Genetic Structure and Genome-Wide Association Analysis of Growth and Reproductive Traits in Fengjing Pigs

The Fengjing pig is one of the local pig breed resources in China and has many excellent germplasm characteristics. However, research on its genome is lacking. To explore the degree of genetic diversity of the Fengjing pig and to deeply explore its excellent traits, this study took Fengjing pigs as the research object and used the Beadchip Array Infinium iSelect-96|XT KPS_PorcineBreedingChipV2 for genotyping. We analyzed the genetic diversity, relatedness, inbreeding coefficient, and population structure within the Fengjing pig population. Our findings revealed that the proportion of polymorphic markers (PN) was 0.469, and the effective population size was 6.8. The observed and expected heterozygosity were 0.301 and 0.287, respectively. The G-matrix results indicated moderate relatedness within the population, with certain individuals exhibiting closer genetic relationships. The NJ evolutionary tree classified Fengjing boars into five family lines. The average inbreeding coefficient based on ROH was 0.318, indicating a high level of inbreeding. GWAS identified twenty SNPs significantly associated with growth traits (WW, 2W, and 4W) and reproductive traits (TNB and AWB). Notably, WNT8B, RAD21, and HAO1 emerged as candidate genes influencing 2W, 4W, and TNB, respectively. Genes such as WNT8B were verified by querying the PigBiobank database. In conclusion, this study provides a foundational reference for the conservation and utilization of Fengjing pig germplasm resources and offers insights for future molecular breeding efforts in Fengjing pigs.

Genome-Wide Association Study and FST Analysis Reveal Four Quantitative Trait Loci and Six Candidate Genes for Meat Color in Pigs

Meat color is the primary criterion by which consumers evaluate meat quality. However, there are a few candidate genes and molecular markers of meat color that were reported for pig molecular breeding. The purpose of the present study is to identify the candidate genes affecting meat color and provide the theoretical basis for meat color molecular breeding. A total of 306 Suhuai pigs were slaughtered, and meat color was evaluated at 45 min and 24 h after slaughter by CIELAB color space. All individuals were genotyped using GeneSeek GGP-Porcine 80K SNP BeadChip. The genomic estimated breeding values (GEBVs), heritability, and genetic correlation of meat color were calculated by DMU software. The genome-wide association studies (GWASs) and the fixation index (F_ST) tests were performed to identify SNPs related to meat color, and the candidate genes within 1 Mb upstream and downstream of significant SNPs were screened by functional enrichment analysis. The heritability of L* 45 min, L* 24 h, a* 45 min, a* 24 h, b* 45 min, and b* 24 h was 0.20, 0.16, 0.30, 0.13, 0.29, and 0.22, respectively. The genetic correlation between a* (a* 45 min and a* 24 h) and L* (L* 45 min and L* 24 h) is strong, whereas the genetic correlation between b* 45 min and b* 24 h is weak. Forty-nine significant SNPs associated with meat color were identified through GWAS and F_ST tests. Among these SNPs, 34 SNPs were associated with L* 45 min within a 5-Mb region on Sus scrofa chromosome 11 (SSC11); 22 SNPs were associated with a* 45 min within a 14.72-Mb region on SSC16; six SNPs were associated with b* 45 min within a 4.22-Mb region on SSC13; 11 SNPs were associated with b* 24 h within a 2.12-Mb region on SSC3. These regions did not overlap with meat color–associated QTLs reported previously. Moreover, six candidate genes (HOMER1, PIK3CG, PIK3CA, VCAN, FABP3, and FKBP1B), functionally related to muscle development, phosphatidylinositol phosphorylation, and lipid binding, were detected around these significant SNPs. Taken together, our results provide a set of potential molecular markers for the genetic improvement of meat color in pigs.

Single-cell RNA sequencing reveals the induction of novel myeloid and myeloid-associated cell populations in visceral fat with long-term obesity

Macrophages and other immune cells are important contributors to obesity-associated inflammation; however, the cellular identities of these specific populations remain unknown. In this study, we identified individual populations of myeloid cells found in mouse epididymal/visceral adipose tissue by single-cell RNA sequencing, immunofluorescence, and flow cytometry. Multiple canonical correlation analysis identified 11 unique myeloid and myeloid-associate cell populations. In obese mice, we detected an increased percentage of monocyte-derived pro-inflammatory cells expressing Cd9 and Trem2, as well as significantly decreased percentages of multiple cell populations, including tissue-resident cells expressing Lyve1, Mafb, and Mrc1. We have identified and validated a novel myeloid/macrophage population defined by Ly6a expression, exhibiting both myeloid and mesenchymal characteristics, which increased with obesity and showed high pro-fibrotic characteristics in vitro. Our mouse adipose tissue myeloid cell atlas provides an important resource to investigate obesity-associated inflammation and fibrosis.

