Comparative study of predicted miRNA between Indonesia and China (Wuhan) SARS-CoV-2: a bioinformatics analysis
Rahmadi Agus, Fasyah Ismaily, Sudigyo Digdo, Budiarto Arif, Mahesworo Bharuno, Hidayat Alam Ahmad, Pardamean Bens,
소속 상세정보
( Rahmadi Agus )
Universitas Muhammadiyah Prof. Dr. Hamka Faculty of Medicine
( Fasyah Ismaily )
Universitas Muhammadiyah Prof. Dr. Hamka Faculty of Medicine
( Sudigyo Digdo )
Bina Nusantara University Bioinformatics and Data Science Research Center
( Budiarto Arif )
Bina Nusantara University Bioinformatics and Data Science Research Center
( Mahesworo Bharuno )
Bina Nusantara University Bioinformatics and Data Science Research Center
( Hidayat Alam Ahmad )
Bina Nusantara University Bioinformatics and Data Science Research Center
( Pardamean Bens )
Bina Nusantara University Bioinformatics and Data Science Research Center
Abstract
Background: Several reports on the discovery of SARS-CoV-2 mutations and variations in Indonesia COVID-19 cases led to genomic dysregulation with the first pandemic cases in Wuhan, China. MicroRNA (miRNA) plays an important role in this genetic regulation and contributes to the enhancement of viral RNA binding through the host mRNA.
Objective: This research is aimed to detect miRNA targets of SARS-CoV-2 and examines their role in Indonesia cases against Wuhan cases.
Methods: SARS-CoV-2 sequences were obtained from GISAID (https://www.gisaid.org/), NCBI (https://ncbi.nlm.nih.gov), and National Genomics Data Center (https://bigd.big.ac.cn/gwh/) databases. MiRDB (https://github.com/gbnegrini/mirdb-custom-target-search) was used to annotate and predict target human mature miRNAs. For statistical analysis, we utilized a series chi-square test to obtain significant miRNA. DIANA-miRPath v3.0 (http://www.microrna.gr/miRPathv3) analyzed the Gene Ontology of mature miRNAs.
Result: The statistical results detected five significant miRNAs. Two miRNAs: hsa-miR-4778-5p and hsa-miR-4531 were consistently found in the majority of Wuhan samples, while they were only found in less than half of the Indonesia samples. The other three miRNA, hsa-miR-6844, hsa-miR-627-5p, and hsa-miR-3674, were discovered in most samples in both groups but with a significant difference ratio. Among these five significant miRNA targets, hsa-miR-6844 is the only miRNA that has an association with the ORF1ab gene of SARS-CoV-2.
Conclusion: The Gene Ontology analysis of five significant miRNA targets indicates a significant role in inflammation and the immune system. The specific detection of host miRNAs in this study shows that there are differences in the characteristics of SARS-CoV-2 between Indonesia and Wuhan.
키워드
miRNA; SARS-CoV-2; Indonesia; Wuhan; Genome data mining; Bioinformatics
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