Genetic variants in microRNA biogenesis genes as novel indicators for secondary growth in Populus.
Identifieur interne : 000D86 ( Main/Curation ); précédent : 000D85; suivant : 000D87Genetic variants in microRNA biogenesis genes as novel indicators for secondary growth in Populus.
Auteurs : Beibei Chen [République populaire de Chine] ; Jinhui Chen [République populaire de Chine] ; Qingzhang Du [République populaire de Chine] ; Daling Zhou [République populaire de Chine] ; Longxin Wang [République populaire de Chine] ; Jianbo Xie [République populaire de Chine] ; Ying Li [République populaire de Chine] ; Deqiang Zhang [République populaire de Chine]Source :
- The New phytologist [ 1469-8137 ] ; 2018.
Descripteurs français
- KwdFr :
- Bois (croissance et développement), Bois (génétique), Cellulose (métabolisme), Déséquilibre de liaison (génétique), Gènes de plante (MeSH), Génotype (MeSH), Marqueurs génétiques (MeSH), Polymorphisme de nucléotide simple (génétique), Populus (croissance et développement), Populus (génétique), Régulation de l'expression des gènes végétaux (MeSH), Stabilité de l'ARN (génétique), Séquence nucléotidique (MeSH), Variation génétique (MeSH), microARN (biosynthèse), microARN (génétique), Épistasie (MeSH), Études d'associations génétiques (MeSH).
- MESH :
- biosynthèse : microARN.
- croissance et développement : Bois, Populus.
- génétique : Bois, Déséquilibre de liaison, Polymorphisme de nucléotide simple, Populus, Stabilité de l'ARN, microARN.
- métabolisme : Cellulose.
- Gènes de plante, Génotype, Marqueurs génétiques, Régulation de l'expression des gènes végétaux, Séquence nucléotidique, Variation génétique, Épistasie, Études d'associations génétiques.
English descriptors
- KwdEn :
- Base Sequence (MeSH), Cellulose (metabolism), Epistasis, Genetic (MeSH), Gene Expression Regulation, Plant (MeSH), Genes, Plant (MeSH), Genetic Association Studies (MeSH), Genetic Markers (MeSH), Genetic Variation (MeSH), Genotype (MeSH), Linkage Disequilibrium (genetics), MicroRNAs (biosynthesis), MicroRNAs (genetics), Polymorphism, Single Nucleotide (genetics), Populus (genetics), Populus (growth & development), RNA Stability (genetics), Wood (genetics), Wood (growth & development).
- MESH :
- chemical , biosynthesis : MicroRNAs.
- chemical , genetics : MicroRNAs.
- chemical , metabolism : Cellulose.
- genetics : Linkage Disequilibrium, Polymorphism, Single Nucleotide, Populus, RNA Stability, Wood.
- growth & development : Populus, Wood.
- Base Sequence, Epistasis, Genetic, Gene Expression Regulation, Plant, Genes, Plant, Genetic Association Studies, Genetic Markers, Genetic Variation, Genotype.
Abstract
MicroRNAs (miRNAs) function as key regulators of complex traits, but how genetic alterations in miRNA biogenesis genes (miRBGs) affect quantitative variation has not been elucidated. We conducted transcript analyses and association genetics to investigate how miRBGs, miRNA genes (MIRNAs) and their respective targets contribute to secondary growth in a natural population of 435 Populus tomentosa individuals. This analysis identified 29 843 common single-nucleotide polymorphisms (SNPs; frequency > 0.10) within 682 genes (80 miRBGs, 152 MIRNAs, and 457 miRNA targets). Single-SNP association analysis found SNPs in 234 candidate genes exhibited significant additive/dominant effects on phenotypes. Among these, specific candidates that associated with the same traits produced 791 miRBG-MIRNA-target combinations, suggesting possible genetic miRBG-MIRNA and MIRNA-target interactions, providing an important clue for the regulatory mechanisms of miRBGs. Multi-SNP association found 4672 epistatic pairs involving 578 genes that showed significant associations with traits and identified 106 miRBG-MIRNA-target combinations. Two multi-hierarchical networks were constructed based on correlations of miRBG-miRNA and miRNA-target expression to further probe the mechanisms of trait diversity underlying changes in miRBGs. Our study opens avenues for the investigation of miRNA function in perennial plants and underscored miRBGs as potentially modulating quantitative variation in traits.
