Supplemental material for: Genome-wide association study and fine-mapping using imputed sequences to prioritize candidate genes for 30 complex traits in 50,309 Holstein bulls

Identifying causal genetic variants underlying economically important
traits in dairy cattle is essential for understanding their genetic basis
and optimizing breeding programs. The growing availability of sequenced
reference genomes and individuals with both phenotypic and genotypic data
notably enhances our ability to detect genetic associations and further
pinpoint causal effects. This comprehensive genome-wide association study
of dairy cattle utilized de-regressed breeding values as phenotypes and
analyzed 11,292,243 quality-controlled, imputed DNA sequence variants from
50,309 Holstein bulls. The number of bulls with available phenotypes
ranged from 23,121 to 50,309 across 30 complex traits categorized into
production and yield, type, and longevity and health. We performed GWAS
using our SLEMM-GWA approach, which accounts for the varying reliability
of de-regressed breeding values across individuals and demonstrates
computational efficiency for large sample sizes and sequence data. This
analysis identified 381 significant association peaks (P < 5E-8),
of which 126 represent novel findings. Subsequent Bayesian fine-mapping
provided statistical prioritization by assigning posterior conditional
inclusion probabilities to individual variants and genes, yielding a list
of credible candidate genes—an advancement over conventional GWAS
reporting of all proximal genes. This prioritization offered direct
statistical support for previously reported genes, and, more importantly,
identified credible candidate genes within the 126 newly discovered peaks,
including AOPEP, GC, E2F6, MGST1, VPS13B, ZNF652, ASPH, SFMBT1, and
MAPRE2. These findings enhance the understanding of the genetic
architecture of these complex dairy traits and provide valuable insights
for the refinement of genomic selection strategies and breeding programs
in Holstein cattle.