ArticleBMC genomics2014
Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 2 of them syntheses that pooled it.
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Who cites it
64 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Genome-wide association analysis using multiple Atlantic salmon populations.Genetics, selection, evolution : GSE · 2025Pooled it
- RAPID COMMUNICATION: Multi-breed validation study unraveled genomic regions associated with puberty traits segregating across tropically adapted breeds1.Journal of animal science · 2019Pooled it
- Resolving Cattle GWAS Loci: Current Progress, Persistent Challenges and Future Directions.Current issues in molecular biology · 2026Review
- Effects of the Temperature-Humidity Index on Milk Production Traits and Gene-Environment Interactions in Chinese Holstein Cows.Animals : an open access journal from MDPI · 2026Article
- Genomic insights into female productivity in limousine cattle: a single-step genome-wide association on longevity, fertility, and conformation traits.BMC genomics · 2026Article
- Association of single nucleotide polymorphisms in the entire coding region of the SOCS2 gene with milk traits in Sahiwal cattle.Tropical animal health and production · 2025Article
- Using genotype imputation to integrate Canola populations for genome-wide association and genomic prediction of blackleg resistance.BMC genomics · 2025Article
- Genomic analysis reveals genetic diversity and selection signatures of the Yantai Black pig during domestication and breeding.Frontiers in genetics · 2025Article
- Multi-omics integration identifies regulatory factors underlying bovine subclinical mastitis.Journal of animal science and biotechnology · 2024Article
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- Genome-wide identification and annotation of SNPs for economically important traits in Frieswal™, newly evolved crossbred cattle of India.3 Biotech · 2023Article
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- Genome-wide identification and annotation of SNPs and their mapping in candidate genes related to milk production and fertility traits in Badri cattle.Tropical animal health and production · 2023Article
- Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle.BMC genomics · 2022Article
- The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis.Animals : an open access journal from MDPI · 2022Article
- Functionally prioritised whole-genome sequence variants improve the accuracy of genomic prediction for heat tolerance.Genetics, selection, evolution : GSE · 2022Article
- Genome-wide association study identifies quantitative trait loci affecting cattle temperament.Zoological research · 2022Article
- The Role of microRNAs in the Mammary Gland Development, Health, and Function of Cattle, Goats, and Sheep.Non-coding RNA · 2021Review
- Article
4 more citing papers are in PubMed but not listed here.
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers.
resultsBy using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions.
conclusionWhere QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle.
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