MicroRNAs (miRNAs) are small noncoding regulatory RNAs that play key roles in many diverse biological processes such as spermatogenesis. However, no study has been performed on the miRNA transcriptome of developing porcine testes. Here, we employed Solexa deep sequencing technology to extend the repertoire of porcine testis miRNAs and extensively compare the expression patterns of sexually immature and mature porcine testes. Solexa sequencing of two small RNA libraries derived from immature (30 days) and mature (180 days) pig testis samples yielded over 25 million high-quality reads. Overall, the two developmental stages had significantly different small RNA compositions. A custom data analysis pipeline identified 398 known and ⁄ or homologous conserved porcine miRNAs, 15 novel pig-specific miRNAs and 56 novel candidate miRNAs. We further observed multiple mature miRNA variants and identified a new bidirectional transcribed miRNA locus, ssc-mir-181a. A total of 122 miRNAs were differentially expressed in the immature and mature testes, and 10 were validated using quantitative RT-PCR. Furthermore, GO and KEGG pathway analyses of the predicted miRNA targets further illustrate the likely roles for these differentially expressed miRNAs in spermatogenesis. This study is the first comparative profile of the miRNA transcriptome in immature and mature porcine testes using a deep sequencing approach, and it provides a useful resource for future studies on the role of miRNAs in spermatogenesis and male infertility treatment.

Maternally expressed gene 3 (MEG3) is a long non-coding RNA that is a crucial regulator of skeletal muscle development. Some single-nucleotide polymorphism (SNP) mutants in MEG3 had strong associations with meat quality traits. Nevertheless, the function and mechanism of MEG3 mutants on porcine skeletal muscle development have not yet been well-demonstrated. In this study, eight SNPs were identified in MEG3 of fat- and lean-type pig breeds. Four of these SNPs (g.3087C > T, g.3108C > T, g.3398C > T, and g.3971A > C) were significantly associated with meat quality and consisted of the CCCA haplotype for fat-type pigs and the TTCC haplotype for lean-type pigs. Quantitative real-time PCR results showed that the expression of MEG3-TTCC was higher than that of MEG3-CCCA in transcription level (P < 0.01). The stability assay showed that the lncRNA stability of MEG3-TTCC was lower than that of MEG3-CCCA (P < 0.05). Furthermore, the results of qRT-PCR, Western blot, and Cell Counting Kit-8 assays demonstrated that the overexpression of MEG3-TTCC more significantly inhibited the proliferation of porcine skeletal muscle satellite cells (SCs) than that of MEG3-CCCA (P < 0.05). Moreover, the overexpression of MEG3-TTCC more significantly promoted the differentiation of SCs than that of MEG3-CCCA (P < 0.05). The Western blot assay suggested that the overexpression of MEG3-TTCC and MEG3-CCCA inhibited the proliferation of SCs by inhibiting PI3K/AKT and MAPK/ERK1/2 signaling pathways. The overexpression of the two haplotypes also promoted the differentiation of SCs by activating the JAK2/STAT3 signaling pathway in different degrees. These data are valuable for further studies on understanding the crucial role of lncRNAs in skeletal muscle development.

No abstract

Agouti signalling protein (ASIP) is a coat colour-related protein and also is a protein-related to lipid metabolism, which had first been found in agoutis. According to our previous study, ASIP is a candidate gene that affects the lipid metabolism in bovine adipocytes. However, its effect on milk lipid has not been reported yet. This study focused on the effect of the ASIP gene on the lipid metabolism of mammary epithelial cells in cattle. The ASIP gene was knocked out in bMECs by using CRISPR/Cas9 technology. The result of transcriptome sequencing showed that the differentially expressed genes associated with lipid metabolism were mainly enriched in the fatty acids metabolism pathways. Furthermore, the contents of intracellular triglycerides were significantly increased (p < 0.05), and cholesterol tended to rise (p > 0.05) in bMECs with the knockout of the ASIP gene. Fatty acid assays showed a significant alteration in medium and long-chain fatty acid content. Saturated and polyunsaturated fatty acids were significantly up-regulated (p < 0.05), and monounsaturated fatty acids were significantly decreased in the ASIP knockout bMECs (p < 0.05). The Q-PCR analysis showed that knockout of ASIP resulted in a significant reduction of gene expressions like PPARγ, FASN, SCD, and a significant up-regulation of genes like FABP4, ELOVL6, ACSL1, HACD4 prompted increased mid-to long-chain fatty acid synthesis. Overall, ASIP plays a pivotal role in regulating lipid metabolism in bMECs, which could further influence the component of lipid in milk.

Pedigree-derived relationships for individuals from an intercross of several lines cannot easily account for the segregation variance that is mainly caused by loci with alternative alleles fixed in different lines. However, when all founders are genotyped for a large number of markers, such relationships can be derived for descendants as expected genomic relationships conditional on the observed founder allele frequencies. A tabular method was derived in detail for autosomes and the X-chromosome. As a case study, we analyzed litter size and body weights at three different ages in an advanced mouse intercross (29 generations, total pedigree size 19,266) between a line selected for high litter size (FL1) and a highly inbred control line (DUKsi). Approximately 60% of the total genetic variance was due to segregation variance. Estimated heritability values were 0.20 (0.03), 0.34 (0.04), 0.23 (0.03), 0.41 (0.03) and 0.47 (0.02) for litter size, litter weight and body weight at ages of 21, 42 and 63 days, respectively (standard errors in brackets). These values were between 12% and 65% higher than observed in analyses that treated founders as unrelated. Fields of applications include experimental populations (selection experiments or advanced intercross lines) with a limited number of founders, which can be genotyped at a reasonable cost. In principle any number of founder lines can be treated. Additional genotypes from individuals in later generations can be combined into a joint relationship matrix by capitalizing on previously published approaches.