Dataset Information

RNA Sequence Analyses throughout the Course of Mouse Cardiac Laminopathy Identify Differentially Expressed Genes for Cell Cycle Control and Mitochondrial Function.

ABSTRACT: Lamin A/C (LMNA) gene mutations are a known cause of familial dilated cardiomyopathy, but the precise mechanisms triggering disease progression remain unknown. We hypothesize that analysis of differentially expressed genes (DEGs) throughout the course of Lmna knockout (Lmna^-/-)-induced cardiomyopathy may reveal novel Lmna-mediated alterations of signaling pathways leading to dilated cardiomyopathy. Although Lmna was the only DEG down-regulated at 1 week of age, we identified 730 and 1004 DEGs in Lmna^-/- mice at 2 weeks and 1 month of age, respectively. At 2 weeks, Lmna^-/- mice demonstrated both down- and up-regulation of the key genes involving cell cycle control, mitochondrial dysfunction, and oxidative phosphorylation, as well as down-regulated genes governing DNA damage repair and up-regulated genes involved in oxidative stress response, cell survival, and cardiac hypertrophy. At 1 month, the down-regulated genes included those involved in oxidative phosphorylation, mitochondrial dysfunction, nutrient metabolism, cardiac β-adrenergic signaling, action potential generation, and cell survival. We also found 96 overlapping DEGs at both ages involved in oxidative phosphorylation, mitochondrial function, and calcium signaling. Impaired oxidative phosphorylation was observed at early disease stage, even before the appearance of disease phenotypes, and worsened with disease progression, suggesting its importance in the pathogenesis and progression of LMNA cardiomyopathy. Reduction of oxidative stress might therefore prevent or delay the development from Lmna mutation to LMNA cardiomyopathy.

SUBMITTER: Shao Z

PROVIDER: S-EPMC7170950 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Increasing evidence has indicated that modulation of epigenetic mechanisms, especially methylation and long-non-coding RNA (lncRNA) regulation, plays a pivotal role in the process of atherosclerosis; however, few studies focused on revealing the epigenetic-related subgroups during atherosclerotic progression using unsupervised clustering analysis. Hence, we aimed to identify the epigenetics-related differentially expressed genes associated with atherosclerosis subtypes and characterize their clinical utility in atherosclerosis. Eighty samples with expression data (GSE40231) and 49 samples with methylation data (GSE46394) from a large artery plaque were downloaded from the GEO database, and aberrantly methylated-differentially expressed (AMDE) genes were identified based on the relationship between methylation and expression. Furthermore, we conducted weighted correlation network analysis (WGCNA) and co-expression analysis to identify the core AMDE genes strongly involved in atherosclerosis. K-means clustering was used to characterize two subtypes of atherosclerosis in GSE40231, and then 29 samples were recognized as validation dataset (GSE28829). In a blood sample cohort (GSE90074), chi-square test and logistic analysis were performed to explore the clinical implication of the K-means clusters. Furthermore, significance analysis of microarrays and prediction analysis of microarrays (PAM) were applied to identify the signature AMDE genes. Moreover, the classification performance of signature AMDE gene-based classifier from PAM was validated in another blood sample cohort (GSE34822). A total of 1,569 AMDE mRNAs and eight AMDE long non-coding RNAs (lncRNAs) were identified by differential analysis. Through the WGCNA and co-expression analysis, 32 AMDE mRNAs and seven AMDE lncRNAs were identified as the core genes involved in atherosclerosis development. Functional analysis revealed that AMDE genes were strongly related to inflammation and axon guidance. In the clinical analysis, the atherosclerotic subtypes were associated with the severity of coronary artery disease and risk of adverse events. Eight genes, including PARP15, SERGEF, PDGFD, MRPL45, UBR1, STAU1, WIZ, and LSM4, were selected as the signature AMDE genes that most significantly differentiated between atherosclerotic subtypes. Ultimately, the area under the curve of signature AMDE gene-based classifier for atherosclerotic subtypes was 0.858 and 0.812 in GSE90074 and GSE34822, respectively. This study identified the AMDE genes (lncRNAs and mRNAs) that could be implemented in clinical clustering to recognize high-risk atherosclerotic patients.

Dataset Information

RNA Sequence Analyses throughout the Course of Mouse Cardiac Laminopathy Identify Differentially Expressed Genes for Cell Cycle Control and Mitochondrial Function.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets