University of Limerick Institutional Repository

High imputation accuracy from informative low-to-medium density single nucleotide polymorphism genotypes is achievable in sheep

DSpace Repository

Show simple item record O'Brien, Aine C. Judge, Michelle M. Fair, Seán Berry, Donagh P. 2019-04-02T14:24:59Z 2019
dc.description peer-reviewed en_US
dc.description The full text of this article will not be available in ULIR until the embargo expires on the 05/02/2020
dc.description.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 en_US
dc.language.iso eng en_US
dc.publisher Oxford University Press en_US
dc.relation.ispartofseries Journal of Animal Science;
dc.rights This is a pre-copyedited, author-produced PDF of an article accepted for publication in [insert journal title] following peer review. The version of record High imputation accuracy from informative low-to-medium density single nucleotide polymorphism genotypes is achievable in sheep, 2019 Journal of Animal Science is available online at: en_US
dc.subject linkage disequilibrium en_US
dc.subject minor allele frequency en_US
dc.subject multi-breed en_US
dc.subject single nucleotide polymorphism selection en_US
dc.title High imputation accuracy from informative low-to-medium density single nucleotide polymorphism genotypes is achievable in sheep en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1093/jas/skz043 2020-02-05
dc.embargo.terms 2020-02-05 en_US
dc.rights.accessrights info:eu-repo/semantics/embargoedAccess en_US
dc.internal.rssid 2903629

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ULIR


My Account