>787</fpage><lpage>799</lpage><pub-id pub-id-type="doi">10.1016/j.molcel.2004.05.027</pub-id><pub-id pub-id-type="pmid">15200956</pub-id></mixed-citation></ref><ref id="B19"><mixed-citation publication-type="journal"><name><surname>Sunkar</surname><given-names>R</given-names></name><name><surname>Zhu</surname><given-names>JK</given-names></name><article-title>Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis</article-title><source>Plant Cell</source><year>2004</year><volume>16</volume><fpage>2001</fpage><lpage>2019</lpage><pub-id pub-id-type="doi">10.1105/tpc.104.022830</pub-id><pub-id pub-id-type="pmid">15258262</pub-id></mixed-citation></ref><ref id="B20"><mixed-citation publication-type="journal"><name><surname>Lu</surname><given-names>S</given-names></name><name><surname>Sun</surname><given-names>YH</given-names></name><name><surname>Shi</surname><given-names>R</given-names></name><name><surname>Clark</surname><given-names>C</given-names></name><name><surname>Li</surname><given-names>L</given-names></name><name><surname>Chiang</surname><given-names>VL</given-names></name><article-title>Novel and mechanical stress-responsive MicroRNAs in <italic>Populus trichocarpa </italic>that are absent from Arabidopsis</article-title><source>Plant Cell</source><year>2005</year><volume>17</volume><fpage>2186</fpage><lpage>2203</lpage><pub-id pub-id-type="doi">10.1105/tpc.105.033456</pub-id><pub-id pub-id-type="pmid">15994906</pub-id></mixed-citation></ref><ref id="B21"><mixed-citation publication-type="journal"><name><surname>Mallory</surname><given-names>AC</given-names></name><name><surname>Vaucheret</surname><given-names>H</given-names></name><article-title>Functions of microRNAs and related small RNAs in plants</article-title><source>Nat Genet</source><year>2006</year><volume>38</volume><fpage>S31</fpage><lpage>36</lpage><pub-id pub-id-type="doi">10.1038/ng1791</pub-id><pub-id pub-id-type="pmid">16736022</pub-id></mixed-citation></ref><ref id="B22"><mixed-citation publication-type="journal"><name><surname>Aung</surname><given-names>K</given-names></name><name><surname>Lin</surname><given-names>SI</given-names></name><name><surname>Wu</surname><given-names>CC</given-names></name><name><surname>Huang</surname><given-names>YT</given-names></name><name><surname>Su</surname><given-names>CL</given-names></name><name><surname>Chiou</surname><given-names>TJ</given-names></name><article-title>pho2, a phosphate overaccumulator, is caused by a nonsense mutation in a MicroRNA399 target gene</article-title><source>Plant Physiol</source><year>2006</year><volume>141</volume><fpage>1000</fpage><lpage>1011</lpage><pub-id pub-id-type="doi">10.1104/pp.106.078063</pub-id><pub-id pub-id-type="pmid">16679417</pub-id></mixed-citation></ref><ref id="B23"><mixed-citation publication-type="journal"><name><surname>Moxon</surname><given-names>S</given-names></name><name><surname>Jing</surname><given-names>R</given-names></name><name><surname>Szittya</surname><given-names>G</given-names></name><name><surname>Schwach</surname><given-names>F</given-names></name><name><surname>Rusholme Pilcher</surname><given-names>RL</given-names></name><name><surname>Moulton</surname><given-names>V</given-names></name><name><surname>Dalmay</surname><given-names>T</given-names></name><article-title>Deep sequencing of tomato short RNAs identifies microRNAs targeting genes involved in fruit ripening</article-title><source>Genome Res</source><year>2008</year><volume>18</volume><fpage>1602</fpage><lpage>1609</lpage><pub-id pub-id-type="doi">10.1101/gr.080127.108</pub-id><pub-id pub-id-type="pmid">18653800</pub-id></mixed-citation></ref><ref id="B24"><mixed-citation publication-type="journal"><name><surname>Pant</surname><given-names>BD</given-names></name><name><surname>Musialak-Lange</surname><given-names>M</given-names></name><name><surname>Nuc</surname><given-names>P</given-names></name><name><surname>May</surname><given-names>P</given-names></name><name><surname>Buhtz</surname><given-names>A</given-names></name><name><surname>Kehr</surname><given-names>J</given-names></name><name><surname>Walther</surname><given-names>D</given-names></name><name><surname>Scheible</surname><given-names>WR</given-names></name><article-title>Identification of nutrient-responsive Arabidopsis and rapeseed microRNAs by comprehensive real-time polymerase chain reaction profiling and small RNA sequencing</article-title><source>Plant Physiol</source><year>2009</year><volume>150</volume><fpage>1541</fpage><lpage>1555</lpage><pub-id pub-id-type="doi">10.1104/pp.109.139139</pub-id><pub-id pub-id-type="pmid">19465578</pub-id></mixed-citation></ref><ref id="B25"><mixed-citation publication-type="journal"><name><surname>Ramachandran</surname><given-names>V</given-names></name><name><surname>Chen</surname><given-names>X</given-names></name><article-title>Small RNA metabolism in Arabidopsis</article-title><source>Trends Plant Sci</source><year>2008</year><volume>13</volume><fpage>368</fpage><lpage>374</lpage><pub-id pub-id-type="doi">10.1016/j.tplants.2008.03.008</pub-id><pub-id pub-id-type="pmid">18501663</pub-id></mixed-citation></ref><ref id="B26"><mixed-citation publication-type="journal"><name><surname>Llave</surname><given-names>C</given-names></name><name><surname>Kasschau</surname><given-names>KD</given-names></name><name><surname>Rector</surname><given-names>MA</given-names></name><name><surname>Carrington</surname><given-names>JC</given-names></name><article-title>Endogenous and silencing-associated small RNAs in plants</article-title><source>Plant Cell</source><year>2002</year><volume>14</volume><fpage>1605</fpage><lpage>1619</lpage><pub-id pub-id-type="doi">10.1105/tpc.003210</pub-id><pub-id pub-id-type="pmid">12119378</pub-id></mixed-citation></ref><ref