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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Transcriptome analysis of <italic>Nicotiana benthamiana</italic> infected by <italic>Tobacco curly shoot virus</italic></title><author><name sortKey="Li, Ke" sort="Li, Ke" uniqKey="Li K" first="Ke" last="Li">Ke Li</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Wu, Gentu" sort="Wu, Gentu" uniqKey="Wu G" first="Gentu" last="Wu">Gentu Wu</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Li, Mingjun" sort="Li, Mingjun" uniqKey="Li M" first="Mingjun" last="Li">Mingjun Li</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Ma, Mingge" sort="Ma, Mingge" uniqKey="Ma M" first="Mingge" last="Ma">Mingge Ma</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Du, Jiang" sort="Du, Jiang" uniqKey="Du J" first="Jiang" last="Du">Jiang Du</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Sun, Miao" sort="Sun, Miao" uniqKey="Sun M" first="Miao" last="Sun">Miao Sun</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Sun, Xianchao" sort="Sun, Xianchao" uniqKey="Sun X" first="Xianchao" last="Sun">Xianchao Sun</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Qing, Ling" sort="Qing, Ling" uniqKey="Qing L" first="Ling" last="Qing">Ling Qing</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30176884</idno><idno type="pmc">6122796</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122796</idno><idno type="RBID">PMC:6122796</idno><idno type="doi">10.1186/s12985-018-1044-1</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">000240</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000240</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Transcriptome analysis of <italic>Nicotiana benthamiana</italic> infected by <italic>Tobacco curly shoot virus</italic></title><author><name sortKey="Li, Ke" sort="Li, Ke" uniqKey="Li K" first="Ke" last="Li">Ke Li</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Wu, Gentu" sort="Wu, Gentu" uniqKey="Wu G" first="Gentu" last="Wu">Gentu Wu</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Li, Mingjun" sort="Li, Mingjun" uniqKey="Li M" first="Mingjun" last="Li">Mingjun Li</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Ma, Mingge" sort="Ma, Mingge" uniqKey="Ma M" first="Mingge" last="Ma">Mingge Ma</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Du, Jiang" sort="Du, Jiang" uniqKey="Du J" first="Jiang" last="Du">Jiang Du</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Sun, Miao" sort="Sun, Miao" uniqKey="Sun M" first="Miao" last="Sun">Miao Sun</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Sun, Xianchao" sort="Sun, Xianchao" uniqKey="Sun X" first="Xianchao" last="Sun">Xianchao Sun</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Qing, Ling" sort="Qing, Ling" uniqKey="Qing L" first="Ling" last="Qing">Ling Qing</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">Virology Journal</title><idno type="eISSN">1743-422X</idno><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p id="Par1"><italic>Tobacco curly shoot virus</italic> (TbCSV) is a monopartite begomovirus associated with betasatellite (Tobacco curly shoot betasatellite<italic>,</italic> TbCSB), which causes serious leaf curl disease on tomato and tobacco in China. It is interesting that TbCSV induced severe upward leaf curling in <italic>Nicotiana benthamiana</italic>, but in the presence of TbCSB, symptoms changed to be downward leaf curling. However, the mechanism of interactions between viral pathogenicity, host defense, viral-betasatellite interactions and virus-host interactions remains unclear.</p></sec><sec><title>Methods</title><p id="Par2">In this study, RNA-seq was used to analyze differentially expressed genes (DEGs) in <italic>N. benthamiana</italic> plants infected by TbCSV (Y35A) and TbCSV together with TbCSB (Y35AB) respectively.</p></sec><sec><title>Results</title><p id="Par3">Through mapping to <italic>N. benthamiana</italic> reference genome, 59,814 unigenes were identified<italic>.</italic> Transcriptome analysis revealed that a total of 4081 and 3196 DEGs were identified in Y35AB vs CK (control check) and Y35A vs CK, respectively. Both GO and KEGG analyses were conducted to classify the DEGs. Ten of the top 15 GO terms were enriched in both DEGs of Y35AB vs CK and Y35A vs CK, and these enriched GO terms mainly classified into three categories including biological process, cellular component and molecular function. KEGG pathway analysis indicated that 118 and 111 pathways were identified in Y35AB vs CK and Y35A vs CK, respectively, of which nine and six pathways were significantly enriched. Three major pathways in Y35AB vs CK involved in metabolic pathways, carbon metabolism and photosynthesis, while those in Y35A vs CK were related to Ribosome, Glyoxylate and dicarboxylate metabolism and DNA replication. We observed that 8 PR genes were significantly up-regulated and 44 LRR-RLK genes were significantly differentially expressed in Y35A treatment or in Y35AB treatment. In addition, 7 and 13 genes were identified to be significantly changed in biosynthesis and signal transduction pathway of brassinosteroid (BR) and jasmonic acid (JA) respectively.</p></sec><sec><title>Conclusions</title><p id="Par4">These results presented here would be particularly useful to further elucidate the response of the host plant against virus infection.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (10.1186/s12985-018-1044-1) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Xie, Y" uniqKey="Xie Y">Y Xie</name></author><author><name sortKey="Zhou, Xp" uniqKey="Zhou X">XP Zhou</name></author><author><name sortKey="Zhang, Zk" uniqKey="Zhang Z">ZK Zhang</name></author><author><name sortKey="Qi, Yj" uniqKey="Qi Y">YJ Qi</name></author></analytic></biblStruct><biblStruct><analytic><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Virol J</journal-id><journal-id journal-id-type="iso-abbrev">Virol. J</journal-id><journal-title-group><journal-title>Virology Journal</journal-title></journal-title-group><issn pub-type="epub">1743-422X</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">30176884</article-id><article-id pub-id-type="pmc">6122796</article-id><article-id pub-id-type="publisher-id">1044</article-id><article-id pub-id-type="doi">10.1186/s12985-018-1044-1</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research</subject></subj-group></article-categories><title-group><article-title>Transcriptome analysis of <italic>Nicotiana benthamiana</italic> infected by <italic>Tobacco curly shoot virus</italic></article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Li</surname><given-names>Ke</given-names></name><address><email>lihai8730@163.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Wu</surname><given-names>Gentu</given-names></name><address><email>wugtu@163.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Li</surname><given-names>Mingjun</given-names></name><address><email>lmj603@163.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Ma</surname><given-names>Mingge</given-names></name><address><email>1248289377@qq.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Du</surname><given-names>Jiang</given-names></name><address><email>dujiang20080803@163.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Sun</surname><given-names>Miao</given-names></name><address><email>445879215@qq.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Sun</surname><given-names>Xianchao</given-names></name><address><email>sunxianchao@163.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Qing</surname><given-names>Ling</given-names></name><address><phone>0086-023-68250695</phone><email>qling@swu.edu.cn</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.263906.8</institution-id><institution>College of Plant Protection,</institution><institution>Southwest University,</institution></institution-wrap>Chongqing, 400716 People’s Republic of China</aff></contrib-group><pub-date pub-type="epub"><day>3</day><month>9</month><year>2018</year></pub-date><pub-date pub-type="pmc-release"><day>3</day><month>9</month><year>2018</year></pub-date><pub-date pub-type="collection"><year>2018</year></pub-date><volume>15</volume><elocation-id>138</elocation-id><history><date date-type="received"><day>4</day><month>1</month><year>2018</year></date><date date-type="accepted"><day>14</day><month>8</month><year>2018</year></date></history><permissions><copyright-statement>© The Author(s). 2018</copyright-statement><license license-type="OpenAccess"><license-p><bold>Open Access</bold>This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><abstract id="Abs1"><sec><title>Background</title><p id="Par1"><italic>Tobacco curly shoot virus</italic> (TbCSV) is a monopartite begomovirus associated with betasatellite (Tobacco curly shoot betasatellite<italic>,</italic> TbCSB), which causes serious leaf curl disease on tomato and tobacco in China. It is interesting that TbCSV induced severe upward leaf curling in <italic>Nicotiana benthamiana</italic>, but in the presence of TbCSB, symptoms changed to be downward leaf curling. However, the mechanism of interactions between viral pathogenicity, host defense, viral-betasatellite interactions and virus-host interactions remains unclear.</p></sec><sec><title>Methods</title><p id="Par2">In this study, RNA-seq was used to analyze differentially expressed genes (DEGs) in <italic>N. benthamiana</italic> plants infected by TbCSV (Y35A) and TbCSV together with TbCSB (Y35AB) respectively.</p></sec><sec><title>Results</title><p id="Par3">Through mapping to <italic>N. benthamiana</italic> reference genome, 59,814 unigenes were identified<italic>.