Genome-wide association study (GWAS) analyses have identified numerous loci associated with economic traits in cattle. Many of these loci reside in noncoding regions, and the regulatory mechanisms through which they influence complex traits remain poorly understood. Here, we integrated 657 RNA-seq libraries from 275 Huaxi cattle across three tissues (longissimus dorsi muscle, liver, and subcutaneous backfat) with ∼ 10 million imputed SNP genotypes to systematically map cis-molecular quantitative trait loci (cis-molQTLs) across four transcriptomic regulatory layers: gene expression (eQTLs), splicing (sQTLs), alternative polyadenylation (aQTLs), and RNA editing (edQTLs). These cis-molQTL classes display distinct genomic distributions and functional enrichments, yet operate in a coordinated manner within complex trait regulatory networks and are significantly enriched near GWAS- and QTLdb-reported loci for growth, carcass, and meat quality traits. Using 1788 genotyped and phenotyped Huaxi cattle, a GREML framework showed that these multi-layer cis-molQTL SNPs collectively explain 61.9% of total SNP-based heritability across 19 complex traits. Incorporating cis-molQTL annotations into genomic prediction models, including MultiBLUP, BayesRC, and molGBLUP, improved prediction accuracy for most traits relative to the baseline GBLUP model (mean increase of 0.05), highlighting the value of multi-layer regulatory variation for functionally informed genomic prediction and precision breeding.
Shiyuan Qiu, Lili Du, Bo-Yu Zhang et al.· Genomics, Proteomics & Bioin...· 0 citations
The genetic dissection of complex traits in livestock continues to pose a significant challenge in the field of animal genetics and breeding. Although traditional genome-wide association studies (GWAS) are capable of localizing genetic variants associated with specific traits, they are insufficient to elucidate the underlying physiological mechanisms. An integrated analysis of multi-trait GWAS and multi-transcriptomic data systematically identifies key tissues and cell types influencing complex traits in beef cattle and elucidates their genetic regulatory basis. We systematically mapped tissue- and cell-type-specific regulatory architectures underlying 20 economically important traits in beef cattle. Tissue-level analyses revealed distinct trait-tissue associations: fatty acid traits, including C16:0 and C20:4, were enriched in liver; carcass traits, including marbling score and carcass weight, in renal cortex/medulla and longissimus dorsi muscle; meat-quality traits such as pH in cartilaginous tissues; and total fat content in bone marrow. At cellular resolution, analysis of eight trait-associated tissues identified 38 discrete cell types. Myofibers were significantly associated with most carcass traits, including rib-eye area and backfat thickness, whereas hepatocytes emerged as key regulators of fatty acid and meat-quality traits, such as C16:0 and crude protein content. Transcription factor analysis identified cell-type-specific regulators: TBX15, SOX6, and TCF12 in myofibers; FOXA2 and NR1H4 in hepatocytes; and IRF8 and IKZF1 in microglia. Notably, hepatocytes and microglia showed complementary, trait-specific association patterns: hepatocytes were enriched for C16:0 associated saturated fatty-acid metabolic pathways, while microglia were enriched for C16:1 and unsaturated fatty-acid–related pathways, suggesting potential cross-tissue coordination in lipid regulation. Our study links specific tissues and cell types to phenotypic variation in beef cattle and identifies core transcriptional regulators and pathways driving trait variation. These cell-resolved maps provide mechanistic insight into how genetic variation shapes economically important traits, offering a valuable resource for functional studies, cell-informed precision breeding strategies, and the design of large-scale molecular phenotyping.
Boyu Zhang, Shiyuan Qiu, Zhenwei Du et al.· Journal of Animal Science an...· 0 citations
The functions of noncoding variants associated with complex traits in livestock remain poorly understood. In this study, we investigated two candidate noncoding variants within the XKR4-CHCHD7 locus identified from our previous analysis. Dual-luciferase reporter assays demonstrated allele-specific regulatory activity of these two regions in bovine muscle satellite cells (BMSCs), 293T cells, and C2C12 cells. Endogenous deletion of the candidate regions using a clustered regularly interspaced short palindromic repeats (CRISPR)-based high-fidelity Cas12Max (hfCas12Max) system revealed that the region containing chr14:22840845 (SNP-0845) exerted broader effects on BMSC function including reduced proliferation and migration, altered cell-cycle progression, and enhanced myogenic differentiation. Expression screening of candidate effector genes further identified PENK and TMEM68 as downstream candidate genes for SNP-0845. Rescue experiments further showed that PENK exerted stronger recovery effects than TMEM68 on the proliferation and migration defects caused by deletion of this region, supporting PENK as a major candidate effector downstream of the SNP-0845. Functional assays showed that PENK knockdown impaired BMSC proliferation and migration while promoting myogenic differentiation, whereas PENK overexpression partially reversed these effects. In vivo Penk knockdown reduced quadriceps femoris weight and altered muscle fiber composition in mice. Collectively, our findings suggest that a noncoding regulatory region modulates BMSC fate and muscle growth-related processes through PENK.
Tianyi Wu, Feng Liu, Qunhao Niu et al.· International Journal of Mol...· 0 citations