id="B27"><mixed-citation publication-type="journal"><name><surname>Lindow</surname><given-names>M</given-names></name><name><surname>Krogh</surname><given-names>A</given-names></name><article-title>Computational evidence for hundreds of non-conserved plant microRNAs</article-title><source>BMC Genomics</source><year>2005</year><volume>6</volume><fpage>119</fpage><pub-id pub-id-type="doi">10.1186/1471-2164-6-119</pub-id><pub-id pub-id-type="pmid">16159385</pub-id></mixed-citation></ref><ref id="B28"><mixed-citation publication-type="journal"><name><surname>Rajagopalan</surname><given-names>R</given-names></name><name><surname>Vaucheret</surname><given-names>H</given-names></name><name><surname>Trejo</surname><given-names>J</given-names></name><name><surname>Bartel</surname><given-names>DP</given-names></name><article-title>A diverse and evolutionarily fluid set of microRNAs in <italic>Arabidopsis thaliana</italic></article-title><source>Genes Dev</source><year>2006</year><volume>20</volume><fpage>3407</fpage><lpage>3425</lpage><pub-id pub-id-type="doi">10.1101/gad.1476406</pub-id><pub-id pub-id-type="pmid">17182867</pub-id></mixed-citation></ref><ref id="B29"><mixed-citation publication-type="journal"><name><surname>Jones-Rhoades</surname><given-names>MW</given-names></name><name><surname>Bartel</surname><given-names>DP</given-names></name><name><surname>Bartel</surname><given-names>B</given-names></name><article-title>MicroRNAs and their regulatory roles in plants</article-title><source>Annu Rev Plant Biol</source><year>2006</year><volume>57</volume><fpage>19</fpage><lpage>53</lpage><pub-id pub-id-type="doi">10.1146/annurev.arplant.57.032905.105218</pub-id><pub-id pub-id-type="pmid">16669754</pub-id></mixed-citation></ref><ref id="B30"><mixed-citation publication-type="journal"><name><surname>Wang</surname><given-names>JF</given-names></name><name><surname>Zhou</surname><given-names>H</given-names></name><name><surname>Chen</surname><given-names>YQ</given-names></name><name><surname>Luo</surname><given-names>QJ</given-names></name><name><surname>Qu</surname><given-names>LH</given-names></name><article-title>Identification of 20 microRNAs from <italic>Oryza sativa</italic></article-title><source>Nucleic Acids Res</source><year>2004</year><volume>32</volume><fpage>1688</fpage><lpage>1695</lpage><pub-id pub-id-type="doi">10.1093/nar/gkh332</pub-id><pub-id pub-id-type="pmid">15020705</pub-id></mixed-citation></ref><ref id="B31"><mixed-citation publication-type="journal"><name><surname>Sunkar</surname><given-names>R</given-names></name><name><surname>Girke</surname><given-names>T</given-names></name><name><surname>Jain</surname><given-names>PK</given-names></name><name><surname>Zhu</surname><given-names>JK</given-names></name><article-title>Cloning and characterization of microRNAs from rice</article-title><source>Plant Cell</source><year>2005</year><volume>17</volume><fpage>1397</fpage><lpage>1411</lpage><pub-id pub-id-type="doi">10.1105/tpc.105.031682</pub-id><pub-id pub-id-type="pmid">15805478</pub-id></mixed-citation></ref><ref id="B32"><mixed-citation publication-type="journal"><name><surname>Bonnet</surname><given-names>E</given-names></name><name><surname>Wuyts</surname><given-names>J</given-names></name><name><surname>Rouze</surname><given-names>P</given-names></name><name><surname>Peer</surname><given-names>Y Van de</given-names></name><article-title>Detection of 91 potential conserved plant microRNAs in <italic>Arabidopsis thaliana </italic>and <italic>Oryza sativa </italic>identifies important target genes</article-title><source>Proc Natl Acad Sci USA</source><year>2004</year><volume>101</volume><fpage>11511</fpage><lpage>11516</lpage><pub-id pub-id-type="doi">10.1073/pnas.0404025101</pub-id><pub-id pub-id-type="pmid">15272084</pub-id></mixed-citation></ref><ref id="B33"><mixed-citation publication-type="journal"><name><surname>Adai</surname><given-names>A</given-names></name><name><surname>Johnson</surname><given-names>C</given-names></name><name><surname>Mlotshwa</surname><given-names>S</given-names></name><name><surname>Archer-Evans</surname><given-names>S</given-names></name><name><surname>Manocha</surname><given-names>V</given-names></name><name><surname>Vance</surname><given-names>V</given-names></name><name><surname>Sundaresan</surname><given-names>V</given-names></name><article-title>Computational prediction of miRNAs in <italic>Arabidopsis thaliana</italic></article-title><source>Genome Res</source><year>2005</year><volume>15</volume><fpage>78</fpage><lpage>91</lpage><pub-id pub-id-type="doi">10.1101/gr.2908205</pub-id><pub-id pub-id-type="pmid">15632092</pub-id></mixed-citation></ref><ref id="B34"><mixed-citation publication-type="journal"><name><surname>Zhang</surname><given-names>BH</given-names></name><name><surname>Pan</surname><given-names>XP</given-names></name><name><surname>Wang</surname><given-names>QL</given-names></name><name><surname>Cobb</surname><given-names>GP</given-names></name><name><surname>Anderson</surname><given-names>TA</given-names></name><article-title>Identification and characterization of new plant microRNAs using EST analysis</article-title><source>Cell Res</source><year>2005</year><volume>15</volume><fpage>336</fpage><lpage>360</lpage><pub-id pub-id-type="doi">10.1038/sj.cr.7290302</pub-id><pub-id pub-id-type="pmid">15916721</pub-id></mixed-citation></ref><ref id="B35"><mixed-citation publication-type="journal"><name><surname>Gleave</surname><given-names>AP</given-names></name><name><surname>Ampomah-Dwamena</surname><given-names>C</given-names></name><name><surname>Berthold</surname><given-names>S</given-names></name><name><surname>Dejnoprat</surname><given-names>S</given-names></name><name><surname>Karunairetnam</surname><given-names>S</given-names></name><name><surname>Nain</surname><given-names>B</given-names></name><name><surname>Wang</surname><given-names>Y-Y</given-names></name><name><surname>Crowhurst</surname><given-names>RN</given-names></name><name><surname>MacDiarmid</surname><given-names>RM</given-names></name><article-title>Identification