</italic> Transcriptome analysis revealed that a total of 4081 and 3196 DEGs were identified in Y35AB vs CK (control check) and Y35A vs CK, respectively. Both GO and KEGG analyses were conducted to classify the DEGs. Ten of the top 15 GO terms were enriched in both DEGs of Y35AB vs CK and Y35A vs CK, and these enriched GO terms mainly classified into three categories including biological process, cellular component and molecular function. KEGG pathway analysis indicated that 118 and 111 pathways were identified in Y35AB vs CK and Y35A vs CK, respectively, of which nine and six pathways were significantly enriched. Three major pathways in Y35AB vs CK involved in metabolic pathways, carbon metabolism and photosynthesis, while those in Y35A vs CK were related to Ribosome, Glyoxylate and dicarboxylate metabolism and DNA replication. We observed that 8 PR genes were significantly up-regulated and 44 LRR-RLK genes were significantly differentially expressed in Y35A treatment or in Y35AB treatment. In addition, 7 and 13 genes were identified to be significantly changed in biosynthesis and signal transduction pathway of brassinosteroid (BR) and jasmonic acid (JA) respectively.</p></sec><sec><title>Conclusions</title><p id="Par4">These results presented here would be particularly useful to further elucidate the response of the host plant against virus infection.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (10.1186/s12985-018-1044-1) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Begomovirus</kwd><kwd><italic>Tobacco curly shoot virus</italic></kwd><kwd>Betasatellite</kwd><kwd><italic>Nicotiana benthamiana</italic></kwd><kwd>RNA-seq</kwd></kwd-group><funding-group><award-group><funding-source><institution>the Fundamental Research Funds for the Central Universities </institution></funding-source><award-id>(Grant No. XDJK2017A006 and XDJK2015D039)</award-id><principal-award-recipient><name><surname>Qing</surname><given-names>Ling</given-names></name></principal-award-recipient></award-group></funding-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2018</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="Sec1"><title>Background</title><p id="Par5"><italic>Tobacco curly shoot virus</italic> (TbCSV), a monopartite begomovirus (genus <italic>Begomovirus</italic>, family <italic>Geminiviridae</italic>), was isolated from tobacco in Yunnan province, China in 2002 [<xref ref-type="bibr" rid="CR1">1</xref>]. Some TbCSV isolates were identified associating with a betasatellite molecule (Tobacco curly shoot betasatellite<italic>,</italic> TbCSB) [<xref ref-type="bibr" rid="CR2">2</xref>]. TbCSV is one of the most important pathogens causing leaf curl disease on tomato and tobacco, and is a severe constraint to crop yields. TbCSV consists of a circular single-stranded DNA genome that encodes 6 proteins, including AV1 (coat protein, CP) and AV2 in virion-sense strand whilst AC1 (replication-related, Rep), AC2 (transcriptional activator, TrAP), AC3 (replication enhancer, REn) and AC4 in complementary-sense strand [<xref ref-type="bibr" rid="CR1">1</xref>]. TbCSB is a small circular single-stranded DNA molecule which encodes a sole protein βC1 [<xref ref-type="bibr" rid="CR2">2</xref>].</p><p id="Par6">Viral infection is a complicated procedure involving in the interaction between viruses and host plants. Understanding host responses to viral infection is advantageous in the development of effective strategies for virus control. In recent years, the interactions between viruses and host plants were clarified through analysis of transcriptomics [<xref ref-type="bibr" rid="CR3">3</xref>–<xref ref-type="bibr" rid="CR5">5</xref>]. RNA-seq is a recently developed approach to transcriptome profiling via deep-sequencing technologies, which provides a far more precise measurement of levels of transcripts and their isoforms than other methods [<xref ref-type="bibr" rid="CR6">6</xref>]. Thus, this technique was widely applied in interpretation the interaction between virus infection and host plant. The multiple resistance mechanisms against cotton leaf curl disease (CLCuD) were revealed by the transcriptome analysis based on an RNA-seq in a naturally immune cotton species (<italic>Gossypium arboreum</italic>) caused by CLCuD [<xref ref-type="bibr" rid="CR7">7</xref>]. The technology of transcriptomics and proteomics were employed to study the differential host gene expression during <italic>Mungbean yellow mosaic India virus</italic> (MYMIV) and <italic>Mungbean yellow mosaic virus</italic> (MYMV) infection under natural conditions [<xref ref-type="bibr" rid="CR8">8</xref>]. The differential regulations of host genes revealed to be involved in cell cycle, cell-wall biogenesis, chloroplast, photosynthesis, hormone and sulphur assimilation pathways which may contribute to symptom development in soybean plants [<xref ref-type="bibr" rid="CR8">8</xref>]. Recently, a research performed RNA-seq-based transcriptome sequencing of <italic>Jatropha curcas mosaic virus</italic>-infected and healthy leaf tissues of <italic>J. curcas</italic>, which provides a repertoire of molecular components after viral infection [<xref ref-type="bibr" rid="CR9">9</xref>]. Similarly, several host genes were identified to be involved in different cellular and physiological processes during the infection of other viruses, including <italic>South African cassava mosaic virus</italic> (SACMV) [<xref ref-type="bibr" rid="CR10">10</xref>], <italic>Tomato yellow leaf curl Sardinia virus</italic> (TYLCSV), <italic>Mungbean yellow mosaic India virus</italic> (MYMIV) [<xref ref-type="bibr" rid="CR11">11</xref>, <xref ref-type="bibr" rid="CR12">12</xref>], and <italic>Chilli leaf curl virus</italic> (ChiLCV) [<xref ref-type="bibr" rid="CR13">13</xref>].</p><p id="Par7">At present, it has been reported that the infectious clone of TbCSV induced severe upward leaf curling in <italic>N. benthamiana</italic>, but in the presence of TbCSB the symptom changed to a downward leaf curl [<xref ref-type="bibr" rid="CR14">14</xref>]. Thus, TbCSV may represent an evolutionary intermediate between the truly monopartite begomoviruses and those that require the association of betasatellite [<xref ref-type="bibr" rid="CR14">14</xref>]. Moreover, studies showed that AC2 and AC4 proteins of TbCSV mediate suppression of RNA silencing [<xref ref-type="bibr" rid="CR15">15</xref>], and βC1 protein of TbCSB could bind single- and double- stranded DNA to suppress host RNA silencing activities [<xref ref-type="bibr" rid="CR16">16</xref>]. However, it remains unclear that the molecular mechanism of viral pathogenicity, host defense and viral-host interactions. In this study, in order to get insights into the molecular mechanisms in response to TbCSV infection in <italic>N. benthamiana</italic> plants, the transcriptome analysis of <italic>N. benthamiana</italic> infected by TbCSV or TbCSV/TbCSB was performed, including differentially expressed genes, GO enrichment, KEGG enrichment, pathogenesis-related (PR) protein genes, LRR-RLK genes, brassinosteroid and jasmonic acid pathways. These data contribute to a better knowledge on the molecular mechanisms of TbCSV- and TbCSV/TbCSB- host interaction, and serve as a basis for devising new strategies to control TbCSV/TbCSB disease complex.</p></sec><sec id="Sec2"><title>Methods</title><sec id="Sec3"><title>Virus sources and agroinoculation</title><p id="Par8">The infectious clones of TbCSV isolate Y35 (pBinY35A-1.9) (Y35A) and its betasatellite (pBinY35β-2.0) (Y35B) were provided by Professor Xueping Zhou in the Biotechnology Institute of Zhejiang University. Both viral infectious clones were introduced into <italic>Agrobacterium tumefaciens</italic> strain EHA105. <italic>N. benthamiana</italic> (accession: Nb-1) plants were grown in a greenhouse under a 16 h light and 8 h dark cycle at 26 °C. The <italic>Agrobacterium</italic> with infectious clones was infiltrated into <italic>N. benthamiana</italic> leaves at 4–6 leaf stage as previously described [<xref ref-type="bibr" rid="CR2">2</xref>].</p></sec><sec id="Sec4"><title>DNA extraction and PCR detection</title><p id="Par9">Leaf samples were collected at 20 days-post inoculation (dpi) and total DNA were extracted using CTAB method [<xref ref-type="bibr" rid="CR17">17</xref>]. The TbCSV-specific primers (TbCSV-F, 5′-ATGCCTCAGCCAAGAAAACTTTT-3′; TbCSV-R, 5′-TCAACACGACGACGTCTGTTCCC-3′) and TbCSB-specific primers (TbCSB-F, 5′-ATGACAATTAAATACAACAACAAG-3′; TbCSB-R, 5′-TCATACATTAGCTATTGTCCC-3′) were designed to amplify fragments of 1086 bp and 357 bp in size, respectively. PCR reactions were performed in a 20 μL volume with reaction mixtures containing 10 μL of 2 × Taq Master Mix (Novoprotein Scientific Inc., Shanghai, China), 0.5 μL of DNA, 0.25 μM of each primer and a proper volume of ddH<sub>2</sub>O. The PCR reaction conditions were as follows: 94 °C for 3 min, followed by 35 cycles of denaturation for 30 s at 94 °C, annealing for 30 s at 52 °C, extension for 30–65 s at 72 °C (depending on primer pairs used in distinct reactions), and a final extension for 10 min at 72 °C.</p></sec><sec id="Sec5"><title>Materials for RNA sequencing</title><p id="Par10">Leaf tissues of <italic>N. benthamiana</italic> plants were sampled at 20 dpi, and were immediately frozen and ground in liquid nitrogen and stored at − 80 °C. After PCR detection, RNA-seq was performed for stored samples. Three treatments were setting as follows: plants infected with TbCSV alone (Y35A treatment); plants infected with TbCSV and TbCSB (Y35AB treatment); uninfected plants as control (CK). There are three biological replicates per treatment respectively.