Real-time reverse transcription-PCR expression profiling of porcine troponin I family in three different types of muscles during development

Genetic basis of phenotypic convergence in pig terminal sires using pathway-based selection signature detection methods

The primary purpose of genetic improvement in lean pig breeds is to enhance production performance. Owing to their similar breeding directions, Duroc and Pietrain pigs are ideal models for investigating the phenotypic convergence underlying artificial selection. However, most important economic traits are controlled by a polygenic basis, so traditional strategies for detecting selection signatures may not fully reveal the genetic basis of complex traits. The pathway-based gene network analysis method utilizes each pathway as a unit, overcoming the limitations of traditional strategies for detecting selection signatures by revealing the selection of complex biological processes. Here, we utilized 13 122 398 high-quality SNPs from whole-genome sequencing data of 48 Pietrain pigs, 156 Duroc pigs and 36 European wild boars to detect selective signatures. After calculating FST and iHS scores, we integrated the pathway information and utilized the r/bioconductor graphite and signet packages to construct gene networks, identify subnets and uncover candidate genes underlying selection. Using the traditional strategy, a total of 47 genomic regions exhibiting parallel selection were identified. The enriched genes, including INO80, FZR1, LEPR and FAF1, may be associated with reproduction, fat deposition and skeletal development. Using the pathway-based selection signatures detection method, we identified two significant biological pathways and eight potential candidate genes underlying parallel selection, such as VTN, FN1 and ITGAV. This study presents a novel strategy for investigating the genetic basis of complex traits and elucidating the phenotypic convergence underlying artificial selection, by integrating traditional selection signature methods with pathway-based gene network analysis.

Identification of Potential Sex-Specific Biomarkers in Pigs with Low and High Intramuscular Fat Content Using Integrated Bioinformatics and Machine Learning

Intramuscular fat (IMF) content is a key determinant of pork quality. Controlling the genetic and physiological factors of IMF and the expression patterns of various genes is important for regulating the IMF content and improving meat quality in pig breeding. Growing evidence has suggested the role of genetic factors and breeds in IMF deposition; however, research on the sex factors of IMF deposition is still lacking. The present study aimed to identify potential sex-specific biomarkers strongly associated with IMF deposition in low- and high-IMF pig populations. The GSE144780 expression dataset of IMF deposition-related genes were obtained from the Gene Expression Omnibus. Initially, differentially expressed genes (DEGs) were detected in male and female low-IMF (162 DEGs, including 64 up- and 98 down-regulated genes) and high-IMF pigs (202 DEGs, including 147 up- and 55 down-regulated genes). Moreover, hub genes were screened via PPI network construction. Furthermore, hub genes were screened for potential sex-specific biomarkers using the least absolute shrinkage and selection operator machine learning algorithm, and sex-specific biomarkers in low-IMF (troponin I (TNNI1), myosin light chain 9(MYL9), and serpin family C member 1(SERPINC1)) and high-IMF pigs (CD4 molecule (CD4), CD2 molecule (CD2), and amine oxidase copper-containing 2(AOC2)) were identified, and then verified by quantitative real-time PCR (qRT-PCR) in semimembranosus muscles. Additionally, the gene set enrichment analysis and single-sample gene set enrichment analysis of hallmark gene sets were collectively performed on the identified biomarkers. Finally, the transcription factor-biomarker and lncRNA-miRNA-mRNA (biomarker) networks were predicted. The identified potential sex-specific biomarkers may provide new insights into the molecular mechanisms of IMF deposition and the beneficial foundation for improving meat quality in pig breeding.

Overexpression of the QKI Gene Promotes Differentiation of Goat Myoblasts into Myotubes

The QKI genes encode RNA-binding proteins regulating cell proliferation, differentiation, and apoptosis. The Goat QKI has six isoforms, but their roles in myogenesis are unclear. In this study, the six isoforms of the QKI gene were overexpressed in goat myoblast. Immunofluorescence, qPCR and Western blot were used to evaluate the effect of QKI on the differentiation of goat myoblast. An RNA-Seq was performed on the cells with the gain of the function from the major isoforms to screen differentially expressed genes (DEGs). The results show that six isoforms had different degrees of deletion in exons 6 and 7, and caused the appearance of different types of encoded amino acids. The expression levels of the QKI-1 and QKI-5 groups were upregulated in the biceps femoris and latissimus dorsi muscle tissues compared with those of the QKI-4, QKI-7, QKI-3 and QKI-6 groups. After 6 d of myoblast differentiation, QKI-5 and the myogenic differentiators MyoG, MyoD, and MyHC were upregulated. Compared to the negative control group, QKI promoted myotube differentiation and the myoblasts overexpressing QKI-5 formed large, abundant myotubes. In summary, we identified that the overexpression of the QKI gene promotes goat-myoblast differentiation and that QKI-5 is the major isoform, with a key role. The RNA-Seq screened 76 upregulated and 123 downregulated DEGs between the negative control and the QKI-5-overexpressing goat myoblasts after d 6 of differentiation. The GO and KEGG analyses associated the downregulated DEGs with muscle-related biological functions. Only the pathways related to muscle growth and development were enriched. This study provides a theoretical basis for further exploring the regulatory mechanism of QKI in skeletal-muscle development in goats.

Deep RNA sequencing of pectoralis muscle transcriptomes during late-term embryonic to neonatal development in indigenous Chinese duck breeds

Pectoral muscle (PM) comprises an important component of overall meat mass in ducks. However, PM has shown arrested or even reduced growth during late embryonic development, and the molecular mechanisms underlying PM growth during the late embryonic to neonatal period in ducks have not been addressed. In this study, we characterized potential candidate genes and signaling pathways related to PM development using RNA sequencing of PM samples selected at embryonic days (E) 21 and 27 and 5 days post-hatch (dph) in two duck breeds (Gaoyou and Jinding ducks). A total of 393 differentially expressed genes (DEGs) were identified, which showed higher or lower expression levels at E27 compared with E21 and 5 dph, reflecting the pattern of PM growth rates. Among these, 43 DEGs were common to all three time points in both duck breeds. These DEGs may thus be involved in regulating this developmental process. Specifically, KEGG pathway analysis of the 393 DEGs showed that genes involved with different metabolism pathways were highly expressed, while genes involved with cell cycle pathways showed lower expression levels at E27. These DEGs may thus be involved in the mechanisms responsible for the phenomenon of static or decreased breast muscle growth in duck breeds during the late embryonic period. These results increase the available genetic information for ducks and provide valuable resources for analyzing the mechanisms underlying the process of PM development.