Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa).
Identifieur interne : 001C04 ( Main/Exploration ); précédent : 001C03; suivant : 001C05Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa).
Auteurs : Regis W. Oubida [États-Unis] ; Dashzeveg Gantulga [États-Unis] ; Man Zhang [États-Unis] ; Lecong Zhou [États-Unis] ; Rajesh Bawa [États-Unis] ; Jason A. Holliday [États-Unis]Source :
- Frontiers in plant science [ 1664-462X ] ; 2015.
Abstract
Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines are frequently observed for these traits, but environmental constraints also track longitude and altitude. We combined extensive phenotyping of 12 candidate adaptive traits, multivariate regression trees, quantitative genetics, and a genome-wide panel of SNP markers to better understand the interplay among geography, climate, and adaptation to abiotic factors in Populus trichocarpa. Heritabilities were low to moderate (0.13-0.32) and population differentiation for many traits exceeded the 99th percentile of the genome-wide distribution of FST, suggesting local adaptation. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, evapotranspiration (Eref) explained the most variation, with subsequent splits related to mean temperature of the warmest month, frost-free period (FFP), and mean annual precipitation (MAP). These grouping matched relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref) had the lowest growth, and lowest cold injury index; the southern British Columbia group (low Eref and intermediate temperatures) had average growth and cold injury index; the group from the coast of California and Oregon (high Eref and FFP) had the highest growth performance and the highest cold injury index; and the southernmost, high-altitude group (with high Eref and low FFP) performed poorly, had high cold injury index, and lower water use efficiency. Taken together, these results suggest variation in both temperature and water availability across the range shape multivariate adaptive traits in poplar.
DOI: 10.3389/fpls.2015.00181
PubMed: 25870603
PubMed Central: PMC4375981
Affiliations:
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Oubida</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author><author><name sortKey="Gantulga, Dashzeveg" sort="Gantulga, Dashzeveg" uniqKey="Gantulga D" first="Dashzeveg" last="Gantulga">Dashzeveg Gantulga</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author><author><name sortKey="Zhang, Man" sort="Zhang, Man" uniqKey="Zhang M" first="Man" last="Zhang">Man Zhang</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author><author><name sortKey="Zhou, Lecong" sort="Zhou, Lecong" uniqKey="Zhou L" first="Lecong" last="Zhou">Lecong Zhou</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author><author><name sortKey="Bawa, Rajesh" sort="Bawa, Rajesh" uniqKey="Bawa R" first="Rajesh" last="Bawa">Rajesh Bawa</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author><author><name sortKey="Holliday, Jason A" sort="Holliday, Jason A" uniqKey="Holliday J" first="Jason A" last="Holliday">Jason A. Holliday</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA</wicri:regionArea><placeName><region type="state">Virginie</region></placeName></affiliation></author></analytic><series><title level="j">Frontiers in plant science</title><idno type="ISSN">1664-462X</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines are frequently observed for these traits, but environmental constraints also track longitude and altitude. We combined extensive phenotyping of 12 candidate adaptive traits, multivariate regression trees, quantitative genetics, and a genome-wide panel of SNP markers to better understand the interplay among geography, climate, and adaptation to abiotic factors in Populus trichocarpa. Heritabilities were low to moderate (0.13-0.32) and population differentiation for many traits exceeded the 99th percentile of the genome-wide distribution of FST, suggesting local adaptation. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, evapotranspiration (Eref) explained the most variation, with subsequent splits related to mean temperature of the warmest month, frost-free period (FFP), and mean annual precipitation (MAP). These grouping matched relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref) had the lowest growth, and lowest cold injury index; the southern British Columbia group (low Eref and intermediate temperatures) had average growth and cold injury index; the group from the coast of California and Oregon (high Eref and FFP) had the highest growth performance and the highest cold injury index; and the southernmost, high-altitude group (with high Eref and low FFP) performed poorly, had high cold injury index, and lower water use efficiency. Taken together, these