</p></sec><sec id="Sec6"><title>RNA extraction and cDNA synthesis</title><p id="Par11">Total RNA was extracted from <italic>N. benthamiana</italic> leaf tissues with RNAiso Plus (TAKARA Bio, Inc) as manufacturer’s protocol. All RNA samples were first treated with gDNA Eraser (TAKARA Bio, Inc) and reverse-transcribed using a Prime Script RT reagent Kit (Perfect Real Time) according to manufacturer’s instructions.</p></sec><sec id="Sec7"><title>Library preparation for transcriptome sequencing</title><p id="Par12">A total amount of 3 μg RNA per sample was used as input for RNA sample preparations. Sequencing libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. Briefly, mRNA was purifed by using poly-T oligo-attached magnetic beads. After fragmentation, the cDNA was synthesized, and NEBNext Adaptors with hairpin loop structures were ligated to prepare for hybridization. PCR products were purifed (AMPure XP system), and library quality was assessed by Agilent Bioanalyzer 2100 system [<xref ref-type="bibr" rid="CR18">18</xref>]. Finally, nine libraries were successfully constructed, and were sequenced using HiSeq™ 2500 equipment (Illumina, SanDiego, CA, USA) by 50 bp single-end (SE50) methods.</p></sec><sec id="Sec8"><title>Quality control</title><p id="Par13">For sequence quality control, raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing ploy-N and low quality reads from raw data. Meanwhile, Q20, Q30, GC-content and sequence duplication level of clean data were calculated. All the downstream analyses were based on the clean data with high quality [<xref ref-type="bibr" rid="CR19">19</xref>].</p></sec><sec id="Sec9"><title>Reads mapping to the reference genome</title><p id="Par14">The draft sequence of the <italic>N. benthamiana</italic> reference genome have been downloaded from the SGN ftp site (<ext-link ext-link-type="uri" xlink:href="ftp://ftp.solgenomics.net/genomes/Nicotiana_benthamiana/assemblies">ftp://ftp.solgenomics.net/genomes/Nicotiana_benthamiana/assemblies</ext-link>) directly [<xref ref-type="bibr" rid="CR20">20</xref>]. Index of the reference genome was built using Bowtie v2.2.3 (Broad Institute, Cambridge, MA, USA) [<xref ref-type="bibr" rid="CR21">21</xref>] and single-end clean reads were aligned to the reference genome using TopHat v2.0.12 (Broad Institute, Cambridge, MA, USA) (mismatch = 2) [<xref ref-type="bibr" rid="CR22">22</xref>]. The TopHat was selected as the mapping tool for that TopHat can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other non-splice mapping tools [<xref ref-type="bibr" rid="CR23">23</xref>].</p></sec><sec id="Sec10"><title>Quantification of gene expression level</title><p id="Par15">HTSeq v0.6.1 was used to count reads numbers mapped to each gene [<xref ref-type="bibr" rid="CR24">24</xref>]. And then FPKM (Fragments per kilobase of transcript sequence per millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. FPKM, expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced, considers the effect of sequencing depth and gene length for the reads count at the same time, and is currently the most commonly used method for estimating gene expression levels [<xref ref-type="bibr" rid="CR25">25</xref>].</p></sec><sec id="Sec11"><title>Differential gene expression analysis</title><p id="Par16">Differential expression analysis of Y35AB vs CK and Y35A vs CK was performed using the DESeq R package (1.18.0) (parameters: negative binomial distribution-based statistic, BH-FDR corrected <italic>p</italic>-value < 0.05) [<xref ref-type="bibr" rid="CR26">26</xref>], which provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting <italic>p</italic>-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate (FDR).</p></sec><sec id="Sec12"><title>GO term and KEGG pathway enrichment analysis</title><p id="Par17">Gene Ontology (GO; <ext-link ext-link-type="uri" xlink:href="http://www.geneontology.org">http://www.geneontology.org</ext-link>) enrichment analysis of differentially expressed genes (DEGs) was implemented by the GOseq R package (corrected <italic>p</italic>-value < 0.05) [<xref ref-type="bibr" rid="CR27">27</xref>], in which gene length bias was corrected. GO terms with corrected <italic>p</italic>-value less than 0.05 were considered significantly enriched by differential expressed genes. REVIGO was used for analysis of the enriched GO terms (<ext-link ext-link-type="uri" xlink:href="http://revigo.irb.hr">http://revigo.irb.hr</ext-link>). KEGG (<ext-link ext-link-type="uri" xlink:href="http://www.genome.jp/kegg">http://www.genome.jp/kegg</ext-link>) is a database resource for understanding high-level functions and utilities of the biological system from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies. And KOBAS software was used to test the statistical enrichment of differential expression genes in KEGG pathways (corrected <italic>p</italic>-value < 0.05) [<xref ref-type="bibr" rid="CR28">28</xref>].</p></sec><sec id="Sec13"><title>Quantitative real-time PCR validation</title><p id="Par18">To validate the RNA-seq data, quantitative real-time PCR (RT-qPCR) was conducted to examine the selected pattern of DEGs. For reverse transcription, 1 μg of total RNA was treated with gDNA Eraser (TAKARA Bio, Inc) and reverse-transcribed using a Prime Script RT reagent Kit (Perfect Real Time) and oligo (dT) as the primer according to the manufacturer’s protocol. Primer sets were designed using AlleleID software (v6.0) (Additional file <xref rid="MOESM1" ref-type="media">1</xref>: Table S1). RT-qPCR was conducted by using NovoStart® SYBR qPCR Super Mix Plus (Novoprotein, Shanghai, China) on CFX 96 Real-Time System (Bio-Rad). Actin was used as a reference for calculating relative abundances using the 2<sup>-△△Ct</sup> method [<xref ref-type="bibr" rid="CR29">29</xref>]. All RT-qPCR experiments were performed in triplicate.</p></sec></sec><sec id="Sec14"><title>Results</title><sec id="Sec15"><title>Plants with typical viral symptoms in Y35A and Y35AB treatments</title><p id="Par19">At 20 dpi, Y35A inoculated plants showed slight upward leaf curling and Y35AB inoculated plants showed severe downward leaf curl (Fig. <xref rid="Fig1" ref-type="fig">1a</xref>-<xref rid="Fig1" ref-type="fig">c</xref>). PCR detection showed that they are consistent with expectations (Fig. <xref rid="Fig1" ref-type="fig">1d</xref>-<xref rid="Fig1" ref-type="fig">e</xref>). Symptom observation and virus detection results showed that these plants were reliable for follow-up RNA-seq. Leaf tissues at same positions were collected from every treatment for RNA-seq.<fig id="Fig1"><label>Fig. 1</label><caption><p>Comparison of <italic>N. benthamiana</italic> plant symptoms of virus-infected with healthy control at 20 dpi. <bold>a</bold> Co-inoculation of TbCSV and TbCSB (Y35AB). <bold>b</bold> Solitary inoculation of TbCSV (Y35A). <bold>c</bold> Healthy control (CK). <bold>d</bold> Specific detection of TbCSV DNA-A in the nine plants for sequencing by PCR with primers TbCSV-F/TbCSV-R. <bold>e</bold> Specific detection of TbCSB in the nine plants for sequencing by PCR with primers TbCSB-F/TbCSB-R. M1: BM2000 + 1.5 kb DNA Marker; M2: DNA Marker I; 1–3: Y35AB plants; 4–6: Y35A plants; 7–9: CK plants; P: positive control; N: negative control, respectivly</p></caption><graphic xlink:href="12985_2018_1044_Fig1_HTML" id="MO1"></graphic></fig></p></sec><sec id="Sec16"><title>Overview of transcriptome sequencing</title><p id="Par20">To profile gene expression during virus infection, RNA-seq libraries were constructed for the control- and virus-inoculated <italic>N. benthamiana</italic> plants. 5.76 GB clean bases data and 59,814 unigenes were obtained from nine samples. There were 11834496–13118731, 12537134–15503750 and 11290015–12633203 clean reads in the three treatments of Y35AB, Y35A, and CK. The proportion of total reads that mapped to <italic>N. benthamiana</italic> genome of each sample was more than 96.09%, and that of uniquely mapped was above 72.69%. More than 95.58% of the clean reads had quality scores at the Q30 (an error probability for base calling of 0.1%) level [<xref ref-type="bibr" rid="CR30">30</xref>]. Furthermore, the GC content ranges from 43.58 to 44.38%. The sequencing data are summarized in Table <xref rid="Tab1" ref-type="table">1</xref>.