Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.
Identifieur interne : 003552 ( PubMed/Checkpoint ); précédent : 003551; suivant : 003553Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.
Auteurs : Agota Fodor [France] ; Vincent Segura [France] ; Marie Denis [France] ; Samuel Neuenschwander [Suisse] ; Alexandre Fournier-Level [Australie] ; Philippe Chatelet [France] ; Félix Abdel Aziz Homa [France] ; Thierry Lacombe [France] ; Patrice This [France] ; Loic Le Cunff [France]Source :
- PloS one [ 1932-6203 ] ; 2014.
Descripteurs français
- KwdFr :
- Biodiversité, Caractère quantitatif héréditaire, Déséquilibre de liaison, Hétérozygote, Locus de caractère quantitatif, Modèles génétiques, Modèles statistiques, Phénotype, Reproductibilité des résultats, Simulation numérique, Sélection, Sélection génétique, Vitis (génétique), Étude d'association pangénomique, Études d'associations génétiques, Évolution biologique.
- MESH :
- génétique : Vitis.
- Biodiversité, Caractère quantitatif héréditaire, Déséquilibre de liaison, Hétérozygote, Locus de caractère quantitatif, Modèles génétiques, Modèles statistiques, Phénotype, Reproductibilité des résultats, Simulation numérique, Sélection, Sélection génétique, Étude d'association pangénomique, Études d'associations génétiques, Évolution biologique.
English descriptors
- KwdEn :
- Biodiversity, Biological Evolution, Breeding, Computer Simulation, Genetic Association Studies, Genome-Wide Association Study, Heterozygote, Linkage Disequilibrium, Models, Genetic, Models, Statistical, Phenotype, Quantitative Trait Loci, Quantitative Trait, Heritable, Reproducibility of Results, Selection, Genetic, Vitis (genetics).
- MESH :
- genetics : Vitis.
- Biodiversity, Biological Evolution, Breeding, Computer Simulation, Genetic Association Studies, Genome-Wide Association Study, Heterozygote, Linkage Disequilibrium, Models, Genetic, Models, Statistical, Phenotype, Quantitative Trait Loci, Quantitative Trait, Heritable, Reproducibility of Results, Selection, Genetic.
Abstract
Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.
DOI: 10.1371/journal.pone.0110436
PubMed: 25365338
Affiliations:
- Australie, France, Suisse
- Canton de Vaud, Centre-Val de Loire, Languedoc-Roussillon, Occitanie (région administrative), Région Centre, Victoria (État)
- Lausanne, Melbourne, Montpellier, Orléans
- Université de Melbourne
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pubmed:25365338Le document en format XML
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UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="Le Cunff, Loic" sort="Le Cunff, Loic" uniqKey="Le Cunff L" first="Loic" last="Le Cunff">Loic Le Cunff</name><affiliation wicri:level="3"><nlm:affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2014">2014</date><idno type="RBID">pubmed:25365338</idno><idno type="pmid">25365338</idno><idno type="doi">10.1371/journal.pone.0110436</idno><idno type="wicri:Area/PubMed/Corpus">003335</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">003335</idno><idno type="wicri:Area/PubMed/Curation">003224</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">003224</idno><idno type="wicri:Area/PubMed/Checkpoint">003224</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">003224</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.</title><author><name sortKey="Fodor, Agota" sort="Fodor, Agota" uniqKey="Fodor A" first="Agota" last="Fodor">Agota Fodor</name><affiliation wicri:level="3"><nlm:affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="Segura, Vincent" sort="Segura, Vincent" uniqKey="Segura V" first="Vincent" last="Segura">Vincent Segura</name><affiliation wicri:level="3"><nlm:affiliation>UR 588 AGPF, INRA, Orléans, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UR 588 AGPF, INRA, Orléans</wicri:regionArea><placeName><region type="region">Centre-Val de Loire</region><region type="old region">Région Centre</region><settlement type="city">Orléans</settlement></placeName></affiliation></author><author><name sortKey="Denis, Marie" sort="Denis, Marie" uniqKey="Denis M" first="Marie" last="Denis">Marie Denis</name><affiliation wicri:level="3"><nlm:affiliation>UMR AGAP, CIRAD, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMR AGAP, CIRAD, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="Neuenschwander, Samuel" sort="Neuenschwander, Samuel" uniqKey="Neuenschwander S" first="Samuel" last="Neuenschwander">Samuel Neuenschwander</name><affiliation wicri:level="3"><nlm:affiliation>University of Lausanne, Department of Ecology and Evolution, Lausanne, Switzerland; University of Lausanne, Swiss Institute of Bioinformatics, Vital-IT, Lausanne, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>University of Lausanne, Department of Ecology and Evolution, Lausanne, Switzerland; University of Lausanne, Swiss Institute of Bioinformatics, Vital-IT, Lausanne</wicri:regionArea><placeName><settlement