Mouse anti-Human ZNF24 monoclonal antibody, clone 5B2

Preservation of denatured dermis exerts promotive functions in wound healing and improves the appearance and function of skin. Angiogenesis is crucial for wound healing during burn injury. However, the potential molecular mechanism of angiogenesis in the recovery after burn injury remains to be elucidated. Herein, RNA chromatin immunoprecipitation (ChIP) sequencing analysis revealed upregulation of long intergenic non-coding RNA 00174 (linc00174) in the post-burn tissues. linc00174 overexpression promoted angiogenic activities of human umbilical vein endothelial cells (HUVECs) in the heat-denatured cell model, characterized by the promotion of cell proliferation, migration, and tube formation. Mechanistically, linc00174 directly bound to enhancer of zeste homolog 2 (EZH2), thus stimulating the protein level of trimethylation at lysine 27 of histone H3 (H3K27me3). Moreover, inhibition of EZH2 resulted in downregulation of ZNF24 and Runx1, as well as a decline of vascular endothelial growth factor A (VEGFA). Furthermore, EZH2 modulated epigenetic repression of ZNF24 and Runx1 through the promoter of H3K27me3. Additionally, ZNF24 and Runx1 both functioned as transcriptional inhibitors of VEGFA. Taken together, these findings uncover that linc00174 epigenetically inhibits ZNF24 and Runx1 expression through binding to EZH2, thus attenuating the suppression of VEGFA, contributing to the facilitation of angiogenesis during the recovery of heat-denatured endothelial cells.

Background: Joint modeling and analysis of phenotypic, genotypic and transcriptomic data have the potential to uncover the genetic control of gene activity and phenotypic variation, as well as shed light on the manner and extent of connectedness among these variables. Current studies mainly report associations, i.e. undirected connections among variables without causal interpretation. Knowledge regarding causal relationships among genes and phenotypes can be used to predict the behavior of complex systems, as well as to optimize management practices and selection strategies. Here, we performed a multistep procedure for inferring causal networks underlying carcass fat deposition and muscularity in pigs using multi-omics data obtained from an F-2 Duroc x Pietrain resource pig population. Results: We initially explored marginal associations between genotypes and phenotypic and expression traits through whole-genome scans, and then, in genomic regions with multiple significant hits, we assessed gene-phenotype network reconstruction using causal structural learning algorithms. One genomic region on SSC6 showed significant associations with three relevant phenotypes, off-midline10th-rib backfat thickness, loin muscle weight, and average intramuscular fat percentage, and also with the expression of seven genes, including ZNF24, SSX2IP, and AKR7A2. The inferred network indicated that the genotype affects the three phenotypes mainly through the expression of several genes. Among the phenotypes, fat deposition traits negatively affected loin muscle weight. Conclusions: Our findings shed light on the antagonist relationship between carcass fat deposition and lean meat content in pigs. In addition, the procedure described in this study has the potential to unravel gene-phenotype networks underlying complex phenotypes.