<table-wrap id="Tab1"><label>Table 1</label><caption><p>Summary of the results of RNA-seq data</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Sample name</th><th>Y35AB-1</th><th>Y35AB-2</th><th>Y35AB-3</th><th>Y35A-1</th><th>Y35A-2</th><th>Y35A-3</th><th>CK-1</th><th>CK-2</th><th>CK-3</th><th>mean</th></tr></thead><tbody><tr><td>Raw reads</td><td>12166453</td><td>11965470</td><td>13272880</td><td>15527372</td><td>12560210</td><td>14214740</td><td>12646000</td><td>11302705</td><td>11794017</td><td>12827761</td></tr><tr><td>Clean reads</td><td>12032720</td><td>11834496</td><td>13118731</td><td>15503750</td><td>12537134</td><td>14192135</td><td>12633203</td><td>11290015</td><td>11782562</td><td>12769416</td></tr><tr><td>Clean bases</td><td>0.60G</td><td>0.59G</td><td>0.66G</td><td>0.78G</td><td>0.63G</td><td>0.71G</td><td>0.63G</td><td>0.56G</td><td>0.59G</td><td>0.64</td></tr><tr><td rowspan="2">Total mapped</td><td>11620770</td><td>11438690</td><td>12605297</td><td>14934455</td><td>12075773</td><td>13732342</td><td>12346163</td><td>11139553</td><td>11524248</td><td>12379699</td></tr><tr><td>96.58%</td><td>96.66%</td><td>96.09%</td><td>96.33%</td><td>96.32%</td><td>96.76%</td><td>97.73%</td><td>98.67%</td><td>97.81%</td><td>96.99%</td></tr><tr><td rowspan="2">Uniquely mapped</td><td>8961324</td><td>8847537</td><td>9609766</td><td>11389720</td><td>9176512</td><td>10320807</td><td>9238644</td><td>8316046</td><td>8564617</td><td>9380553</td></tr><tr><td>74.47%</td><td>74.76%</td><td>73.25%</td><td>73.46%</td><td>73.19%</td><td>72.72%</td><td>73.13%</td><td>73.66%</td><td>72.69%</td><td>73.48%</td></tr><tr><td>Q30 (%)</td><td>95.74</td><td>95.68</td><td>95.58</td><td>96.20</td><td>96.08</td><td>96.14</td><td>95.76</td><td>95.70</td><td>95.80</td><td>95.85</td></tr><tr><td>GC contents (%)</td><td>43.58</td><td>43.75</td><td>44.11</td><td>44.15</td><td>44.23</td><td>44.38</td><td>43.93</td><td>43.80</td><td>43.92</td><td>43.98</td></tr></tbody></table><table-wrap-foot><p>Note: Clean reads: Reads from sequencing after filtering low-quality reads. Clean bases: The number of clean reads is multiplied by the length and converted to G. Q30: The percentage of bases with a Phred value >30</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec17"><title>Analysis of DEGs</title><p id="Par21">An adjusted <italic>p</italic>-value < 0.05 by DESeq was used to identify DEGs. In the Y35AB vs CK, 4081 DEGs (Fig. <xref rid="Fig2" ref-type="fig">2a</xref>, Additional file <xref rid="MOESM2" ref-type="media">2</xref>: Table S2), including 1775 up-regulated and 2306 down-regulated genes, were identified (Fig. <xref rid="Fig2" ref-type="fig">2c</xref>). And 3196 transcripts (1391 up-regulated and 1805 down-regulated genes) showed significant changes in Y35A vs CK (Fig. <xref rid="Fig2" ref-type="fig">2b</xref>, <xref rid="Fig2" ref-type="fig">c</xref> and Additional file <xref rid="MOESM3" ref-type="media">3</xref>: Table S3). However, a total of 1232 DEGs in Y35AB vs CK overlap with those in Y35A vs CK, including 445 up-regulated and 786 down-regulated genes (Fig. <xref rid="Fig2" ref-type="fig">2c</xref>).<fig id="Fig2"><label>Fig. 2</label><caption><p>Volcano plots and Venn diagrams of DEGs (<bold>a</bold>-<bold>b</bold>). DEGs of Y35AB vs CK and Y35A vs CK displayed by volcano plots. The abscissa shows the fold change difference in the expression of genes in different groups, and the vertical coordinates indicate the adjusted <italic>p</italic>-values for the differences in expression. Genes without significant differences are indicated by blue dots. The up-regulated genes are represented by red dots, and the down-regulated genes are represented by green dots. Venn diagrams showing the overlap in DEGs between Y35AB vs CK and Y35A vs CK (<bold>c</bold>)</p></caption><graphic xlink:href="12985_2018_1044_Fig2_HTML" id="MO2"></graphic></fig></p></sec><sec id="Sec18"><title>GO enrichment analysis</title><p id="Par22">Gene Ontology, an internationally standardized gene function classification system, was used to classify the DEGs. The results were enriched in Y35AB vs CK and Y35A vs CK, and 124 and 76 of them were significantly enriched, respectively. Further, the top 15 GO functional annotation terms were listed, and 10 of them were shared between Y35AB vs CK and Y35A vs CK, associated with biological process, metabolic process, cellular process, organic substance metabolic process, primary metabolic process, cellular metabolic process, nitrogen compound metabolic process, biosynthetic process, cellular nitrogen compound metabolic process and organic substance biosynthetic process (Fig. <xref rid="Fig3" ref-type="fig">3</xref>, Additional files <xref rid="MOESM4" ref-type="media">4</xref> and <xref rid="MOESM5" ref-type="media">5</xref>: Tables S4 and S5). Furthermore, it was found that these enriched GO terms mainly classified into biological process.<fig id="Fig3"><label>Fig. 3</label><caption><p>Most of the top 15 GO terms of three categories significantly enriched in DGEs of Y35AB vs CK and Y35A vs CK. MF, molecular function; BP, biological process; CC, cellular component</p></caption><graphic xlink:href="12985_2018_1044_Fig3_HTML" id="MO3"></graphic></fig></p></sec><sec id="Sec19"><title>KEGG pathway enrichment analysis</title><p id="Par23">In order to further clarify molecular and biological functions of the genes, these DEGs were mapped to the KEGG database. KEGG pathway analysis indicated that 118 and 111 pathways were identified in Y35AB vs CK and Y35A vs CK, respectively, of which nine and six were significantly enriched with <italic>p-</italic>value< 0.05. The significantly enrichment analysis showed that DEGs of Y35AB vs CK involved in metabolic pathways, carbon metabolism, photosynthesis, carbon fixation in photosynthetic organisms, glyoxylate and dicarboxylate metabolism, porphyrin and chlorophyll metabolism, DNA replication, pentose phosphate pathway and nitrogen metabolism. While, DEGs involved in ribosome, glyoxylate and dicarboxylate metabolism, DNA replication, circadian rhythm-plant, photosynthesis-antenna proteins and nitrogen metabolism were significantly enriched in Y35A vs CK (Fig. <xref rid="Fig4" ref-type="fig">4</xref>, Additional files <xref rid="MOESM6" ref-type="media">6</xref> and <xref rid="MOESM7" ref-type="media">7</xref>: Tables S6 and S7).<fig id="Fig4"><label>Fig. 4</label><caption><p>KEGG pathways of the more or main significantly enriched in DGEs. The rich factor reflects the degree of enriched DGEs in a given pathway. The number of enriched DGEs in the pathway is indicated by the circle area, and the circle color represents the ranges of the corrected <italic>p</italic>-value</p></caption><graphic xlink:href="12985_2018_1044_Fig4_HTML" id="MO4"></graphic></fig></p><p id="Par24">Metabolic pathway was the major pathway which contains the largest number of DEGs in both Y35AB vs CK and Y35A vs CK, but DEGs involved in metabolic pathway were not significantly different in Y35A vs CK, it further indicated that the presence of TbCSB differentially changed metabolic pathways in <italic>N. benthamiana.</italic> The rich factor of porphyrin and chlorophyll metabolism pathway in Y35AB vs CK was near 1.00, the results showed that almost all genes in this pathway differentially expressed in TbCSV associated with betasatellite infected plants. Nevertheless, ribosome pathway might play an important role in response to TbCSV infection for the number of enriched DEGs in ribosome pathway wasnear to that enriched in metabolic pathways, and the rich factor was more than 0.75.</p></sec><sec id="Sec20"><title>Screening of Y35AB vs CK and Y35A vs CK common highly expressed DEGs</title><p id="Par25">FPKM reflecting both the effect of sequencing depth and gene length for the read count, and is a commonly used method for estimating gene expression levels [<xref ref-type="bibr" rid="CR31">31</xref>]. The fold change in gene expression was used to distinguish differentially expressed genes between samples because of the significance of digital gene expression profiles [<xref ref-type="bibr" rid="CR32">32</xref>]. The intersection of highly expressed DGEs in Y35AB vs CK and Y35A vs CK was considered. Finally, 17 DEGs were identified (|log<sub>2</sub>(Fold change)| ≥ 1 and FPKM≥50) from significantly enriched KEGG pathways, these 17 genes were shared between Y35AB vs CK and Y35A vs CK all down-regulated, and involved in six pathways, including photosynthesis, porphyrin and chlorophyll metabolism, metabolic pathways, carbon metabolism, carbon fixation in photosynthetic organisms, and glyoxylate and dicarboxylate metabolism. Additionally, six DEGs that not enriched in any pathway were screened (|log<sub>2</sub> (Fold change) | ≥ 2 and FPKM≥50), including four up-regulated and two down-regulated. In total, 23 candidate genes were screened as shown in Table <xref rid="Tab2" ref-type="table">2</xref>.<table-wrap id="Tab2"><label>Table 2</label><caption><p>Screened candidate genes in Y35AB and Y35A</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Gene symbol</th><th>Unigene ID</th><th>Protein properties</th><th>log<sub>2</sub>FC<sup>a</sup></th><th>log<sub>2</sub>FC<sup>b</sup></th><th>pathway</th></tr></thead><tbody><tr><td><italic>PsaFa</italic></td><td>Niben101Scf 00271g04024</td><td>photosystem I reaction center subunitIII, chloroplastic-like</td><td>-1.4180</td><td>-1.1769</td><td>Photosynthesis</td></tr><tr><td><italic>PsaFb</italic></td><td>Niben101Scf 02156g05001</td><td>photosystem I reaction center subunit III, chloroplastic-like</td><td>-1.5190</td><td>-1.6335</td><td>Photosynthesis</td></tr><tr><td><italic>PsaFc</italic></td><td>Niben101Scf 04964g00002</td><td>photosystem I reaction center subunit III, chloroplastic-like</td><td>-1.5257</td><td>-1.2865</td><td>Photosynthesis</td></tr><tr><td><italic>PsaNa</italic></td><td>Niben101Scf 17701g01020</td><td>photosystem I reaction center subunit N, chloroplastic-like</td><td>-1.6702</td><td>-1.5537</td><td>Photosynthesis</td></tr><tr><td><italic>PsaNb</italic></td><td>Niben101Scf 35628g00001</td><td>photosystem I reaction center subunit N, chloroplastic-like</td><td>-1.3129</td><td>-1.0396</td><td>Photosynthesis</td></tr><tr><td><italic>ChlHa</italic></td><td>Niben101Scf 04388g00011</td><td>magnesium-chelatase subunit ChlH, chloroplastic-like</td><td>-1.6623</td><td>-2.1794</td><td>Porphyrin and chlorophyll metabolism</td></tr><tr><td><italic>ChlHb</italic></td><td>Niben101Scf 07214g00015</td><td>magnesium-chelatase subunit ChlH, chloroplastic-like</td><td>-1.4638</td><td>-1.8585</td><td>Porphyrin and chlorophyll metabolism</td></tr><tr><td><italic>BchP</italic></td><td>Niben101Scf 06249g03002</td><td>geranylgeranyl diphosphate reductase, chloroplastic-like</td><td>-1.8576</td><td>-1.0521</td><td>Porphyrin and chlorophyll metabolism</td></tr><tr><td><italic>HemA</italic></td><td>Niben101Scf 