type="city">Lausanne</settlement><region nuts="3" type="region">Canton de Vaud</region></placeName></affiliation></author><author><name sortKey="Fournier Level, Alexandre" sort="Fournier Level, Alexandre" uniqKey="Fournier Level A" first="Alexandre" last="Fournier-Level">Alexandre Fournier-Level</name><affiliation wicri:level="4"><nlm:affiliation>Department of Genetics, The University of Melbourne, Parkville, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Department of Genetics, The University of Melbourne, Parkville</wicri:regionArea><orgName type="university">Université de Melbourne</orgName><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Chatelet, Philippe" sort="Chatelet, Philippe" uniqKey="Chatelet P" first="Philippe" last="Chatelet">Philippe Chatelet</name><affiliation wicri:level="3"><nlm:affiliation>UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="Homa, Felix Abdel Aziz" sort="Homa, Felix Abdel Aziz" uniqKey="Homa F" first="Félix Abdel Aziz" last="Homa">Félix Abdel Aziz Homa</name><affiliation wicri:level="3"><nlm:affiliation>UMR AGAP, CIRAD, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMR AGAP, CIRAD, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="Lacombe, Thierry" sort="Lacombe, Thierry" uniqKey="Lacombe T" first="Thierry" last="Lacombe">Thierry Lacombe</name><affiliation wicri:level="3"><nlm:affiliation>UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="This, Patrice" sort="This, Patrice" uniqKey="This P" first="Patrice" last="This">Patrice This</name><affiliation wicri:level="3"><nlm:affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author><author><name sortKey="Le Cunff, Loic" sort="Le Cunff, Loic" uniqKey="Le Cunff L" first="Loic" last="Le Cunff">Loic Le Cunff</name><affiliation wicri:level="3"><nlm:affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier</wicri:regionArea><placeName><region type="region">Occitanie (région administrative)</region><region type="old region">Languedoc-Roussillon</region><settlement type="city">Montpellier</settlement></placeName></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Biodiversity</term><term>Biological Evolution</term><term>Breeding</term><term>Computer Simulation</term><term>Genetic Association Studies</term><term>Genome-Wide Association Study</term><term>Heterozygote</term><term>Linkage Disequilibrium</term><term>Models, Genetic</term><term>Models, Statistical</term><term>Phenotype</term><term>Quantitative Trait Loci</term><term>Quantitative Trait, Heritable</term><term>Reproducibility of Results</term><term>Selection, Genetic</term><term>Vitis (genetics)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Biodiversité</term><term>Caractère quantitatif héréditaire</term><term>Déséquilibre de liaison</term><term>Hétérozygote</term><term>Locus de caractère quantitatif</term><term>Modèles génétiques</term><term>Modèles statistiques</term><term>Phénotype</term><term>Reproductibilité des résultats</term><term>Simulation numérique</term><term>Sélection</term><term>Sélection génétique</term><term>Vitis (génétique)</term><term>Étude d'association pangénomique</term><term>Études d'associations génétiques</term><term>Évolution biologique</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Vitis</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Vitis</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Biodiversity</term><term>Biological Evolution</term><term>Breeding</term><term>Computer Simulation</term><term>Genetic Association Studies</term><term>Genome-Wide Association Study</term><term>Heterozygote</term><term>Linkage Disequilibrium</term><term>Models, Genetic</term><term>Models, Statistical</term><term>Phenotype</term><term>Quantitative Trait Loci</term><term>Quantitative Trait, Heritable</term><term>Reproducibility of Results</term><term>Selection, Genetic</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Biodiversité</term><term>Caractère quantitatif héréditaire</term><term>Déséquilibre de liaison</term><term>Hétérozygote</term><term>Locus de caractère quantitatif</term><term>Modèles génétiques</term><term>Modèles statistiques</term><term>Phénotype</term><term>Reproductibilité des résultats</term><term>Simulation numérique</term><term>Sélection</term><term>Sélection génétique</term><term>Étude d'association pangénomique</term><term>Études d'associations génétiques</term><term>Évolution biologique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25365338</PMID><DateCreated><Year>2014</Year><Month>11</Month><Day>04</Day></DateCreated><DateCompleted><Year>2015</Year><Month>08</Month><Day>10</Day></DateCompleted><DateRevised><Year>2017</Year><Month>02</Month><Day>20</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>9</Volume><Issue>11</Issue><PubDate><Year>2014</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.