Association of tissue inhibitor of metalloproteinase 2 with non-alcoholic fatty liver disease in metabolic syndrome

The aim of this case-control study was to assess TIMP2 level in subjects with or without metabolic syndrome (MetS) and to associate levels with non-alcoholic fatty liver changes (NAFLD). Thirty-three MetS subjects and 55 controls were recruited. Anthropometric data, lipid and glucose profile, TIMP2 and liver ultrasound was performed. High TIMP2 was seen in MetS group (145.28 ± 23.11 pg/ml) versus controls (19.06 ± 1.19 pg/ml; p < .001). Serum cholesterol, triglyceride, LDL-c and glucose levels were significantly higher in MetS subjects (p < .05). MetS individuals (72.72%) showed positive fatty liver changes versus 14.5% controls. Elevated TIMP2 positively correlated with waist circumference, body fat, blood glucose and NAFLD. Furthermore, every unit rise in waist circumference and TIMP2 and a unit decrease in HDL were associated with higher odds of developing NAFLD (p < .05). There may be concurrent relationship between TIMP2 and NAFLD in MetS that requires further evaluation to improve risk assessment and early diagnosis of MetS.

Deep transcriptome analysis using RNA-Seq suggests novel insights into molecular aspects of fat-tail metabolism in sheep

Fat-tail content of sheep breeds is varied and the molecular mechanisms regulating fat-tail development have not been well characterized. Aiming at better identifying the important candidate genes and their functional pathways contributing to fat deposition in the tail, a comparative transcriptome analysis was performed between fat- (Lori-Bakhtiari) and thin-tailed (Zel) Iranian sheep breeds using RNA-seq. The experiment was conducted on six male lambs (three lambs per each breed) at seven months of age. Four different combinations of aligners and statistical methods including Hisat2 + edgeR, Hisat2 + DESeq2, STAR + edgeR and STAR + DESeq2 were used to identify the differentially expressed genes (DEGs). The DEGs were selected for functional enrichment analysis and protein-protein interaction (PPI) network construction. Module analysis was also conducted to mine the functional sub-networks from the PPI network. In total, 264 genes including 80 up- and 184 down-regulated genes were identified as DEGs. The RNA-Seq results were validated by Q-RT-PCR. Functional analysis of DEGs and the module analysis of PPI network demonstrated that in addition to pathways affecting lipid metabolism, a series of enriched functional terms related to "response to interleukin", "MAPK signaling pathways", "Wnt signaling pathway", "ECM-receptor interaction", "regulation of actin cytoskeleton", and "response to cAMP" might contribute to the deposition of fat in tails of sheep. Overall results using RNA-Seq analysis characterized important candidate genes involved in the fatty acid metabolism and regulation of fat deposition, suggesting novel insights into molecular aspects of fat-tail metabolism in sheep. Selected DEGs should be further investigated as potential markers associated with the fat-tail development in sheep breeds.

The expression of CCN2, IQSEC, RSPO1, DNAJC15, RIPK2, IL13RA2, IRS1, and IRS2 genes in blood of obese boys with insulin resistance

The development of obesity and its metabolic complications is associated with dysregulation of various intrinsic mechanisms, which control basic metabolic processes via changes in the expression of numerous regulatory genes. We studied the expression of the subset of genes, which responsible for control of cell growth and glucose metabolism, in blood cells of obese boys with normal and impaired insulin sensitivity as well as in normal (control) individuals. It was shown that obesity with normal insulin sensitivity enhances the expression of IRS1, RIPK2, IL13RA2, RSPO1, IQSEC, and CCN2 genes but decreases the expression level IRS2 and DNAJC15 genes in the blood cells as compared to control group. Insulin resistance in obese boys leads to up-regulation of IRS2, RSPO1, and DNAJC15 gene expressions as wells to down-regulation of IRS1 and RIPK2 genes in the blood cells versus obese patients with normal insulin sensitivity. Results of this study provide evidence that obesity affects the expression of the subset of genes related to cell growth and glucose metabolism in blood cells and that insulin resistance in obesity is associated with changes in the expression level of IRS1, IRS2, RIPK2, RSPO1, and DNA JC15 genes, which contribute to the development of insulin resistance and glucose intolerance and possibly reflect some changes in fat tissue.