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The identification of genomic regions that affect additive genetic variation and contain genes involved in controlling growth and fat deposition has enormous impact in the farm animal industry (e.g., carcass merit and meat quality). Therefore, a genomewide association study was implemented in an F2 pig population using a 60,000 SNP marker panel for traits related to growth and fat deposition. Estimated genomic EBV were linearly transformed to calculate SNP effects and to identify genomic positions possibly associated with the genetic variability of each trait. Genomic segments were then defined considering the markers included in a region 1 Mb up- and downstream from the SNP with the smallest P-value and a false discovery rate < 0.05 for each trait. The significance for each 2-Mb segment was tested using the Bonferroni correction. Significant SNP were detected on SSC2, SSC3, SSC5, and SSC6, but 2-Mb segment significant effects were observed on SSC3 for weight at birth (wt_birth) and on SSC6 for 10th-rib backfat and last-rib backfat measured by ultrasound at different ages. Furthermore, a 6-Mb segment on SSC6 was also considered because the 2-Mb segments for 10 different fat deposition traits were overlapped. Although the segment effects for each trait remain significant, the proportion of additive variance explained by this larger segment was slightly smaller in some traits. In general, the results confirm the presence of genetic variability for wt_birth on SSC3 (18.0-20.2 Mb) and for fat deposition traits on SSC6 (133.8-136.0 Mb). Within these regions, fibrosin (FBRS) and myosin light chain, phosphorylatable, fast skeletal muscle (MYLPF) genes could be considered as candidates for the wt_birth signal on SSC3, and the SERPINE1 mRNAbinding protein 1 gene (SERBP1) may be a candidate for the fat deposition trait signals on SSC6. [ABSTRACT FROM AUTHOR]

Fetal myogenesis represents a critical period of porcine skeletal muscle development and requires coordinated expression of thousands of genes. Epigenetic mechanisms, including DNA methylation, drive transcriptional regulation during development; however, these processes are understudied in developing porcine tissues. We performed bisulfite sequencing to assess DNA methylation in pig longissimus dorsi muscle at 41- and 70-days gestation (dg), as well as RNA- and small RNA-sequencing to identify coordinated changes in methylation and expression between myogenic stages. We identified 45 739 differentially methylated regions (DMRs) between stages, and the majority ( N  = 34 232) were hypomethylated at 70 versus 41 dg. Integration of methylation and transcriptomic data revealed strong associations between differential gene methylation and expression. Differential miRNA methylation was significantly negatively correlated with abundance, and dynamic expression of assayed miRNAs persisted postnatally. Motif analysis revealed significant enrichment of myogenic regulatory factor motifs among hypomethylated regions, suggesting that DNA hypomethylation may function to increase accessibility of muscle-specific transcription factors. We show that developmental DMRs are enriched for GWAS SNPs for muscle- and meat-related traits, demonstrating the potential for epigenetic processes to influence phenotypic diversity. Our results enhance understanding of DNA methylation dynamics of porcine myogenesis and reveal putative cis -regulatory elements governed by epigenetic processes.

Genomic relationships based on markers capture the actual instead of the expected (based on pedigree) proportion of genome shared identical by descent (IBD). Several methods exist to estimate genomic relationships. In this research, we compare four such methods that were tested looking at the empirical distribution of the estimated relationships across 6704 pairs of half-sibs from a cross-bred pig population. The first method based on multiple marker linkage analysis displayed a mean and standard deviation (SD) in close agreement with the expected ones and was robust to changes in the minor allele frequencies (MAF). A single marker method that accounts for linkage disequilibrium (LD) and inbreeding came second, showing more sensitivity to changes in the MAF. Another single marker method that considers neither inbreeding nor LD showed the smallest empirical SD and was the most sensible to changes in MAF. A higher mean and SD were displayed by VanRaden's method, which was not sensitive to changes in MAF. Therefore, the method based on multiple marker linkage analysis and the single marker method that considers LD and inbreeding performed closer to theoretical values and were consistent with the estimates reported in literature for human half-sibs., (© 2016 Blackwell Verlag GmbH.)