Journal article
Effect direction meta-analysis of GWAS identifies extreme, prevalent and shared pleiotropy in a large mammal
R Xiang, I van den Berg, IM MacLeod, HD Daetwyler, ME Goddard
Communications Biology | NATURE PUBLISHING GROUP | Published : 2020
Abstract
In genome-wide association studies (GWAS), variants showing consistent effect directions across populations are considered as true discoveries. We model this information in an Effect Direction MEta-analysis (EDME) to quantify pleiotropy using GWAS of 34 Cholesky-decorrelated traits in 44,000+ cattle with sequence variants. The effect-direction agreement between independent bull and cow datasets was used to quantify the false discovery rate by effect direction (FDRed) and the number of affected traits for prioritised variants. Variants with multi-trait p < 1e–6 affected 1∼22 traits with an average of 10 traits. EDME assigns pleiotropic variants to each trait which informs the biology behind c..
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Funding Acknowledgements
Australian Research Council's Discovery Projects (DP160101056) supported R.X. and M.E.G. DairyBio (a joint venture project between Agriculture Victoria and Dairy Australia) funded computing resources used in the analysis. I.B. was supported by the Center for Genomic Selection in Animals and Plants (GenSAP) funded by Innovation Fund Denmark (grant 0603-00519B). No funding bodies participated in the design of the study nor analysis, or interpretation of data nor in writing the manuscript. DataGene and CRV (www.crv4all-international.com/) provided access to data used in this study. We thank Gert Nieuwhof, Kon Konstantinov and Timothy P. Hancock (DataGene) and Chris Schrooten (CRV) for preparation and provision of data. We thank partners from the 1000-bull genome project for the data access. We thank Dr. Mekonnen Haile-Mariam for deriving the deregressed phenotypes from international MACE and Dr. Sunduimijid Bolormaa for sequence variant data imputation.