title: Computational Systems Biology Approach Predicts Regulators and Targets of microRNAs and Their Genomic Hotspots in Apoptosis Process.
abstract: Novel computational systems biology tools such as common targets analysis, common regulators analysis, pathway discovery, and transcriptomic-based hotspot discovery provide new opportunities in understanding of apoptosis molecular mechanisms. In this study, after measuring the global contribution of microRNAs in the course of apoptosis by Affymetrix platform, systems biology tools were utilized to obtain a comprehensive view on the role of microRNAs in apoptosis process. Network analysis and pathway discovery highlighted the crosstalk between transcription factors and microRNAs in apoptosis. Within the transcription factors, PRDM1 showed the highest upregulation during the course of apoptosis, with more than 9-fold expression increase compared to non-apoptotic condition. Within the microRNAs, MIR1208 showed the highest expression in non-apoptotic condition and downregulated by more than 6 fold during apoptosis. Common regulators algorithm showed that TNF receptor is the key upstream regulator with a high number of regulatory interactions with the differentially expressed microRNAs. BCL2 and AKT1 were the key downstream targets of differentially expressed microRNAs. Enrichment analysis of the genomic locations of differentially expressed microRNAs led us to the discovery of chromosome bands which were highly enriched (p < 0.01) with the apoptosis-related microRNAs, such as 13q31.3, 19p13.13, and Xq27.3 This study opens a new avenue in understanding regulatory mechanisms and downstream functions in the course of apoptosis as well as distinguishing genomic-enriched hotspots for apoptosis process.
authors.affiliation: National Center of Biotechnology (NCB), King Abdulaziz City for Science and Technology (KACST), Riyadh, 6086, Saudi Arabia. ibrahim.alanazi@adelaide.edu.au.|School of Biological Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia. ibrahim.alanazi@adelaide.edu.au.
authors.forename: Ibrahim O
authors.initials: IO
authors.lastname: Alanazi
authors.affiliation: School of Biological Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia. esmaeil.ebrahimie@adelaide.edu.au.|Institute of Biotechnology, Shiraz University, Shiraz, Iran. esmaeil.ebrahimie@adelaide.edu.au.|Division of Information Technology, Engineering and the Environment, School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, Australia. esmaeil.ebrahimie@adelaide.edu.au.|School of Biological Sciences, Faculty of Science and Engineering, Flinders University, Adelaide, Australia. esmaeil.ebrahimie@adelaide.edu.au.|Department of Genetics and Evolution, School of Biological Sciences, North Terrace Campus, The University of Adelaide, Adelaide, SA, 5005, Australia. esmaeil.ebrahimie@adelaide.edu.au.
authors.forename: Esmaeil
authors.initials: E
authors.lastname: Ebrahimie
mesh_terms: D000465:Algorithms; D017209:Apoptosis / Q000187:drug effects; D002460:Cell Line; D004815:Epidermal Growth Factor / Q000494:pharmacology*; D023281:Genomics / Q000379:methods*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D000074462:Positive Regulatory Domain I-Binding Factor 1; D040901:Proteomics / Q000379:methods; D012097:Repressor Proteins / Q000235:genetics; D049490:Systems Biology; D014157:Transcription Factors / Q000235:genetics*; D059467:Transcriptome / Q000187:drug effects
chemical_list: D035683:MicroRNAs; D012097:Repressor Proteins; D014157:Transcription Factors; C087042:PRDM1 protein, human; D004815:Epidermal Growth Factor; D000074462:Positive Regulatory Domain I-Binding Factor 1
keywords: Apoptosi; Hotspots; MicroRNA; Network analysis; Transcription factors