Dataset Information

Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome.

ABSTRACT: Inference of co-expression network and identification of disease-related modules and gene sets can help us understand disease-related molecular pathophysiology. We aimed to identify a cardiovascular disease (CVD)-related transcriptomic signature, specifically, in peripheral blood tissue, based on differential expression (DE) and differential co-expression (DcoE) analyses. Publicly available blood sample datasets for coronary artery disease (CAD) and acute coronary syndrome (ACS) statuses were integrated to establish a co-expression network. A weighted gene co-expression network analysis was used to construct modules that include genes with highly correlated expression values. The DE criterion is a linear regression with module eigengenes for module-specific genes calculated from principal component analysis and disease status as the dependent and independent variables, respectively. The DcoE criterion is a paired t-test for intramodular connectivity between disease and matched control statuses. A total of 21 and 23 modules were established from CAD status- and ACS-related datasets, respectively, of which six modules per disease status (i.e., obstructive CAD and ACS) were selected based on the DE and DcoE criteria. For each module, gene-gene interactions with extremely high correlation coefficients were individually selected under the two conditions. Genes displaying a significant change in the number of edges (gene-gene interaction) were selected. A total of 6, 10, and 7 genes in each of the three modules were identified as potential CAD status-related genes, and 14 and 8 genes in each of the two modules were selected as ACS-related genes. Our study identified gene sets and genes that were dysregulated in CVD blood samples. These findings may contribute to the understanding of CVD pathophysiology.

SUBMITTER: Lee T

PROVIDER: S-EPMC9496853 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome.

Lee Taesic T Hwang Sangwon S Seo Dong Min DM Shin Ha Chul HC Kim Hyun Soo HS Kim Jang-Young JY Uh Young Y

Cells 20220914 18

Inference of co-expression network and identification of disease-related modules and gene sets can help us understand disease-related molecular pathophysiology. We aimed to identify a cardiovascular disease (CVD)-related transcriptomic signature, specifically, in peripheral blood tissue, based on differential expression (DE) and differential co-expression (DcoE) analyses. Publicly available blood sample datasets for coronary artery disease (CAD) and acute coronary syndrome (ACS) statuses were in ...[more]

PMID: 36139449

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Project description:Nitrogen is an important plant nutrient that has a significant role in crop yield. Hence, to fulfill the needs of sustainable agriculture, it is necessary to improve biological nitrogen fixation in leguminous crops. Nod inducing gene families plays a crucial role in the interaction between rhizobia and legumes, leading to biological nitrogen fixation. However, nod inducing genes identification and characterization has not yet been performed in Arachis hypogaea. In this study, identification and genome-wide analysis of nod inducing genes are performed so that to explore their potential functions in the Arachis hypogaea for the first time. Nod genes were comprehensively analyzed by phylogenetic clustering analysis, gene structure determination, detection of conserved motifs, subcellular localization, conserved motifs, cis-acting elements and promoter region analysis. This study identified 42 Nod inducing genes in Arachis hypogaea, their sequences were submitted to NCBI and accession numbers were obtained. Potential involvement of these genes in biological nitrogen fixation has been unraveled, such as, phylogenetic analysis revealed that nod inducing genes evolved independently in Arachis hypogaea, the amino acid structures exhibited 20 highly conserved motifs, the proteins are present at different locations in cells and the gene structures revealed that all the genes are full-length genes with upstream intronic regions. Further, the promoter analysis determined a large number of cis-regulatory elements involved in nodulation. Moreover, this study not only provides identification and characterization of genes underlying developmental and functional stages of nodulation and biological nitrogen fixation but also lays the foundation for further revelation of nod inducing gene family. Besides, identification and structural analysis of these genes in Arachis hypogaea may provide a theoretical basis for the study of evolutionary relationships in future analysis.

Dataset Information

Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome.

Publications

Identification of Cardiovascular Disease-Related Genes Based on the Co-Expression Network Analysis of Genome-Wide Blood Transcriptome.

Similar Datasets

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