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A study of the differential expression profiles of Keshan disease lncRNA/mRNA genes based on RNA-seq

Authors
  • Huang, Guangyong1
  • Liu, Jingwen2
  • Wang, Yuehai1
  • Xiang, Youzhang3
  • 1 Liaocheng People’s Hospital of Shandong University, Liaocheng , (China)
  • 2 Liaocheng Vocational & Technical College, Liaocheng , (China)
  • 3 Shandong Institute for Endemic Disease Control, Jinan , (China)
Type
Published Article
Journal
Cardiovascular Diagnosis and Therapy
Publisher
AME Publishing Company
Publication Date
Apr 01, 2021
Volume
11
Issue
2
Pages
411–421
Identifiers
DOI: 10.21037/cdt-20-746
PMID: 33968619
PMCID: PMC8102268
Source
PubMed Central
Keywords
Disciplines
  • Original Article
License
Unknown

Abstract

Background This study aims to analyze the differential expression profiles of lncRNA in Keshan disease (KSD) and to explore the molecular mechanism of the disease occurrence and development. Methods RNA-seq technology was used to construct the lncRNA/mRNA expression library of a KSD group (n=10) and a control group (n=10), and then Cuffdiff software was used to obtain the gene lncRNA/mRNA FPKM value as the expression profile of lncRNA/mRNA. The fold changes between the two sets of samples were calculated to obtain differential lncRNA/mRNA expression profiles, and a bioinformatics analysis of differentially expressed genes was performed. Results A total of 89,905 lncRNAs and 20,315 mRNAs were detected. Statistical analysis revealed that 921 lncRNAs had obvious differential expression, among which 36 were up-regulated and 885 were down-regulated; 2,771 mRNAs presented with obvious differential expression, among which 253 were up-regulated and 2,518 were down-regulated, and cluster analysis indicated that the gene expression trends among the sample groups were consistent. The differentially expressed lncRNAs were tested for target genes, and 117 genes were found to be regulated by differential lncRNAs, which were concentrated in six signaling pathways, among which the apoptosis FoxO signaling pathway ranked first, so the target genes IGF1R and TGFB2 were screened out. Conclusions In this study, RNA-seq technology was used to obtain the differential gene expression profiles of KSD, and bioinformatics analysis was performed to screen out target genes, pointing out the direction for further research into the etiology, pathogenesis and drug treatment targets of KSD.

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