Comparative gene expression profiling of muscle reveals potential candidate genes affecting drip loss in pork

Analysis of Transcriptome Differences Between Subcutaneous and Intramuscular Adipose Tissue of Tibetan Pigs

Background/Objectives: Fat deposition traits in pigs directly influence pork flavor, tenderness, and juiciness and are closely linked to overall pork quality. The Tibetan pig, an indigenous breed in China, not only possesses a high intramuscular fat content but also exhibits a unique fat metabolism pattern due to long-term adaptation to harsh environments. This makes it an excellent genetic and physiological model for investigating fat deposition characteristics. Adipose tissue from different body regions displays varying morphologies, cytokines, and adipokines. This study aimed to examine adipose tissue deposition characteristics in different parts of Tibetan pigs and provide additional data to explore the underlying mechanisms of differential fat deposition. Methods: Our research identified significant differences in the morphology and gene expression patterns between subcutaneous fat (abdominal fat [AF] and back fat [BF]) and intramuscular fat (IMF) in Tibetan pigs. Results: Histological observations revealed that subcutaneous fat cells were significantly larger in area and diameter compared to IMF cells. The transcriptomic analysis further identified differentially expressed genes (DEGs) between subcutaneous fat and IMF, with a total of 65 DEGs in BF vs. IMF and 347 DEGs in AF vs. IMF, including 25 DEGs common to both comparisons. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that these genes were significantly associated with lipid metabolism-related signaling pathways, such as the Wnt, mTOR, and PI3K-Akt signaling pathways. Several DEGs, including DDAH1, ADRA1B, SLCO3A1, and THBS3, may be linked to the differences in fat deposition in different parts of Tibetan pigs, thereby affecting meat quality and nutritional value. Conclusions: These findings provide new insights into the unique fat distribution and deposition characteristics of Tibetan pigs and establish a foundation for breeding strategies aimed at improving pork quality.

Comparative transcriptome analysis of longissimus dorsi muscle reveal potential genes affecting meat trait in Chinese indigenous Xiang pig

In this study, we compared the transcriptome of longissimus dorsi muscle between Guizhou Xiang pigs (XP) and Western commercial Large White pigs (LW), which show diffirent meat quality between them. In terms of meat quality traits, the pH 45 min, color score, backfat thickness, and intramuscular fat (IMF) content were higher in Xiang pigs than in Large White pigs (P < 0.01), while the drip loss, lean meat percentage, shear force, and longissimus dorsi muscle area of Xiang pigs were lower than that of Large White pigs (P < 0.01). Nutrients such as monounsaturated fatty acid (MUFA), total amino acids (TAA), delicious amino acids (DAA) and essential amino acids (EAA) in Xiang pigs were higher than that in Large White pigs, and the proportion of polyunsaturated fatty acid (PUFA) of Xiang pigs was significantly lower than Large White pigs (P < 0.01). Transcriptome analysis identified 163 up-regulated genes and 88 genes down-regulated in Xiang pigs longissimus dorsi muscle. Combined with the correlation analysis and quantitative trait locis (QTLs) affecting meat quality, a total of 227 DEGs were screened to be significantly associated with meat quality values. Enrichment analysis indicated that numerous members of genes were gathered in muscle development, adipogenesis, amino acid metabolism, fatty acid metabolism and synthesis. Of those, 29 genes were identified to be hub genes that might be related with the meat quality of Xiang pig, such as MYOD1, ACTB, ASNS, FOXO1, ARG2, SLC2A4, PLIN2, and SCD. Thus, we screened and identified the potential functional genes for the formation of meat quality in Xiang pigs, which provides a corresponding theoretical basis for the study of the molecular regulatory mechanism of pork quality and the improvement of pork quality.

Revelation of genetic diversity and genomic footprints of adaptation in Indian pig breeds

In the present study, the genetic diversity measures among four Indian domestic breeds of pig namely Agonda Goan, Ghurrah, Ghungroo, and Nicobari, of different agro-climatic regions of country were explored and compared with European commercial breeds, European wild boar and Chinese domestic breeds. The double digest restriction site-associated DNA sequencing (ddRADseq) data of Indian pigs (102) and Landrace (10 animals) were generated and whole genome sequencing data of exotic pigs (60 animals) from public data repository were used in the study. The principal component analysis (PCA), admixture analysis and phylogenetic analysis revealed that Indian breeds were closer in ancestry to Chinese breeds than European breeds. European breeds exhibited highest genetic diversity measures among all the considered breeds. Among Indian breeds, Agonda Goan and Ghurrah were found to be more genetically diverse than Nicobari and Ghungroo. The selection signature regions in Indian pigs were explored using iHS and XP-EHH, and during iHS analysis, it was observed that genes related to growth, reproduction, health, meat quality, sensory perception and behavior were found to be under selection pressure in Indian pig breeds. Strong selection signatures were recorded in 24.25-25.25 Mb region of SSC18, 123.25-124 Mb region of SSC15 and 118.75-119.5 Mb region of SSC2 in most of the Indian breeds upon pairwise comparison with European commercial breeds using XP-EHH. These regions were harboring some important genes such as EPHA4 for thermotolerance, TAS2R16, FEZF1, CADPS2 and PTPRZ1 for adaptability to scavenging system of rearing, TRIM36 and PGGT1B for disease resistance and CCDC112, PIAS1, FEM1B and ITGA11 for reproduction.

Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork

Low level of drip loss (DL) is an important quality characteristic of meat with high economic value. However, the key genes and regulatory networks contributing to DL in pork remain largely unknown. To accurately identify the key genes affecting DL in muscles postmortem, 12 Duroc × (Landrace × Yorkshire) pigs with extremely high (n = 6, H group) and low (n = 6, L group) DL at both 24 and 48 h postmortem were selected for transcriptome sequencing. The analysis of differentially expressed genes and weighted gene co-expression network analysis (WGCNA) were performed to find the overlapping genes using the transcriptome data, and functional enrichment and protein-protein interaction (PPI) network analysis were conducted using the overlapping genes. Moreover, we used machine learning to identify the key genes and regulatory networks related to DL based on the interactive genes of the PPI network. Finally, nine potential key genes (IRS1, ESR1, HSPA6, INSR, SPOP, MSTN, LGALS4, MYLK2, and FRMD4B) mainly associated with the MAPK signaling pathway, the insulin signaling pathway, and the calcium signaling pathway were identified, and a single-gene set enrichment analysis (GSEA) was performed to further annotate the functions of these potential key genes. The GSEA results showed that these genes are mainly related to ubiquitin-mediated proteolysis and oxidative reactions. Taken together, our results indicate that the potential key genes influencing DL are mainly related to insulin signaling mediated differences in glycolysis and ubiquitin-mediated changes in muscle structure and improve the understanding of gene expression and regulation related to DL and contribute to future molecular breeding for improving pork quality.

Identification of candidate genomic regions for egg yolk moisture content based on a genome-wide association study

BACKGROUND

Eggs represent important sources of protein and are widely loved by consumers. Egg yolk taste is an important index for egg selection, and the moisture content of the egg yolk affects the taste. To understand the molecular mechanism underlying egg yolk moisture content, this study determined the phenotype and heritability of egg yolk water content and conducted a genome-wide association study (GWAS) using a mixed linear model.

RESULTS

We determined the phenotype and heritability of thermogelled egg yolk water content (TWC) and found that the average TWC was 47.73%. Moreover, significant variations occurred (41.06-57.12%), and the heritability was 0.11, which indicates medium-low heritability. Through the GWAS, 48 single nucleotide polymorphisms (SNPs) related to TWC (20 significantly, 28 suggestively) were obtained, and they were mainly located on chromosomes 10 and 13. We identified 36 candidate genes based on gene function and found that they were mainly involved in regulating fat, protein, and water content and embryonic development. FGF9, PIAS1, FEM1B, NOX5, GLCE, VDAC1, IGFBP7, and THOC5 were involved in lipid formation and regulation; AP3S2, GNPDA1, HSPA4, AP1B1, CABP7, EEF1D, SYTL3, PPP2CA, SKP1, and UBE2B were involved in protein folding and hydrolysis; and CSF2, SOWAHA, GDF9, FSTL4, RAPGEF6, PAQR5, and ZMAT5 were related to embryonic development and egg production. Moreover, MICU2, ITGA11, WDR76, BLM, ANPEP, TECRL, EWSR1, and P4HA2 were related to yolk quality, while ITGA11, WDR76, BLM, and ANPEP were potentially significantly involved in egg yolk water content and thus deserve further attention and research. In addition, this study identified a 19.31-19.92 Mb genome region on GGA10, and a linkage disequilibrium analysis identified strong correlations within this region. Thus, GGA10 may represent a candidate region for TWC traits.

CONCLUSION

The molecular genetic mechanism involved in TWC was revealed through heritability measurements and GWAS, which identified a series of SNPs, candidate genes, and candidate regions related to TWC. These results provide insights on the molecular mechanism of egg yolk moisture content and may aid in the development of new egg traits.

Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population

Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07-0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits.

