An integration analysis based on genomic, transcriptomic and QTX information reveals credible candidate genes for fat-related traits in pigs

Integrating genome-wide association study with RNA-seq revealed DBI as a good candidate gene for intramuscular fat content in Beijing black pigs

Increasing intramuscular fat (IMF) content can enhance the sensory quality of meat, including tenderness, juiciness, flavor, and color. Genome-wide association study and RNA-sequencing (RNA-seq) analysis were used to identify candidate IMF genes in Beijing Black pigs, a popular species among consumers in northern China. Two and three single nucleotide polymorphisms were significantly associated with IMF in SSC13 and SSC15 respectively. Solute carrier family 4 member 7 (SLC4A7) on SSC13 and insulin induced gene 2 (INSIG2), coiled-coil domain containing 93 (CCDC93), and diazepam binding inhibitor acyl-CoA binding protein (DBI) on SSC15 are good candidate genes in this population. Furthermore, RNA-seq analysis was performed between high and low IMF groups, and 534 differentially expressed genes were identified. In addition, based on differentially expressed genes, Kyoto Encyclopedia of Genes and Genomes analysis revealed that peroxisome proliferator-activated receptors and FoxO signaling pathway pathways might contribute to IMF. Moreover, the DBI gene was identified as a candidate for IMF both by genome-wide association study and RNA-seq analysis, suggesting that it might be a crucial candidate gene for influencing IMF in Beijing Black pigs.

Non-contact detection method of pregnant sows backfat thickness based on two-dimensional images

Since sow backfat thickness (BFT) is highly correlated with its service life and reproductive effectiveness, dynamic monitoring of BFT is a critical component of large-scale sow farm productivity. Existing contact measures of sow BFT have their problems including, high measurement intensity and sows' stress reaction, low biological safety, and difficulty in meeting the requirements for multiple measurements. This article presents a two-dimensional (2D) image-based approach for determining the BFT of pregnant sows when combined with the backfat growth rate (BGR). The 2D image features of sows extracted by convolutional neural networks (CNN) and the artificially defined phenotypic features of sows such as hip width, hip height, body length, hip height-width ratio, length-width ratio, and waist-hip ratio, were used respectively, combined with BGR, to construct a prediction model for sow BFT using support vector regression (SVR). Following testing and comparison, it was shown that using CNN to extract features from images could effectively replace artificially defined features, BGR contributed to the model's accuracy improvement. The CNN-BGR-SVR model performed the best, with R² of 0.72 and mean absolute error of 1.21 mm, and root mean square error of 1.50 mm, and mean absolute percentage error of 7.57%. The results demonstrated that the CNN-BGR-SVR model based on 2D images was capable of detecting sow BFT, establishing a new reference for non-contact sow BFT detection technology.

Potential functional variants in AHR signaling pathways are associated with age at puberty in swine

Puberty in female pigs is defined as age at first estrus and gilts that have an earlier age at puberty are more likely to have greater lifetime productivity. Because age at puberty is predictive for sow longevity and lifetime productivity, but not routinely measured in commercial herds, it would be beneficial to use genomic or marker-assisted selection to improve these traits. A GWAS at the US Meat Animal Research Center (USMARC) identified several loci associated with age at puberty in pigs. Candidate genes in these regions were scanned for potential functional variants using sequence information from the USMARC swine population founder animals and public databases. In total, 135 variants (SNP and insertion/deletions) in 39 genes were genotyped in 1284 phenotyped animals from a validation population sired by Landrace and Yorkshire industry semen using the Agena MassArray system. Twelve variants in eight genes were associated with age at puberty (P < 0.005) with estimated additive SNP effects ranging from 1.6 to 5.3 days. Nine of these variants were non-synonymous coding changes in AHR, CYP1A2, OR2M4, SDCCAG8, TBC1D1 and ZNF608, two variants were deletions of one and four codons in aryl hydrocarbon receptor, AHR, and the most significant SNP was near an acceptor splice site in the acetyl-CoA carboxylase alpha, ACACA. Several of the loci identified have a physiological and a genetic role in sexual maturation in humans and other animals and are involved in AHR-mediated pathways. Further functional validation of these variants could identify causative mutations that influence age at puberty in gilts and possibly sow lifetime productivity.