Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations
Several studies have evaluated computational methods that infer the haplotypes from population genotype data in European cattle populations. However, little is known about how well they perform in African indigenous and crossbred populations. This study investigates: (1) global and local ancestry in...
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Frontiers Media S.A.
2021-03-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.584355/full |
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author | Netsanet Z. Gebrehiwot Hassan Aliloo Eva M. Strucken Karen Marshall Mohammad Al Kalaldeh Ayao Missohou John P. Gibson |
author_facet | Netsanet Z. Gebrehiwot Hassan Aliloo Eva M. Strucken Karen Marshall Mohammad Al Kalaldeh Ayao Missohou John P. Gibson |
author_sort | Netsanet Z. Gebrehiwot |
collection | DOAJ |
description | Several studies have evaluated computational methods that infer the haplotypes from population genotype data in European cattle populations. However, little is known about how well they perform in African indigenous and crossbred populations. This study investigates: (1) global and local ancestry inference; (2) heterozygosity proportion estimation; and (3) genotype imputation in West African indigenous and crossbred cattle populations. Principal component analysis (PCA), ADMIXTURE, and LAMP-LD were used to analyse a medium-density single nucleotide polymorphism (SNP) dataset from Senegalese crossbred cattle. Reference SNP data of East and West African indigenous and crossbred cattle populations were used to investigate the accuracy of imputation from low to medium-density and from medium to high-density SNP datasets using Minimac v3. The first two principal components differentiated Bos indicus from European Bos taurus and African Bos taurus from other breeds. Irrespective of assuming two or three ancestral breeds for the Senegalese crossbreds, breed proportion estimates from ADMIXTURE and LAMP-LD showed a high correlation (r ≥ 0.981). The observed ancestral origin heterozygosity proportion in putative F1 crosses was close to the expected value of 1.0, and clearly differentiated F1 from all other crosses. The imputation accuracies (estimated as correlation) between imputed and the real data in crossbred animals ranged from 0.142 to 0.717 when imputing from low to medium-density, and from 0.478 to 0.899 for imputation from medium to high-density. The imputation accuracy was generally higher when the reference data came from the same geographical region as the target population, and when crossbred reference data was used to impute crossbred genotypes. The lowest imputation accuracies were observed for indigenous breed genotypes. This study shows that ancestral origin heterozygosity can be estimated with high accuracy and will be far superior to the use of observed individual heterozygosity for estimating heterosis in African crossbred populations. It was not possible to achieve high imputation accuracy in West African crossbred or indigenous populations based on reference data sets from East Africa, and population-specific genotyping with high-density SNP assays is required to improve imputation. |
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spelling | doaj.art-47f6fa31b0434ffb9f34f6bdbeb601782022-12-21T21:24:38ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-03-011210.3389/fgene.2021.584355584355Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle PopulationsNetsanet Z. Gebrehiwot0Hassan Aliloo1Eva M. Strucken2Karen Marshall3Mohammad Al Kalaldeh4Ayao Missohou5John P. Gibson6Centre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, AustraliaCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, AustraliaCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, AustraliaInternational Livestock Research Institute and Centre for Tropical Livestock Genetics and Health, Nairobi, KenyaCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, AustraliaL‘École Inter-États des Sciences et Médecine Vétérinaires de Dakar (EISMV), Dakar, SenegalCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, AustraliaSeveral studies have evaluated computational methods that infer the haplotypes from population genotype data in European cattle populations. However, little is known about how well they perform in African indigenous and crossbred populations. This study investigates: (1) global and local ancestry inference; (2) heterozygosity proportion estimation; and (3) genotype imputation in West African indigenous and crossbred cattle populations. Principal component analysis (PCA), ADMIXTURE, and LAMP-LD were used to analyse a medium-density single nucleotide polymorphism (SNP) dataset from Senegalese crossbred cattle. Reference SNP data of East and West African indigenous and crossbred cattle populations were used to investigate the accuracy of imputation from low to medium-density and from medium to high-density SNP datasets using Minimac v3. The first two principal components differentiated Bos indicus from European Bos taurus and African Bos taurus from other breeds. Irrespective of assuming two or three ancestral breeds for the Senegalese crossbreds, breed proportion estimates from ADMIXTURE and LAMP-LD showed a high correlation (r ≥ 0.981). The observed ancestral origin heterozygosity proportion in putative F1 crosses was close to the expected value of 1.0, and clearly differentiated F1 from all other crosses. The imputation accuracies (estimated as correlation) between imputed and the real data in crossbred animals ranged from 0.142 to 0.717 when imputing from low to medium-density, and from 0.478 to 0.899 for imputation from medium to high-density. The imputation accuracy was generally higher when the reference data came from the same geographical region as the target population, and when crossbred reference data was used to impute crossbred genotypes. The lowest imputation accuracies were observed for indigenous breed genotypes. This study shows that ancestral origin heterozygosity can be estimated with high accuracy and will be far superior to the use of observed individual heterozygosity for estimating heterosis in African crossbred populations. It was not possible to achieve high imputation accuracy in West African crossbred or indigenous populations based on reference data sets from East Africa, and population-specific genotyping with high-density SNP assays is required to improve imputation.https://www.frontiersin.org/articles/10.3389/fgene.2021.584355/fullADMIXTUREAfrican cattleglobal ancestryMinimacLAMP-LDlocal ancestry |
spellingShingle | Netsanet Z. Gebrehiwot Hassan Aliloo Eva M. Strucken Karen Marshall Mohammad Al Kalaldeh Ayao Missohou John P. Gibson Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations Frontiers in Genetics ADMIXTURE African cattle global ancestry Minimac LAMP-LD local ancestry |
title | Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations |
title_full | Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations |
title_fullStr | Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations |
title_full_unstemmed | Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations |
title_short | Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations |
title_sort | inference of ancestries and heterozygosity proportion and genotype imputation in west african cattle populations |
topic | ADMIXTURE African cattle global ancestry Minimac LAMP-LD local ancestry |
url | https://www.frontiersin.org/articles/10.3389/fgene.2021.584355/full |
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