Identification of polyunsaturated fatty acids related key modules and genes in metabolic dysfunction-associated fatty liver disease using WGCNA analysis

Identification of crucial modules and genes associated with backfat tissue development by WGCNA in Ningxiang pigs

Fat deposition is an economically important trait in pigs. Ningxiang pig, one of the four famous indigenous breeds in China, is characterized by high fat content. The underlying gene expression pattern in different developmental periods of backfat tissue remains unclear, and the purpose of this investigation is to explore the potential molecular regulators of backfat tissue development in Ningxiang pigs. Backfat tissue (three samples for each stage) was initially collected from different developmental stages (60, 120, 180, 240, 300, and 360 days after birth), and histological analysis and RNA sequencing (RNA-seq) were then conducted. Fragments per kilobase of transcript per million (FPKM) method was used to qualify gene expressions, and differentially expressed genes (DEGs) were identified. Furthermore, strongly co-expressed genes in modules, which were named by color, were clustered by Weighted gene co-expression network analysis (WGCNA) based on dynamic tree cutting algorithm. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment were subsequently implemented, and hub genes were described in each module. Finally, QPCR analysis was employed to validate RNA-seq data. The results showed that adipocyte area increased and adipocyte number decreased with development of backfat tissue. A total of 1,024 DEGs were identified in five comparison groups (120 days vs. 60 days, 180 days vs. 120 days, 240 days vs. 180 days, 300 days vs. 240 days, and 360 days vs. 300 days). The turquoise, red, pink, paleturquoise, darkorange, and darkgreen module had the highest correlation coefficient with 60, 120, 180, 240, 300, and 360 days developmental stage, while the tan, black and turquoise module had strong relationship with backfat thickness, adipocyte area, and adipocyte number, respectively. Thirteen hub genes (ACSL1, ACOX1, FN1, DCN, CHST13, COL1A1, COL1A2, COL6A3, COL5A1, COL14A1, OAZ3, DNM1, and SELP) were recognized. ACSL1 and ACOX1 might perform function in the early developmental stage of backfat tissue (60 days), and FN1, DCN, COL1A1, COL1A2, COL5A1, COL6A3, and COL14A1 have unignorable position in backfat tissue around 120 days developmental stage. Besides, hub genes SELP and DNM1 in modules significantly associated with backfat thickness and adipocyte area might be involved in the process of backfat tissue development. These findings contribute to understand the integrated mechanism underlying backfat tissue development and promote the progress of genetic improvement in Ningxiang pigs.

Analysis of the Genetic Relationship between Atherosclerosis and Non-Alcoholic Fatty Liver Disease through Biological Interaction Networks

Non-alcoholic fatty liver disease (NAFLD) seems to have some molecular links with atherosclerosis (ATH); however, the molecular pathways which connect both pathologies remain unexplored to date. The identification of common factors is of great interest to explore some therapeutic strategies to improve the outcomes for those affected patients. Differentially expressed genes (DEGs) for NAFLD and ATH were extracted from the GSE89632 and GSE100927 datasets, and common up- and downregulated DEGs were identified. Subsequently, a protein-protein interaction (PPI) network based on the common DEGs was performed. Functional modules were identified, and the hub genes were extracted. Then, a Gene Ontology (GO) and pathway analysis of common DEGs was performed. DEGs analysis in NAFLD and ATH showed 21 genes that were regulated similarly in both pathologies. The common DEGs with high centrality scores were ADAMTS1 and CEBPA which appeared to be down- and up-regulated in both disorders, respectively. For the analysis of functional modules, two modules were identified. The first one was oriented to post-translational protein modification, where ADAMTS1 and ADAMTS4 were identified, and the second one mainly related to the immune response, where CSF3 was identified. These factors could be key proteins with an important role in the NAFLD/ATH axis.