10063g00003</td><td>glutamyl-tRNA reductase 1,chloroplastic-like</td><td>-1.4101</td><td>-2.0903</td><td>Porphyrin and chlorophyll metabolism</td></tr><tr><td><italic>DXS</italic></td><td>Niben101Scf 00246g04005</td><td>probable 1-deoxy-D-xylulose-5-phosphate synthase, chloroplastic-like</td><td>-1.0040</td><td>-1.0126</td><td>Metabolic pathways</td></tr><tr><td><italic>GME1-X1</italic></td><td>Niben101Scf 01696g06050</td><td>GDP-mannose 3,5-epimerase 1-like,transcript variant X1</td><td>-1.6022</td><td>-1.1137</td><td>Metabolic pathways</td></tr><tr><td><italic>CAB3A</italic></td><td>Niben101Scf 03961g00004</td><td>chlorophyll a-b binding protein 50, chloroplastic-like</td><td>-1.1418</td><td>-1.0719</td><td>Metabolic pathways</td></tr><tr><td><italic>GDCSa</italic></td><td>Niben101Scf 02480g02012</td><td>glycine dehydrogenase (decarboxylating), mitochondrial-like</td><td>-1.5732</td><td>-1.1698</td><td>Carbon metabolism</td></tr><tr><td><italic>GDCSb</italic></td><td>Niben101Scf 03839g04019</td><td>glycine dehydrogenase (decarboxylating), mitochondrial-like</td><td>-1.1991</td><td>-1.0395</td><td>Carbon metabolism</td></tr><tr><td><italic>rbcS</italic></td><td>Niben101Scf 02381g04022</td><td>ribulose bisphosphate carboxylase small chain S41, chloroplastic-like</td><td>-1.2691</td><td>0.7603</td><td>Carbon fixation in photosynthetic organisms</td></tr><tr><td><italic>FBA1</italic></td><td>Niben101Scf 02864g04008</td><td>fructose-bisphosphate aldolase 1,chloroplastic-like</td><td>-1.3167</td><td>-1.0072</td><td>Carbon fixation in photosynthetic organisms</td></tr><tr><td><italic>glsF</italic></td><td>Niben101Scf 04198g01002</td><td>ferredoxin-dependent glutamate synthase, chloroplastic-like</td><td>-1.1161</td><td>-1.0704</td><td>Glyoxylate and dicarboxylate metabolism</td></tr><tr><td><italic>GRP</italic></td><td>Niben101Scf 03052g00011</td><td>glycine-rich protein-like</td><td>2.1379</td><td>1.4647</td><td>No pathway enriched</td></tr><tr><td><italic>GRP3a</italic></td><td>Niben101Scf 01084g05013</td><td>glycine-rich protein 3-like</td><td>3.9423</td><td>3.1735</td><td>No pathway enriched</td></tr><tr><td><italic>GRP3b</italic></td><td>Niben101Scf 01084g03004</td><td>glycine-rich protein 3-like</td><td>2.0529</td><td>1.8836</td><td>No pathway enriched</td></tr><tr><td><italic>CAX3</italic></td><td>Niben101Scf 01329g00002</td><td>vacuolar cation/proton exchanger 3-like</td><td>-2.2799</td><td>-1.2535</td><td>No pathway enriched</td></tr><tr><td><italic>FSD1</italic></td><td>Niben101Scf 03679g03009</td><td>Fe superoxide dismutas ,chloroplastic-like</td><td>-2.1527</td><td>-1.9924</td><td>No pathway enriched</td></tr><tr><td><italic>PU</italic></td><td>Niben101Scf 10524g02015</td><td>putative uncharacterized protein</td><td>2.0616</td><td>0.9243</td><td>No pathway enriched</td></tr></tbody></table><table-wrap-foot><p><italic>FC</italic> Fold change</p><p><sup>a</sup>Y35AB vs. CK</p><p><sup>b</sup>Y35A vs. CK</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec21"><title>Validation of the selected genes by RT-qPCR</title><p id="Par26">To validate the RNA-seq data, 12 genes were selected randomly for RT-qPCR analysis from the Table <xref rid="Tab2" ref-type="table">2</xref>, including genes <italic>GDCSa</italic>, <italic>GDCSb</italic>, <italic>PsaFa</italic>, <italic>PsaFb</italic>, <italic>PsaFc</italic>, <italic>PsaNa</italic>, <italic>PsaNb</italic>, <italic>glsF</italic>, <italic>CAX3</italic>, <italic>GRP</italic>, <italic>GRP3a</italic> and <italic>PU</italic>. The results indicated that the genes expression patterns by RT-qPCR were consistent with that by transcriptome sequencing (Fig. <xref rid="Fig5" ref-type="fig">5</xref>), the fold changes between RNA-seq and RT-qPCR were different which maybe caused by the sensitive of methodology or the used samples between RNA-seq and RT-qPCR were not the same one.<fig id="Fig5"><label>Fig. 5</label><caption><p>Comparison of relative expression levels determined by RNA-seq and qPCR on 12 genes selected. All qPCR reactions were used three biological replica samples, repeated three times, and the data are presented as the mean ± SD. Relative expression levels are calculated from Ct values according to the 2<sup>–ΔΔCt</sup> method. Actin was the reference gene for these qPCR experiments. Asterisks indicate statistically significant differences compared with CK, “*” indicate significant difference (0.01 ≤ <italic>p</italic> < 0.05), “**” indicate extremely significant difference (<italic>P</italic> < 0.01)</p></caption><graphic xlink:href="12985_2018_1044_Fig5_HTML" id="MO5"></graphic></fig></p></sec><sec id="Sec22"><title>Analysis of pathogenesis-related (PR) genes</title><p id="Par27">An important feature of the plant defense in response to pathogen attack is the induction and accumulation of various PR proteins which are also a part of systematic acquired resistance (SAR). There were 29 PR genes identified by a local BLAST in RNA-seq dataset and online BLAST analysis based on reported PR family genes in <italic>N. tabacum</italic>. Among them, eight genes (27.6%) were significantly up-regulated, including <italic>PR-2</italic> (Glucan endo-1,3-beta-glucosidase-like), <italic>PR-3</italic> (Chitinase 8, glycoside hydrolase), <italic>PR-5</italic> (Pathogenesis-related thaumatin superfamily protein), <italic>PR-11</italic> (Chitinase-3-like protein 2), <italic>PR-17</italic> (Plant basic secretory protein family protein), of them four genes were found in Y35AB vs CK, and five genes were observed in Y35A vs CK (Table <xref rid="Tab3" ref-type="table">3</xref>).<table-wrap id="Tab3"><label>Table 3</label><caption><p>Screened PRP family genes</p></caption><table frame="hsides" rules="groups"><thead><tr><th>PR family</th><th>Unigene ID</th><th>Protein properties</th><th>log<sub>2</sub>FC<sup>a</sup></th><th>qvalue<sup>a</sup></th><th>log<sub>2</sub>FC<sup>b</sup></th><th>qvalue<sup>b</sup></th></tr></thead><tbody><tr><td rowspan="4">PR1</td><td>Niben101Scf13926g01014</td><td>Cysteine-rich secretory protein, allergen V5/Tpx-1-related</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf03376g03004</td><td>Cysteine-rich secretory protein, allergen V5/Tpx-1-related</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf00107g03008</td><td>Cysteine-rich secretory protein, allergen V5/Tpx-1-related</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf01999g07002</td><td>Cysteine-rich secretory protein, allergen V5/Tpx-1-related</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="5">PR2</td><td>Niben101Scf01001g00005</td><td>Glucan endo-1,3-beta-glucosidase-like, Glycoside hydrolase, family 17</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf01001g00004</td><td>Glucan endo-1,3-beta-glucosidase-like, Glycoside hydrolase, family 17</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf01001g00003</td><td>Glucan endo-1,3-beta-glucosidase-like, Glycoside hydrolase, family 17</td><td></td><td></td><td>Inf</td><td>0.023496</td></tr><tr><td>Niben101Ctg13736g00004</td><td>Glucan endo-1,3-beta-glucosidase-like, Glycoside hydrolase, family 17</td><td></td><td></td><td>Inf</td><td>1.94E-04</td></tr><tr><td>Niben101Scf04869g03002</td><td>Glucan endo-1,3-beta-glucosidase-like, Glycoside hydrolase, family 17</td><td>3.9490</td><td>0.038646</td><td>5.4381</td><td>2.14E-04</td></tr><tr><td></td><td>Niben101Scf01001g00006</td><td>Glucan endo-1,3-beta-glucosidase-like, Glycoside hydrolase, family 17</td><td></td><td></td><td></td><td></td></tr><tr><td>PR3</td><td>Niben101Scf02041g00002</td><td>Chitinase 8, Glycoside hydrolase, family 19</td><td></td><td></td><td>5.1058</td><td>1.99E-05</td></tr><tr><td rowspan="2">PR4</td><td>Niben101Scf01400g00014</td><td>Thaumatin-like protein</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf03436g01016</td><td>Thaumatin-like protein</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">PR5</td><td>Niben101Scf00126g00008</td><td>Pathogenesis-related thaumatin superfamily protein</td><td>0.9949</td><td>0.027102</td><td></td><td></td></tr><tr><td>Niben101Scf05554g05006</td><td>Pathogenesis-related thaumatin superfamily protein</td><td>1.4585</td><td>3.24E-08</td><td></td><td></td></tr><tr><td rowspan="2">PR6</td><td>Niben101Scf00953g05001</td><td>Cysteine-rich secretory protein, allergen V5/Tpx-1-related</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf04053g01004</td><td>Cysteine-rich secretory protein, allergen V5/Tpx-1-related</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">PR9</td><td>Niben101Scf03460g04004</td><td>Peroxidase 53, Haem peroxidase</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf07182g05012</td><td>Peroxidase 53, Haem peroxidase</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">PR10</td><td>Niben101Scf03526g00006</td><td>Major pollen allergen Bet v 1-M/N, Bet v I type allergen</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf10735g00016</td><td>Major pollen allergen Bet v 1-M/N, Bet v I type allergen</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf02474g01024</td><td>Major pollen allergen Bet v 1-M/N, Bet v I type allergen</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf01938g04007</td><td>Major pollen allergen Bet v 1-M/N, Bet v I type allergen</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">PR11</td><td>Niben101Scf06295g04023</td><td>Chitinase-3-like protein 2, Glycoside hydrolase superfamily</td><td>4.4843</td><td>0.007133</td><td></td><td></td></tr><tr><td>Niben101Scf01789g04010</td><td>Chitinase-3-like protein 2, Glycoside hydrolase superfamily</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">PR17</td><td>Niben101Scf03385g02011</td><td>Plant