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Genome-wide fine-mapping identifies pleiotropic and functional variants that predict many traits across global cattle populations.

Ruidong XiangIona M MacLeodHans D DaetwylerGerben de JongErin O'ConnorChris SchrootenAmanda J ChamberlainMichael E Goddard
Published in: Nature communications (2021)
The difficulty in finding causative mutations has hampered their use in genomic prediction. Here, we present a methodology to fine-map potentially causal variants genome-wide by integrating the functional, evolutionary and pleiotropic information of variants using GWAS, variant clustering and Bayesian mixture models. Our analysis of 17 million sequence variants in 44,000+ Australian dairy cattle for 34 traits suggests, on average, one pleiotropic QTL existing in each 50 kb chromosome-segment. We selected a set of 80k variants representing potentially causal variants within each chromosome segment to develop a bovine XT-50K genotyping array. The custom array contains many pleiotropic variants with biological functions, including splicing QTLs and variants at conserved sites across 100 vertebrate species. This biology-informed custom array outperformed the standard array in predicting genetic value of multiple traits across populations in independent datasets of 90,000+ dairy cattle from the USA, Australia and New Zealand.
Keyphrases
  • copy number
  • genome wide
  • dna methylation
  • high resolution
  • high throughput
  • high density
  • air pollution
  • gene expression
  • transcription factor
  • healthcare
  • mass spectrometry
  • single cell
  • rna seq
  • health information