Genome-Wide Association Study Based on Random Regression Model Reveals Candidate Genes Associated with Longitudinal Data in Chinese Simmental Beef Cattle

Simple Summary

Genome-wide association study (GWAS) has become the main approach for detecting functional genes that affects complex traits. For growth traits, the conventional GWAS method can only deal with the single-record traits observed at specific time points, rather than the longitudinal traits measured at multiple time points. Previous studies have reported the random regression model (RRM) for longitudinal data could overcome the limitation of the traditional GWAS model. Here, we present an association analysis based on RRM (GWAS-RRM) for 808 Chinese Simmental beef cattle at four stages of age. Ultimately, 37 significant single-nucleotide polymorphisms (SNPs) and several important candidate genes were screened to be associated with the body weight. Enrichment analysis showed these genes were significantly enriched in the signaling transduction pathway and lipid metabolism. This study not only offers a further understanding of the genetic basis for growth traits in beef cattle, but also provides a robust analytics tool for longitudinal traits in various species.

Abstract

Body weight (BW) is an important longitudinal trait that directly described the growth gain of bovine in production. However, previous genome-wide association study (GWAS) mainly focused on the single-record traits, with less attention paid to longitudinal traits. Compared with traditional GWAS models, the association studies based on the random regression model (GWAS-RRM) have better performance in the control of the false positive rate through considering time-stage effects. In this study, the BW trait data were collected from 808 Chinese Simmental beef cattle aged 0, 6, 12, and 18 months, then we performed a GWAS-RRM to fit the time-varied SNP effect. The results showed a total of 37 significant SNPs were associated with BW. Gene functional annotation and enrichment analysis indicated FGF4, ANGPT4, PLA2G4A, and ITGA5 were promising candidate genes for BW. Moreover, these genes were significantly enriched in the signaling transduction pathway and lipid metabolism. These findings will provide prior molecular information for bovine gene-based selection, as well as facilitate the extensive application of GWAS-RRM in domestic animals.

Transcriptome profiling analysis of muscle tissue reveals potential candidate genes affecting water holding capacity in Chinese Simmental beef cattle

Water holding capacity (WHC) is an important sensory attribute that greatly influences meat quality. However, the molecular mechanism that regulates the beef WHC remains to be elucidated. In this study, the longissimus dorsi (LD) muscles of 49 Chinese Simmental beef cattle were measured for meat quality traits and subjected to RNA sequencing. WHC had significant correlation with 35 kg water loss (r = − 0.99, p < 0.01) and IMF content (r = 0.31, p < 0.05), but not with SF (r = − 0.20, p = 0.18) and pH (r = 0.11, p = 0.44). Eight individuals with the highest WHC (H-WHC) and the lowest WHC (L-WHC) were selected for transcriptome analysis. A total of 865 genes were identified as differentially expressed genes (DEGs) between two groups, of which 633 genes were up-regulated and 232 genes were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that DEGs were significantly enriched in 15 GO terms and 96 pathways. Additionally, based on protein–protein interaction (PPI) network, animal QTL database (QTLdb), and relevant literature, the study not only confirmed seven genes (HSPA12A, HSPA13, PPARγ, MYL2, MYPN, TPI, and ATP2A1) influenced WHC in accordance with previous studies, but also identified ATP2B4, ACTN1, ITGAV, TGFBR1, THBS1, and TEK as the most promising novel candidate genes affecting the WHC. These findings could offer important insight for exploring the molecular mechanism underlying the WHC trait and facilitate the improvement of beef quality.

Identification of genes related to intramuscular fat independent of backfat thickness in Duroc pigs using single-step genome-wide association

Intramuscular fat (IMF) is an important meat-quality trait of pigs, which influences pork's shearing force, hydraulics, tenderness and juicy flavor. However, to achieve a higher percentage of lean meat, pigs with lower backfat thickness (BF) are intensively selected for, which may lead to a reduction in pork quality. Therefore, the objective of this study was to locate loci that affect IMF without changing BF. A single-step GWAS was performed on 950 Duroc pigs genotyped by a 50K SNP chip in order to detect genomic variants relevant to IMF and BF. The significant SNPs detected were afterwards divided into a BF subset (seven SNPs), an IMF subset (11 SNPs) and a subset of both traits (12 SNPs), according to their P-value and LD. After SNP and QTL annotation, our results indicated that SSC1: 167938652, 166363826, 164829874 and 167171587 might be associated with IMF without changing BF. In the subset of both traits, we found that the combined effect of ALGA0006602 (SSC1: 159538854) and 12784636 (SSC1: 160773437) might improve the IMF without changing BF. Our gene annotation result showed that TLE3, ITGA11, SMAD6, PAQR5 and [RNF152^A/G × MC4R^A/A ] genes might affect IMF independently of BF. We believe that the SNPs and genes identified in this study will be valuable for the future molecular breeding of IMF in Duroc pigs.