Integrating genetic and genomic analyses of combined health data across ecotypes to improve disease resistance in indigenous African chickens

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cg.authorship.typesCGIAR and advanced research instituteen_US
cg.contributor.affiliationUniversity of Edinburghen_US
cg.contributor.affiliationScotland's Rural Collegeen_US
cg.contributor.affiliationCentre for Tropical Livestock Genetics and Healthen_US
cg.contributor.affiliationUniversity of Londonen_US
cg.contributor.affiliationUniversity of Nottinghamen_US
cg.contributor.affiliationUniversity of Liverpoolen_US
cg.contributor.affiliationInternational Livestock Research Instituteen_US
cg.contributor.affiliationUniversity of Greenwichen_US
cg.contributor.crpLivestocken_US
cg.contributor.donorBiotechnology and Biological Sciences Research Council, United Kingdomen_US
cg.contributor.donorDepartment for International Development, United Kingdomen_US
cg.contributor.donorScottish Governmenten_US
cg.contributor.donorBill & Melinda Gates Foundationen_US
cg.coverage.regionAfricaen_US
cg.creator.identifierTadelle Dessie: 0000-0002-1630-0417en_US
cg.creator.identifierOlivier Hanotte: 0000-0002-2877-4767en_US
cg.creator.identifierJudy Bettridge: 0000-0002-3917-4660en_US
cg.howPublishedFormally Publisheden_US
cg.identifier.doihttps://doi.org/10.3389/fgene.2020.543890en_US
cg.isijournalISI Journalen_US
cg.issn1664-8021en_US
cg.journalFrontiers in Geneticsen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.ilriANIMAL BREEDINGen_US
cg.subject.ilriANIMAL DISEASESen_US
cg.subject.ilriCHICKENSen_US
cg.subject.ilriGENETICSen_US
cg.subject.ilriINDIGENOUS BREEDSen_US
cg.subject.ilriPOULTRYen_US
cg.volume11en_US
dc.contributor.authorBanos, Giorgiosen_US
dc.contributor.authorLindsay, V.en_US
dc.contributor.authorDesta, T.T.en_US
dc.contributor.authorBettridge, Judy M.en_US
dc.contributor.authorSánchez Molano, E.en_US
dc.contributor.authorVallejo Trujillo, Adrianaen_US
dc.contributor.authorMatika, O.en_US
dc.contributor.authorDessie, Tadelleen_US
dc.contributor.authorWigley, P.en_US
dc.contributor.authorChristley, Robert M.en_US
dc.contributor.authorKaiser, P.en_US
dc.contributor.authorHanotte, Olivier H.en_US
dc.contributor.authorPsifidi, A.en_US
dc.date.accessioned2020-11-26T08:42:41Zen_US
dc.date.available2020-11-26T08:42:41Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/110306en_US
dc.titleIntegrating genetic and genomic analyses of combined health data across ecotypes to improve disease resistance in indigenous African chickensen_US
dcterms.abstractPoultry play an important role in the agriculture of many African countries. The majority of chickens in sub-Saharan Africa are indigenous, raised in villages under semi-scavenging conditions. Vaccinations and biosecurity measures rarely apply, and infectious diseases remain a major cause of mortality and reduced productivity. Genomic selection for disease resistance offers a potentially sustainable solution but this requires sufficient numbers of individual birds with genomic and phenotypic data, which is often a challenge to collect in the small populations of indigenous chicken ecotypes. The use of information across-ecotypes presents an attractive possibility to increase the relevant numbers and the accuracy of genomic selection. In this study, we performed a joint analysis of two distinct Ethiopian indigenous chicken ecotypes to investigate the genomic architecture of important health and productivity traits and explore the feasibility of conducting genomic selection across-ecotype. Phenotypic traits considered were antibody response to Infectious Bursal Disease (IBDV), Marek's Disease (MDV), Fowl Cholera (PM) and Fowl Typhoid (SG), resistance to Eimeria and cestode parasitism, and productivity (body weight and body condition score (BCS)). Combined data from the two chicken ecotypes, Horro (n=384) and Jarso (n=376), were jointly analysed for genetic parameter estimation, genome-wide association studies (GWAS), genomic breeding value (GEBVs) calculation, genomic predictions, whole-genome sequencing (WGS), and pathways analyses. Estimates of across-ecotype heritability were significant and moderate in magnitude (0.22-0.47) for all traits except for SG and BCS. GWAS identified several significant genomic associations with health and productivity traits. The WGS analysis revealed putative candidate genes and mutations for IBDV (TOLLIP, ANGPTL5, BCL9, THEMIS2), MDV (GRM7), SG (MAP3K21), Eimeria (TOM1L1) and cestodes (TNFAIP1, ATG9A, NOS2) parasitism, which warrant further investigation. Reliability of GEBVs increased compared to within-ecotype calculations but accuracy of genomic prediction did not, probably because the genetic distance between the two ecotypes offset the benefit from increased sample size. However, for some traits genomic prediction was only feasible in across-ecotype analysis. Our results generally underpin the potential of genomic selection to enhance health and productivity across-ecotypes. Future studies should establish the required minimum sample size and genetic similarity between ecotypes to ensure accurate joint genomic selection.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceScientistsen_US
dcterms.available2020-10-09en_US
dcterms.bibliographicCitationBanos, G., Lindsay, V., Desta, T.T., Bettridge, J., Sanchez-Molano, E., Vallejo-Trujillo, A., Matika, O., Dessie, T., Wigley, P., Christley, R.M., Kaiser, P., Hanotte, O. and Psifidi, A. 2020. Integrating genetic and genomic analyses of combined health data across ecotypes to improve disease resistance in indigenous African chickens. Frontiers in Genetics 11:543890.en_US
dcterms.issued2020-10-09en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherFrontiers Mediaen_US
dcterms.subjectchickensen_US
dcterms.subjectgeneticsen_US
dcterms.subjectindigenous breedsen_US
dcterms.subjectpoultryen_US
dcterms.subjectanimal diseasesen_US
dcterms.subjectanimal breedingen_US
dcterms.typeJournal Articleen_US

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