and characterization of primary microRNAs from apple (<italic>Malus domestica </italic>cv. Royal Gala) exprssed sequence tags</article-title><source>Tree Genet Genomes</source><year>2008</year><volume>4</volume><fpage>343</fpage><lpage>358</lpage><pub-id pub-id-type="doi">10.1007/s11295-007-0113-1</pub-id></mixed-citation></ref><ref id="B36"><mixed-citation publication-type="journal"><name><surname>Song</surname><given-names>C</given-names></name><name><surname>Fang</surname><given-names>J</given-names></name><name><surname>Li</surname><given-names>X</given-names></name><name><surname>Liu</surname><given-names>H</given-names></name><name><surname>Thomas Chao</surname><given-names>C</given-names></name><article-title>Identification and characterization of 27 conserved microRNAs in citrus</article-title><source>Planta</source><year>2009</year><volume>230</volume><fpage>671</fpage><lpage>685</lpage><pub-id pub-id-type="doi">10.1007/s00425-009-0971-x</pub-id><pub-id pub-id-type="pmid">19585144</pub-id></mixed-citation></ref><ref id="B37"><mixed-citation publication-type="journal"><name><surname>Morin</surname><given-names>RD</given-names></name><name><surname>Aksay</surname><given-names>G</given-names></name><name><surname>Dolgosheina</surname><given-names>E</given-names></name><name><surname>Ebhardt</surname><given-names>HA</given-names></name><name><surname>Magrini</surname><given-names>V</given-names></name><name><surname>Mardis</surname><given-names>ER</given-names></name><name><surname>Sahinalp</surname><given-names>SC</given-names></name><name><surname>Unrau</surname><given-names>PJ</given-names></name><article-title>Comparative analysis of the small RNA transcriptomes of <italic>Pinus contorta </italic>and <italic>Oryza sativa</italic></article-title><source>Genome Res</source><year>2008</year><volume>18</volume><fpage>571</fpage><lpage>584</lpage><pub-id pub-id-type="doi">10.1101/gr.6897308</pub-id><pub-id pub-id-type="pmid">18323537</pub-id></mixed-citation></ref><ref id="B38"><mixed-citation publication-type="journal"><name><surname>Lu</surname><given-names>C</given-names></name><name><surname>Tej</surname><given-names>SS</given-names></name><name><surname>Luo</surname><given-names>S</given-names></name><name><surname>Haudenschild</surname><given-names>CD</given-names></name><name><surname>Meyers</surname><given-names>BC</given-names></name><name><surname>Green</surname><given-names>PJ</given-names></name><article-title>Elucidation of the small RNA component of the transcriptome</article-title><source>Science</source><year>2005</year><volume>309</volume><fpage>1567</fpage><lpage>1569</lpage><pub-id pub-id-type="doi">10.1126/science.1114112</pub-id><pub-id pub-id-type="pmid">16141074</pub-id></mixed-citation></ref><ref id="B39"><mixed-citation publication-type="journal"><name><surname>Lu</surname><given-names>C</given-names></name><name><surname>Kulkarni</surname><given-names>K</given-names></name><name><surname>Souret</surname><given-names>FF</given-names></name><name><surname>MuthuValliappan</surname><given-names>R</given-names></name><name><surname>Tej</surname><given-names>SS</given-names></name><name><surname>Poethig</surname><given-names>RS</given-names></name><name><surname>Henderson</surname><given-names>IR</given-names></name><name><surname>Jacobsen</surname><given-names>SE</given-names></name><name><surname>Wang</surname><given-names>W</given-names></name><name><surname>Green</surname><given-names>PJ</given-names></name><etal></etal><article-title>MicroRNAs and other small RNAs enriched in the Arabidopsis RNA-dependent RNA polymerase-2 mutant</article-title><source>Genome Res</source><year>2006</year><volume>16</volume><fpage>1276</fpage><lpage>1288</lpage><pub-id pub-id-type="doi">10.1101/gr.5530106</pub-id><pub-id pub-id-type="pmid">16954541</pub-id></mixed-citation></ref><ref id="B40"><mixed-citation publication-type="journal"><name><surname>Fahlgren</surname><given-names>N</given-names></name><name><surname>Howell</surname><given-names>MD</given-names></name><name><surname>Kasschau</surname><given-names>KD</given-names></name><name><surname>Chapman</surname><given-names>EJ</given-names></name><name><surname>Sullivan</surname><given-names>CM</given-names></name><name><surname>Cumbie</surname><given-names>JS</given-names></name><name><surname>Givan</surname><given-names>SA</given-names></name><name><surname>Law</surname><given-names>TF</given-names></name><name><surname>Grant</surname><given-names>SR</given-names></name><name><surname>Dangl</surname><given-names>JL</given-names></name><etal></etal><article-title>High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes</article-title><source>PLoS One</source><year>2007</year><volume>2</volume><fpage>e219</fpage><pub-id pub-id-type="doi">10.1371/journal.pone.0000219</pub-id><pub-id pub-id-type="pmid">17299599</pub-id></mixed-citation></ref><ref id="B41"><mixed-citation publication-type="journal"><name><surname>Nobuta</surname><given-names>K</given-names></name><name><surname>Venu</surname><given-names>RC</given-names></name><name><surname>Lu</surname><given-names>C</given-names></name><name><surname>Belo</surname><given-names>A</given-names></name><name><surname>Vemaraju</surname><given-names>K</given-names></name><name><surname>Kulkarni</surname><given-names>K</given-names></name><name><surname>Wang</surname><given-names>W</given-names></name><name><surname>Pillay</surname><given-names>M</given-names></name><name><surname>Green</surname><given-names>PJ</given-names></name><name><surname>Wang</surname><given-names>GL</given-names></name><etal></etal><article-title>An