Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/28714
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJeyaruban, M Gen
dc.contributor.authorGurman, P Men
dc.contributor.authorJohnston, D Jen
dc.contributor.authorSwan, A Aen
dc.contributor.authorBanks, R Gen
dc.contributor.authorGirard, C Jen
dc.date.accessioned2020-05-17T22:39:09Z-
dc.date.available2020-05-17T22:39:09Z-
dc.date.issued2019-
dc.identifier.citationProceedings of the Association for the Advancement of Animal Breeding and Genetics, v.23, p. 79-82en
dc.identifier.issn1328-3227en
dc.identifier.urihttps://hdl.handle.net/1959.11/28714-
dc.description.abstractThis study investigated the accuracy of predicting future phenotypes of young Angus and Hereford cattle using Single-step Genomic BLUP (SSGBLUP) compared to the traditional pedigree-based BLUP evaluation (NRMBLUP). Forward cross-validation, using two comparison methods, was used to quantify the predictability of the two evaluations. For each breed, two data sets named ‘full’ and ‘partial’ were generated. The ‘full’ data set included all relationships, all genotypes and phenotypes of animals born up to November 2018. For ‘partial’ data sets, phenotypes of animals born after December 2014 were removed and the data for animals removed after December 2014 were used as the ‘validation data set’. SSGBLUP and NRMBLUP analyses were performed separately for the full and partial data sets and EBVs were predicted for animals in the validation data set. In Method 1, R squared values (R²), regression coefficients (REG) and adjusted correlation (ACOR), between pre-corrected phenotypes and predicted EBVs were compared. In Method 2, correlation ratios between EBVs from full and partial evaluations were estimated to calculate the increase in predictability between the SSGBLUP and NRMBLUP. The estimated R², REG and ACOR using SSGBLUP were higher than those from NRMBLUP. A similar pattern was observed for correlation ratios from Method 2. The increase in ability to predict future phenotypes using Method 1 ranged from 30 to 50% and 10 to 36% for genotyped and 2 to 4% and 1 to 2 % for non-genotyped Angus and Hereford cattle, respectively. Using Method 2, the ability to predict future phenotypes ranged from 22 to 40% and 6 to 28% for genotyped and 1 to 2% and 0.5 to 1 % for non-genotyped Angus and Hereford cattle in the validation set, respectively. This study showed that there was an increase in the accuracy to predict future performance from SSGBLUP compared to NRMBLUP in Angus and Hereford cattle. The increase in predictive ability varied according to the heritability of a trait, the number of phenotypes and genotypes included in the evaluation and whether the animals were genotyped or not in the evaluation.en
dc.languageenen
dc.publisherAssociation for the Advancement of Animal Breeding and Genetics (AAABG)en
dc.relation.ispartofProceedings of the Association for the Advancement of Animal Breeding and Geneticsen
dc.titleValidation of Single Step Genomic Best Linear Unbiased Prediction in Beef Cattleen
dc.typeConference Publicationen
dc.relation.conferenceAAABG 2019: 23rd Conference of the Association for the Advancement of Animal Breeding and Geneticsen
dcterms.accessRightsBronzeen
local.contributor.firstnameM Gen
local.contributor.firstnameP Men
local.contributor.firstnameD Jen
local.contributor.firstnameA Aen
local.contributor.firstnameR Gen
local.contributor.firstnameC Jen
local.subject.for2008070201 Animal Breedingen
local.subject.seo2008830301 Beef Cattleen
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.schoolAnimal Genetics and Breeding Uniten
local.profile.emailgjeyarub@une.edu.auen
local.profile.emailpgurman@une.edu.auen
local.profile.emaildjohnsto@une.edu.auen
local.profile.emailaswan@une.edu.auen
local.profile.emailrbanks@une.edu.auen
local.profile.emailcgirard@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference27th October - 1st November, 2019en
local.conference.placeArmidale, Australiaen
local.publisher.placeArmidale, Australiaen
local.format.startpage79en
local.format.endpage82en
local.url.openhttp://www.aaabg.org/aaabghome/fullproc23.phpen
local.peerreviewedYesen
local.identifier.volume23en
local.access.fulltextYesen
local.contributor.lastnameJeyarubanen
local.contributor.lastnameGurmanen
local.contributor.lastnameJohnstonen
local.contributor.lastnameSwanen
local.contributor.lastnameBanksen
local.contributor.lastnameGirarden
dc.identifier.staffune-id:gjeyaruben
dc.identifier.staffune-id:pgurmanen
dc.identifier.staffune-id:djohnstoen
dc.identifier.staffune-id:aswanen
dc.identifier.staffune-id:rbanksen
dc.identifier.staffune-id:cgirarden
local.profile.orcid0000-0002-0231-0120en
local.profile.orcid0000-0002-4375-115Xen
local.profile.orcid0000-0002-4995-8311en
local.profile.orcid0000-0001-8048-3169en
local.profile.orcid0000-0001-7303-033Xen
local.profile.orcid0000-0003-0542-7073en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/28714en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleValidation of Single Step Genomic Best Linear Unbiased Prediction in Beef Cattleen
local.relation.fundingsourcenoteMeat and Livestock Australia (project number L.GEN.0174)en
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.relation.urlhttp://www.aaabg.org/aaabghome/en
local.conference.detailsAAABG 2019: 23rd Conference of the Association for the Advancement of Animal Breeding and Genetics, Armidale, Australia, 27 October-1 Novemberen
local.search.authorJeyaruban, M Gen
local.search.authorGurman, P Men
local.search.authorJohnston, D Jen
local.search.authorSwan, A Aen
local.search.authorBanks, R Gen
local.search.authorGirard, C Jen
local.istranslatedNoen
local.uneassociationYesen
dc.date.presented2019-10-28-
local.atsiresearchNoen
local.conference.venueUniversity of New Englanden
local.sensitive.culturalNoen
local.year.published2019en
local.year.presented2019en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/fa8e11dc-ce18-4d49-a1f8-87111e7e5438en
local.subject.for2020300305 Animal reproduction and breedingen
local.subject.seo2020100401 Beef cattleen
local.date.start2019-10-27-
local.date.end2019-11-01-
Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Conference Publication
Files in This Item:
2 files
File Description SizeFormat 
Show simple item record

Page view(s)

2,300
checked on Feb 25, 2024

Download(s)

6
checked on Feb 25, 2024
Google Media

Google ScholarTM

Check


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