ArticleBMC genetics2018
Comparing SNP panels and statistical methods for estimating genomic breed composition of individual animals in ten cattle breeds.
Article in BMC genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed.
- Article
- Use of Cluster Analysis for Identifying Metafounders.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Single nucleotide polymorphism information estimates breed and variety composition ratio in food.Current research in food science · 2026Article
- A deep learning strategy for accurate identification of purebred and hybrid pigs across SNP chips.Journal of animal science and biotechnology · 2025Article
- Population structure and breed identification of Chinese indigenous sheep breeds using whole genome SNPs and InDels.Genetics, selection, evolution : GSE · 2024Article
- Definition of metafounders based on population structure analysis.Genetics, selection, evolution : GSE · 2024Article
- A Comprehensive Genomic Analysis of Chinese Indigenous Ningxiang Pigs: Genomic Breed Compositions, Runs of Homozygosity, and Beyond.International journal of molecular sciences · 2023Article
- Breed identification using breed-informative SNPs and machine learning based on whole genome sequence data and SNP chip data.Journal of animal science and biotechnology · 2023Article
- A web tool for the global identification of pig breeds.Genetics, selection, evolution : GSE · 2023Article
- The use of a genomic relationship matrix for breed assignment of cattle breeds: comparison and combination with a machine learning method.Journal of animal science · 2023Article
- Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information.Frontiers in genetics · 2023Article
- A look under the hood of genomic-estimated breed compositions for brangus cattle: What have we learned?Frontiers in genetics · 2023Article
- Estimation of dam line composition of 3-way crossbred animals using genomic information.Genetics, selection, evolution : GSE · 2022Article
- Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip.Tropical animal health and production · 2022Article
- Assessing accuracy of genotype imputation in the Afrikaner and Brahman cattle breeds of South Africa.Tropical animal health and production · 2022Article
- Interacting Proteins, Polymorphisms and the Susceptibility of Animals to SARS-CoV-2.Animals : an open access journal from MDPI · 2021Review
- SNP panels for the estimation of dairy breed proportion and parentage assignment in African crossbred dairy cattle.Genetics, selection, evolution : GSE · 2021Article
- Whole-Genome SNP Characterisation Provides Insight for Sustainable Use of Local South African Livestock Populations.Frontiers in genetics · 2021Article
- Functional Analysis of Haplotypes in BovineAnimals : an open access journal from MDPI · 2020Article
- A low-density SNP genotyping panel for the accurate prediction of cattle breeds.Journal of animal science · 2020Article
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8 authors.
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Abstract
backgroundSNPs are informative to estimate genomic breed composition (GBC) of individual animals, but selected SNPs for this purpose were not made available in the commercial bovine SNP chips prior to the present study. The primary objective of the present study was to select five common SNP panels for estimating GBC of individual animals initially involving 10 cattle breeds (two dairy breeds and eight beef breeds). The performance of the five common SNP panels was evaluated based on admixture model and linear regression model, respectively. Finally, the downstream implication of GBC on genomic prediction accuracies was investigated and discussed in a Santa Gertrudis cattle population.
resultsThere were 15,708 common SNPs across five currently-available commercial bovine SNP chips. From this set, four subsets (1,000, 3,000, 5,000, and 10,000 SNPs) were selected by maximizing average Euclidean distance (AED) of SNP allelic frequencies among the ten cattle breeds. For 198 animals presented as Akaushi, estimated GBC of the Akaushi breed (GBCA) based on the admixture model agreed very well among the five SNP panels, identifying 166 animals with GBCA = 1. Using the same SNP panels, the linear regression approach reported fewer animals with GBCA = 1. Nevertheless, estimated GBCA using both models were highly correlated (r = 0.953 to 0.992). In the genomic prediction of a Santa Gertrudis population (and crosses), the results showed that the predictability of molecular breeding values using SNP effects obtained from 1,225 animals with no less than 0.90 GBC of Santa Gertrudis (GBCSG) decreased on crossbred animals with lower GBCSG.
conclusionsOf the two statistical models used to compute GBC, the admixture model gave more consistent results among the five selected SNP panels than the linear regression model. The availability of these common SNP panels facilitates identification and estimation of breed compositions using currently-available bovine SNP chips. In view of utility, the 1 K panel is the most cost effective and it is convenient to be included as add-on content in future development of bovine SNP chips, whereas the 10 K and 16 K SNP panels can be more resourceful if used independently for imputation to intermediate or high-density genotypes.
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