Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools
Introduction: Diabetic kidney disease (DKD) remains the leading cause of chronic kidney disease (CKD) world- wide. Current biomarkers and treatment still fall short at preventing its progression. In search for a better diagnostic or therapeutic target, much interest in microRNAs, which act as post-t...
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| Format: | Article |
| Language: | English |
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Faculty of Medicine and Health Sciences, Universiti Putra Malaysia
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/99302/1/2022121911571010_MJMHS_0498.pdf |
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| author | Zahari Sham, Siti Yazmin Azwar, Shamin Wai, Kien Yip Ng, Chin Tat Abdullah, Maha Thevandran, Kalaiselvam Osman, Malina Heng, Fong Seow |
| author_facet | Zahari Sham, Siti Yazmin Azwar, Shamin Wai, Kien Yip Ng, Chin Tat Abdullah, Maha Thevandran, Kalaiselvam Osman, Malina Heng, Fong Seow |
| author_sort | Zahari Sham, Siti Yazmin |
| collection | UPM |
| description | Introduction: Diabetic kidney disease (DKD) remains the leading cause of chronic kidney disease (CKD) world- wide. Current biomarkers and treatment still fall short at preventing its progression. In search for a better diagnostic or therapeutic target, much interest in microRNAs, which act as post-translational regulators of gene expression has emerged. An upregulation of miR-101-3p was identified in the sera of type 2 diabetic patients with macroalbu- minuria in a selected Malaysian population by profiler RT-PCR array. Using bioinformatics tools, this study aimed to predict the mRNA targets of miR-101-3p. Given the scarcity of bioinformatics studies in DKD, this study also attempted to fill the gap. Methods: The mRNA targets were identified from two experimentally validated databases, namely Tarbase and MirTarBase. The commonly identified mRNA targets were submitted to Metascape and Enrichr bioinformatic tools. Results: A total of 2630 and 342 mRNA targets of miR-101-3p were identified by Tarbase and miRTarbase, respectively. One-hundred ninety-seven (197) mRNA targets were submitted for functional enrichment analysis. Our bioinformatics and bibliographical analyses suggested that ras-related C3 botulinum toxin substrate 1 (RAC1) and Ras-associated protein-1 b (RAP1b) were the most promising putative mRNA targets of miR-101-3p. The most enriched Gene Ontology term and pathway associated with these putative mRNA targets included Ras protein signal transduction and focal adhesion, respectively. Based on these analyses, their molecular mechanisms were proposed. Conclusion: Given the structural heterogeneity of the kidneys and cell type-dependent miRNA modula- tion, an in-silico target prediction of miR-101-3p increases the probability of a successful future in-vitro experimental verification. |
| first_indexed | 2024-03-06T11:11:07Z |
| format | Article |
| id | upm.eprints-99302 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T11:11:07Z |
| publishDate | 2022 |
| publisher | Faculty of Medicine and Health Sciences, Universiti Putra Malaysia |
| record_format | dspace |
| spelling | upm.eprints-993022023-03-06T07:53:05Z http://psasir.upm.edu.my/id/eprint/99302/ Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools Zahari Sham, Siti Yazmin Azwar, Shamin Wai, Kien Yip Ng, Chin Tat Abdullah, Maha Thevandran, Kalaiselvam Osman, Malina Heng, Fong Seow Introduction: Diabetic kidney disease (DKD) remains the leading cause of chronic kidney disease (CKD) world- wide. Current biomarkers and treatment still fall short at preventing its progression. In search for a better diagnostic or therapeutic target, much interest in microRNAs, which act as post-translational regulators of gene expression has emerged. An upregulation of miR-101-3p was identified in the sera of type 2 diabetic patients with macroalbu- minuria in a selected Malaysian population by profiler RT-PCR array. Using bioinformatics tools, this study aimed to predict the mRNA targets of miR-101-3p. Given the scarcity of bioinformatics studies in DKD, this study also attempted to fill the gap. Methods: The mRNA targets were identified from two experimentally validated databases, namely Tarbase and MirTarBase. The commonly identified mRNA targets were submitted to Metascape and Enrichr bioinformatic tools. Results: A total of 2630 and 342 mRNA targets of miR-101-3p were identified by Tarbase and miRTarbase, respectively. One-hundred ninety-seven (197) mRNA targets were submitted for functional enrichment analysis. Our bioinformatics and bibliographical analyses suggested that ras-related C3 botulinum toxin substrate 1 (RAC1) and Ras-associated protein-1 b (RAP1b) were the most promising putative mRNA targets of miR-101-3p. The most enriched Gene Ontology term and pathway associated with these putative mRNA targets included Ras protein signal transduction and focal adhesion, respectively. Based on these analyses, their molecular mechanisms were proposed. Conclusion: Given the structural heterogeneity of the kidneys and cell type-dependent miRNA modula- tion, an in-silico target prediction of miR-101-3p increases the probability of a successful future in-vitro experimental verification. Faculty of Medicine and Health Sciences, Universiti Putra Malaysia 2022-12 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/99302/1/2022121911571010_MJMHS_0498.pdf Zahari Sham, Siti Yazmin and Azwar, Shamin and Wai, Kien Yip and Ng, Chin Tat and Abdullah, Maha and Thevandran, Kalaiselvam and Osman, Malina and Heng, Fong Seow (2022) Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools. Malaysian Journal of Medicine and Health Sciences, 18 (supp.21). pp. 64-71. ISSN 2636-9346 https://medic.upm.edu.my/upload/dokumen/2022121911571010_MJMHS_0498.pdf 10.47836/mjmhs18.s21.11 |
| spellingShingle | Zahari Sham, Siti Yazmin Azwar, Shamin Wai, Kien Yip Ng, Chin Tat Abdullah, Maha Thevandran, Kalaiselvam Osman, Malina Heng, Fong Seow Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools |
| title | Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools |
| title_full | Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools |
| title_fullStr | Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools |
| title_full_unstemmed | Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools |
| title_short | Prediction of mRNA targets of miR-101-3p in diabetic kidney disease by bioinformatics tools |
| title_sort | prediction of mrna targets of mir 101 3p in diabetic kidney disease by bioinformatics tools |
| url | http://psasir.upm.edu.my/id/eprint/99302/1/2022121911571010_MJMHS_0498.pdf |
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