WITHDRAWN: Downregulation of AC061961.2, LINGO1-AS1, and RP11-13E1.5 is associated with dilated cardiomyopathy progression

Abstract

Purpose: This study aimed to explore lncRNAs implicated in dilated cardiomyopathy (DCM) using high-throughput sequencing.Methods: From February 2016 to May 2017, ten samples of failing hearts collected from the left ventricles of DCM patients undergoing heart transplants, and ten control samples obtained from normal heart donors were included in this study. After sequencing, raw data were processed, and differentially expressed genes (DEGs) and lncRNAs between samples from patients with DCM and controls were screened, followed by functional enrichment analysis and Weighted Gene Coexpression Network Analysis (WGCNA). Five key lncNRAs were validated through real-time PCR.Results: After processing sequence data, 1398 DEGs were identified between DCM and control groups, including 267 lncRNAs. WGCNA identified seven modules that were significantly correlated with DCM. The top 50 genes in the three modules (black, dark-green, and green-yellow) were significantly correlated with the DCM disease state. Four core enrichment lncRNAs, such as AC061961.2, LINGO1-AS1, and RP11-557H15.4, in the green-yellow module were associated with functions of neurotransmitter secretion. Five core enrichment lncRNAs, such as KB-1299A7.2 and RP11-13E1.5, in the black module co-regulated functions associated with the regulation of blood circulation and heart contraction. AC061961.2, LINGO1-AS1, and RP11-13E1.5 were confirmed to be downregulated in DCM tissues by real-time PCR.Conclusion: The present study suggests that downregulation of AC061961.2, LINGO1-AS1, and RP11-13E1.5 is associated with DCM progression, and these may serve as key diagnostic biomarkers and therapeutic targets for DCM.

Using weighted gene co-expression network analysis to identify key modules and hub genes in tongue squamous cell carcinoma

“…[7] Compared with gene differential expression analysis, it can better analyze the changes of the whole biological process, making it possible to identify hundreds of pathogenic genes and treatment targets at the same time. [8] WGCNA technology has been successfully used in the study of many biological problems, and some important discoveries have been made. [9,10] Giulietti et al [11] constructed lncRNA co-expression network, revealing Linc1133 and Linc0205 as new biomarkers of pancreatic ductal adenocarcinoma.…”