ArticleJournal of animal science2019
High imputation accuracy from informative low-to-medium density single nucleotide polymorphism genotypes is achievable in sheep1.
Article in Journal of animal science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- Pedigree-assisted genotype imputation enables cost-effective genomic prediction in Penaeus vannamei.Scientific reports · 2026Article
- Identifying low-density, ancestry-informative SNP markers through whole genome resequencing in Indian, Chinese, and wild yak.BMC genomics · 2024Article
- The size and composition of haplotype reference panels impact the accuracy of imputation from low-pass sequencing in cattle.Genetics, selection, evolution : GSE · 2023Article
- Assessing single-nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle.Journal of animal science · 2021Article
- Genotype Imputation to Improve the Cost-Efficiency of Genomic Selection in Rabbits.Animals : an open access journal from MDPI · 2021Article
- SNP-based heritability and genetic architecture of cranial cruciate ligament rupture in Labrador Retrievers.Animal genetics · 2020Article
- Article
- Animal-ImputeDB: a comprehensive database with multiple animal reference panels for genotype imputation.Nucleic acids research · 2020Article
- Development of a low-density panel for genomic selection of pigs in Russia.Translational animal science · 2020Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of the present study was to quantify the accuracy of imputing medium-density single nucleotide polymorphism (SNP) genotypes from lower-density panels (384 to 12,000 SNPs) derived using alternative selection methods to select the most informative SNPs. Four different selection methods were used to select SNPs based on genomic characteristics (i.e., minor allele frequency (MAF) and linkage disequilibrium (LD)) within five sheep breeds (642 Belclare, 645 Charollais, 715 Suffolk, 440 Texel, and 620 Vendeen) separately. Selection methods evaluated included (i) random, (ii) splitting the genome into blocks of equal length and selecting SNPs within block based on MAF and LD patterns, (iii) equidistant location while optimizing MAF, (iv) a combination of MAF, distance from already selected SNPs, and weak LD with the SNP(s) already selected. All animals were genotyped on the Illumina OvineSNP50 Beadchip containing 51,135 SNPs of which 44,040 remained after edits. Within each breed separately, the youngest 100 animals were assumed to represent the validation population; the remaining animals represented the reference population. Imputation was undertaken under three different conditions: (i) SNPs were selected within a given breed and imputed for all breeds individually, (ii) all breeds were collectively used to select SNPs and were included as the reference population, and (iii) the SNPs were selected for each breed separately and imputation was undertaken for all breeds but excluding from the reference population, the breed from which the SNPs were selected. Regardless of SNP selection method, mean animal allele concordance rate improved at a diminishing rate while the variability in mean animal allele concordance rate reduced as the panel density increased. The SNP selection method impacted the accuracy of imputation although the effect reduced as the density of the panel increased. Overall, the most accurate SNP selection method for panels with <9,000 SNPs was that based on MAF and LD pattern within genomic blocks. The mean animal allele concordance rate varied from 0.89 in Texel to 0.97 in Vendeen. Greater imputation accuracy was achieved when SNPs were selected and imputed within each breed individually compared with when SNPs were selected across all breeds and imputed using a multi-breed reference population. In all, results indicate that accurate genotype imputation to medium density is achievable with low-density genotype panels with at least 6,000 SNPs.
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