Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/10094
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHayes, B Jen
dc.contributor.authorBowman, P Jen
dc.contributor.authorDaetwyler, H Den
dc.contributor.authorKijas, J Wen
dc.contributor.authorVan Der Werf, Julius Hen
dc.date.accessioned2012-05-07T15:24:00Z-
dc.date.issued2012-
dc.identifier.citationAnimal Genetics, 43(1), p. 72-80en
dc.identifier.issn1365-2052en
dc.identifier.issn0268-9146en
dc.identifier.urihttps://hdl.handle.net/1959.11/10094-
dc.description.abstractAlthough genomic selection offers the prospect of improving the rate of genetic gain in meat, wool and dairy sheep breeding programs, the key constraint is likely to be the cost of genotyping. Potentially, this constraint can be overcome by genotyping selection candidates for a low density (low cost) panel of SNPs with sparse genotype coverage, imputing a much higher density of SNP genotypes using a densely genotyped reference population. These imputed genotypes would then be used with a prediction equation to produce genomic estimated breeding values. In the future, it may also be desirable to impute very dense marker genotypes or even whole genome re-sequence data from moderate density SNP panels. Such a strategy could lead to an accurate prediction of genomic estimated breeding values across breeds, for example. We used genotypes from 48 640 (50K) SNPs genotyped in four sheep breeds to investigate both the accuracy of imputation of the 50K SNPs from low density SNP panels, as well as prospects for imputing very dense or whole genome re-sequence data from the 50K SNPs (by leaving out a small number of the 50K SNPs at random). Accuracy of imputation was low if the sparse panel had less than 5000 (5K) markers. Across breeds, it was clear that the accuracy of imputing from sparse marker panels to 50K was higher if the genetic diversity within a breed was lower, such that relationships among animals in that breed were higher. The accuracy of imputation from sparse genotypes to 50K genotypes was higher when the imputation was performed within breed rather than when pooling all the data, despite the fact that the pooled reference set was much larger. For Border Leicesters, Poll Dorsets and White Suffolks, 5K sparse genotypes were sufficient to impute 50K with 80% accuracy. For Merinos, the accuracy of imputing 50K from 5K was lower at 71%, despite a large number of animals with full genotypes (2215) being used as a reference. For all breeds, the relationship of individuals to the reference explained up to 64% of the variation in accuracy of imputation, demonstrating that accuracy of imputation can be increased if sires and other ancestors of the individuals to be imputed are included in the reference population. The accuracy of imputation could also be increased if pedigree information was available and was used in tracking inheritance of large chromosome segments within families. In our study, we only considered methods of imputation based on population-wide linkage disequilibrium (largely because the pedigree for some of the populations was incomplete). Finally, in the scenarios designed to mimic imputation of high density or whole genome re-sequence data from the 50K panel, the accuracy of imputation was much higher (86-96%). This is promising, suggesting that in silico genome re-sequencing is possible in sheep if a suitable pool of key ancestors is sequenced for each breed.en
dc.languageenen
dc.publisherWiley-Blackwell Publishing Ltden
dc.relation.ispartofAnimal Geneticsen
dc.titleAccuracy of genotype imputation in sheep breedsen
dc.typeJournal Articleen
dc.identifier.doi10.1111/j.1365-2052.2011.02208.xen
dc.subject.keywordsGeneticsen
local.contributor.firstnameB Jen
local.contributor.firstnameP Jen
local.contributor.firstnameH Den
local.contributor.firstnameJ Wen
local.contributor.firstnameJulius Hen
local.subject.for2008060499 Genetics not elsewhere classifieden
local.subject.seo2008830399 Livestock Raising not elsewhere classifieden
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailjvanderw@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20120428-16045en
local.publisher.placeUnited Kingdomen
local.format.startpage72en
local.format.endpage80en
local.identifier.scopusid84855698387en
local.peerreviewedYesen
local.identifier.volume43en
local.identifier.issue1en
local.contributor.lastnameHayesen
local.contributor.lastnameBowmanen
local.contributor.lastnameDaetwyleren
local.contributor.lastnameKijasen
local.contributor.lastnameVan Der Werfen
dc.identifier.staffune-id:jvanderwen
local.profile.orcid0000-0003-2512-1696en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:10285en
dc.identifier.academiclevelAcademicen
local.title.maintitleAccuracy of genotype imputation in sheep breedsen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorHayes, B Jen
local.search.authorBowman, P Jen
local.search.authorDaetwyler, H Den
local.search.authorKijas, J Wen
local.search.authorVan Der Werf, Julius Hen
local.uneassociationUnknownen
local.identifier.wosid000298874000010en
local.year.published2012en
local.subject.for2020310599 Genetics not elsewhere classifieden
local.subject.seo2020100407 Insectsen
Appears in Collections:Journal Article
Files in This Item:
2 files
File Description SizeFormat 
Show simple item record

SCOPUSTM   
Citations

97
checked on Feb 17, 2024

Page view(s)

1,138
checked on Jun 11, 2023

Download(s)

2
checked on Jun 11, 2023
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.