expression atlas of rice mRNAs and small RNAs</article-title><source>Nat Biotechnol</source><year>2007</year><volume>25</volume><fpage>473</fpage><lpage>477</lpage><pub-id pub-id-type="doi">10.1038/nbt1291</pub-id><pub-id pub-id-type="pmid">17351617</pub-id></mixed-citation></ref><ref id="B42"><mixed-citation publication-type="journal"><name><surname>Lu</surname><given-names>C</given-names></name><name><surname>Jeong</surname><given-names>DH</given-names></name><name><surname>Kulkarni</surname><given-names>K</given-names></name><name><surname>Pillay</surname><given-names>M</given-names></name><name><surname>Nobuta</surname><given-names>K</given-names></name><name><surname>German</surname><given-names>R</given-names></name><name><surname>Thatcher</surname><given-names>SR</given-names></name><name><surname>Maher</surname><given-names>C</given-names></name><name><surname>Zhang</surname><given-names>L</given-names></name><name><surname>Ware</surname><given-names>D</given-names></name><etal></etal><article-title>Genome-wide analysis for discovery of rice microRNAs reveals natural antisense microRNAs (nat-miRNAs)</article-title><source>Proc Natl Acad Sci USA</source><year>2008</year><volume>105</volume><fpage>4951</fpage><lpage>4956</lpage><pub-id pub-id-type="doi">10.1073/pnas.0708743105</pub-id><pub-id pub-id-type="pmid">18353984</pub-id></mixed-citation></ref><ref id="B43"><mixed-citation publication-type="journal"><name><surname>Sunkar</surname><given-names>R</given-names></name><name><surname>Zhou</surname><given-names>X</given-names></name><name><surname>Zheng</surname><given-names>Y</given-names></name><name><surname>Zhang</surname><given-names>W</given-names></name><name><surname>Zhu</surname><given-names>JK</given-names></name><article-title>Identification of novel and candidate miRNAs in rice by high throughput sequencing</article-title><source>BMC Plant Biol</source><year>2008</year><volume>8</volume><fpage>25</fpage><pub-id pub-id-type="doi">10.1186/1471-2229-8-25</pub-id><pub-id pub-id-type="pmid">18312648</pub-id></mixed-citation></ref><ref id="B44"><mixed-citation publication-type="journal"><name><surname>Xue</surname><given-names>LJ</given-names></name><name><surname>Zhang</surname><given-names>JJ</given-names></name><name><surname>Xue</surname><given-names>HW</given-names></name><article-title>Characterization and expression profiles of miRNAs in rice seeds</article-title><source>Nucleic Acids Res</source><year>2009</year><volume>37</volume><fpage>916</fpage><lpage>930</lpage><pub-id pub-id-type="doi">10.1093/nar/gkn998</pub-id><pub-id pub-id-type="pmid">19103661</pub-id></mixed-citation></ref><ref id="B45"><mixed-citation publication-type="journal"><name><surname>Axtell</surname><given-names>MJ</given-names></name><name><surname>Snyder</surname><given-names>JA</given-names></name><name><surname>Bartell</surname><given-names>DP</given-names></name><article-title>Common functions for diverse small RNAs of land plants</article-title><source>Plant Cell</source><year>2007</year><volume>19</volume><fpage>1750</fpage><lpage>1769</lpage><pub-id pub-id-type="doi">10.1105/tpc.107.051706</pub-id><pub-id pub-id-type="pmid">17601824</pub-id></mixed-citation></ref><ref id="B46"><mixed-citation publication-type="journal"><name><surname>Barakat</surname><given-names>A</given-names></name><name><surname>Wall</surname><given-names>K</given-names></name><name><surname>Leebens-Mack</surname><given-names>J</given-names></name><name><surname>Wang</surname><given-names>YJ</given-names></name><name><surname>Carlson</surname><given-names>JE</given-names></name><name><surname>dePamphilis</surname><given-names>CW</given-names></name><article-title>Large-scale identification of microRNAs from a basal eudicot (<italic>Eschscholzia californica</italic>) and conservation in flowering plants</article-title><source>Plant J</source><year>2007</year><volume>51</volume><fpage>991</fpage><lpage>1003</lpage><pub-id pub-id-type="doi">10.1111/j.1365-313X.2007.03197.x</pub-id><pub-id pub-id-type="pmid">17635767</pub-id></mixed-citation></ref><ref id="B47"><mixed-citation publication-type="journal"><name><surname>Barakat</surname><given-names>A</given-names></name><name><surname>Wall</surname><given-names>PK</given-names></name><name><surname>Diloreto</surname><given-names>S</given-names></name><name><surname>Depamphilis</surname><given-names>CW</given-names></name><name><surname>Carlson</surname><given-names>JE</given-names></name><article-title>Conservation and divergence of microRNAs in Populus</article-title><source>BMC Genomics</source><year>2007</year><volume>8</volume><fpage>481</fpage><pub-id pub-id-type="doi">10.1186/1471-2164-8-481</pub-id><pub-id pub-id-type="pmid">18166134</pub-id></mixed-citation></ref><ref id="B48"><mixed-citation publication-type="journal"><name><surname>Molnar</surname><given-names>A</given-names></name><name><surname>Schwach</surname><given-names>F</given-names></name><name><surname>Studholme</surname><given-names>DJ</given-names></name><name><surname>Thuenemann</surname><given-names>EC</given-names></name><name><surname>Baulcombe</surname><given-names>DC</given-names></name><article-title>miRNAs control gene expression in the single-cell alga <italic>Chlamydomonas reinhardtii</italic></article-title><source>Nature</source><year>2007</year><volume>447</volume><fpage>1126</fpage><lpage>1129</lpage><pub-id pub-id-type="doi">10.1038/nature05903</pub-id><pub-id pub-id-type="pmid">17538623</pub-id></mixed-citation></ref><ref id="B49"><mixed-citation publication-type="journal"><name><surname>Yao</surname><given-names>Y</given-names></name><name><surname>Guo</surname><given-names>G</given-names></name><name><surname>Ni</surname><given-names>Z</given-names></name><name><surname>Sunkar</surname><given-names>R</given-names></name><name><surname>Du</surname><given-names>J</given-names></name><name><surname>Zhu</surname><given-names>JK</given-names></name><name><surname>Sun</surname><given-names>Q</given-names></name><article-title>Cloning and characterization of microRNAs from wheat (<italic>Triticum aestivum </italic>L.)