Differential profiling analysis of miRNAs reveals a regulatory role in low N stress response of Populus.
Identifieur interne : 001E22 ( Main/Exploration ); précédent : 001E21; suivant : 001E23Differential profiling analysis of miRNAs reveals a regulatory role in low N stress response of Populus.
Auteurs : Yuanyuan Ren [Oman] ; Fengshuo Sun ; Jia Hou ; Lei Chen ; Yiyun Zhang ; Xiangyang Kang ; Yanwei WangSource :
- Functional & integrative genomics [ 1438-7948 ] ; 2015.
Descripteurs français
- KwdFr :
- ARN des plantes (génétique), ARN des plantes (métabolisme), Analyse de profil d'expression de gènes (MeSH), Azote (pharmacologie), Populus (effets des médicaments et des substances chimiques), Populus (génétique), Populus (physiologie), Reproductibilité des résultats (MeSH), Régulation de l'expression des gènes végétaux (effets des médicaments et des substances chimiques), Régulation négative (effets des médicaments et des substances chimiques), Régulation négative (génétique), Régulation positive (effets des médicaments et des substances chimiques), Régulation positive (génétique), Stress physiologique (effets des médicaments et des substances chimiques), Stress physiologique (génétique), Séquence conservée (MeSH), Séquençage nucléotidique à haut débit (MeSH), microARN (génétique), microARN (métabolisme).
- MESH :
- effets des médicaments et des substances chimiques : Populus, Régulation de l'expression des gènes végétaux, Régulation négative, Régulation positive, Stress physiologique.
- génétique : ARN des plantes, Populus, Régulation négative, Régulation positive, Stress physiologique, microARN.
- métabolisme : ARN des plantes, microARN.
- pharmacologie : Azote.
- physiologie : Populus.
- Analyse de profil d'expression de gènes, Reproductibilité des résultats, Séquence conservée, Séquençage nucléotidique à haut débit.
English descriptors
- KwdEn :
- Conserved Sequence (MeSH), Down-Regulation (drug effects), Down-Regulation (genetics), Gene Expression Profiling (MeSH), Gene Expression Regulation, Plant (drug effects), High-Throughput Nucleotide Sequencing (MeSH), MicroRNAs (genetics), MicroRNAs (metabolism), Nitrogen (pharmacology), Populus (drug effects), Populus (genetics), Populus (physiology), RNA, Plant (genetics), RNA, Plant (metabolism), Reproducibility of Results (MeSH), Stress, Physiological (drug effects), Stress, Physiological (genetics), Up-Regulation (drug effects), Up-Regulation (genetics).
- MESH :
- chemical , genetics : MicroRNAs, RNA, Plant.
- drug effects : Down-Regulation, Gene Expression Regulation, Plant, Populus, Stress, Physiological, Up-Regulation.
- genetics : Down-Regulation, Populus, Stress, Physiological, Up-Regulation.
- chemical , metabolism : MicroRNAs, RNA, Plant.
- chemical , pharmacology : Nitrogen.
- physiology : Populus.
- Conserved Sequence, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Reproducibility of Results.
Abstract
Nitrogen (N) is an essential mineral element for plant growth processes, and its availability severely affects the productivity of plants, especially trees. MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 21 nucleotides in length that play important roles in plant growth, development and stress responses. To identify Populus miRNAs and their functions in response to nutrition stress, high-throughput sequencing was performed using Populus tomentosa plantlets treated with or without low concentrations of N. We identified 160 conserved miRNAs, 15 known but non-conserved miRNAs, 2 candidate novel miRNAs and 71 corresponding miRNA*s. Differential expression analysis showed that expression of the 21 conserved miRNA families was significantly altered. Real-time quantitative PCR (qPCR) was used to further validate and analyze the dynamic expression of the identified miRNAs. A total of 218 target genes from the low-N-responsive miRNAs were predicted, and their functions were further annotated in combination with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These results suggest that miRNAs play important roles in the response of Populus to low N stress. Furthermore, this study provides the first identification and profiles of N stress-responsive miRNAs from trees.
