{"title":"Transcriptomic meta-analysis reveals biomarker pairs and key pathways in Tetralogy of Fallot.","authors":"Sona Charles, J Sreekumar, Jeyakumar Natarajan","doi":"10.1142/S0219720022400042","DOIUrl":null,"url":null,"abstract":"<p><p>Tetralogy of Fallot (TOF) is a cyanotic congenital condition contributed by genetic, epigenetic as well as environmental factors. We applied sparse machine learning algorithms to RNAseq and sRNAseq data to select the prospective biomarker candidates. Furthermore, we applied filtering techniques to identify a subset of biomarker pairs in TOF. Differential expression analysis disclosed 2757 genes and 214 miRNAs, which are dysregulated. Weighted gene co-expression network analysis on the differentially expressed genes extracted five significant modules that are enriched in GO terms, extracellular matrix, signaling and calcium ion binding. Also, voomNSC selected two genes and five miRNAs and transformed PLDA-predicted 72 genes and 38 miRNAs as prognostic biomarkers. Out of the selected biomarkers, miRNA target analysis revealed 14 miRNA-gene interactions. Also, 10 out of 14 pairs were oppositely expressed and four out of 10 oppositely expressed biomarker pairs shared common pathways of focal adhesion and P13K-Akt signaling. In conclusion, our study demonstrated the concept of biomarker pairs, which may be considered for clinical validation due to the high literature as well as experimental support.</p>","PeriodicalId":48910,"journal":{"name":"Journal of Bioinformatics and Computational Biology","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bioinformatics and Computational Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1142/S0219720022400042","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/8/3 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Tetralogy of Fallot (TOF) is a cyanotic congenital condition contributed by genetic, epigenetic as well as environmental factors. We applied sparse machine learning algorithms to RNAseq and sRNAseq data to select the prospective biomarker candidates. Furthermore, we applied filtering techniques to identify a subset of biomarker pairs in TOF. Differential expression analysis disclosed 2757 genes and 214 miRNAs, which are dysregulated. Weighted gene co-expression network analysis on the differentially expressed genes extracted five significant modules that are enriched in GO terms, extracellular matrix, signaling and calcium ion binding. Also, voomNSC selected two genes and five miRNAs and transformed PLDA-predicted 72 genes and 38 miRNAs as prognostic biomarkers. Out of the selected biomarkers, miRNA target analysis revealed 14 miRNA-gene interactions. Also, 10 out of 14 pairs were oppositely expressed and four out of 10 oppositely expressed biomarker pairs shared common pathways of focal adhesion and P13K-Akt signaling. In conclusion, our study demonstrated the concept of biomarker pairs, which may be considered for clinical validation due to the high literature as well as experimental support.
期刊介绍:
The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information.
The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.