</article-title><source>Genome Biol</source><year>2007</year><volume>8</volume><fpage>R96</fpage><pub-id pub-id-type="doi">10.1186/gb-2007-8-6-r96</pub-id><pub-id pub-id-type="pmid">17543110</pub-id></mixed-citation></ref><ref id="B50"><mixed-citation publication-type="journal"><name><surname>Qiu</surname><given-names>D</given-names></name><name><surname>Pan</surname><given-names>X</given-names></name><name><surname>Wilson</surname><given-names>IW</given-names></name><name><surname>Li</surname><given-names>F</given-names></name><name><surname>Liu</surname><given-names>M</given-names></name><name><surname>Teng</surname><given-names>W</given-names></name><name><surname>Zhang</surname><given-names>B</given-names></name><article-title>High throughput sequencing technology reveals that the taxoid elicitor methyl jasmonate regulates microRNA expression in Chinese yew (<italic>Taxus chinensis</italic>)</article-title><source>Gene</source><year>2009</year><volume>436</volume><fpage>37</fpage><lpage>44</lpage><pub-id pub-id-type="doi">10.1016/j.gene.2009.01.006</pub-id><pub-id pub-id-type="pmid">19393185</pub-id></mixed-citation></ref><ref id="B51"><mixed-citation publication-type="journal"><name><surname>Meyers</surname><given-names>BC</given-names></name><name><surname>Axtell</surname><given-names>MJ</given-names></name><name><surname>Bartel</surname><given-names>B</given-names></name><name><surname>Bartel</surname><given-names>DP</given-names></name><name><surname>Baulcombe</surname><given-names>D</given-names></name><name><surname>Bowman</surname><given-names>JL</given-names></name><name><surname>Cao</surname><given-names>X</given-names></name><name><surname>Carrington</surname><given-names>JC</given-names></name><name><surname>Chen</surname><given-names>X</given-names></name><name><surname>Green</surname><given-names>PJ</given-names></name><etal></etal><article-title>Criteria for annotation of plant MicroRNAs</article-title><source>Plant Cell</source><year>2008</year><volume>20</volume><fpage>3186</fpage><lpage>3190</lpage><pub-id pub-id-type="doi">10.1105/tpc.108.064311</pub-id><pub-id pub-id-type="pmid">19074682</pub-id></mixed-citation></ref><ref id="B52"><mixed-citation publication-type="journal"><name><surname>Ambros</surname><given-names>V</given-names></name><name><surname>Bartel</surname><given-names>B</given-names></name><name><surname>Bartel</surname><given-names>DP</given-names></name><name><surname>Burge</surname><given-names>CB</given-names></name><name><surname>Carrington</surname><given-names>JC</given-names></name><name><surname>Chen</surname><given-names>XM</given-names></name><name><surname>Dreyfuss</surname><given-names>G</given-names></name><name><surname>Eddy</surname><given-names>SR</given-names></name><name><surname>Griffiths-Jones</surname><given-names>S</given-names></name><name><surname>Marshall</surname><given-names>M</given-names></name><etal></etal><article-title>A uniform system for microRNA annotation</article-title><source>RNA</source><year>2003</year><volume>9</volume><fpage>277</fpage><lpage>279</lpage><pub-id pub-id-type="doi">10.1261/rna.2183803</pub-id><pub-id pub-id-type="pmid">12592000</pub-id></mixed-citation></ref><ref id="B53"><mixed-citation publication-type="journal"><name><surname>Chen</surname><given-names>C</given-names></name><name><surname>Ridzon</surname><given-names>DA</given-names></name><name><surname>Broomer</surname><given-names>AJ</given-names></name><name><surname>Zhou</surname><given-names>Z</given-names></name><name><surname>Lee</surname><given-names>DH</given-names></name><name><surname>Nguyen</surname><given-names>JT</given-names></name><name><surname>Barbisin</surname><given-names>M</given-names></name><name><surname>Xu</surname><given-names>NL</given-names></name><name><surname>Mahuvakar</surname><given-names>VR</given-names></name><name><surname>Andersen</surname><given-names>MR</given-names></name><etal></etal><article-title>Real-time quantification of microRNAs by stem-loop RT-PCR</article-title><source>Nucleic Acids Res</source><year>2005</year><volume>33</volume><fpage>e179</fpage><pub-id pub-id-type="doi">10.1093/nar/gni178</pub-id><pub-id pub-id-type="pmid">16314309</pub-id></mixed-citation></ref><ref id="B54"><mixed-citation publication-type="journal"><name><surname>Varkonyi-Gasic</surname><given-names>E</given-names></name><name><surname>Wu</surname><given-names>R</given-names></name><name><surname>Wood</surname><given-names>M</given-names></name><name><surname>Walton</surname><given-names>EF</given-names></name><name><surname>Hellens</surname><given-names>RP</given-names></name><article-title>Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs</article-title><source>Plant Methods</source><year>2007</year><volume>3</volume><fpage>12</fpage><pub-id pub-id-type="doi">10.1186/1746-4811-3-12</pub-id><pub-id pub-id-type="pmid">17931426</pub-id></mixed-citation></ref><ref id="B55"><mixed-citation publication-type="journal"><name><surname>Feng</surname><given-names>J</given-names></name><name><surname>Wang</surname><given-names>K</given-names></name><name><surname>Liu</surname><given-names>X</given-names></name><name><surname>Chen</surname><given-names>S</given-names></name><name><surname>Chen</surname><given-names>J</given-names></name><article-title>The