DOI: 10.1111/nph.15262
PubMed: 29916214
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pubmed:29916214Le document en format XML
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Genetic variants in microRNA biogenesis genes as novel indicators for secondary growth in Populus.</title>
<author><name sortKey="Chen, Beibei" sort="Chen, Beibei" uniqKey="Chen B" first="Beibei" last="Chen">Beibei Chen</name>
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<author><name sortKey="Chen, Jinhui" sort="Chen, Jinhui" uniqKey="Chen J" first="Jinhui" last="Chen">Jinhui Chen</name>
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<author><name sortKey="Du, Qingzhang" sort="Du, Qingzhang" uniqKey="Du Q" first="Qingzhang" last="Du">Qingzhang Du</name>
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<author><name sortKey="Zhou, Daling" sort="Zhou, Daling" uniqKey="Zhou D" first="Daling" last="Zhou">Daling Zhou</name>
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<author><name sortKey="Wang, Longxin" sort="Wang, Longxin" uniqKey="Wang L" first="Longxin" last="Wang">Longxin Wang</name>
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<author><name sortKey="Xie, Jianbo" sort="Xie, Jianbo" uniqKey="Xie J" first="Jianbo" last="Xie">Jianbo Xie</name>
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<series><title level="j">The New phytologist</title>
<idno type="eISSN">1469-8137</idno>
<imprint><date when="2018" type="published">2018</date>
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<term>Cellulose (metabolism)</term>
<term>Epistasis, Genetic (MeSH)</term>
<term>Gene Expression Regulation, Plant (MeSH)</term>
<term>Genes, Plant (MeSH)</term>
<term>Genetic Association Studies (MeSH)</term>
<term>Genetic Markers (MeSH)</term>
<term>Genetic Variation (MeSH)</term>
<term>Genotype (MeSH)</term>
<term>Linkage Disequilibrium (genetics)</term>
<term>MicroRNAs (biosynthesis)</term>
<term>MicroRNAs (genetics)</term>
<term>Polymorphism, Single Nucleotide (genetics)</term>
<term>Populus (genetics)</term>
<term>Populus (growth & development)</term>
<term>RNA Stability (genetics)</term>
<term>Wood (genetics)</term>
<term>Wood (growth & development)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Bois (croissance et développement)</term>
<term>Bois (génétique)</term>
<term>Cellulose (métabolisme)</term>
<term>Déséquilibre de liaison (génétique)</term>
<term>Gènes de plante (MeSH)</term>
<term>Génotype (MeSH)</term>
<term>Marqueurs génétiques (MeSH)</term>
<term>Polymorphisme de nucléotide simple (génétique)</term>
<term>Populus (croissance et développement)</term>
<term>Populus (génétique)</term>
<term>Régulation de l'expression des gènes végétaux (MeSH)</term>
<term>Stabilité de l'ARN (génétique)</term>
<term>Séquence nucléotidique (MeSH)</term>
<term>Variation génétique (MeSH)</term>
<term>microARN (biosynthèse)</term>
<term>microARN (génétique)</term>
<term>Épistasie (MeSH)</term>
<term>Études d'associations génétiques (MeSH)</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="biosynthesis" xml:lang="en"><term>MicroRNAs</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>MicroRNAs</term>
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</keywords>
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<term>Populus</term>
</keywords>
<keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Linkage Disequilibrium</term>
<term>Polymorphism, Single Nucleotide</term>
<term>Populus</term>
<term>RNA Stability</term>
<term>Wood</term>
</keywords>
<keywords scheme="MESH" qualifier="growth & development" xml:lang="en"><term>Populus</term>
<term>Wood</term>
</keywords>
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<term>Déséquilibre de liaison</term>
<term>Polymorphisme de nucléotide simple</term>
<term>Populus</term>
<term>Stabilité de l'ARN</term>
<term>microARN</term>
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</keywords>
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<term>Epistasis, Genetic</term>
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<term>Genes, Plant</term>
<term>Genetic Association Studies</term>
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<term>Marqueurs génétiques</term>
<term>Régulation de l'expression des gènes végétaux</term>
