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Updated: Aug 7, 2025

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level
Published on: November 2, 2020
Bioinformatic analysis and validation of cardiac hypertrophy-related genes
Ai Meng1, Siang Wei, Lihuan Yan
1College of Life Science, Shanxi Agricultural University, Taigu, China.
Abstract:
In this study, we have screened genes involved in myocardial hypertrophy (MH) using a mice model for compensatory stress overload (transverse aortic constriction, TAC) and bioinformatics. Microarrays were downloaded, and according to the Venn diagram, three groups of data intersections were obtained. Gene function was analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), whereas protein-protein interactions (PPI) were analyzed using the STRING database. A mouse aortic arch ligation model was established to verify and screen the expression of hub genes. A total of 53 (DEGs) and 32 PPI genes were screened out. GO analysis showed DEGs mainly involved in cytokine and peptide inhibitor activity. KEGG analysis focused on ECM receptor interaction and osteoclast differentiation. Expedia co-expression gene network analysis showed that Serpina3n, Cdkn1a, Fos, Col5a2, Fn1 and Timp1 participated in the occurrence and development of MH. RT-qPCR verified that all the other 9 hub genes except Lox were highly expressed in TAC mice. This study lays a foundation for further study on the molecular mechanism of MH and for screening of molecular markers.
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