quantification of tomato microRNAs response to viral infection by stem-loop real-time RT-PCR</article-title><source>Gene</source><year>2009</year><volume>437</volume><fpage>14</fpage><lpage>21</lpage><pub-id pub-id-type="doi">10.1016/j.gene.2009.01.017</pub-id><pub-id pub-id-type="pmid">19374024</pub-id></mixed-citation></ref><ref id="B56"><mixed-citation publication-type="journal"><name><surname>Zhang</surname><given-names>Y</given-names></name><article-title>miRU: an automated plant miRNA target prediction server</article-title><source>Nucleic Acids Res</source><year>2005</year><volume>33</volume><fpage>W701</fpage><lpage>704</lpage><pub-id pub-id-type="doi">10.1093/nar/gki383</pub-id><pub-id pub-id-type="pmid">15980567</pub-id></mixed-citation></ref><ref id="B57"><mixed-citation publication-type="journal"><name><surname>Ossowski</surname><given-names>S</given-names></name><name><surname>Schwab</surname><given-names>R</given-names></name><name><surname>Weigel</surname><given-names>D</given-names></name><article-title>Gene silencing in plants using artificial microRNAs and other small RNAs</article-title><source>Plant J</source><year>2008</year><volume>53</volume><fpage>674</fpage><lpage>690</lpage><pub-id pub-id-type="doi">10.1111/j.1365-313X.2007.03328.x</pub-id><pub-id pub-id-type="pmid">18269576</pub-id></mixed-citation></ref><ref id="B58"><mixed-citation publication-type="journal"><name><surname>Moxon</surname><given-names>S</given-names></name><name><surname>Schwach</surname><given-names>F</given-names></name><name><surname>Dalmay</surname><given-names>T</given-names></name><name><surname>Maclean</surname><given-names>D</given-names></name><name><surname>Studholme</surname><given-names>DJ</given-names></name><name><surname>Moulton</surname><given-names>V</given-names></name><article-title>A toolkit for analysing large-scale plant small RNA datasets</article-title><source>Bioinformatics</source><year>2008</year><volume>24</volume><fpage>2252</fpage><lpage>2253</lpage><pub-id pub-id-type="doi">10.1093/bioinformatics/btn428</pub-id><pub-id pub-id-type="pmid">18713789</pub-id></mixed-citation></ref><ref id="B59"><mixed-citation publication-type="journal"><name><surname>Zuker</surname><given-names>M</given-names></name><article-title>Mfold web server for nucleic acid folding and hybridization prediction</article-title><source>Nucleic Acids Res</source><year>2003</year><volume>31</volume><fpage>3406</fpage><lpage>3415</lpage><pub-id pub-id-type="doi">10.1093/nar/gkg595</pub-id><pub-id pub-id-type="pmid">12824337</pub-id></mixed-citation></ref><ref id="B60"><mixed-citation publication-type="journal"><name><surname>Carra</surname><given-names>A</given-names></name><name><surname>Mica</surname><given-names>E</given-names></name><name><surname>Gambino</surname><given-names>G</given-names></name><name><surname>Pindo</surname><given-names>M</given-names></name><name><surname>Moser</surname><given-names>C</given-names></name><name><surname>Pe</surname><given-names>ME</given-names></name><name><surname>Schubert</surname><given-names>A</given-names></name><article-title>Cloning and characterization of small non-coding RNAs from grape</article-title><source>Plant J</source><year>2009</year><volume>59</volume><fpage>750</fpage><lpage>763</lpage><pub-id pub-id-type="doi">10.1111/j.1365-313X.2009.03906.x</pub-id><pub-id pub-id-type="pmid">19453456</pub-id></mixed-citation></ref><ref id="B61"><mixed-citation publication-type="journal"><name><surname>Arazi</surname><given-names>T</given-names></name><name><surname>Talmor-Neiman</surname><given-names>M</given-names></name><name><surname>Stav</surname><given-names>R</given-names></name><name><surname>Riese</surname><given-names>M</given-names></name><name><surname>Huijser</surname><given-names>P</given-names></name><name><surname>Baulcombe</surname><given-names>DC</given-names></name><article-title>Cloning and characterization of micro-RNAs from moss</article-title><source>Plant J</source><year>2005</year><volume>43</volume><fpage>837</fpage><lpage>848</lpage><pub-id pub-id-type="doi">10.1111/j.1365-313X.2005.02499.x</pub-id><pub-id pub-id-type="pmid">16146523</pub-id></mixed-citation></ref><ref id="B62"><mixed-citation publication-type="journal"><name><surname>Luo</surname><given-names>QJ</given-names></name><name><surname>Samanta</surname><given-names>MP</given-names></name><name><surname>Koksal</surname><given-names>F</given-names></name><name><surname>Janda</surname><given-names>J</given-names></name><name><surname>Galbraith</surname><given-names>DW</given-names></name><name><surname>Richardson</surname><given-names>CR</given-names></name><name><surname>Ou-Yang</surname><given-names>F</given-names></name><name><surname>Rock</surname><given-names>CD</given-names></name><article-title>Evidence for antisense transcription associated with microRNA target mRNAs in Arabidopsis</article-title><source>PLoS Genet</source><year>2009</year><volume>5</volume><fpage>e1000457</fpage><pub-id pub-id-type="doi">10.1371/journal.pgen.1000457</pub-id><pub-id pub-id-type="pmid">19381263</pub-id></mixed-citation></ref><ref id="B63"><mixed-citation publication-type="journal"><name><surname>Morin</surname><given-names>RD</given-names></name><name><surname>O'Connor</surname><given-names>MD</given-names></name><name><surname>Griffith</surname><given-names>M</given-names></name><name><surname>Kuchenbauer</surname><given-names>F</given-names></name><name><surname>Delaney</surname><given-names>A</given-names></name><name><surname>Prabhu</surname><given-names>AL</given-names></name><name><surname>Zhao</surname><given-names>Y</given-names></name><name><surname>McDonald</surname><given-names>H</given-names></name><name><surname>Zeng</surname><given-names>T</given-names></name><name><surname>Hirst</surname><given-names>M</given-names></name><etal></etal><article-title>Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells</article-title><source>Genome