Allele-specific expression reveals functional SNPs affecting muscle-related genes in bovine

Single nucleotide polymorphisms showing allele-specific expression (ASE SNPs) are useful for cis-regulatory variants discovery. Despite this potential, there are expensive costs involved in genome-level ASE analysis for large sample sizes. If different data resolutions are available, genotype imputation can be used to mitigate this limitation. Aiming to increase the power to detect regulatory variants, we used a large dataset (>4 million) of imputed SNP genotypes and RNA-Seq data from 190 Nelore steers. Differences between major and minor allele expressions in muscle were tested with a Binomial Test. We identified 38,177 ASE SNPs (FDR <= 0.05) within 7304 linkage disequilibrium blocks. After that, we searched for aseQTLs (i.e., neighboring SNPs potentially regulating the ASE SNPs' allelic expression) by comparing the ASE of heterozygous to homozygous sample groups under a Wilcoxon Rank Sum test. We identified 21,543 aseQTLs potentially regulating 430 ASE SNPs (FDR <= 0.05). A total of 3333 cis-eQTLs (being 2098 ASE SNPs and 1075 aseQTLs) were associated with the expression of 758 transcripts (FDR <= 0.05), demonstrating the cis-regulatory effect of these ASE SNPs and aseQTLs. Data integration showed reproducibility with previous studies in bovine ASE and genomic imprinting. Furthermore, we identified 36,756 novel ASE regions due to the imputation approach. Comparisons with epigenetics data from Functional Annotation of Animal Genomes (FAANG) suggest a regulatory potential of the ASE-related SNPs. The affected genes were enriched in metabolic pathways essential for muscle homeostasis. These findings reinforce the potential of using ASE for discovering cis-regulatory SNPs that may affect muscle-related traits.

Automated summary

This study utilized a large dataset of imputed SNP genotypes and RNA-Seq data from Nelore steers to identify ASE SNPs and aseQTLs in muscle, demonstrating the cis-regulatory effect of these variants and discovering numerous novel ASE regions. These findings highlight the potential of using ASE to uncover cis-regulatory SNPs affecting muscle-related traits.