Whole genome analysis of African indigenous cattle breeds to assess genetic diversity, demographic history and selection signatures

dc.contributor.advisorJoubert, Fourie
dc.contributor.coadvisorZwane, Avhashoni Agnes
dc.contributor.emailU20744049@tuks.co.zaen_US
dc.contributor.postgraduateMalima, Maano Bryton
dc.date.accessioned2023-02-02T05:23:34Z
dc.date.available2023-02-02T05:23:34Z
dc.date.created2023-04-09
dc.date.issued2022
dc.descriptionDissertation (MSc (Bioinformatics))--University of Pretoria, 2022.en_US
dc.description.abstractThe development and application of next-generation sequencing technologies have enabled the investigation of genomic data better and more efficiently. This progress has led to population genomic analysis of many African indigenous breeds such as Muturu, N’Dama, Sheko, Ankole, Afar, and Fogera. However, no study has used whole-genome sequence data to understand relationships between South African (SA) cattle breeds such as Nguni, Afrikaner, and Bonsmara, and African breeds such as Ankole, Kenana, and N’Dama, as a result, information such as genomic diversity, effective population changes, and adaptations remain unclear and this negatively impacts efforts of conservation and breed improvement. This study aimed to investigate the genomic relationships between three SA and three African cattle breeds, to assess genomic diversity, demographic history, introgression, and to identify regions of selection signatures. A total of 15 animals from SA cattle breeds Nguni (5), Afrikaner (5), and Bonsmara (5), were sequenced using Illumina Hiseq 2500 platform at 10X coverage. Data for Ankole (5), Kenana (5), and N’Dama (5) were obtained from the study of Kim et al. (2017). Variant calling was done using GATK and a total of 37,482,988 (SNPs) and 4,931,938 (InDels) were obtained across the breeds. Analysis of Next Generation Sequencing Data (ANGSD) was used to generate phylogeny, heterozygosity estimates, and introgression events using ABBA/BABA patterns. Principal component analysis, nucleotide diversity, ancestral admixtures, and Treemix were applied to unveil relationships and gene flow events. Then evidence of selection signatures was explored using two statistical methods iHS and XP-EHH. Kenana cattle exhibited higher levels of genetic diversity, followed by Ankole, Nguni, Afrikaner, Bonsmara, and N’Dama, and surprisingly Bonsmara, a SA composite, had higher genetic diversity than N’Dama. Relatedness, introgression and migration analysis supported findings of previous studies which indicated close relationships between SA indigenous cattle breeds and further unearth novel relationships between Nguni, Ankole, and Kenana cattle. This analysis also revealed the shared ancestry between Nguni and N’Dama, as well as their contribution to Ankole’s genetic makeup, because of close relatedness between Bonsmara and Holstein, Water Buffalo was used to validate observed relationships. Moreover, we also observed Bonsmara ancestry and its relationship with taurine breeds. The demographic history analysis revealed how the effective population sizes of African breeds changed over different climatic epochs. Notably, we observed two contractions and two population expansions which are consistent with previous findings. The timing of the population sizes overlapped with the recorded ancient human activities such as migration and domestication. Selection signature xiv analysis identified 112 iHS and 120 XP-EHH candidate regions in the study populations. The annotation of candidate regions revealed potential genes associated with reproduction, growth, milk production, meat quality, diseases, and disease resistance. In particular genes such as CNTN6, KCNIP4, APP, MAP4K4, CDH13, PLCB4 and AGO2 showed strong positive selection. These findings provide important genomic information on genetic relationships between local and African indigenous cattle breeds, as well as the understanding of selection and adaptation events that will help in the improvement of these breeds.en_US
dc.description.availabilityUnrestricteden_US
dc.description.degreeMSc (Bioinformatics)en_US
dc.description.departmentGeneticsen_US
dc.description.departmentBiochemistry, Genetics and Microbiology (BGM)
dc.description.sponsorshipMeat Industry Trust, Agricultural Research Council-Animal Production (ARC-AP).en_US
dc.description.sponsorshipNational Research Foundation.en_US
dc.identifier.citationMalima, MB 2022, Whole genome analysis of African indigenous cattle breeds to assess genetic diversity, demographic history and selection signatures, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd https://repository.up.ac.za/handle/2263/89069en_US
dc.identifier.doi10.25403/UPresearchdata.21701465en_US
dc.identifier.otherA2023
dc.identifier.urihttps://repository.up.ac.za/handle/2263/89069
dc.identifier.uriDOI: https://doi.org/10.25403/UPresearchdata.21701465.v1
dc.language.isoenen_US
dc.publisherUniversity of Pretoria
dc.rights© 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subjectUCTDen_US
dc.subjectWhole genome sequencingen_US
dc.subjectAfrican indigenous cattle breedsen_US
dc.subjectDemographic historyen_US
dc.subjectGenetic diversityen_US
dc.subjectCattle breedingen_US
dc.subject.otherNatural and agricultural sciences theses SDG-02
dc.subject.otherSDG-02: Zero hunger
dc.subject.otherNatural and agricultural sciences theses SDG-12
dc.subject.otherSDG-12: Responsible consumption and production
dc.titleWhole genome analysis of African indigenous cattle breeds to assess genetic diversity, demographic history and selection signaturesen_US
dc.typeDissertationen_US

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