Cattle internal organs as accessible raw materials have a long history of being widely used in beef processing, feed and pharmaceutical industry. These traits not only are of economic interest to breeders, but they are intrinsically linked to many valuable traits, such as growth, health, and productivity. Using the Illumina Bovine HD 770K SNP array, we performed a genome-wide association study for heart weight, liver weight, spleen weight, lung weight, and kidney weight in 1,217 Simmental cattle. In our research, 38 significant single nucleotide polymorphisms (SNPs) ( P < 1.49 × 10⁻⁶) were identified for five internal organ weight traits. These SNPs are within or near 13 genes, and some of them have been reported previously, including NDUFAF4, LCORL, BT.94996, SLIT2, FAM184B, LAP3, BBS12, MECOM, CD300LF, HSD17B3, TLR4, MXI1, and MB21D2. In addition, we detected four haplotype blocks on BTA6 containing 18 significant SNPs associated with spleen weight. Our results offer worthy insights into understanding the genetic mechanisms of internal organs' development, with potential application in breeding programs of Simmental beef cattle.

Growth traits are crucial for the economic viability in broiler production, as they significantly contribute to the cost of rearing. Maximizing body weight (BW) while minimizing feed intake is key to enhancing the efficiency of broiler breeding. Identifying the genetic architecture associated with BW trait is therefore a critical step in enhancing breeding strategies. We conducted a genome-wide association study (GWAS) using two statistical approaches: single-trait GWAS and longitudinal GWAS. The study was performed on the BW trait at five developmental stages (72, 81, 89, 113, and 120 days) and mid-test metabolic weight (MWT) across four growth cycles. Transcriptome sequencing analysis was also included to investigate the differential expression of candidate genes identified through the GWAS models, particularly linked to BW and MWT traits. Utilizing the chicken 55K single nucleotide polymorphism (SNP) array, we identified 52,060 SNPs in the genomic data of 4,493 Wenchang chickens. The single-trait GWAS model revealed 42 BW-associated SNPs, corresponding to 18 potential genes. For MWT, 47 SNPs were associated, mapping to 31 candidate genes. The longitudinal GWAS model identified 34 BW-linked SNPs, annotated with 22 candidate genes, and 21 MWT-linked SNPs, annotated with 10 candidate genes. Notably, 16 SNPs on chromosome 4 were associated with both BW and MWT, located within the 73.08Mb-76.82Mb region. Nine genes were annotated from this region, including STIM2, SEL1L3, SEPSECS, LGI2, SOD3, KCNIP4, NCAPG, FAM184B, LDB2. Notably, there are 32 overlapping SNPs identified in both the single-trait and longitudinal GWAS models, suggesting consistent associations for both BW and MWT. These overlapping SNPs represent robust loci that may influence both traits across different statistical approaches. Transcriptome sequencing indicated differential expression of LDB2 and SEL1L3 between high and low BW groups. Our study has uncovered novel candidate genes that are potentially involved in growth traits, providing valuable insights for broiler breeding. The identified SNPs and genes could serve as genetic markers for selecting broilers with improved growth efficiency, which may lead to more cost-effective and productive broiler farming.

Broilers are a globally significant resource for food production, and their relative growth rate (RGR) has attracted increasing attention for improving broiler monitoring, feed management and feed conversion. The main objectives of this study were to identify key candidate genes affecting the RGR in white-feathered broiler by integrating genomic and transcriptomic datasets. This study reports a meta-analysis of genome-wide association studies (GWAS) using 3 purebred lines (n = 3,727) and 5,841,467 input SNPs to understand the genetic control of the RGR. A total of 101 associated SNPs located on 6 chromosomes were identified, 16 of which were common in the GWAS and meta cohorts. Fine mapping of a significant peak with 7 linked SNP (r² > 0.94) located within the coding region of RAP2C revealed that chr4:3474286 (C > G) among these SNPs was a highly putative causal variant (PIP = 19%) and explained 2.26% of the RGR variation. Further analyses indicated that the surface expression level of the RAP2C gene in the blood, macrophage, lung tissue, and cecum tissue of commercial broiler breed (Ross) was higher than in the corresponding tissues of other egg-laying hens and local breeds. In addition, there was a significant difference in the expression of the RAP2C gene between the high (H, n = 5) and low (L, n = 4) RGR groups. A total of 301 differentially expressed genes (DEGs) related to the RGR in white-feathered broiler were identified by transcriptome differential analysis between the H and L populations, among which NFKBIA, CSF1R and TLR2A were important hub genes. Furthermore, the candidate genes identified based on GWASs, meta-analysis and DEGs analysis were significantly enriched for gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in the growth cone, integrated-mediated signaling pathway, and MAPK signaling pathway. Overall, the RAP2C, NFKBIA, CSF1R and TLR2A genes are considered the most important candidate genes influencing RGR trait in white-feathered broiler. These findings provide valuable insights into the complex system that regulates broiler growth.

Heat stress (HS) poses a significant threat to poultry production, impairing growth, metabolism, and survival. This study investigates the transcriptomic responses of broiler heart and liver tissues to acute (2h, 38°C) and chronic (6h, 38°C) HS, revealing distinct and shared molecular adaptations. Differential gene expression (DEG) analysis identified more pronounced transcriptomic changes under chronic HS (heart: 2,503 DEGs; liver: 2,236 DEGs) compared to acute HS (heart: 1,217 DEGs; liver: 1,843 DEGs). Shared DEGs (1,193 genes) included heat shock proteins (HSP90AA1, HSPA4, HSPB8), antioxidants (GPX1), and structural regulators (CSRP3, MYOZ3), indicating conserved stress responses. Tissue-specific patterns emerged: the heart emphasized cytokine signaling and protein folding, while the liver exhibited metabolic suppression and cytoskeletal remodeling. Weighted gene co-expression network analysis (WGCNA) highlighted stress-duration-dependent modules, with liver modules linked to metabolism and heart modules to immune and redox regulation. Temporal clustering revealed dynamic expression shifts, with chronic HS enhancing protein chaperone activity and acute HS triggering rapid signaling adjustments. These findings elucidate key molecular mechanisms underlying HS adaptation, offering potential targets for improving poultry thermotolerance through nutritional or genetic strategies.