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Gene copy number variations involved in balsam poplar (Populus balsamifera L.) adaptive variations.

Identifieur interne : 000946 ( Main/Exploration ); précédent : 000945; suivant : 000947

Gene copy number variations involved in balsam poplar (Populus balsamifera L.) adaptive variations.

Auteurs : Julien Prunier [Canada] ; Isabelle Giguère [Canada] ; Natalie Ryan [Canada] ; Robert Guy [Canada] ; Raju Soolanayakanahally [Canada] ; Nathalie Isabel [Canada] ; John Mackay [Royaume-Uni] ; Ilga Porth [Canada]

Source :

RBID : pubmed:30270494

Descripteurs français

English descriptors

Abstract

Gene copy number variations (CNVs) involved in phenotypic variations have already been shown in plants, but genomewide testing of CNVs for adaptive variation was not doable until recent technological developments. Thus, reports of the genomic architecture of adaptation involving CNVs remain scarce to date. Here, we investigated F1 progenies of an intraprovenance cross (north-north cross, 58th parallel) and an interprovenances cross (north-south cross, 58th/49th parallels) for CNVs using comparative genomic hybridization on arrays of probes targeting gene sequences in balsam poplar (Populus balsamifera L.), a widespread North American forest tree. A total of 1,721 genes were found in varying copy numbers over the set of 19,823 tested genes. These gene CNVs presented an estimated average size of 8.3 kb and were distributed over poplar's 19 chromosomes including 22 hotspot regions. Gene CNVs number was higher for the interprovenance progeny in accordance with an expected higher genetic diversity related to the composite origin of this family. Regression analyses between gene CNVs and seven adaptive trait variations resulted in 23 significant links; among these adaptive gene CNVs, 30% were located in hotspots. One-to-five gene CNVs were found related to each of the measured adaptive traits and annotated for both biotic and abiotic stress responses. These annotations can be related to the occurrence of a higher pathogenic pressure in the southern parts of balsam poplar's distribution, and higher photosynthetic assimilation rates and water-use efficiency at high latitudes. Overall, our findings suggest that gene CNVs typically having higher mutation rates than SNPs may in fact represent efficient adaptive variations against fast-evolving pathogens.