results suggest variation in both temperature and water availability across the range shape multivariate adaptive traits in poplar. </div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">25870603</PMID><DateCompleted><Year>2015</Year><Month>04</Month><Day>14</Day></DateCompleted><DateRevised><Year>2020</Year><Month>09</Month><Day>29</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1664-462X</ISSN><JournalIssue CitedMedium="Print"><Volume>6</Volume><PubDate><Year>2015</Year></PubDate></JournalIssue><Title>Frontiers in plant science</Title><ISOAbbreviation>Front Plant Sci</ISOAbbreviation></Journal><ArticleTitle>Partitioning of multivariate phenotypes using regression trees reveals complex patterns of adaptation to climate across the range of black cottonwood (Populus trichocarpa).</ArticleTitle><Pagination><MedlinePgn>181</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3389/fpls.2015.00181</ELocationID><Abstract><AbstractText>Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines are frequently observed for these traits, but environmental constraints also track longitude and altitude. We combined extensive phenotyping of 12 candidate adaptive traits, multivariate regression trees, quantitative genetics, and a genome-wide panel of SNP markers to better understand the interplay among geography, climate, and adaptation to abiotic factors in Populus trichocarpa. Heritabilities were low to moderate (0.13-0.32) and population differentiation for many traits exceeded the 99th percentile of the genome-wide distribution of FST, suggesting local adaptation. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, evapotranspiration (Eref) explained the most variation, with subsequent splits related to mean temperature of the warmest month, frost-free period (FFP), and mean annual precipitation (MAP). These grouping matched relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref) had the lowest growth, and lowest cold injury index; the southern British Columbia group (low Eref and intermediate temperatures) had average growth and cold injury index; the group from the coast of California and Oregon (high Eref and FFP) had the highest growth performance and the highest cold injury index; and the southernmost, high-altitude group (with high Eref and low FFP) performed poorly, had high cold injury index, and lower water use efficiency. Taken together, these results suggest variation in both temperature and water availability across the range shape multivariate adaptive traits in poplar. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Oubida</LastName><ForeName>Regis W</ForeName><Initials>RW</Initials><AffiliationInfo><Affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gantulga</LastName><ForeName>Dashzeveg</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Man</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhou</LastName><ForeName>Lecong</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bawa</LastName><ForeName>Rajesh</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Holliday</LastName><ForeName>Jason A</ForeName><Initials>JA</Initials><AffiliationInfo><Affiliation>Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>03</Month><Day>27</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Front Plant Sci</MedlineTA><NlmUniqueID>101568200</NlmUniqueID><ISSNLinking>1664-462X</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Populus trichocarpa</Keyword><Keyword MajorTopicYN="N">black cottonwood</Keyword><Keyword MajorTopicYN="N">common garden</Keyword><Keyword MajorTopicYN="N">local adaptation</Keyword><Keyword MajorTopicYN="N">regression tree</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>05</Month><Day>28</Day></PubMedPubDate><PubMedPubDate 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IdType="pubmed">8244001</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Virginie</li></region></list><tree><country name="États-Unis"><region name="Virginie"><name sortKey="Oubida, Regis W" sort="Oubida, Regis W" uniqKey="Oubida R" first="Regis W" last="Oubida">Regis W. Oubida</name></region><name sortKey="Bawa, Rajesh" sort="Bawa, Rajesh" uniqKey="Bawa R" first="Rajesh" last="Bawa">Rajesh Bawa</name><name sortKey="Gantulga, Dashzeveg" sort="Gantulga, Dashzeveg" uniqKey="Gantulga D" first="Dashzeveg" last="Gantulga">Dashzeveg Gantulga</name><name sortKey="Holliday, Jason A" sort="Holliday, Jason A" uniqKey="Holliday J" first="Jason A" last="Holliday">Jason A. Holliday</name><name sortKey="Zhang, Man" sort="Zhang, Man" uniqKey="Zhang M" first="Man" last="Zhang">Man Zhang</name><name sortKey="Zhou, Lecong" sort="Zhou, Lecong" uniqKey="Zhou L" first="Lecong" last="Zhou">Lecong Zhou</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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