Variance explained by whole genome sequence variants in coding and regulatory genome annotations for six dairy traits

Area of Science:

• Genomics
• Quantitative Genetics
• Animal Breeding

Background:

• Whole genome sequencing (WGS) in cattle yields millions of sequence variants, posing a challenge to identify those influencing complex traits.
• Hypothesis: Variants in specific functional classes (splice sites, coding regions, DNA methylation, lncRNA) disproportionately explain trait variance.

Purpose of the Study:

• To test the hypothesis that certain functional variant classes explain more variance in complex traits than others.
• To identify which functional annotations are most effective for prioritizing sequence variants associated with complex traits in cattle.

Main Methods:

• Utilized two variance component approaches to analyze 28.3 million imputed WGS variants in 16,581 dairy cattle.
• Assessed variance explained by variants within specific functional classes (e.g., splice sites, coding regions, DNA methylation targets).

Main Results:

• Sequence variants in splice site regions and synonymous classes captured the highest proportion of variance, up to 50% across production and fertility traits.
• Variants in DNA methylation target sites also explained a significant proportion of variance.
• Splice site variants individually explained the largest proportion of variance per variant.

Conclusions:

• Functional annotations effectively filter WGS variants into more informative subsets for complex trait association studies.
• Variants in splice sites, protein-coding genes, regulatory regions, and DNA methylated regions are crucial for explaining variation in milk production and fertility.
• The significant variance explained by synonymous variants suggests potential functional roles or highlights challenges in variant annotation and imputation accuracy.