Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations

South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer's extension of the Fst statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations' ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.

Genomic Analyses Revealed the Genetic Difference and Potential Selection Genes of Growth Traits in Two Duroc Lines

Duroc pigs are famous for their high growth rate, feed conversion efficiency, and lean meat percentage. Given that they have been subjected to artificial selection and breeding in multiple countries, various lines with obvious differences in production performance have formed. In this study, we genotyped 3,770 American Duroc (AD) pigs and 2,098 Canadian Duroc (CD) pigs using the GeneSeek Porcine SNP50 Beadchip to dissect the genetic differences and potential selection genes of growth traits in these two Duroc pig lines. Population structure detection showed that there were significant genetic differences between the two Duroc pig lines. Hence, we performed F _ST and cross-population extended haplotype homozygosity (XP-EHH) analyses between the two lines. As a result, we identified 38 annotated genes that were significantly enriched in the gland development pathway in the AD line, and 61 annotated genes that were significantly enriched in the immune-related pathway in the CD line. For three growth traits including backfat thickness (BFT), loin muscle depth (LMD), and loin muscle area (LMA), we then performed selection signature detection at 5 and 10% levels within the line and identified different selected regions and a series of candidate genes that are involved in lipid metabolism and skeletal muscle development or repair, such as IRX3, EBF2, WNT10B, TLR2, PITX3, and SGCD. The differences in selected regions and genes between the two lines may be the cause of the differences in growth traits. Our study suggests significant genetic differences between the AD and CD lines, which provide a theoretical basis for selecting different Duroc lines as sires for different needs.

A large-scale genome-wide association analysis reveals QTL and candidate genes for intramuscular fat content in Duroc pigs

This study aimed at identifying genomic regions and genes associated with intramuscular fat content (IMF) in Duroc pigs using a weighted single-step GWAS. Data from 3912 pigs, of which 3770 animals were genotyped with GeneSeek Porcine 50K Bead chip, were used for the association analysis. We identified 19 genomic regions that each explained >1% of the additive genetic variance associated with IMF. Notably, a consistent QTL on SSC7 (117.42-117.92 Mb) was confirmed, explaining 3.70% of the additive genetic variance, and two genes, BDKRB2 and ATG2B, were highlighted as promising candidates for IMF. Two QTL (SSC7, 94.19-94.64 Mb; SSC14, 123.25-123.75 Mb), which harbored MED6 and MAP3K9 genes and TCF7L2 gene respectively, were newly identified as associated with IMF. In conclusion, we identified a consistent QTL and additional genomic regions and genes that contributed to the genetic variance of IMF using a large-scale sample size of genotyped pigs and genealogical information.

How to Improve Meat Quality and Welfare in Entire Male Pigs by Genetics

Simple Summary

Successful breeding of entire male pigs needs a better understanding of factors driving meat quality and behavior traits as entire male pigs have lower meat quality, including an occasional strong defect known as boar taint, and more aggressive and sexual behavior. The review provides an update on how genetic factors affecting boar taint compounds and aggressive behavior in male pigs with emphasis on application in selection.

Abstract

Giving up surgical castration is desirable to avoid pain during surgery but breeding entire males raises issues on meat quality, particularly on boar taint, and aggression. It has been known for decades that boar taint is directly related to sexual development in uncastrated male pigs. The proportion of tainted carcasses depends on many factors, including genetics. The selection of lines with a low risk of developing boar taint should be considered as the most desirable solution in the medium to long term. It has been evidenced that selection against boar taint is feasible, and has been set up in a balanced way in some pig populations to counterbalance potential unfavorable effects on reproductive performances. Selection against aggressive behaviors, though theoretically feasible, faces phenotyping challenges that compromise selection in practice. In the near future, new developments in modelization, automatic recording, and genomic data will help define breeding objectives to solve entire male meat quality and welfare issues.

Genes and SNPs Involved with Scrotal and Umbilical Hernia in Pigs

Hernia is one of the most common defects in pigs. The most prevalent are the scrotal (SH), inguinal (IH) and umbilical (UH) hernias. We compared the inguinal ring transcriptome of normal and SH-affected pigs with the umbilical ring transcriptome of normal and UH-affected pigs to discover genes and pathways involved with the development of both types of hernia. A total of 13,307 transcripts was expressed in the inguinal and 13,302 in the umbilical ring tissues with 94.91% of them present in both tissues. From those, 35 genes were differentially expressed in both groups, participating in 108 biological processes. A total of 67 polymorphisms was identified in the inguinal ring and 76 in the umbilical ring tissue, of which 11 and 14 were novel, respectively. A single nucleotide polymorphism (SNP) with deleterious function was identified in the integrin α M (ITGAM) gene. The microtubule associated protein 1 light chain 3 γ (MAP1LC3C), vitrin (VIT), aggrecan (ACAN), alkaline ceramidase 2 (ACER2), potassium calcium-activated channel subfamily M α 1 (KCNMA1) and synaptopodin 2 (SYNPO2) genes are highlighted as candidates to trigger both types of hernia. We generated the first comparative study of the pig umbilical and inguinal ring transcriptomes, contributing to the understanding of the genetic mechanism involved with these two types of hernia in pigs and probably in other mammals.

