The impact of modelling and pooled data on the accuracy of genomic prediction in small holder dairy data

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cg.authorship.typesCGIAR and developing country instituteen_US
cg.contributor.affiliationInternational Livestock Research Instituteen_US
cg.contributor.affiliationUniversity of New Englanden_US
cg.contributor.affiliationScotland's Rural Collegeen_US
cg.contributor.affiliationNelson Mandela Africa Institution of Science and Technologyen_US
cg.contributor.crpLivestocken_US
cg.contributor.donorBill & Melinda Gates Foundationen_US
cg.coverage.countryKenyaen_US
cg.coverage.countryTanzaniaen_US
cg.coverage.iso3166-alpha2KEen_US
cg.coverage.iso3166-alpha2TZen_US
cg.coverage.regionAfricaen_US
cg.coverage.regionEastern Africaen_US
cg.coverage.regionSouthern Africaen_US
cg.creator.identifierRaphael Mrode: 0000-0003-1964-5653en_US
cg.creator.identifierAlly Okeyo Mwai: 0000-0003-2379-7801en_US
cg.creator.identifierOjango J.M.K.: 0000-0003-0224-5370en_US
cg.creator.identifierJohn Gibson: 0000-0003-0371-2401en_US
cg.howPublishedFormally Publisheden_US
cg.identifier.urlhttp://www.wcgalp.org/proceedings/2018/impact-modelling-and-pooled-data-accuracy-genomic-prediction-small-holder-dairyen_US
cg.subject.ilriANIMAL BREEDINGen_US
cg.subject.ilriANIMAL PRODUCTIONen_US
cg.subject.ilriDAIRYINGen_US
cg.subject.ilriDATAen_US
cg.subject.ilriLIVESTOCKen_US
dc.contributor.authorMrode, Raphael A.en_US
dc.contributor.authorAliloo, Hassanen_US
dc.contributor.authorStrucken, E.M.en_US
dc.contributor.authorCoffey, M.en_US
dc.contributor.authorOjango, Julie M.K.en_US
dc.contributor.authorMujibi, Denisen_US
dc.contributor.authorGibson, John P.en_US
dc.contributor.authorOkeyo Mwai, Allyen_US
dc.date.accessioned2018-11-05T17:04:20Zen_US
dc.date.available2018-11-05T17:04:20Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/97872en_US
dc.titleThe impact of modelling and pooled data on the accuracy of genomic prediction in small holder dairy dataen_US
dcterms.abstractThe lack of data recording in smallholder dairy cattle system implies that the availability of molecular data could offer some quick wins in terms of using the genomic information in genomic evaluation and therefore genomic selection (GS). Initial studies have reported low to medium accuracy of genomic prediction when the size of data is limited. The African dairy genetic gains (ADGG) project is generating more data across two countries in East Africa and would offer more opportunity to further examine the application of GS. In anticipation of having more data in future, this paper examined the impact of fitting GBLUP models with dominance effects, a multi-trait GBLUP that fits exotic breed and non-exotic breed proportion as different traits and the analysis of pooled data from Kenya and Tanzania on the accuracy of genomic predictions. In addition, it examines if chromosome regions with highest contributions to top GEBV cows with high exotic and high indigenous genes are different. The estimates of dominance variance were essentially zero, possibly due to the limited data set, and therefore the model with dominance effect resulted in no increase of genomic accuracy compared to a model with only additive effects. The fitting of the proportion of exotic and non-exotic genes as different traits resulted in slightly lower accuracies of cows with more than 35% exotic genes but almost doubled the accuracy of those with < 36% exotic genes. However, the model resulted in an increase in the predictive ability of the models with regressions tending toward unity and a reduction in prediction bias. The pooled data resulted in increased accuracy for the Tanzania data set but not for Kenya, mostly due to different breeds being involved in the crossbreeding and the genetic kinships between both populations was very weak. The chromosome regions with largest contributions to the top GEBV cows with high exotic genes were different from those with high levels of indigenous breed, indicating the need for a proper and well planned GWAS study.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceScientistsen_US
dcterms.bibliographicCitationMrode, R., Aliloo, H., Strucken, E.M., Coffey, M., Ojango, J., Mujibi, D., Gibson, J.P. and Okeyo, M. 2018. The impact of modelling and pooled data on the accuracy of genomic prediction in small holder dairy data. IN: Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Methods and Tools - Prediction 2: 615en_US
dcterms.issued2018-10en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-NC-ND-4.0en_US
dcterms.subjectdataen_US
dcterms.subjectanimal breedingen_US
dcterms.subjectdairiesen_US
dcterms.subjectlivestocken_US
dcterms.typeConference Paperen_US

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