Aug 2026· Journal of Animal Science and Biotechnology· Vol 17· 0 citations· 62 references
Medicine
TL;DR
The hepatic transcriptomic landscape of Nelore cattle is characterized and the multilayered genetic architecture of the liver that controls meat quality traits in beef cattle is characterized, supporting the use of integrative omics to guide functional genomic selection.
Abstract
The integration of multiple omics strategies represents a transformative paradigm in farm animal genetics and breeding. By capturing molecular complexity across biological layers, integrative omics offers new opportunities to reveal the regulatory mechanisms underlying economically important traits. Here, we characterize the hepatic transcriptomic landscape of Nelore cattle and its relationship with meat and carcass quality phenotypes. For that, we integrated gene expression data, co-expression networks, expression quantitative trait locus (eQTL) mapping, single-nucleotide polymorphism (SNP)–phenotype associations, chromatin accessibility, and transcription factor motif analyses using hepatic RNA-seq data from 90 animals and assay for transposase‑accessible chromatin using sequencing (ATAC-seq) data from two animals. Weighted gene co-expression network analysis (WGCNA) identified 10 gene modules associated with our phenotypes of interest, particularly the blue module (r = −0.4), which is linked to meat color and enriched in insulin and mTOR signaling pathways. eQTL mapping revealed 1,198 cis- and 39,227 trans-eQTLs (false discovery rate [FDR] < 0.05), including hotspots on chromosome 25. Notably, rs449155362 was found to regulate 848 genes, within them MLXIPL, a transcription factor involved in glucose and lipid metabolism. Phenotype–eQTL associations revealed 54 SNPs (FDR < 0.05) related to meat and carcass traits, among which rs110069409, within an open chromatin region, modulates PLA2G2D1 expression and was associated with meat color (yellowness 24 h after the slaughter—b*₀), representing a convergence point across regulatory layers. These findings provide novel insights into the multilayered genetic architecture of the liver that controls meat quality traits in beef cattle, supporting the use of integrative omics to guide functional genomic selection.
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
Feed efficiency (FE) is a complex trait which determines livestock production profitability, yet the molecular mechanisms behind it remain unclear. This study investigated the blood transcriptomic profile of lambs, alongside genotype data with the aim to uncover the genetic basis of FE traits such as absolute dry matter intake (DMI
absolute
), DMI adjusted for body size (DMI
adjusted
), average daily live weight gain (ADG), and residual feed intake (RFI).
Bulk RNA-Seq and genotype data were analysed using three complementary approaches: differential gene expression (DGE) analysis, weighted gene co-expression network analysis (WGCNA), and cis-expression Quantitative Trait Loci (cis-eQTL) mapping. These methods were used independently to identify genes and regulatory networks associated with FE traits and to investigate evidence supporting multi-trait candidate gene selection.
DGE analysis revealed 2, 24, 85 and 4 differentially expressed genes for DMI
absolute
, DMI
adjusted
, ADG, and RFI (
P
adjusted
< 0.05), functionally enriched in sensory perception, ATP-dependent chromatin remodeling, Notch signaling and immune response pathways. 9 gene modules significantly associated with the FE traits (
P
≤ 0.05) with correlations ranging from
r
= -0.56 to 0.49, were identified using WGCNA. Single nucleotide polymorphism (SNP)-level cis-eQTL analysis identified 93 eSNPs associated with 74 genes (false discovery rate (FDR) < 0.05), while permutation-derived gene level analysis identified 280 eGenes (FDR < 0.2, empirical
P
< 0.03). Across the three analyses, applying thresholds of DGE (
P
adjusted
< 0.05), WGCNA (correlation,
P
≤ 0.05), and cis-eQTL gene-level significance (empirical
P
< 0.05), multiple overlapping genes were identified including
DNMT3A, KANSL1, NCOR1
for DMI
adjusted
,
ACOX2, FANCF, CIMIP2B, LOC101115106, ARMH2, LOC132657496
for ADG, and
LOC114114576
for RFI representing regulators of variations in FE.
The integration of DGE, WGCNA, and cis-eQTL analyses identified key genes and regulatory mechanisms associated with variation in FE traits. These results highlight that integrated multi-trait candidate gene identification approaches can reveal key genes that lower feed intake while maintaining animal growth, supporting breeding strategies aimed at improving efficiency and long-term economic sustainability in sheep.
S. C. Chacko Kaitholil, Mark H. Mooney, O. Cristóbal-Carballo et al.· Frontiers in Genetics· 0 citations
Structural variations (SVs) represent a significant source of genomic diversity, with demonstrated roles in livestock gene expression and traits. However, a comprehensive understanding of the SV landscape across large sample sets and its impact on gene regulation in cattle remains incomplete. This study aimed to construct high-fidelity pangenome graphs by integrating both assembly-based and whole-genome sequencing (WGS) derived SV catalogs. We evaluated the efficacy of pangenome graphs for SV genotyping and identified 80,328 high-quality SVs from a cohort of 2929 samples. We systematically characterized these SVs, including their linkage disequilibrium with single nucleotide polymorphisms (SNPs), functional annotations, formation mechanisms, and genomic distributions. Furthermore, we generated paired WGS (24.4 ×) and blood RNA-seq data in 170 Simmental cattle. Utilizing our pangenome graphs, we identified 637 SV-expression quantitative trait loci (SV-eQTL), which accounted for 10.81% of expression heritability of target genes, with 38.09% of the effects linked to promoter/enhancer regions. Forty-six of these SV-eQTL were replicated using CattleGTEx results through SV imputation using a joint SNP-SV reference panel. Notably, insertions in the GHSR gene were significantly associated with its expression levels, likely linked to Bos indicus cattle adaptation to heat tolerance. Our findings provide novel insights into the SV landscape and its contribution to gene regulation, underscoring its importance in cattle genetics and genomics.