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<front><div type="abstract" xml:lang="en">MicroRNAs (miRNAs) function as key regulators of complex traits, but how genetic alterations in miRNA biogenesis genes (miRBGs) affect quantitative variation has not been elucidated. We conducted transcript analyses and association genetics to investigate how miRBGs, miRNA genes (MIRNAs) and their respective targets contribute to secondary growth in a natural population of 435 Populus tomentosa individuals. This analysis identified 29 843 common single-nucleotide polymorphisms (SNPs; frequency > 0.10) within 682 genes (80 miRBGs, 152 MIRNAs, and 457 miRNA targets). Single-SNP association analysis found SNPs in 234 candidate genes exhibited significant additive/dominant effects on phenotypes. Among these, specific candidates that associated with the same traits produced 791 miRBG-MIRNA-target combinations, suggesting possible genetic miRBG-MIRNA and MIRNA-target interactions, providing an important clue for the regulatory mechanisms of miRBGs. Multi-SNP association found 4672 epistatic pairs involving 578 genes that showed significant associations with traits and identified 106 miRBG-MIRNA-target combinations. Two multi-hierarchical networks were constructed based on correlations of miRBG-miRNA and miRNA-target expression to further probe the mechanisms of trait diversity underlying changes in miRBGs. Our study opens avenues for the investigation of miRNA function in perennial plants and underscored miRBGs as potentially modulating quantitative variation in traits.</div>
</front>
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<DateCompleted><Year>2019</Year>
<Month>09</Month>
<Day>25</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>09</Month>
<Day>30</Day>
</DateRevised>
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<JournalIssue CitedMedium="Internet"><Volume>219</Volume>
<Issue>4</Issue>
<PubDate><Year>2018</Year>
<Month>09</Month>
</PubDate>
</JournalIssue>
<Title>The New phytologist</Title>
<ISOAbbreviation>New Phytol</ISOAbbreviation>
</Journal>
<ArticleTitle>Genetic variants in microRNA biogenesis genes as novel indicators for secondary growth in Populus.</ArticleTitle>
<Pagination><MedlinePgn>1263-1282</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1111/nph.15262</ELocationID>
<Abstract><AbstractText>MicroRNAs (miRNAs) function as key regulators of complex traits, but how genetic alterations in miRNA biogenesis genes (miRBGs) affect quantitative variation has not been elucidated. We conducted transcript analyses and association genetics to investigate how miRBGs, miRNA genes (MIRNAs) and their respective targets contribute to secondary growth in a natural population of 435 Populus tomentosa individuals. This analysis identified 29 843 common single-nucleotide polymorphisms (SNPs; frequency > 0.10) within 682 genes (80 miRBGs, 152 MIRNAs, and 457 miRNA targets). Single-SNP association analysis found SNPs in 234 candidate genes exhibited significant additive/dominant effects on phenotypes. Among these, specific candidates that associated with the same traits produced 791 miRBG-MIRNA-target combinations, suggesting possible genetic miRBG-MIRNA and MIRNA-target interactions, providing an important clue for the regulatory mechanisms of miRBGs. Multi-SNP association found 4672 epistatic pairs involving 578 genes that showed significant associations with traits and identified 106 miRBG-MIRNA-target combinations. Two multi-hierarchical networks were constructed based on correlations of miRBG-miRNA and miRNA-target expression to further probe the mechanisms of trait diversity underlying changes in miRBGs. Our study opens avenues for the investigation of miRNA function in perennial plants and underscored miRBGs as potentially modulating quantitative variation in traits.</AbstractText>
<CopyrightInformation>© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.</CopyrightInformation>
</Abstract>
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<ForeName>Beibei</ForeName>
<Initials>B</Initials>
<AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Chen</LastName>
<ForeName>Jinhui</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
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<ForeName>Qingzhang</ForeName>
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</AffiliationInfo>
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<AffiliationInfo><Affiliation>Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
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<ForeName>Daling</ForeName>
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<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Longxin</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Xie</LastName>
<ForeName>Jianbo</ForeName>
<Initials>J</Initials>
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</AffiliationInfo>
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</AffiliationInfo>
<AffiliationInfo><Affiliation>National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
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<AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, China.</Affiliation>
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<Keyword MajorTopicYN="Y">secondary growth</Keyword>
<Keyword MajorTopicYN="Y">transcript profiling</Keyword>
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<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2018</Year>
<Month>03</Month>
<Day>02</Day>
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<PubMedPubDate PubStatus="accepted"><Year>2018</Year>
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<Day>06</Day>
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