Pork quality is an economically important trait and one of the main selection criteria for breeding in the swine industry. In this genome-wide association study (GWAS), 455 pigs from a porcine Large White × Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip, and phenotyped for intramuscular fat content (IMF), marbling, moisture, color L*, color a*, color b* and color score in the longissimus muscle (LM). Association tests between each trait and the SNPs were performed via the Genome Wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approach. From the Ensembl porcine database, SNP annotation was implemented using Sus scrofa Build 9. A total of 45 SNPs showed significant association with one or multiple meat quality traits. Of the 45 SNPs, 36 were located on SSC12. These significantly associated SNPs aligned to or were in close approximation to previously reported quantitative trait loci (QTL) and some were located within introns of previously reported candidate genes. Two haplotype blocks ASGA0100525-ASGA0055225-ALGA0067099-MARC0004712-DIAS0000861, and ASGA0085522-H3GA0056170 were detected in the significant region. The first block contained the genes MYH1, MYH2 and MYH4. A SNP (ASGA0094812) within an intron of the USP43 gene was significantly associated with five meat quality traits. The present results effectively narrowed down the associated regions compared to previous QTL studies and revealed haplotypes and candidate genes on SSC12 for meat quality traits in pigs.

Backfat thickness is strongly associated with meat quality, fattening efficiency, reproductive performance, and immunity in pigs. Fat storage and fatty acid synthesis mainly occur in adipose tissue. Therefore, we used a high-throughput massively parallel sequencing approach to identify transcriptomes in adipose tissue, and whole-genome differences from three full-sibling pairs of pigs with opposite (high and low) backfat thickness phenotypes. We obtained an average of 38.69 million reads for six samples, 78.68% of which were annotated in the reference genome. Eighty-nine overlapping differentially expressed genes were identified among the three pair comparisons. Whole-genome resequencing also detected multiple genetic variations between the pools of DNA from the two groups. Compared with the animal quantitative trait loci (QTL) database, 20 differentially expressed genes were matched to the QTLs associated with fatness in pigs. Our technique of integrating transcriptome, whole-genome resequencing, and QTL database information provided a rich source of important differentially expressed genes and variations. Associate analysis between selected SNPs and backfat thickness revealed that two SNPs and one haplotype of ME1 significantly affected fat deposition in pigs. Moreover, genetic analysis confirmed that variations in the differentially expressed genes may affect fat deposition.

Recent advances in our ability to design DNA binding factors with specificity for desired sequences have resulted in a revolution in genetic engineering, enabling directed changes to the genome to be made relatively easily. Technologies that facilitate specific and precise genome editing, such as knock-in, are critical for determining the functions of genes and for understanding fundamental biological processes. The CRISPR/Cas9 system has recently emerged as a powerful tool for functional genomic studies in mammals. Rosa26 gene can encode a non-essential nuclear RNA in almost all organizations, and become a hot point of exogenous gene insertion. Here, we describe efficient, precise CRISPR/Cas9-mediated Integration using a donor vector with tGFP sequence targeted in the sheep genomic Rosa26 locus. We succeeded in integrating with high efficiency an exogenous tGFP (turboGFP) gene into targeted genes in frame. Due to its simplicity, design flexibility, and high efficiency, we propose that CRISPR/Cas9-mediated knock-in will become a standard method for the generation transgenic sheep.

Hematological traits, which are important indicators of immune function in animals, have been commonly examined as biomarkers of disease and disease severity in humans and animals. Genome-wide significant quantitative trait loci (QTLs) provide important information for use in breeding programs of animals such as pigs. QTLs for hematological parameters (hematological traits) have been detected in pig chromosomes, although these are often mapped by linkage analysis to large intervals making identification of the underlying mutation problematic. Single nucleotide polymorphisms (SNPs) are the common form of genetic variation among individuals and are thought to account for the majority of inherited traits. In this study, a genome-wide association study (GWAS) was performed to detect regions of association with hematological traits in a three-generation resource population produced by intercrossing Large White boars and Minzhu sows during the period from 2007 to 2011. Illumina PorcineSNP60 BeadChip technology was used to genotype each animal and seven hematological parameters were measured (hematocrit (HCT), hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), red blood cell count (RBC) and red blood cell volume distribution width (RDW)). Data were analyzed in a three step Genome-wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) method. A total of 62 genome-wide significant and three chromosome-wide significant SNPs associated with hematological parameters were detected in this GWAS. Seven and five SNPs were associated with HCT and HGB, respectively. These SNPs were all located within the region of 34.6-36.5 Mb on SSC7. Four SNPs within the region of 43.7-47.0 Mb and fifty-five SNPs within the region of 42.2-73.8 Mb on SSC8 showed significant association with MCH and MCV, respectively. At chromosome-wide significant level, one SNP at 29.2 Mb on SSC1 and two SNPs within the region of 26.0-26.2 Mb were found to be significantly associated with RBC and RDW, respectively. Many of the SNPs were located within previously reported QTL regions and appeared to narrow down the regions compared with previously described QTL intervals. In current research, a total of seven significant SNPs were found within six candidate genes SCUBE3, KDR, TDO, IGFBP7, ADAMTS3 and AFP. In addition, the KIT gene, which has been previously reported to relate to hematological parameters, was located within the region significantly associated with MCH and MCV and could be a candidate gene. These results of this study may lead to a better understanding of the molecular mechanisms of hematological parameters in pigs.

The effects of virus-like double-stranded RNA (dsRNA, PolyI:C) and DNA methyltransferase inhibitor (Aza-CdR) on CD4 gene expression were investigated in a porcine kidney cell line (PK15). We found that expression levels of TLR3 and IFNαwere significantly upregulated by PolyI:C, compared to the untreated PK15 cells, which shows that PolyI:C successfully mimics viral infection in PK15 cells. We also found that PolyI:C (10 μg/ml) and/or Aza-CdR (5 μM) significantly induces DNA demethylation of porcine CD4, promoting the binding of NF-κB to the CpG site on the CD4 promoter and activating expression of CD4. These data help clarify the regulatory mechanism of DNA methylation of the CD4 gene in non-immune cell response to virus replication. Further study is warranted to identify CD4 gene expression regulated by DNA methylation and live virus infection.