Increased genomic prediction accuracy in wheat breeding using a large Australian panel.
Identifieur interne : 000075 ( PubMed/Corpus ); précédent : 000074; suivant : 000076Increased genomic prediction accuracy in wheat breeding using a large Australian panel.
Auteurs : Adam Norman ; Julian Taylor ; Emi Tanaka ; Paul Telfer ; James Edwards ; Jean-Pierre Martinant ; Haydn KuchelSource :
- TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik [ 1432-2242 ] ; 2017.
English descriptors
- KwdEn :
- MESH :
Abstract
Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom(TM) Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.
DOI: 10.1007/s00122-017-2975-4
PubMed: 28887586
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pubmed:28887586Le document en format XML
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(NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Telfer, Paul" sort="Telfer, Paul" uniqKey="Telfer P" first="Paul" last="Telfer">Paul Telfer</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Edwards, James" sort="Edwards, James" uniqKey="Edwards J" first="James" last="Edwards">James Edwards</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Martinant, Jean Pierre" sort="Martinant, Jean Pierre" uniqKey="Martinant J" first="Jean-Pierre" last="Martinant">Jean-Pierre Martinant</name><affiliation><nlm:affiliation>Centre of Research, Limagrain Field Seeds Pty Ltd, Chappes, France.</nlm:affiliation></affiliation></author><author><name sortKey="Kuchel, Haydn" sort="Kuchel, Haydn" uniqKey="Kuchel H" first="Haydn" last="Kuchel">Haydn Kuchel</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28887586</idno><idno type="pmid">28887586</idno><idno type="doi">10.1007/s00122-017-2975-4</idno><idno type="wicri:Area/PubMed/Corpus">000075</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000075</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Increased genomic prediction accuracy in wheat breeding using a large Australian panel.</title><author><name sortKey="Norman, Adam" sort="Norman, Adam" uniqKey="Norman A" first="Adam" last="Norman">Adam Norman</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia. adam.norman@agtbreeding.com.au.</nlm:affiliation></affiliation></author><author><name sortKey="Taylor, Julian" sort="Taylor, Julian" uniqKey="Taylor J" first="Julian" last="Taylor">Julian Taylor</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Tanaka, Emi" sort="Tanaka, Emi" uniqKey="Tanaka E" first="Emi" last="Tanaka">Emi Tanaka</name><affiliation><nlm:affiliation>National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Telfer, Paul" sort="Telfer, Paul" uniqKey="Telfer P" first="Paul" last="Telfer">Paul Telfer</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Edwards, James" sort="Edwards, James" uniqKey="Edwards J" first="James" last="Edwards">James Edwards</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Martinant, Jean Pierre" sort="Martinant, Jean Pierre" uniqKey="Martinant J" first="Jean-Pierre" last="Martinant">Jean-Pierre Martinant</name><affiliation><nlm:affiliation>Centre of Research, Limagrain Field Seeds Pty Ltd, Chappes, France.</nlm:affiliation></affiliation></author><author><name sortKey="Kuchel, Haydn" sort="Kuchel, Haydn" uniqKey="Kuchel H" first="Haydn" last="Kuchel">Haydn Kuchel</name><affiliation><nlm:affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</nlm:affiliation></affiliation></author></analytic><series><title level="j">TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik</title><idno type="eISSN">1432-2242</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Australia</term><term>Chromosome Mapping</term><term>Genomics</term><term>Genotype</term><term>Linear Models</term><term>Linkage Disequilibrium</term><term>Models, Genetic</term><term>Phenotype</term><term>Plant Breeding</term><term>Polymorphism, Single Nucleotide</term><term>Quantitative Trait Loci</term><term>Triticum (genetics)</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Triticum</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Australia</term><term>Chromosome Mapping</term><term>Genomics</term><term>Genotype</term><term>Linear Models</term><term>Linkage Disequilibrium</term><term>Models, Genetic</term><term>Phenotype</term><term>Plant Breeding</term><term>Polymorphism, Single Nucleotide</term><term>Quantitative Trait Loci</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom(TM) Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28887586</PMID><DateCreated><Year>2017</Year><Month>09</Month><Day>09</Day></DateCreated><DateCompleted><Year>2017</Year><Month>11</Month><Day>09</Day></DateCompleted><DateRevised><Year>2017</Year><Month>11</Month><Day>17</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1432-2242</ISSN><JournalIssue CitedMedium="Internet"><Volume>130</Volume><Issue>12</Issue><PubDate><Year>2017</Year><Month>Dec</Month></PubDate></JournalIssue><Title>TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik</Title><ISOAbbreviation>Theor. Appl. Genet.</ISOAbbreviation></Journal><ArticleTitle>Increased genomic prediction accuracy in wheat breeding using a large Australian panel.</ArticleTitle><Pagination><MedlinePgn>2543-2555</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s00122-017-2975-4</ELocationID><Abstract><AbstractText Label="KEY MESSAGE" NlmCategory="UNASSIGNED">Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom(TM) Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Norman</LastName><ForeName>Adam</ForeName><Initials>A</Initials><Identifier Source="ORCID">http://orcid.org/0000-0002-0794-4907</Identifier><AffiliationInfo><Affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia. adam.norman@agtbreeding.com.au.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Australian Grain Technologies Pty Ltd, Perkins Building, Roseworthy Campus, Roseworthy, SA, Australia. adam.norman@agtbreeding.com.au.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Taylor</LastName><ForeName>Julian</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tanaka</LastName><ForeName>Emi</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>National Institute for Applied Statistics Research Australia (NIASRA), School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Telfer</LastName><ForeName>Paul</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Australian Grain Technologies Pty Ltd, Perkins Building, Roseworthy Campus, Roseworthy, SA, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Edwards</LastName><ForeName>James</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Australian Grain Technologies Pty Ltd, Perkins Building, Roseworthy Campus, Roseworthy, SA, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Martinant</LastName><ForeName>Jean-Pierre</ForeName><Initials>JP</Initials><AffiliationInfo><Affiliation>Centre of Research, Limagrain Field Seeds Pty Ltd, Chappes, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kuchel</LastName><ForeName>Haydn</ForeName><Initials>H</Initials><AffiliationInfo><Affiliation>School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Glen Osmond, SA, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Australian Grain Technologies Pty Ltd, Perkins Building, Roseworthy Campus, Roseworthy, SA, Australia.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>09</Month><Day>08</Day></ArticleDate></Article><MedlineJournalInfo><Country>Germany</Country><MedlineTA>Theor Appl Genet</MedlineTA><NlmUniqueID>0145600</NlmUniqueID><ISSNLinking>0040-5752</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Theor Appl Genet. 2007 Dec;116(1):95-111</RefSource><PMID Version="1">17952402</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Genetics. 2010 Oct;186(2):713-24</RefSource><PMID 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