Insights on meat quality from combining traditional studies and proteomics

Following a century of major discoveries on the mechanisms determining meat colour and tenderness using traditional scientific methods, further research into complex and interactive factors contributing to variations in meat quality is increasingly being based on data-driven "omics" approaches such as proteomics. Using two recent meta-analyses of proteomics studies on beef colour and tenderness, this review examines how knowledge of the mechanisms and factors underlying variations in these meat qualities can be both confirmed and extended by data-driven approaches. While proteomics seems to overlook some sources of variations in beef toughness, it highlights the role of post-mortem energy metabolism in setting the conditions for development of meat colour and tenderness, and also points to the complex interplay of energy metabolism, calcium regulation and mitochondrial metabolism. In using proteomics as a future tool for explaining variations in meat quality, the need for confirmation by further hypothesis-driven experimental studies of post-hoc explanations of why certain proteins are biomarkers of beef quality in data-driven studies is emphasised.

Single-Locus and Multi-Locus Genome-Wide Association Studies for Intramuscular Fat in Duroc Pigs

Intramuscular fat (IMF) is an important quantitative trait of meat, which affects the associated sensory properties and nutritional value of pork. To gain a better understanding of the genetic determinants of IMF, we used a composite strategy, including single-locus and multi-locus association analyses to perform genome-wide association studies (GWAS) for IMF in 1,490 Duroc boars. We estimated the genomic heritability of IMF to be 0.23 ± 0.04. A total of 30 single nucleotide polymorphisms (SNPs) were found to be significantly associated with IMF. The single-locus mixed linear model (MLM) and multiple-locus methods multi-locus random-SNP-effect mixed linear model (mrMLM), fast multi-locus random-SNP-effect efficient mixed model association (FASTmrEMMA), and integrative sure independence screening expectation maximization Bayesian least absolute shrinkage and selection operator model (ISIS EM-BLASSO) analyses identified 5, 9, 8, and 21 significant SNPs, respectively. Interestingly, a novel quantitative trait locus (QTL) on SSC 7 was found to affect IMF. In addition, 10 candidate genes (BDKRB2, GTF2IRD1, UTRN, TMEM138, DPYD, CASQ2, ZNF518B, S1PR1, GPC6, and GLI1) were found to be associated with IMF based on their potential functional roles in IMF. GO analysis showed that most of the genes were involved in muscle and organ development. A significantly enriched KEGG pathway, the sphingolipid signaling pathway, was reported to be associated with fat deposition and obesity. Identification of novel variants and functional genes will advance our understanding of the genetic mechanisms of IMF and provide specific opportunities for marker-assisted or genomic selection in pigs. In general, such a composite single-locus and multi-locus strategy for GWAS may be useful for understanding the genetic architecture of economic traits in livestock.

Bayes Factor-Based Regulatory Gene Network Analysis of Genome-Wide Association Study of Economic Traits in a Purebred Swine Population

Early stage prediction of economic trait performance is important and directly linked to profitability of farm pig production. Genome-wide association study (GWAS) has been applied to find causative genomic regions of traits. This study established a regulatory gene network using GWAS for critical economic pig characteristics, centered on easily measurable body fat thickness in live animals. We genotyped 2,681 pigs using Illumina Porcine SNP60, followed by GWAS to calculate Bayes factors for 47,697 single nucleotide polymorphisms (SNPs) of seven traits. Using this information, SNPs were annotated with specific genes near genome locations to establish the association weight matrix. The entire network consisted of 226 nodes and 6,921 significant edges. For in silico validation of their interactions, we conducted regulatory sequence analysis of predicted target genes of transcription factors (TFs). Three key regulatory TFs were identified to guarantee maximum coverage: AT-rich interaction domain 3B (ARID3B), glial cell missing homolog 1 (GCM1), and GLI family zinc finger 2 (GLI2). We identified numerous genes targeted by ARID3B, associated with cellular processes. GCM1 and GLI2 were involved in developmental processes, and their shared target genes regulated multicellular organismal process. This system biology-based function analysis might contribute to enhancing understanding of economic pig traits.