Browsing by Author "Reynolds EGM"

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    Fine mapping highlights ITGAL and MUS81 loss-of-function mutations modulating recessive impacts in dairy cattle
    (John Wiley and Sons Ltd on behalf of Stichting International Foundation for Animal Genetics, 2025-08-01) Duntsch L; Jivanji S; Lopdell T; Reynolds EGM; Williams L; Littlejohn MD
    We recently described several major-effect recessive loci impacting anatomical and lactation traits in dairy cattle. Two of these loci in particular presented multiple candidate causative variants, comprising tightly linked coding variants that could not be easily differentiated on a statistical or functional basis. Here, we re-examine the candidacy of these variants by leveraging a dataset of 1 million genotyped animals. Assessing lactation and bodyweight effects in conjunction with rare, recombined genotypes for the IL4R, KIAA0556, ITGAL, DPF2, and MUS81 candidates, we highlight ITGAL and MUS81 as the most likely causative genes for the two QTL. Recombinant homozygotes for these genes present larger, more significant effects than other candidates at the same loci, with both representing premature stop mutations anticipated to inactivate ITGAL and MUS81. We further examined homozygotes for the ITGAL mutation to better understand the range of phenotypes impacted. While outwardly normal, ITGAL mutants showed significant differences in the number and composition of circulating leukocytes, consistent with the role of ITGAL as a key mediator of leukocyte signalling, adhesion, and migration. These results demonstrate how near-perfectly linked candidate mutations can be differentiated given population-scale data, and highlight the ITGAL and MUS81 mutations as diagnostic targets to help manage the frequency of these variants.
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    Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci
    (BioMed Central Ltd, 2022-12) Reynolds EGM; Lopdell T; Wang Y; Tiplady KM; Harland CS; Johnson TJJ; Neeley C; Carnie K; Sherlock RG; Couldrey C; Davis SR; Harris BL; Spelman RJ; Garrick DJ; Littlejohn MD
    BACKGROUND: Deleterious recessive conditions have been primarily studied in the context of Mendelian diseases. Recently, several deleterious recessive mutations with large effects were discovered via non-additive genome-wide association studies (GWAS) of quantitative growth and developmental traits in cattle, which showed that quantitative traits can be used as proxies of genetic disorders when such traits are indicative of whole-animal health status. We reasoned that lactation traits in cattle might also reflect genetic disorders, given the increased energy demands of lactation and the substantial stresses imposed on the animal. In this study, we screened more than 124,000 cows for recessive effects based on lactation traits. RESULTS: We discovered five novel quantitative trait loci (QTL) that are associated with large recessive impacts on three milk yield traits, with these loci presenting missense variants in the DOCK8, IL4R, KIAA0556, and SLC25A4 genes or premature stop variants in the ITGAL, LRCH4, and RBM34 genes, as candidate causal mutations. For two milk composition traits, we identified several previously reported additive QTL that display small dominance effects. By contrasting results from milk yield and milk composition phenotypes, we note differing genetic architectures. Compared to milk composition phenotypes, milk yield phenotypes had lower heritabilities and were associated with fewer additive QTL but had a higher non-additive genetic variance and were associated with a higher proportion of loci exhibiting dominance. CONCLUSIONS: We identified large-effect recessive QTL which are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits, with yield phenotypes acting as a better proxy of underlying biological disorders through presentation of a larger number of major recessive impacts.