Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12522
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dc.contributor.authorDaetwyler, H Den
dc.contributor.authorSwan, Andrewen
dc.contributor.authorVan Der Werf, Julius Hen
dc.contributor.authorHayes, Ben Jen
dc.date.accessioned2013-05-13T10:31:00Z-
dc.date.issued2012-
dc.identifier.citationGenetics Selection Evolution, v.44, p. 1-11en
dc.identifier.issn1297-9686en
dc.identifier.issn0999-193Xen
dc.identifier.urihttps://hdl.handle.net/1959.11/12522-
dc.description.abstractBackground: Genomic predictions can be applied early in life without impacting selection candidates. This is especially useful for meat quality traits in sheep. Carcass and novel meat quality traits were predicted in a multi-breed sheep population that included Merino, Border Leicester, Polled Dorset and White Suffolk sheep and their crosses. Methods: Prediction of breeding values by best linear unbiased prediction (BLUP) based on pedigree information was compared to prediction based on genomic BLUP (GBLUP) and a Bayesian prediction method (BayesR). Cross-validation of predictions across sire families was used to evaluate the accuracy of predictions based on the correlation of predicted and observed values and the regression of observed on predicted values was used to evaluate bias of methods. Accuracies and regression coefficients were calculated using either phenotypes or adjusted phenotypes as observed variables. Results and conclusions: Genomic methods increased the accuracy of predicted breeding values to on average 0.2 across traits (range 0.07 to 0.31), compared to an average accuracy of 0.09 for pedigree-based BLUP. However, for some traits with smaller reference population size, there was no increase in accuracy or it was small. No clear differences in accuracy were observed between GBLUP and BayesR. The regression of phenotypes on breeding values was close to 1 for all methods, indicating little bias, except for GBLUP and adjusted phenotypes (regression = 0.78). Accuracies calculated with adjusted (for fixed effects) phenotypes were less variable than accuracies based on unadjusted phenotypes, indicating that fixed effects influence the latter. Increasing the reference population size increased accuracy, indicating that adding more records will be beneficial. For the Merino, Polled Dorset and White Suffolk breeds, accuracies were greater than for the Border Leicester breed due to the smaller sample size and limited across-breed prediction. BayesR detected only a few large marker effects but one region on chromosome 6 was associated with large effects for several traits. Cross-validation produced very similar variability of accuracy and regression coefficients for BLUP, GBLUP and BayesR, showing that this variability is not a property of genomic methods alone. Our results show that genomic selection for novel difficult-to-measure traits is a feasible strategy to achieve increased genetic gain.en
dc.languageenen
dc.publisherBioMed Central Ltden
dc.relation.ispartofGenetics Selection Evolutionen
dc.titleAccuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validationen
dc.typeJournal Articleen
dc.identifier.doi10.1186/1297-9686-44-33en
dcterms.accessRightsGolden
dc.subject.keywordsQuantitative Genetics (incl Disease and Trait Mapping Genetics)en
local.contributor.firstnameH Den
local.contributor.firstnameAndrewen
local.contributor.firstnameJulius Hen
local.contributor.firstnameBen Jen
local.subject.for2008060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics)en
local.subject.seo2008830310 Sheep - Meaten
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailhans.daetwyler@dpi.vic.gov.auen
local.profile.emailaswan@une.edu.auen
local.profile.emailjvanderw@une.edu.auen
local.profile.emailben.hayes@dpi.vic.gov.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20130408-144319en
local.publisher.placeUnited Kingdomen
local.identifier.runningnumber33en
local.format.startpage1en
local.format.endpage11en
local.identifier.scopusid84868651956en
local.peerreviewedYesen
local.identifier.volume44en
local.access.fulltextYesen
local.contributor.lastnameDaetwyleren
local.contributor.lastnameSwanen
local.contributor.lastnameVan Der Werfen
local.contributor.lastnameHayesen
dc.identifier.staffune-id:aswanen
dc.identifier.staffune-id:jvanderwen
local.profile.orcid0000-0001-8048-3169en
local.profile.orcid0000-0003-2512-1696en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:12729en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleAccuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validationen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorDaetwyler, H Den
local.search.authorSwan, Andrewen
local.search.authorVan Der Werf, Julius Hen
local.search.authorHayes, Ben Jen
local.uneassociationUnknownen
local.identifier.wosid000311904500001en
local.year.published2012en
local.subject.for2020310506 Gene mappingen
local.subject.seo2020100412 Sheep for meaten
Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Journal Article
School of Environmental and Rural Science
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