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An organism-wide ATAC-seq peak catalog for the bovine and its use to identify regulatory variants

    • 1Unit of Animal Genomics, GIGA-R and Faculty of Veterinary Medicine, University of Liège, 4000 Liège, Belgium;
    • 2Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand;
    • 3Clinical Department of Ruminant, University of Liège, 4000 Liège, Belgium;
    • 4Royal Veterinary College, Hatfield, Herts AL9 7TA, United Kingdom;
    • 5School of Veterinary Medicine, University College Dublin, Dublin 4, Ireland;
    • 6GIGA Genomics platform, GIGA Institute, University of Liège, 4000 Liège, Belgium
    • 7 A complete list of the GplusE Consortium authors appears at the end of this paper.
    • 8 Present address: Dairy Research and Innovation Centre, Scotland's Rural College, Barony Campus, Dumfries DG1 3NE, UK
Published September 26, 2023. Vol 33 Issue 10, pp. 1848-1864. https://doi.org/10.1101/gr.277947.123
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Abstract

We report the generation of an organism-wide catalog of 976,813 cis-acting regulatory elements for the bovine detected by the assay for transposase accessible chromatin using sequencing (ATAC-seq). We regroup these regulatory elements in 16 components by nonnegative matrix factorization. Correlation between the genome-wide density of peaks and transcription start sites, correlation between peak accessibility and expression of neighboring genes, and enrichment in transcription factor binding motifs support their regulatory potential. Using a previously established catalog of 12,736,643 variants, we show that the proportion of single-nucleotide polymorphisms mapping to ATAC-seq peaks is higher than expected and that this is owing to an approximately 1.3-fold higher mutation rate within peaks. Their site frequency spectrum indicates that variants in ATAC-seq peaks are subject to purifying selection. We generate eQTL data sets for liver and blood and show that variants that drive eQTL fall into liver- and blood-specific ATAC-seq peaks more often than expected by chance. We combine ATAC-seq and eQTL data to estimate that the proportion of regulatory variants mapping to ATAC-seq peaks is approximately one in three and that the proportion of variants mapping to ATAC-seq peaks that are regulatory is approximately one in 25. We discuss the implication of these findings on the utility of ATAC-seq information to improve the accuracy of genomic selection.

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