Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues

Area of Science:

• Genomics and Bioinformatics
• Animal Genetics
• Epigenetics

Background:

• Identifying genetic variants affecting complex traits in dairy cows is crucial for predicting phenotypes.
• Functional genomic regions are poorly annotated in the bovine genome, hindering causal variant identification.
• Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a powerful method for genome-wide functional region identification.

Purpose of the Study:

• To identify and annotate functional genomic regions in the bovine genome using ChIP-seq.
• To investigate the relationship between functional regions, gene expression, and causal variants in dairy cattle.
• To develop a new strategy for identifying causal variants in cattle, particularly in the mammary gland.

Main Methods:

• Performed ChIP-seq for four histone modifications (H3K4Me1, H3K4Me3, H3K27ac, H3K27Me3) and CTCF in six bovine tissues.
• Generated 86 ChIP-seq samples, identifying millions of functional regions across the genome.
• Utilized Chromatin Hidden Markov Model (ChromHMM) to combine histone modifications and CTCF, annotating regions by comparing with gene activity.

Main Results:

• Identified millions of functional regions, with distinct patterns across different tissues, suggesting tissue-specific regulation.
• Demonstrated a correlation between ChIP peak read counts and nearby gene expression, supporting the cis-regulatory role of identified regions.
• Found that functional regions, especially those correlated with gene expression, were significantly enriched for putative causal variants.

Conclusions:

• This study provides a comprehensive ChIP-seq annotation resource for the bovine genome, including novel data from lactating mammary glands.
• The findings support the hypothesis that complex traits are regulated by variants that alter gene expression.
• Linking regulatory regions to expression and trait quantitative trait loci (QTL) offers a novel strategy for causal variant discovery in cattle.