Res</source><year>2008</year><volume>18</volume><fpage>610</fpage><lpage>621</lpage><pub-id pub-id-type="doi">10.1101/gr.7179508</pub-id><pub-id pub-id-type="pmid">18285502</pub-id></mixed-citation></ref><ref id="B64"><mixed-citation publication-type="journal"><name><surname>Hobert</surname><given-names>O</given-names></name><article-title>Gene regulation by transcription factors and microRNAs</article-title><source>Science</source><year>2008</year><volume>319</volume><fpage>1785</fpage><lpage>1786</lpage><pub-id pub-id-type="doi">10.1126/science.1151651</pub-id><pub-id pub-id-type="pmid">18369135</pub-id></mixed-citation></ref><ref id="B65"><mixed-citation publication-type="journal"><name><surname>Henderson</surname><given-names>IR</given-names></name><name><surname>Zhang</surname><given-names>X</given-names></name><name><surname>Lu</surname><given-names>C</given-names></name><name><surname>Johnson</surname><given-names>L</given-names></name><name><surname>Meyers</surname><given-names>BC</given-names></name><name><surname>Green</surname><given-names>PJ</given-names></name><name><surname>Jacobsen</surname><given-names>SE</given-names></name><article-title>Dissecting <italic>Arabidopsis thaliana </italic>DICER function in small RNA processing, gene silencing and DNA methylation patterning</article-title><source>Nat Genet</source><year>2006</year><volume>38</volume><fpage>721</fpage><lpage>725</lpage><pub-id pub-id-type="doi">10.1038/ng1804</pub-id><pub-id pub-id-type="pmid">16699516</pub-id></mixed-citation></ref><ref id="B66"><mixed-citation publication-type="journal"><name><surname>Zhang</surname><given-names>B</given-names></name><name><surname>Pan</surname><given-names>X</given-names></name><name><surname>Cannon</surname><given-names>CH</given-names></name><name><surname>Cobb</surname><given-names>GP</given-names></name><name><surname>Anderson</surname><given-names>TA</given-names></name><article-title>Conservation and divergence of plant microRNA genes</article-title><source>Plant J</source><year>2006</year><volume>46</volume><fpage>243</fpage><lpage>259</lpage><pub-id pub-id-type="doi">10.1111/j.1365-313X.2006.02697.x</pub-id><pub-id pub-id-type="pmid">16623887</pub-id></mixed-citation></ref><ref id="B67"><mixed-citation publication-type="journal"><name><surname>Sunkar</surname><given-names>R</given-names></name><name><surname>Jagadeeswaran</surname><given-names>G</given-names></name><article-title><italic>In silico </italic>identification of conserved microRNAs in large number of diverse plant species</article-title><source>BMC Plant Biol</source><year>2008</year><volume>8</volume><fpage>37</fpage><pub-id pub-id-type="doi">10.1186/1471-2229-8-37</pub-id><pub-id pub-id-type="pmid">18416839</pub-id></mixed-citation></ref><ref id="B68"><mixed-citation publication-type="journal"><name><surname>Voinnet</surname><given-names>O</given-names></name><article-title>Origin, biogenesis, and activity of plant microRNAs</article-title><source>Cell</source><year>2009</year><volume>136</volume><issue>4</issue><fpage>669</fpage><lpage>687</lpage><pub-id pub-id-type="doi">10.1016/j.cell.2009.01.046</pub-id><pub-id pub-id-type="pmid">19239888</pub-id></mixed-citation></ref><ref id="B69"><mixed-citation publication-type="journal"><name><surname>Axtell</surname><given-names>MJ</given-names></name><name><surname>Jan</surname><given-names>C</given-names></name><name><surname>Rajagopalan</surname><given-names>R</given-names></name><name><surname>Bartel</surname><given-names>DP</given-names></name><article-title>A two-hit trigger for siRNA biogenesis in plants</article-title><source>Cell</source><year>2006</year><volume>127</volume><fpage>565</fpage><lpage>577</lpage><pub-id pub-id-type="doi">10.1016/j.cell.2006.09.032</pub-id><pub-id pub-id-type="pmid">17081978</pub-id></mixed-citation></ref><ref id="B70"><mixed-citation publication-type="journal"><name><surname>Ronemus</surname><given-names>M</given-names></name><name><surname>Vaughn</surname><given-names>MW</given-names></name><name><surname>Martienssen</surname><given-names>RA</given-names></name><article-title>MicroRNA-targeted and small interfering RNA-mediated mRNA degradation is regulated by argonaute, dicer, and RNA-dependent RNA polymerase in Arabidopsis</article-title><source>Plant Cell</source><year>2006</year><volume>18</volume><fpage>1559</fpage><lpage>1574</lpage><pub-id pub-id-type="doi">10.1105/tpc.106.042127</pub-id><pub-id pub-id-type="pmid">16798886</pub-id></mixed-citation></ref><ref id="B71"><mixed-citation publication-type="journal"><name><surname>Allen</surname><given-names>E</given-names></name><name><surname>Xie</surname><given-names>ZX</given-names></name><name><surname>Gustafson</surname><given-names>AM</given-names></name><name><surname>Carrington</surname><given-names>JC</given-names></name><article-title>microRNA-directed phasing during trans-acting siRNA biogenesis in plants</article-title><source>Cell</source><year>2005</year><volume>121</volume><fpage>207</fpage><lpage>221</lpage><pub-id pub-id-type="doi">10.1016/j.cell.2005.04.004</pub-id><pub-id pub-id-type="pmid">15851028</pub-id></mixed-citation></ref><ref id="B72"><mixed-citation publication-type="journal"><name><surname>He</surname><given-names>Y</given-names></name><name><surname>Vogelstein</surname><given-names>B</given-names></name><name><surname>Velculescu</surname><given-names>VE</given-names></name><name><surname>Papadopoulos</surname><given-names>N</given-names></name><name><surname>Kinzler</surname><given-names>KW</given-names></name><article-title>The