DOI: 10.1007/s10142-014-0408-x
PubMed: 25398555
Affiliations:
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débit</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Nitrogen (N) is an essential mineral element for plant growth processes, and its availability severely affects the productivity of plants, especially trees. MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 21 nucleotides in length that play important roles in plant growth, development and stress responses. To identify Populus miRNAs and their functions in response to nutrition stress, high-throughput sequencing was performed using Populus tomentosa plantlets treated with or without low concentrations of N. We identified 160 conserved miRNAs, 15 known but non-conserved miRNAs, 2 candidate novel miRNAs and 71 corresponding miRNA*s. Differential expression analysis showed that expression of the 21 conserved miRNA families was significantly altered. Real-time quantitative PCR (qPCR) was used to further validate and analyze the dynamic expression of the identified miRNAs. A total of 218 target genes from the low-N-responsive miRNAs were predicted, and their functions were further annotated in combination with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These results suggest that miRNAs play important roles in the response of Populus to low N stress. Furthermore, this study provides the first identification and profiles of N stress-responsive miRNAs from trees. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25398555</PMID><DateCompleted><Year>2015</Year><Month>09</Month><Day>07</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1438-7948</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><Issue>1</Issue><PubDate><Year>2015</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Functional & integrative genomics</Title><ISOAbbreviation>Funct Integr Genomics</ISOAbbreviation></Journal><ArticleTitle>Differential profiling analysis of miRNAs reveals a regulatory role in low N stress response of Populus.</ArticleTitle><Pagination><MedlinePgn>93-105</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s10142-014-0408-x</ELocationID><Abstract><AbstractText>Nitrogen (N) is an essential mineral element for plant growth processes, and its availability severely affects the productivity of plants, especially trees. MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 21 nucleotides in length that play important roles in plant growth, development and stress responses. To identify Populus miRNAs and their functions in response to nutrition stress, high-throughput sequencing was performed using Populus tomentosa plantlets treated with or without low concentrations of N. We identified 160 conserved miRNAs, 15 known but non-conserved miRNAs, 2 candidate novel miRNAs and 71 corresponding miRNA*s. Differential expression analysis showed that expression of the 21 conserved miRNA families was significantly altered. Real-time quantitative PCR (qPCR) was used to further validate and analyze the dynamic expression of the identified miRNAs. A total of 218 target genes from the low-N-responsive miRNAs were predicted, and their functions were further annotated in combination with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These results suggest that miRNAs play important roles in the response of Populus to low N stress. Furthermore, this study provides the first identification and profiles of N stress-responsive miRNAs from trees. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ren</LastName><ForeName>Yuanyuan</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing, 100083, People's Republic of China, renyychina@sina.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sun</LastName><ForeName>Fengshuo</ForeName><Initials>F</Initials></Author><Author ValidYN="Y"><LastName>Hou</LastName><ForeName>Jia</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Lei</ForeName><Initials>L</Initials></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Yiyun</ForeName><Initials>Y</Initials></Author><Author ValidYN="Y"><LastName>Kang</LastName><ForeName>Xiangyang</ForeName><Initials>X</Initials></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Yanwei</ForeName><Initials>Y</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>11</Month><Day>16</Day></ArticleDate></Article><MedlineJournalInfo><Country>Germany</Country><MedlineTA>Funct Integr Genomics</MedlineTA><NlmUniqueID>100939343</NlmUniqueID><ISSNLinking>1438-793X</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D035683">MicroRNAs</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D018749">RNA, Plant</NameOfSubstance></Chemical><Chemical><RegistryNumber>N762921K75</RegistryNumber><NameOfSubstance 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MajorTopicYN="N">MicroRNAs</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D009584" MajorTopicYN="N">Nitrogen</DescriptorName><QualifierName UI="Q000494" MajorTopicYN="Y">pharmacology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000187" MajorTopicYN="N">drug effects</QualifierName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018749" MajorTopicYN="N">RNA, Plant</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013312" MajorTopicYN="N">Stress, Physiological</DescriptorName><QualifierName UI="Q000187" MajorTopicYN="N">drug effects</QualifierName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015854" MajorTopicYN="N">Up-Regulation</DescriptorName><QualifierName UI="Q000187" MajorTopicYN="N">drug effects</QualifierName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>01</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>11</Month><Day>03</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2014</Year><Month>09</Month><Day>30</Day></PubMedPubDate><PubMedPubDate 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sortKey="Chen, Lei" sort="Chen, Lei" uniqKey="Chen L" first="Lei" last="Chen">Lei Chen</name><name sortKey="Hou, Jia" sort="Hou, Jia" uniqKey="Hou J" first="Jia" last="Hou">Jia Hou</name><name sortKey="Kang, Xiangyang" sort="Kang, Xiangyang" uniqKey="Kang X" first="Xiangyang" last="Kang">Xiangyang Kang</name><name sortKey="Sun, Fengshuo" sort="Sun, Fengshuo" uniqKey="Sun F" first="Fengshuo" last="Sun">Fengshuo Sun</name><name sortKey="Wang, Yanwei" sort="Wang, Yanwei" uniqKey="Wang Y" first="Yanwei" last="Wang">Yanwei Wang</name><name sortKey="Zhang, Yiyun" sort="Zhang, Yiyun" uniqKey="Zhang Y" first="Yiyun" last="Zhang">Yiyun Zhang</name></noCountry><country name="Oman"><noRegion><name sortKey="Ren, Yuanyuan" sort="Ren, Yuanyuan" uniqKey="Ren Y" first="Yuanyuan" last="Ren">Yuanyuan Ren</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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