basic secretory protein family protein, uncharacterised protein family</td><td></td><td></td><td>2.7696</td><td>6.69E-04</td></tr><tr><td>Niben101Scf03385g01006</td><td>Plant basic secretory protein family protein, uncharacterised protein family</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Scf01341g01002</td><td>Plant basic secretory protein family protein, uncharacterised protein family</td><td></td><td></td><td></td><td></td></tr><tr><td>Niben101Ctg10643g00004</td><td>Plant basic secretory protein family protein, uncharacterised protein family</td><td></td><td></td><td></td><td></td></tr></tbody></table><table-wrap-foot><p>log<sub>2</sub>FC > 0, up-regulated, log<sub>2</sub>FC < 0, down-regulated. Inf: the readcount of control (CK) was zero. Blank lattices show genes expression has no significant difference</p><p><italic>FC</italic> Fold change</p><p><sup>a</sup>Y35AB vs. CK</p><p><sup>b</sup>Y35A vs. CK</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec23"><title>Analysis of LRR-RLKs genes</title><p id="Par28">Leucine-rich repeat receptor-like protein kinases (LRR-RLKs) are the largest of receptor-like kinases in plants and play crucial roles in development and stress responses. In the present study, We combined RNA-seq dataset obtained LRR-RLK sequences with previously NCBI reported sequences to perform analysis, results showed that a total of 71 unigenes were identified potential LRR-RLK genes in RNA-seq dataset, however, 44 significantly different unigenes were observed. Among them, 18 unigenes were found in Y35AB vs CK with 10 unigenes down-regulated and the other 8 unigenes up-regulated, and 32 unigenes expressed in Y35A vs CK, with 20 and 12 unigenes were down-regulated and up-regulated, respectively. Five unigenes were commonly regulated in both Y35AB vs CK and Y35A vs CK, including one up-regulated and four down-regulated unigenes (Table <xref rid="Tab4" ref-type="table">4</xref>).<table-wrap id="Tab4"><label>Table 4</label><caption><p>Screened DEGs of LRR-RLKs</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Unigene ID</th><th>Protein properties</th><th>log<sub>2</sub>FC<sup>a</sup></th><th>qvalue<sup>a</sup></th><th>log<sub>2</sub>FC<sup>b</sup></th><th>qvalue<sup>b</sup></th></tr></thead><tbody><tr><td>Niben101Scf13404g00002</td><td>Brassinosteroid LRR receptor kinase-like; BRI1</td><td></td><td></td><td>-0.8361</td><td>0.000272</td></tr><tr><td>Niben101Scf07123g01015</td><td>Elicitor-inducible leucine-rich repeats receptor-like protein</td><td></td><td></td><td>5.5080</td><td>0.000289</td></tr><tr><td>Niben101Scf00104g02013</td><td>F-box/LRR-repeat protein 17-like</td><td></td><td></td><td>0.8664</td><td>0.021066</td></tr><tr><td>Niben101Scf04252g00009</td><td>F-box/LRR-repeat protein 17-like</td><td></td><td></td><td>1.8551</td><td>0.003213</td></tr><tr><td>Niben101Scf09559g00005</td><td>F-box/LRR-repeat MAX2 homolog A-like</td><td>0.8581</td><td>0.018415</td><td></td><td></td></tr><tr><td>Niben101Scf15394g00006</td><td>F-box/LRR-repeat protein 14-like</td><td>-0.8927</td><td>0.013552</td><td></td><td></td></tr><tr><td>Niben101Scf20268g00001</td><td>LRR receptor-like serine/threonine-protein kinase ERECTA</td><td></td><td></td><td>-0.7116</td><td>0.011214</td></tr><tr><td>Niben101Scf05301g03002</td><td>LRR receptor-like serine/threonine-protein kinase ERL1</td><td>-0.7516</td><td>0.013687</td><td>-0.7589</td><td>0.013627</td></tr><tr><td>Niben101Scf00247g01007</td><td>LRR receptor-like serine/threonine-protein kinase ERL1</td><td></td><td></td><td>-0.5633</td><td>0.024694</td></tr><tr><td>Niben101Scf11723g02003</td><td>LRR receptor-like serine/threonine-protein kinase ERL1</td><td>-0.6679</td><td>0.026512</td><td>-0.7100</td><td>0.017084</td></tr><tr><td>Niben101Scf03619g03004</td><td>LRR receptor-like serine/threonine-protein kinase FEI2</td><td>-0.5426</td><td>0.018415</td><td></td><td></td></tr><tr><td>Niben101Scf03925g01010</td><td>LRR receptor-like serine/threonine-protein kinase GSO1</td><td>2.3343</td><td>0.007479</td><td>3.1551</td><td>0.041202</td></tr><tr><td>Niben101Scf02203g04006</td><td>Plant intracellular Ras-group-related LRR protein 4-like</td><td></td><td></td><td>-0.6640</td><td>0.048845</td></tr><tr><td>Niben101Scf00206g00014</td><td>putative F-box/LRR-repeat protein At5g02700</td><td>1.5307</td><td>0.020135</td><td></td><td></td></tr><tr><td>Niben101Scf00073g04006</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g07650</td><td></td><td></td><td>-1.4546</td><td>0.005161</td></tr><tr><td>Niben101Scf00244g03004</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g06840</td><td>-0.6603</td><td>0.021347</td><td></td><td></td></tr><tr><td>Niben101Scf00418g02007</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g37250</td><td></td><td></td><td>-0.5934</td><td>0.047527</td></tr><tr><td>Niben101Scf00920g09027</td><td>probable LRR receptor-like serine/threonine-protein kinase At5g48740</td><td>-1.1084</td><td>0.000766</td><td></td><td></td></tr><tr><td>Niben101Scf01061g08014</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g20940</td><td></td><td></td><td>-1.0192</td><td>0.001468</td></tr><tr><td>Niben101Scf01278g09008</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g56140</td><td></td><td></td><td>0.9239</td><td>0.023952</td></tr><tr><td>Niben101Scf02357g08010</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g07650</td><td>-0.6424</td><td>0.001803</td><td></td><td></td></tr><tr><td>Niben101Scf02665g15003</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g06840</td><td>-0.5769</td><td>0.044996</td><td></td><td></td></tr><tr><td>Niben101Scf02827g07005</td><td>probable LRR receptor-like serine/threonine-protein kinase At3g47570</td><td></td><td></td><td>2.3756</td><td>0.027087</td></tr><tr><td>Niben101Scf03098g00011</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g34110</td><td></td><td></td><td>-1.2224</td><td>3.35E-06</td></tr><tr><td>Niben101Scf03262g02006</td><td>probable LRR receptor-like serine/threonine-protein kinase At2g24230</td><td></td><td></td><td>-0.6865</td><td>0.030882</td></tr><tr><td>Niben101Scf03445g05005</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g26540</td><td></td><td></td><td>-0.8802</td><td>0.000669</td></tr><tr><td>Niben101Scf03735g07013</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g36180</td><td>2.0409</td><td>0.002356</td><td></td><td></td></tr><tr><td>Niben101Scf05348g01026</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g12460</td><td></td><td></td><td>-1.3373</td><td>3.02E-05</td></tr><tr><td>Niben101Scf05405g07003</td><td>probable LRR receptor-like serine/threonine-protein kinase At3g47570</td><td></td><td></td><td>2.0599</td><td>0.003076</td></tr><tr><td>Niben101Scf05405g07006</td><td>probable LRR receptor-like serine/threonine-protein kinase At3g47570</td><td></td><td></td><td>1.5589</td><td>0.022376</td></tr><tr><td>Niben101Scf05767g05006</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g20940</td><td></td><td></td><td>-0.8478</td><td>0.000497</td></tr><tr><td>Niben101Scf05977g01008</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g12460</td><td></td><td></td><td>-1.2826</td><td>8.11E-05</td></tr><tr><td>Niben101Scf06144g00013</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g20940</td><td></td><td></td><td>-0.9557</td><td>7.81E-05</td></tr><tr><td>Niben101Scf06151g02014</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g67720</td><td>0.7683</td><td>0.046840</td><td></td><td></td></tr><tr><td>Niben101Scf06562g02013</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g26540</td><td>-0.5968</td><td>0.021640</td><td>-0.9943</td><td>2.01E-05</td></tr><tr><td>Niben101Scf06789g03005</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g67720</td><td>0.9483</td><td>0.042093</td><td>0.9711</td><td>0.042650</td></tr><tr><td>Niben101Scf07034g06018</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g36180</td><td></td><td></td><td>-0.8501</td><td>0.034812</td></tr><tr><td>Niben101Scf07515g02006</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g56140</td><td></td><td></td><td>0.6846</td><td>0.005558</td></tr><tr><td>Niben101Scf07681g01013</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g20940</td><td></td><td></td><td>-0.7450</td><td>0.014076</td></tr><tr><td>Niben101Scf07695g01023</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g30520</td><td>0.7628</td><td>0.001146</td><td></td><td></td></tr><tr><td>Niben101Scf07736g01007</td><td>probable LRR receptor-like serine/threonine-protein kinase At1g63430</td><td></td><td></td><td>0.6791</td><td>0.006612</td></tr><tr><td>Niben101Scf08134g02008</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g37250</td><td>-0.5193</td><td>0.047055</td><td>-0.7817</td><td>0.000797</td></tr><tr><td>Niben101Scf10101g00023</td><td>probable LRR receptor-like serine/threonine-protein kinase At4g30520</td><td>0.6651</td><td>0.002463</td><td></td><td></td></tr><tr><td>Niben101Scf11047g00001</td><td>probable LRR receptor-like serine/threonine-protein kinase At2g16250</td><td></td><td></td><td>0.7640</td><td>0.047280</td></tr></tbody></table><table-wrap-foot><p>log<sub>2</sub>FC > 0, up-regulated, log<sub>2</sub>FC < 0, down-regulated. Blank lattices show genes expression has no significant difference</p><p><italic>FC</italic> Fold change</p><p><sup>a</sup>Y35AB vs. CK</p><p><sup>b</sup>Y35A vs. CK</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec24"><title>Analysis of brassinosteroid and jasmonic acid pathway</title><p id="Par29">Plant hormones are not only essential for growth and development, but also play crucial roles in plant defense responses [<xref