Integrated Comparative Transcriptome and circRNA-lncRNA-miRNA-mRNA ceRNA Regulatory Network Analyses Identify Molecular Mechanisms Associated with Intramuscular Fat Content in Beef Cattle.

Intramuscular fat content (IMF), one of the most important carcass traits in beef cattle, is controlled by complex regulatory factors. At present, molecular mechanisms involved in regulating IMF and fat metabolism in beef cattle are not well understood. Our objective was to integrate comparative transcriptomic and competing endogenous RNA (ceRNA) network analyses to identify candidate messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of longissimus dorsi muscle (LDM) tissue for IMF and fat metabolism of 5 beef cattle breeds (Angus, Chinese Simmental, Luxi, Nanyang, and Shandong Black). In total, 34 circRNAs, 57 lncRNAs, 15 miRNAs, and 374 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, 7 key subnets with 16 circRNAs, 43 lncRNAs, 7 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 48, 13, and 28 significantly enriched GO terms related to IMF in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways associated with IMF and fat metabolism that were enriched included metabolic, calcium, cGMP-PKG, thyroid hormone, and oxytocin signaling pathways. Moreover, MCU, CYB5R1, and BAG3 genes were common among the 10 comparative groups defined as important candidate marker genes for fat metabolism in beef cattle. Contributions of transcriptome profiles from various beef breeds and a competing endogenous RNA (ceRNA) regulatory network underlying phenotypic differences in IMF provided novel insights into molecular mechanisms associated with meat quality.

Construction of a circRNA- lincRNA-lncRNA-miRNA-mRNA ceRNA regulatory network identifies genes and pathways linked to goat fertility.

Background: There is growing interest in the genetic improvement of fertility traits in female goats. With high-throughput genotyping, single-cell RNA sequencing (scRNA-seq) is a powerful tool for measuring gene expression profiles. The primary objective was to investigate comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, using scRNA-seq. Methods: Thirty samples from Ji'ning Gray goats (n = 15 for high fertility and n = 15 for low fertility) were retrieved from publicly available scRNA-seq data. Functional enrichment analysis and a literature mining approach were applied to explore modules and hub genes related to fertility. Then, interactions between types of RNAs identified were predicted, and the ceRNA regulatory network was constructed by integrating these interactions with other gene regulatory networks (GRNs). Results and discussion: Comparative transcriptomics-related analyses identified 150 differentially expressed genes (DEGs) between high- and low-fertility groups, based on the fold change (≥5 and ≤-5) and false discovery rate (FDR <0.05). Among these genes, 80 were upregulated and 70 were downregulated. In addition, 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs were identified by literature mining. Furthermore, we identified 18 hub genes (SMAD1, SMAD2, SMAD3, SMAD4, TIMP1, ERBB2, BMP15, TGFB1, MAPK3, CTNNB1, BMPR2, AMHR2, TGFBR2, BMP4, ESR1, BMPR1B, AR, and TGFB2) involved in goat fertility. Identified biological networks and modules were mainly associated with ovary signature pathways. In addition, KEGG enrichment analysis identified regulating pluripotency of stem cells, cytokine-cytokine receptor interactions, ovarian steroidogenesis, oocyte meiosis, progesterone-mediated oocyte maturation, parathyroid and growth hormone synthesis, cortisol synthesis and secretion, and signaling pathways for prolactin, TGF-beta, Hippo, MAPK, PI3K-Akt, and FoxO. Functional annotation of identified DEGs implicated important biological pathways. These findings provided insights into the genetic basis of fertility in female goats and are an impetus to elucidate molecular ceRNA regulatory networks and functions of DEGs underlying ovarian follicular development.

lncRNA-miRNA-mRNA ceRNA Network Involved in Sheep Prolificacy: An Integrated Approach.

