Putative causal variants are enriched in annotated functional regions from 6 bovine tissues

Genetic variants which affect complex traits (causal variants) are thought to be found in functional regions of the genome. Identifying causal variants would be useful for predicting complex traits in dairy cows, however functional regions are poorly annotated in the bovine genome. Functional regions can be identified on a genome-wide scale by assaying for post-translational modifications to histone proteins (histone modifications) and proteins interacting with the genome (eg transcription factors) using a method called Chromatin immunoprecipitation followed by sequencing (ChIP-seq). In this study ChIP-seq was performed to find functional regions in the bovine genome by assaying for 4 histone modifications (H3K4Me1, H3K4Me3, H3K27ac and H3K27Me3) and one transcription factor (CTCF) in 6 tissues (heart, kidney, liver, lung, mammary and spleen) from 2-3 lactating dairy cows. In total 86 ChIP-seq samples were generated, identifying millions of functional regions in the bovine genome. As seen in other studies, the functional regions identified were enriched for putative causal variants from a variety of datasets. Functional regions differed between tissues highlighting areas which might be particularly important to tissue-specific regulation. The read counts in ChIP peaks correlated with nearby gene expression, supporting the cis-regulatory role of these regions. Interestingly, regions which correlated with gene expression were particularly enriched for potential causal variants identifying a potential mechanism by which causal variants affect complex traits. Lastly, ChromHMM was used to annotate sections of the genome based on 7 reoccurring combinations of marks. Our work provides one of the largest ChIP-seq annotation resources in cattle including, for the first time, in the mammary gland of lactating cows. By linking regulatory regions to expression QTL and trait QTL we demonstrate a unique pathway of finding causal variants in cattle. This study is part of the FAANG project, promoting rapid prepublication of data to support the research community. These data are released under Fort Lauderdale principles, as confirmed in the Toronto Statement (Toronto International Data Release Workshop. Birney et al. 2009. Pre-publication data sharing. Nature 461:168-170). Any use of this dataset must abide by the FAANG data sharing principles. Data producers reserve the right to make the first publication of a global analysis of this data. If you are unsure if you are allowed to publish on this dataset, please contact the FAANG Data Coordination Centre and FAANG consortium (email [e-mail] and cc [e-mail]) to enquire. The full guidelines can be found at http://www.faang.org/data-share-principle.