antisense transcriptomes of human cells</article-title><source>Science</source><year>2008</year><volume>322</volume><fpage>1855</fpage><lpage>1857</lpage><pub-id pub-id-type="doi">10.1126/science.1163853</pub-id><pub-id pub-id-type="pmid">19056939</pub-id></mixed-citation></ref><ref id="B73"><mixed-citation publication-type="journal"><name><surname>Kolotilin</surname><given-names>I</given-names></name><name><surname>Koltai</surname><given-names>H</given-names></name><name><surname>Tadmor</surname><given-names>Y</given-names></name><name><surname>Bar-Or</surname><given-names>C</given-names></name><name><surname>Reuveni</surname><given-names>M</given-names></name><name><surname>Meir</surname><given-names>A</given-names></name><name><surname>Nahon</surname><given-names>S</given-names></name><name><surname>Shlomo</surname><given-names>H</given-names></name><name><surname>Chen</surname><given-names>L</given-names></name><name><surname>Levin</surname><given-names>I</given-names></name><article-title>Transcriptional profiling of high pigment-2dg tomato mutant links early fruit plastid biogenesis with its overproduction of phytonutrients</article-title><source>Plant Physiol</source><year>2007</year><volume>145</volume><fpage>389</fpage><lpage>401</lpage><pub-id pub-id-type="doi">10.1104/pp.107.102962</pub-id><pub-id pub-id-type="pmid">17704236</pub-id></mixed-citation></ref><ref id="B74"><mixed-citation publication-type="journal"><name><surname>Liu</surname><given-names>Y</given-names></name><name><surname>Liu</surname><given-names>Q</given-names></name><name><surname>Tao</surname><given-names>N</given-names></name><name><surname>Deng</surname><given-names>X</given-names></name><article-title>Efficient isolation of RNA from fruit peel and pulp of ripening navel orange (<italic>Citrus sinensis </italic>Osbeck)</article-title><source>J Huazhong Agric Univ</source><year>2006</year><volume>25</volume><fpage>300</fpage><lpage>304</lpage></mixed-citation></ref><ref id="B75"><mixed-citation publication-type="journal"><name><surname>Griffiths-Jones</surname><given-names>S</given-names></name><article-title>miRBase: the microRNA sequence database</article-title><source>Methods Mol Biol</source><year>2006</year><volume>342</volume><fpage>129</fpage><lpage>138</lpage><pub-id pub-id-type="pmid">16957372</pub-id></mixed-citation></ref><ref id="B76"><mixed-citation publication-type="journal"><name><surname>Kal</surname><given-names>AJ</given-names></name><name><surname>van Zonneveld</surname><given-names>AJ</given-names></name><name><surname>Benes</surname><given-names>V</given-names></name><name><surname>Berg</surname><given-names>M van den</given-names></name><name><surname>Koerkamp</surname><given-names>MG</given-names></name><name><surname>Albermann</surname><given-names>K</given-names></name><name><surname>Strack</surname><given-names>N</given-names></name><name><surname>Ruijter</surname><given-names>JM</given-names></name><name><surname>Richter</surname><given-names>A</given-names></name><name><surname>Dujon</surname><given-names>B</given-names></name><etal></etal><article-title>Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources</article-title><source>Mol Biol Cell</source><year>1999</year><volume>10</volume><fpage>1859</fpage><lpage>1872</lpage><pub-id pub-id-type="pmid">10359602</pub-id></mixed-citation></ref><ref id="B77"><mixed-citation publication-type="journal"><name><surname>Schmid</surname><given-names>R</given-names></name><name><surname>Blaxter</surname><given-names>ML</given-names></name><article-title>annot8r: GO, EC and KEGG annotation of EST datasets</article-title><source>BMC Bioinformatics</source><year>2008</year><volume>9</volume><fpage>180</fpage><pub-id pub-id-type="doi">10.1186/1471-2105-9-180</pub-id><pub-id pub-id-type="pmid">18400082</pub-id></mixed-citation></ref><ref id="B78"><mixed-citation publication-type="journal"><name><surname>Ashburner</surname><given-names>M</given-names></name><name><surname>Ball</surname><given-names>CA</given-names></name><name><surname>Blake</surname><given-names>JA</given-names></name><name><surname>Botstein</surname><given-names>D</given-names></name><name><surname>Butler</surname><given-names>H</given-names></name><name><surname>Cherry</surname><given-names>JM</given-names></name><name><surname>Davis</surname><given-names>AP</given-names></name><name><surname>Dolinski</surname><given-names>K</given-names></name><name><surname>Dwight</surname><given-names>SS</given-names></name><name><surname>Eppig</surname><given-names>JT</given-names></name><etal></etal><article-title>Gene Ontology: tool for the unification of biology</article-title><source>Nat Genet</source><year>2000</year><volume>25</volume><fpage>25</fpage><lpage>29</lpage><pub-id pub-id-type="doi">10.1038/75556</pub-id><pub-id pub-id-type="pmid">10802651</pub-id></mixed-citation></ref><ref id="B79"><mixed-citation publication-type="journal"><name><surname>Kanehisa</surname><given-names>M</given-names></name><name><surname>Goto</surname><given-names>S</given-names></name><article-title>KEGG: kyoto encyclopedia of genes and genomes</article-title><source>Nucleic Acids Res</source><year>2000</year><volume>28</volume><fpage>27</fpage><lpage>30</lpage><pub-id pub-id-type="doi">10.1093/nar/28.1.27</pub-id><pub-id pub-id-type="pmid">10592173</pub-id></mixed-citation></ref></ref-list></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Bois/explor/OrangerV1/Data/Pmc/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000E129 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd -nk 000E129 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Bois
|area= OrangerV1
|flux= Pmc
|étape= Corpus
|type= RBID
|clé=
|texte=
}}
| This area was generated with Dilib version V0.6.25. |  |