ref-type="bibr" rid="CR33">33</xref>, <xref ref-type="bibr" rid="CR34">34</xref>]. The transcriptome data showed that only one brassinosteroid (BR) synthesis-related gene, 3-epi-6-deoxocathasterone 23-monooxygenase (<italic>CYP90C1/D1</italic>) was significantly decreased upon virus infection (Fig. <xref rid="Fig6" ref-type="fig">6a</xref>), it is likely result in a reduction of brassinosteroid. By contrast, expressions of jasmonic acid (JA) -ralated biosynthesis genes <italic>DOX1</italic>, <italic>HPL1</italic>, <italic>SAMT-X1</italic> were decreased and <italic>PLA1/A2</italic>, <italic>loxF</italic>, <italic>KAT2</italic>, <italic>SAMT-X2</italic> were significantly increased upon virus infection (Fig. <xref rid="Fig6" ref-type="fig">6b</xref>). We conjecture that the expression level of jasmonic acid might was increase. In addition, part of BR and JA signaling genes expression level were also altered, <italic>BRI1</italic>, <italic>BZR2</italic>, <italic>CYCD3-X2</italic> were down-regulated and <italic>BZR1</italic>, <italic>CYCD3-X1</italic> were up-regulated in BR signal transduction pathway, and <italic>JAR1</italic>, <italic>COI1</italic>, <italic>MYC2</italic> were down- regulated and <italic>JAZ1</italic>, <italic>JAZ2</italic> were up-regulated in JA signal transduction pathway (Fig. <xref rid="Fig6" ref-type="fig">6c</xref>). All synthesis- and signal transduction- related significantly difference expressed unigenes of BR and JA pathway shown in Table <xref rid="Tab5" ref-type="table">5</xref>.<fig id="Fig6"><label>Fig. 6</label><caption><p>DEGs of BR and JA in biosynthesis and signal transduction pathway. <bold>a</bold> BR biosynthesis pathway, <bold>b</bold> JA biosynthesis pathway, <bold>c</bold> signal transduction pathway of BR and JA, respectively. Genes with red background were up-regulated, green background were down-regulated, yellow background some were up-regulated and some were down-regulated</p></caption><graphic xlink:href="12985_2018_1044_Fig6_HTML" id="MO6"></graphic></fig><table-wrap id="Tab5"><label>Table 5</label><caption><p>Significant difference expression unigenes of BR and JA pathway</p></caption><table frame="hsides" rules="groups"><thead><tr><th></th><th>Gene symbol</th><th>Unigene ID</th><th>Protein properties</th><th>log<sub>2</sub>FC<sup>a</sup></th><th>qvalue<sup>a</sup></th><th>log<sub>2</sub>FC<sup>b</sup></th><th>qvalue<sup>b</sup></th></tr></thead><tbody><tr><td rowspan="7">BR</td><td><italic>CYP90C1/D1</italic></td><td>Niben101Scf05764g04013</td><td>3-epi-6-deoxocathasterone 23-monooxygenase</td><td>-0.8193</td><td>0.019172</td><td></td><td></td></tr><tr><td><italic>BRI1</italic></td><td>Niben101Scf13404g00002</td><td>Brassinosteroid LRR receptor kinase-like, BRI1</td><td></td><td></td><td>-0.8361</td><td>2.72E-04</td></tr><tr><td><italic>BZR1</italic></td><td>Niben101Scf03110g05009</td><td>Brassinosteroid resistant 1</td><td>0.5592</td><td>0.025611</td><td></td><td></td></tr><tr><td><italic>BZR2</italic></td><td>Niben101Scf06112g01006</td><td>Brassinosteroid resistant 2</td><td></td><td></td><td>-1.2497</td><td>7.36E-07</td></tr><tr><td><italic>CYCD3-X1</italic></td><td>Niben101Scf05643g01012</td><td>Cyclin D3, 3 protein, plant</td><td>1.3753</td><td>1.44E-07</td><td></td><td></td></tr><tr><td><italic>CYCD3-X1</italic></td><td>Niben101Scf02445g10017</td><td>Cyclin D3, 3 protein, plant</td><td>1.2863</td><td>0.002511</td><td></td><td></td></tr><tr><td><italic>CYCD3-X2</italic></td><td>Niben101Scf00107g02002</td><td>Cyclin D3, 2 protein, plant</td><td>-0.8767</td><td>0.017675</td><td>-1.2925</td><td>2.43E-04</td></tr><tr><td rowspan="13">JA</td><td><italic>PLA1/A2</italic></td><td>Niben101Scf00711g02004</td><td>Triacylglycerol lipase SDP1-like; Phospholipase A1/A2</td><td>1.8227</td><td>0.003036</td><td></td><td></td></tr><tr><td><italic>DOX1</italic></td><td>Niben101Scf07070g02002</td><td>Alpha-dioxygenase</td><td>-3.8126</td><td>7.60E-13</td><td>-3.9498</td><td>7.95E-14</td></tr><tr><td><italic>loxF</italic></td><td>Niben101Scf05407g00001</td><td>Linoleate 9S-lipoxygenase-like</td><td>0.9407</td><td>0.021540</td><td></td><td></td></tr><tr><td><italic>HPL1</italic></td><td>Niben101Scf00313g08016</td><td>Fatty acid hydroperoxide lyase, HPL1</td><td>-1.2170</td><td>1.14E-09</td><td>-0.9629</td><td>7.37E-07</td></tr><tr><td><italic>HPL1</italic></td><td>Niben101Scf02207g11009</td><td>Fatty acid hydroperoxide lyase, HPL1</td><td>-1.4966</td><td>1.06E-05</td><td></td><td></td></tr><tr><td><italic>KAT2</italic></td><td>Niben101Scf10189g02009</td><td>3-ketoacyl-CoA thiolase 2, peroxisomal</td><td></td><td></td><td>0.6201</td><td>0.007053</td></tr><tr><td><italic>SAMT-X1</italic></td><td>Niben101Scf05122g00005</td><td>Salicylate carboxymethyltransferase-like</td><td>-1.4545</td><td>2.97E-11</td><td>-0.8505</td><td>2.96E-04</td></tr><tr><td><italic>SAMT-X2</italic></td><td>Niben101Scf01146g12006</td><td>Salicylate carboxymethyltransferase-like</td><td></td><td></td><td>1.6487</td><td>0.010833</td></tr><tr><td><italic>JAR1</italic></td><td>Niben101Scf01076g00005</td><td>Jasmonic acid-amino synthetase</td><td>-0.6477</td><td>0.003456</td><td>-0.8340</td><td>0.001705</td></tr><tr><td><italic>COI1</italic></td><td>Niben101Scf02280g08005</td><td>Coronatine-insensitive 1, COI1</td><td>-0.6123</td><td>0.024317</td><td>-0.8990</td><td>2.81E-04</td></tr><tr><td><italic>JAZ1</italic></td><td>Niben101Scf00298g01006</td><td>Jasmonate ZIM-domain protein 1</td><td>0.7577</td><td>0.039355</td><td></td><td></td></tr><tr><td><italic>JAZ2</italic></td><td>Niben101Scf07798g03026</td><td>Jasmonate ZIM domain-containing protein</td><td></td><td></td><td>0.7728</td><td>3.95E-04</td></tr><tr><td>MYC2</td><td>Niben101Scf15224g00002</td><td>Transcription factor MYC2</td><td></td><td></td><td>-0.6238</td><td>0.042856</td></tr></tbody></table><table-wrap-foot><p>log<sub>2</sub>FC > 0, up-regulated, log<sub>2</sub>FC < 0, down-regulated. Blank lattices show genes expression has no significant difference</p><p><italic>FC</italic> Fold change</p><p><sup>a</sup>Y35AB vs. CK</p><p><sup>b</sup>Y35A vs. CK</p></table-wrap-foot></table-wrap></p></sec></sec><sec id="Sec25"><title>Discussion</title><p id="Par30">TbCSV is a serious threat to many crops in China. In this study, RNA-seq -based transcriptomic characterization and comparative analysis of TbCSV-infected <italic>N. benthamiana</italic> with control plants was used to shed some light on understanding the molecular interactions of this pathosystem. 4081 and 3196 DEGs were screened from Y35AB vs CK and Y35A vs CK, respectively. Among the top 15 enriched physiological pathways, the porphyrin and chlorophyll metabolism, photosynthesis and pentose phosphate pathway were significantly affected in Y35AB vs CK. It suggested that, the disorder of these pathways might be responsible to the more serious leaf curling symptom on Y35AB-infected <italic>N. benthamiana</italic> plants. In addition, previous reports showed that βC1, an essential pathogenicity protein encoded by betasatellite, is required for symptom induction and RNA silencing suppression [<xref ref-type="bibr" rid="CR2">2</xref>, <xref ref-type="bibr" rid="CR16">16</xref>, <xref ref-type="bibr" rid="CR35">35</xref>–<xref ref-type="bibr" rid="CR37">37</xref>]. Thus, βC1 protein might contribute to the specific changes of those genes or biological pathways in Y35AB-infected plants.</p><p id="Par31">In our study, the DEGs expression with high levels that mainly concerned with photosynthesis-related genes including photosynthesis, porphyrin and chlorophyll metabolismand carbon fixation in photosynthetic organisms were down-regulated in <italic>N. benthamiana</italic> plants infected with TbCSV. Meanwhile, the KEGG pathway analysis showed significant enrichments of the photosynthesis, and the porphyrin and chlorophyll metabolism pathway in Y35AB-infected plants, with higher rich factor. It has been reported that photosynthesis-related genes could be affected upon virus infection such as <italic>Tobacco mosaic virus</italic> (TMV) [<xref ref-type="bibr" rid="CR38">38</xref>], <italic>Cucumber mosaic virus</italic> (CMV) [<xref ref-type="bibr" rid="CR39">39</xref>], <italic>Rice stripe virus</italic> (RSV) [<xref ref-type="bibr" rid="CR40">40</xref>, <xref ref-type="bibr" rid="CR41">41</xref>] and <italic>Alfalfa mosaic virus</italic> (AMV) [<xref ref-type="bibr" rid="CR42">42</xref>]. And the chloroplast, one of the most dynamic organelles ofplant cell, plays an active part in the defense response and is crucial for inter organelle signaling [<xref ref-type="bibr" rid="CR43">43</xref>]. Therefore, viruses need to suppress the chloroplast-mediated defense by employing pathogenicity factors, such as effector proteins, for successful infections [<xref ref-type="bibr" rid="CR44">44</xref>, <xref ref-type="bibr" rid="CR45">45</xref>]. Furthermore, a previous study showed that a Radish leaf curl betasatellite (RaLCB) damages the structural and functional integrity of chloroplasts, leading to inhibition of photosynthesis and symptom formation [<xref ref-type="bibr" rid="CR46">46</xref>]. Some photosynthesis-related genes were down-regulated during both Y35A and Y35AB infections, indicating that these genes might participate in the interaction between TbCSV and <italic>N. benthamiana</italic>.