Large-scale genomic resources enable systematic investigation of genetic variation and tissue-specific expression of immune-related pathways in livestock species. Here, we integrated population-level whole-genome sequence data with tissue-specific transcriptional profiling to characterize genomic differentiation and expression patterns of NF-κB pathway-related genes in cattle. Using whole-genome sequence data from the 1000 Bull Genomes Project, we identified prioritized differentiated variants within several NF-κB pathway–related genes, including CD14, NF-κB1, IL-1β, and BAFFR. The mRNA expression levels of selected NF-κB signaling-related genes were quantified across four tissues with relevance to host defense and metabolism in bulls and cows of both breeds. Expression analyses revealed pronounced tissue-dependent regulation, with distinct organ-specific transcriptional patterns across the investigated genes. Intestinal tissues showed lower expression of several innate immune genes, whereas CD14 expression was more prominent in liver-associated comparisons, highlighting functional tissue specialization within the NF-κB signaling network. Breed- and sex-associated effects were gene-dependent rather than uniform across the pathway. Histological assessment of the spleen was performed to provide an anatomical context for observed transcriptional variations. A population-prioritized CD14 missense variant (Asn177Asp), identified from the 1000 Bull Genomes dataset, was contextualized using in silico structural annotation to provide structural context for coding variation. These findings provide descriptive evidence that population-level genomic differentiation in selected NF-κB pathway genes is accompanied by tissue-specific transcriptional differences in cattle.
Mohammed Saeed-Zidane, I. Blaj, A. Yousif et al.· BMC Genomics· 0 citations
Adipose deposition is genetically regulated and acts as a core determinant of meat quality in livestock. Therefore, exploring the gene regulatory mechanisms underlying adipose deposition is essential to advance the research on adipose tissue development and molecular breeding in livestock. To clarify the molecular basis of the superior meat quality of Pinan (PN) cattle, high-throughput RNA sequencing was performed to screen the key genes regulating adipose deposition in PN, with Nanyang (NY) cattle serving as the control (n = 3 per breed). A total of 265 differentially expressed genes (DEGs) were identified in the adipose tissue of PN cattle relative to NY cattle, comprising 135 upregulated and 130 downregulated genes. GO and KEGG enrichment analysis revealed that these DEGs were primarily enriched in lipid binding-related functional categories, particularly lipid antigen binding and exogenous lipid antigen binding, as well as enzymatic functions such as protein xylosyltransferase activity. Meanwhile, RT-qPCR confirmed significant differential expression of WNT16, IGFBP2, PEMT, ADCY5, and IDH3B in adipose tissue between PN and NY cattle, consistent with the RNA-seq data. Moreover, functional validation experiments, including RT-qPCR, CCK-8, EdU, and Oil Red O staining, revealed that RNA interference (RNAi)-mediated ADCY5 knockdown markedly promoted adipocyte proliferation, while significantly inhibiting adipocyte differentiation and lipid droplet formation. Collectively, the present study indicates that the identified DEGs are potentially involved in the regulation of bovine adipose tissue development. Notably, ADCY5 exhibits a crucial regulatory effect on cattle adipose deposition; however, the precise molecular mechanism remains to be further elucidated in future studies.
Xue-Feng Wei, Xi Shan, Li-Ze Yang et al.· Animal Genetics· 0 citations
Lactation performance is a pivotal economic trait in sheep production, yet its underlying epigenetic regulatory mechanisms remain poorly understood. In the present study, we integrated ATAC-seq and RNA-seq to compare chromatin accessibility landscapes and transcriptomic in mammary gland tissues from Sewa sheep (SWS) and East Friesian sheep (EFS). Histological characterization revealed that SWS exhibited significantly smaller mammary acini area, smaller lipid droplet area, and reduced lipid droplet diameter compared to EFS. ATAC-seq analysis identified 15,902 differentially accessible regions (DARs) between the two breeds, with motif enrichment analysis uncovering key transcription factors potentially governing lactation traits. RNA-seq analysis revealed 1163 differentially expressed genes (DEGs), which were involved in lactation regulation. Integrated analysis identified 441 overlapping genes, and enriched in glycolysis/gluconeogenesis (e.g., PGAM1, ENO1) and pyruvate metabolism (e.g., ACACA, ACSS1, ACYP1). Collectively, our study provides new insights into the epigenetic regulatory mechanisms underlying lactation performance differences in sheep.