</ArticleTitle><Pagination><MedlinePgn>e110436</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0110436</ELocationID><Abstract><AbstractText>Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fodor</LastName><ForeName>Agota</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Segura</LastName><ForeName>Vincent</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>UR 588 AGPF, INRA, Orléans, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Denis</LastName><ForeName>Marie</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>UMR AGAP, CIRAD, Montpellier, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Neuenschwander</LastName><ForeName>Samuel</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>University of Lausanne, Department of Ecology and Evolution, Lausanne, Switzerland; University of Lausanne, Swiss Institute of Bioinformatics, Vital-IT, Lausanne, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fournier-Level</LastName><ForeName>Alexandre</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Genetics, The University of Melbourne, Parkville, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chatelet</LastName><ForeName>Philippe</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>UMR AGAP, INRA, Montpellier, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Homa</LastName><ForeName>Félix Abdel Aziz</ForeName><Initials>FA</Initials><AffiliationInfo><Affiliation>UMR AGAP, CIRAD, Montpellier, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lacombe</LastName><ForeName>Thierry</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>UMR AGAP, INRA, Montpellier, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>This</LastName><ForeName>Patrice</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Le Cunff</LastName><ForeName>Loic</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. 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MajorTopicYN="N">Phenotype</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D040641" MajorTopicYN="N">Quantitative Trait Loci</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019655" MajorTopicYN="N">Quantitative Trait, Heritable</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012641" MajorTopicYN="Y">Selection, Genetic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D027843" MajorTopicYN="N">Vitis</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4217727</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>04</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>09</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>11</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>11</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>8</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">25365338</ArticleId><ArticleId IdType="doi">10.1371/journal.pone.0110436</ArticleId><ArticleId IdType="pii">PONE-D-14-18276</ArticleId><ArticleId IdType="pmc">PMC4217727</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Australie</li><li>France</li><li>Suisse</li></country><region><li>Canton de Vaud</li><li>Centre-Val de Loire</li><li>Languedoc-Roussillon</li><li>Occitanie (région administrative)</li><li>Région Centre</li><li>Victoria (État)</li></region><settlement><li>Lausanne</li><li>Melbourne</li><li>Montpellier</li><li>Orléans</li></settlement><orgName><li>Université de Melbourne</li></orgName></list><tree><country name="France"><region name="Occitanie (région administrative)"><name sortKey="Fodor, Agota" sort="Fodor, Agota" uniqKey="Fodor A" first="Agota" last="Fodor">Agota Fodor</name></region><name sortKey="Chatelet, Philippe" sort="Chatelet, Philippe" uniqKey="Chatelet P" first="Philippe" last="Chatelet">Philippe Chatelet</name><name sortKey="Denis, Marie" sort="Denis, Marie" uniqKey="Denis M" first="Marie" last="Denis">Marie Denis</name><name sortKey="Homa, Felix Abdel Aziz" sort="Homa, Felix Abdel Aziz" uniqKey="Homa F" first="Félix Abdel Aziz" last="Homa">Félix Abdel Aziz Homa</name><name sortKey="Lacombe, Thierry" sort="Lacombe, Thierry" uniqKey="Lacombe T" first="Thierry" last="Lacombe">Thierry Lacombe</name><name sortKey="Le Cunff, Loic" sort="Le Cunff, Loic" uniqKey="Le Cunff L" first="Loic" last="Le Cunff">Loic Le Cunff</name><name sortKey="Segura, Vincent" sort="Segura, Vincent" uniqKey="Segura V" first="Vincent" last="Segura">Vincent Segura</name><name sortKey="This, Patrice" sort="This, Patrice" uniqKey="This P" first="Patrice" last="This">Patrice This</name></country><country name="Suisse"><region name="Canton de Vaud"><name sortKey="Neuenschwander, Samuel" sort="Neuenschwander, Samuel" uniqKey="Neuenschwander S" first="Samuel" last="Neuenschwander">Samuel Neuenschwander</name></region></country><country name="Australie"><region name="Victoria (État)"><name sortKey="Fournier Level, Alexandre" sort="Fournier Level, Alexandre" uniqKey="Fournier Level A" first="Alexandre" last="Fournier-Level">Alexandre Fournier-Level</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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