</p><p id="Par32">An important feature of the plant defense response to pathogen attack is the induction and accumulation of various PR proteins, which are also a part of systematic acquired resistance (SAR) [<xref ref-type="bibr" rid="CR47">47</xref>]. Previously, PR proteins were divided into five families based on their localization, isoelectric point, molecular mass, and biological activity [<xref ref-type="bibr" rid="CR48">48</xref>]. PR proteins are currently categorized into 17 families. At present, besides <italic>PR-6</italic> is predicted by automated computational analysis based on a genomic sequence (gene ID: LOC107768382), nine out of 17 families, including <italic>PR-1</italic>, <italic>PR-2</italic> [<xref ref-type="bibr" rid="CR49">49</xref>], <italic>PR-3</italic>, <italic>PR-4</italic>, <italic>PR-5</italic> [<xref ref-type="bibr" rid="CR50">50</xref>], <italic>PR-9</italic> [<xref ref-type="bibr" rid="CR51">51</xref>], <italic>PR-10</italic> [<xref ref-type="bibr" rid="CR52">52</xref>], <italic>PR-11</italic> [<xref ref-type="bibr" rid="CR53">53</xref>], <italic>PR-17</italic> [<xref ref-type="bibr" rid="CR54">54</xref>] families were reported that associated with the acquired resistance to pathogen infections. Among these PR proteins, <italic>PR-1</italic> is generally considered as a marker gene of disease resistance [<xref ref-type="bibr" rid="CR55">55</xref>]. Based on NCBI retrieval and local BLAST analysis, 29 <italic>PR</italic> genes in <italic>N. benthamiana</italic> were identified. In the present study, the expression levels of 8 <italic>PR</italic> genes were found to be significantly regulated in virus-infected <italic>N. benthamiana</italic> plants (Table <xref rid="Tab3" ref-type="table">3</xref>). It was previously reported that in pathogens-infected wheat, the genes encoding peroxidase, <italic>PR-1</italic>, <italic>PR-2</italic>, <italic>PR-3</italic>, <italic>PR-4</italic>, and <italic>PR-5</italic> were induced after 6–12 h and reached the highest levels at 36–48 h [<xref ref-type="bibr" rid="CR56">56</xref>, <xref ref-type="bibr" rid="CR57">57</xref>]. In our research, leaf tissues of <italic>N. benthamiana</italic> plants for RNA-seq assays were collected at 20 dpi, and the transcript levels of some PR genes (8 out of 29) were regulated significantly. For subsequent research, the expression of <italic>PR</italic> genes can be determined in a time course study. Based on our research, we speculated that some types of PR proteins might play roles in defense response to TbCSV infection.</p><p id="Par33">In plants, many cellular signaling transductions are mediated by receptor-like kinases (RLKs). Leucine-rich repeat receptor-like protein kinases (LRR-RLKs) are the largest group of receptor-like kinases in plants and play crucial roles in development and stress responses [<xref ref-type="bibr" rid="CR58">58</xref>]. LRR-RLKs regulate a wide range of plant growth and development, including meristem development [<xref ref-type="bibr" rid="CR59">59</xref>, <xref ref-type="bibr" rid="CR60">60</xref>], secondary growth [<xref ref-type="bibr" rid="CR61">61</xref>], microsporogenesis and embryogenesis [<xref ref-type="bibr" rid="CR62">62</xref>]. Besides, some LRR-RLKs mediated plant resistance against bacterial [<xref ref-type="bibr" rid="CR63">63</xref>, <xref ref-type="bibr" rid="CR64">64</xref>] or viral pathogens [<xref ref-type="bibr" rid="CR65">65</xref>, <xref ref-type="bibr" rid="CR66">66</xref>]. In this study, 71 LRR-RLKs genes were identified. Among them, 44 were differentially expressed in virus-infected <italic>N. benthamiana</italic> plants. The results showed that these LRR-RLKs genes might play important roles in <italic>N. benthamiana</italic> responses to TbCSV infection. By contrast, in the present of TbCSB, less number of <italic>LRR-RLK</italic>s genes were regulated (Table <xref rid="Tab4" ref-type="table">4</xref>).</p><p id="Par34">BR and JA are two important plant hormones that play crucial roles in plant growth and development [<xref ref-type="bibr" rid="CR67">67</xref>] and also involved in plant defense responses to pathogen infections [<xref ref-type="bibr" rid="CR68">68</xref>–<xref ref-type="bibr" rid="CR70">70</xref>]. In the BR signaling pathway, BRASSINAZOLE RESISTANT (BZR) is a transcription factor, which orchestrating plant developmental and physiological processes by regulating BR-target gene expression [<xref ref-type="bibr" rid="CR71">71</xref>, <xref ref-type="bibr" rid="CR72">72</xref>]. BRASSINOSTEROID INSENSITIVE 1 (BRI1) is a brassinosteroid receptor, of which ubiquitously expresses plasma membrane-localized protein kinase [<xref ref-type="bibr" rid="CR73">73</xref>], belonging to an LRR-RLKs subfamily [<xref ref-type="bibr" rid="CR74">74</xref>]. For the JA signaling transduction, the perception of JA is mediated by the co-receptor CORONATINE INSENSITIVE 1 (COI1), which is an F-box protein cooperated with a family of the JASMONATE ZIM-domain (JAZ) transcriptional proteins. Upon the pathogens infection, bioactive JAs promote direct interaction between COI1 and JAZ proteins and then trigger the SCF-COI1 complex, resulting in poly-ubiquitination and degradation of the JAZ proteins. Ultimately, a variety of transcription factors could be activated for the expression of the JA-responsive genes [<xref ref-type="bibr" rid="CR75">75</xref>]. Besides, MYC2 is a bHLH (basic helix-loop-helix) transcription factor and a positive regulator of JA responses [<xref ref-type="bibr" rid="CR76">76</xref>]. A study has shown that rhizobacterium-mediated induction of JA reduces the symptoms of CMV infection in <italic>Arabidopsis thaliana</italic> ecotype Columbia plants [<xref ref-type="bibr" rid="CR77">77</xref>]. In this study, <italic>BRI1</italic>, <italic>BZR1</italic>, <italic>BZR2</italic>, <italic>CYCD3</italic>, <italic>JAR1</italic>, <italic>COI1</italic>, <italic>JAZ</italic> and <italic>MYC2</italic> genes were significantly regulated under the infection of TbCSV (Fig. <xref rid="Fig6" ref-type="fig">6</xref>). It suggested that BR and JA pathways played a role in response to TbCSV infection.</p></sec><sec id="Sec26"><title>Conclusion</title><p id="Par35">In this study, a genome-wide transcript profile was obtianed for <italic>N. benthamiana</italic> plant infected by TbCSV or plus TbCSB using RNA-seq approaches, and genes involved in plant defense system were found to be significantly regulated after TbCSV and TbCSV /TbCSB infection. The information provided in our study would be particularly useful for investigating the molecular mechanisms concerning begomovirus-host interaction and excavate resistance genes.</p></sec><sec sec-type="supplementary-material"><title>Additional files</title><sec id="Sec27"><p><supplementary-material content-type="local-data" id="MOESM1"><media xlink:href="12985_2018_1044_MOESM1_ESM.docx"><label>Additional file 1:</label><caption><p><bold>Table S1.</bold> Primers used for RT-qPCR. (DOCX 18.9 kb)</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="MOESM2"><media xlink:href="12985_2018_1044_MOESM2_ESM.xls"><label>Additional file 2:</label><caption><p><bold>Table S2.</bold> List of DEGs between Y35AB vs CK. (XLS 796 kb)</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="MOESM3"><media xlink:href="12985_2018_1044_MOESM3_ESM.xls"><label>Additional file 3:</label><caption><p><bold>Table S3.</bold> List of DEGs between Y35A vs CK. (XLS 629 kb)</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="MOESM4"><media xlink:href="12985_2018_1044_MOESM4_ESM.xls"><label>Additional file 4:</label><caption><p><bold>Table S4.</bold> Enriched GO terms of DEGs between Y35AB vs CK. (XLS 3.15 mb)</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="MOESM5"><media xlink:href="12985_2018_1044_MOESM5_ESM.xls"><label>Additional file 5:</label><caption><p><bold>Table S5.</bold> Enriched GO terms of DEGs between Y35A vs CK. (XLS 2.83 mb)</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="MOESM6"><media xlink:href="12985_2018_1044_MOESM6_ESM.xls"><label>Additional file 6:</label><caption><p><bold>Table S6.</bold> Enriched KEGG pathways of DEGs between Y35AB vs CK. (XLS 216 kb)</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="MOESM7"><media xlink:href="12985_2018_1044_MOESM7_ESM.xls"><label>Additional file 7:</label><caption><p><bold>Table S7.</bold> Enriched KEGG pathways of DEGs between Y35A vs CK. (XLS 181 kb)</p></caption></media></supplementary-material></p></sec></sec></body><back><ack><title>Acknowledgements</title><p>We are grateful to Professor Xueping Zhou in the Biotechnology Institute of Zhejiang University for providing the infectious clones of TbCSV isolate Y35 (Y35A) and its betasatellite (Y35B).</p><sec id="FPar1"><title>Funding</title><p id="Par36">This research work was supported by the Fundamental Research Funds for the Central Universities (Grant No. XDJK2017A006 and XDJK2015D039), National Natural Science Founding of China (Grant No. 31772127), China Postdoctoral Science Foundation (2015 M572431), and Chongqing Postdoctoral Science special Foundation (Xm2015120).</p></sec><sec id="FPar2"><title>Availability of data and materials</title><p id="Par37">All data and materials described in the manuscript are available in the Additional files <xref rid="MOESM2" ref-type="media">2</xref>, <xref rid="MOESM3" ref-type="media">3</xref>, <xref rid="MOESM4" ref-type="media">4</xref>, <xref rid="MOESM4" ref-type="media">5</xref>, <xref rid="MOESM6" ref-type="media">6</xref> and <xref rid="MOESM7" ref-type="media">7</xref>.</p></sec></ack><notes notes-type="author-contribution"><title>Authors’ contributions</title><p>LQ conceived and designed the study and revised the paper. KL, GW, ML and MM performed the experiments and made analysis of the data. JD, MS and XS participated preparation including discussion and editing. 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