Understanding the molecular pattern of fertility is considered as an important step in breeding of different species, and despite the high importance of the fertility, little success has been achieved in dissecting the interactome basis of sheep fertility. However, the complex mechanisms associated with prolificacy in sheep have not been fully understood. Therefore, this study aimed to use competitive endogenous RNA (ceRNA) networks to evaluate this trait to better understand the molecular mechanisms responsible for fertility. A competitive endogenous RNA (ceRNA) network of the corpus luteum was constructed between Romanov and Baluchi sheep breeds with either good or poor genetic merit for prolificacy using whole-transcriptome analysis. First, the main list of lncRNAs, miRNAs, and mRNA related to the corpus luteum that alter with the breed were extracted, then miRNA−mRNA and lncRNA−mRNA interactions were predicted, and the ceRNA network was constructed by integrating these interactions with the other gene regulatory networks and the protein−protein interaction (PPI). A total of 264 mRNAs, 14 lncRNAs, and 34 miRNAs were identified by combining the GO and KEGG enrichment analyses. In total, 44, 7, 7, and 6 mRNAs, lncRNAs, miRNAs, and crucial modules, respectively, were disclosed through clustering for the corpus luteum ceRNA network. All these RNAs involved in biological processes, namely proteolysis, actin cytoskeleton organization, immune system process, cell adhesion, cell differentiation, and lipid metabolic process, have an overexpression pattern (Padj < 0.01). This study increases our understanding of the contribution of different breed transcriptomes to phenotypic fertility differences and constructed a ceRNA network in sheep (Ovis aries) to provide insights into further research on the molecular mechanism and identify new biomarkers for genetic improvement.

Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis.

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes-CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3-were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine-cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

Omics Multi-Layers Networks Provide Novel Mechanistic and Functional Insights Into Fat Storage and Lipid Metabolism in Poultry.

Fatty acid metabolism in poultry has a major impact on production and disease resistance traits. According to the high rate of interactions between lipid metabolism and its regulating properties, a holistic approach is necessary. To study omics multilayers of adipose tissue and identification of genes and miRNAs involved in fat metabolism, storage and endocrine signaling pathways in two groups of broiler chickens with high and low abdominal fat, as well as high-throughput techniques, were used. The gene-miRNA interacting bipartite and metabolic-signaling networks were reconstructed using their interactions. In the analysis of microarray and RNA-Seq data, 1,835 genes were detected by comparing the identified genes with significant expression differences (p.adjust < 0.01, fold change ≥ 2 and ≤ -2). Then, by comparing between different data sets, 34 genes and 19 miRNAs were detected as common and main nodes. A literature mining approach was used, and seven genes were identified and added to the common gene set. Module finding revealed three important and functional modules, which were involved in the peroxisome proliferator-activated receptor (PPAR) signaling pathway, biosynthesis of unsaturated fatty acids, Alzheimer's disease metabolic pathway, adipocytokine, insulin, PI3K-Akt, mTOR, and AMPK signaling pathway. This approach revealed a new insight to better understand the biological processes associated with adipose tissue.

Frequency of Growth Differentiation Factor 5 rs143383 and asporin D-repeat polymorphisms in patients with hand and knee osteoarthritis in Kurdistan province, Iran.

AIM: Osteoarthritis (OA) is the most common chronic joint disorder, resulting from the breakdown of joint cartilage. It occurs in the knees, hands, and hips, leading to pain, stiffness, inflammation, and swelling. METHODS: In this study, 100 hand and knee OA patients, meeting the American College of Rheumatology criteria were included in the case group, and 100 healthy individuals were allocated to the control group. Blood samples were collected from the participants. After DNA extraction, genotyping was carried out for GDF5 rs143383 C/T polymorphism by allele-specific polymerase chain reaction (ASPCR) and for D-repeat alleles of asporin (ASPN) by conventional PCR assay. RESULTS: The results showed that the frequency of the D14 allele of ASPN was significantly higher than other alleles in the case group (P = .0001). Also, the frequency of the D14 allele among women was significantly higher than in men (P = .004). Moreover, the frequency of the TT allele in GDF5 rs143383 C/T polymorphism was significantly higher than the CC and CT alleles in the case group, compared with the control group (P = .001). A significant difference was found between the TT allele and other alleles in female and male patients compared with the control group (P = .02). CONCLUSIONS: The D14 allele of the ASPN gene and TT allele of the GDF5 gene (rs143383 + 104T/C) are associated with hand and knee OA in the Kurdish population, indicating that these alleles could be risk factors for OA, at least in our populations.