Genetic adaptation of Tibetan poplar (Populus szechuanica var. tibetica) to high altitudes on the Qinghai-Tibetan Plateau.
Identifieur interne : 000382 ( Main/Exploration ); précédent : 000381; suivant : 000383Genetic adaptation of Tibetan poplar (Populus szechuanica var. tibetica) to high altitudes on the Qinghai-Tibetan Plateau.
Auteurs : Chenfei Zheng ; Lizhi Tan ; Mengmeng Sang ; Meixia Ye ; Rongling WuSource :
- Ecology and evolution [ 2045-7758 ] ; 2020.
Abstract
Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, Populus szechuanica var. tibetica, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai-Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high- to low-altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high-altitude adaptation in Tibetan poplar.
DOI: 10.1002/ece3.6508
PubMed: 33144942
PubMed Central: PMC7593140
Affiliations:
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Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Sang, Mengmeng" sort="Sang, Mengmeng" uniqKey="Sang M" first="Mengmeng" last="Sang">Mengmeng Sang</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Ye, Meixia" sort="Ye, Meixia" uniqKey="Ye M" first="Meixia" last="Ye">Meixia Ye</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation><affiliation><nlm:affiliation>Center for Statistical Genetics Pennsylvania State University Hershey PA USA.</nlm:affiliation><wicri:noCountry code="no comma">Center for Statistical Genetics Pennsylvania State University Hershey PA USA.</wicri:noCountry></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:33144942</idno><idno type="pmid">33144942</idno><idno type="doi">10.1002/ece3.6508</idno><idno type="pmc">PMC7593140</idno><idno type="wicri:Area/Main/Corpus">000029</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" 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Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Tan, Lizhi" sort="Tan, Lizhi" uniqKey="Tan L" first="Lizhi" last="Tan">Lizhi Tan</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Sang, Mengmeng" sort="Sang, Mengmeng" uniqKey="Sang M" first="Mengmeng" last="Sang">Mengmeng Sang</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Ye, Meixia" sort="Ye, Meixia" uniqKey="Ye M" first="Meixia" last="Ye">Meixia Ye</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation></author><author><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name><affiliation><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</nlm:affiliation><wicri:noCountry code="no comma">Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</wicri:noCountry></affiliation><affiliation><nlm:affiliation>Center for Statistical Genetics Pennsylvania State University Hershey PA USA.</nlm:affiliation><wicri:noCountry code="no comma">Center for Statistical Genetics Pennsylvania State University Hershey PA USA.</wicri:noCountry></affiliation></author></analytic><series><title level="j">Ecology and evolution</title><idno type="ISSN">2045-7758</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, <i>Populus szechuanica</i> var. <i>tibetica</i>, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai-Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high- to low-altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high-altitude adaptation in Tibetan poplar.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">33144942</PMID><DateRevised><Year>2020</Year><Month>11</Month><Day>05</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">2045-7758</ISSN><JournalIssue CitedMedium="Print"><Volume>10</Volume><Issue>20</Issue><PubDate><Year>2020</Year><Month>Oct</Month></PubDate></JournalIssue><Title>Ecology and evolution</Title><ISOAbbreviation>Ecol Evol</ISOAbbreviation></Journal><ArticleTitle>Genetic adaptation of Tibetan poplar (<i>Populus szechuanica</i> var. <i>tibetica</i>) to high altitudes on the Qinghai-Tibetan Plateau.</ArticleTitle><Pagination><MedlinePgn>10974-10985</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1002/ece3.6508</ELocationID><Abstract><AbstractText>Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, <i>Populus szechuanica</i> var. <i>tibetica</i>, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai-Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high- to low-altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high-altitude adaptation in Tibetan poplar.</AbstractText><CopyrightInformation>© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zheng</LastName><ForeName>Chenfei</ForeName><Initials>C</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-2673-8068</Identifier><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tan</LastName><ForeName>Lizhi</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sang</LastName><ForeName>Mengmeng</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ye</LastName><ForeName>Meixia</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wu</LastName><ForeName>Rongling</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design Center for Computational Biology College of Biological Sciences and Technology Beijing Forestry University Beijing China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Statistical Genetics Pennsylvania State University Hershey PA USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><DataBankList CompleteYN="Y"><DataBank><DataBankName>Dryad</DataBankName><AccessionNumberList><AccessionNumber>10.5061/dryad.5tk1mc7</AccessionNumber></AccessionNumberList></DataBank></DataBankList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>10</Month><Day>01</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Ecol Evol</MedlineTA><NlmUniqueID>101566408</NlmUniqueID><ISSNLinking>2045-7758</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Tibetan poplar</Keyword><Keyword MajorTopicYN="N">adaptation</Keyword><Keyword MajorTopicYN="N">gene flow</Keyword><Keyword MajorTopicYN="N">genetic loci</Keyword><Keyword MajorTopicYN="N">population genetic variation</Keyword></KeywordList><CoiStatement>The authors state that there is no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>08</Month><Day>22</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>05</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>05</Month><Day>28</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>11</Month><Day>4</Day><Hour>5</Hour><Minute>42</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>11</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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M" first="Meixia" last="Ye">Meixia Ye</name><name sortKey="Zheng, Chenfei" sort="Zheng, Chenfei" uniqKey="Zheng C" first="Chenfei" last="Zheng">Chenfei Zheng</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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