DOI: 10.1111/mec.14836
PubMed: 30270494


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Le document en format XML

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<div type="abstract" xml:lang="en">Gene copy number variations (CNVs) involved in phenotypic variations have already been shown in plants, but genomewide testing of CNVs for adaptive variation was not doable until recent technological developments. Thus, reports of the genomic architecture of adaptation involving CNVs remain scarce to date. Here, we investigated F
<sub>1</sub>
progenies of an intraprovenance cross (north-north cross, 58th parallel) and an interprovenances cross (north-south cross, 58th/49th parallels) for CNVs using comparative genomic hybridization on arrays of probes targeting gene sequences in balsam poplar (Populus balsamifera L.), a widespread North American forest tree. A total of 1,721 genes were found in varying copy numbers over the set of 19,823 tested genes. These gene CNVs presented an estimated average size of 8.3 kb and were distributed over poplar's 19 chromosomes including 22 hotspot regions. Gene CNVs number was higher for the interprovenance progeny in accordance with an expected higher genetic diversity related to the composite origin of this family. Regression analyses between gene CNVs and seven adaptive trait variations resulted in 23 significant links; among these adaptive gene CNVs, 30% were located in hotspots. One-to-five gene CNVs were found related to each of the measured adaptive traits and annotated for both biotic and abiotic stress responses. These annotations can be related to the occurrence of a higher pathogenic pressure in the southern parts of balsam poplar's distribution, and higher photosynthetic assimilation rates and water-use efficiency at high latitudes. Overall, our findings suggest that gene CNVs typically having higher mutation rates than SNPs may in fact represent efficient adaptive variations against fast-evolving pathogens.</div>
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<AbstractText>Gene copy number variations (CNVs) involved in phenotypic variations have already been shown in plants, but genomewide testing of CNVs for adaptive variation was not doable until recent technological developments. Thus, reports of the genomic architecture of adaptation involving CNVs remain scarce to date. Here, we investigated F
<sub>1</sub>
progenies of an intraprovenance cross (north-north cross, 58th parallel) and an interprovenances cross (north-south cross, 58th/49th parallels) for CNVs using comparative genomic hybridization on arrays of probes targeting gene sequences in balsam poplar (Populus balsamifera L.), a widespread North American forest tree. A total of 1,721 genes were found in varying copy numbers over the set of 19,823 tested genes. These gene CNVs presented an estimated average size of 8.3 kb and were distributed over poplar's 19 chromosomes including 22 hotspot regions. Gene CNVs number was higher for the interprovenance progeny in accordance with an expected higher genetic diversity related to the composite origin of this family. Regression analyses between gene CNVs and seven adaptive trait variations resulted in 23 significant links; among these adaptive gene CNVs, 30% were located in hotspots. One-to-five gene CNVs were found related to each of the measured adaptive traits and annotated for both biotic and abiotic stress responses. These annotations can be related to the occurrence of a higher pathogenic pressure in the southern parts of balsam poplar's distribution, and higher photosynthetic assimilation rates and water-use efficiency at high latitudes. Overall, our findings suggest that gene CNVs typically having higher mutation rates than SNPs may in fact represent efficient adaptive variations against fast-evolving pathogens.</AbstractText>
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<Affiliation>Department of Plant Sciences, University of Oxford, Oxford, UK.</Affiliation>
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</Author>
<Author ValidYN="Y">
<LastName>Porth</LastName>
<ForeName>Ilga</ForeName>
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<Affiliation>Institute for System and Integrated Biology (IBIS), Université Laval, Québec, Québec, Canada.</Affiliation>
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<AffiliationInfo>
<Affiliation>Centre for Forest Research, Université Laval, Québec, Quebec, Canada.</Affiliation>
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<Agency>National Sciences and Engineering Research Council of Canada</Agency>
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<Grant>
<Agency>Le Ministère de l'Économie, de la Science et de l'Innovation</Agency>
<Country>International</Country>
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<Country>England</Country>
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<DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName>
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<QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName>
</MeshHeading>
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<Keyword MajorTopicYN="Y">Populus </Keyword>
<Keyword MajorTopicYN="Y">CNVs</Keyword>
<Keyword MajorTopicYN="Y">aCGH technology</Keyword>
<Keyword MajorTopicYN="Y">adaptation</Keyword>
<Keyword MajorTopicYN="Y">climate</Keyword>
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<ArticleId IdType="doi">10.1111/mec.14836</ArticleId>
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<li>Québec (ville)</li>
<li>Vancouver</li>
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<li>Université d'Oxford</li>
<li>Université de la Colombie-Britannique</li>
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<name sortKey="Guy, Robert" sort="Guy, Robert" uniqKey="Guy R" first="Robert" last="Guy">Robert Guy</name>
<name sortKey="Isabel, Nathalie" sort="Isabel, Nathalie" uniqKey="Isabel N" first="Nathalie" last="Isabel">Nathalie Isabel</name>
<name sortKey="Porth, Ilga" sort="Porth, Ilga" uniqKey="Porth I" first="Ilga" last="Porth">Ilga Porth</name>
<name sortKey="Porth, Ilga" sort="Porth, Ilga" uniqKey="Porth I" first="Ilga" last="Porth">Ilga Porth</name>
<name sortKey="Prunier, Julien" sort="Prunier, Julien" uniqKey="Prunier J" first="Julien" last="Prunier">Julien Prunier</name>
<name sortKey="Ryan, Natalie" sort="Ryan, Natalie" uniqKey="Ryan N" first="Natalie" last="Ryan">Natalie Ryan</name>
<name sortKey="Soolanayakanahally, Raju" sort="Soolanayakanahally, Raju" uniqKey="Soolanayakanahally R" first="Raju" last="Soolanayakanahally">Raju Soolanayakanahally</name>
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<name sortKey="Mackay, John" sort="Mackay, John" uniqKey="Mackay J" first="John" last="Mackay">John Mackay</name>
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