ArticleMolecular biology reports2012
Isolation and analysis of genes mainly expressed in adult mouse heart using subtractive hybridization cDNA library.
Article in Molecular biology reports, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 7 citations in OpenAlex.
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- Identification of differently expressed genes and small molecule drugs for Tetralogy of Fallot by bioinformatics strategy.Pediatric cardiology · 2014Article
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
Subtractive hybridization cDNA library (SHL) is one of the powerful approaches for isolating differentially expressed genes. Using this technique between mouse heart and skeletal muscle (skm) tissues, we aimed to construct a cDNA-library that was specific to heart tissue and to identify the potential candidate genes that might be responsible for the development of cardiac diseases or related pathophysiological conditions. In the first step of the study, we created a cDNA-library between mouse heart and skm tissues. The homologies of the randomly selected 215 clones were analyzed and then classified by function. A total of 146 genes were analyzed for their expression profiles in the heart and skm tissues in published mouse microarray dataset. In the second step, we analyzed the expression patterns of the selected genes by Northern blot and RNA in situ hybridization (RISH). In Northern blot analyses, the expression levels of Myl3, Myl2, Mfn2, Dcn, Pdlim4, mt-Co3, mt-Co1, Atpase6 and Tsc22d1 genes were higher in heart than skm. For first time with this study, expression patterns of Pdlim4 and Tsc22d1 genes in mouse heart and skm were shown by RISH. In the last step, 43 genes in this library were identified to have relationships mostly with cardiac diseases and/or related phenotypes. This is the first study reporting differentially expressed genes in healthy mouse heart using SHL technique. This study confirms our hypothesis that tissue-specific genes are most likely to have a disease association, if they possess mutations.
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