A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes
Purpose: Infertility affects nearly 12% of couples worldwide, with a male factor being the primary or contributory reason in around 50% of cases. MicroRNAs (miRNAs) are essential post-transcriptional regulators in the spermatogenesis process, and dysregulated miRNAs have been shown to have harmful e...
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| Format: | Article |
| Language: | English |
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Kirsehir Ahi Evran University
2023-12-01
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| Series: | Ahi Evran Medical Journal |
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| Online Access: | https://dergipark.org.tr/tr/download/article-file/2746351 |
| _version_ | 1797374045285515264 |
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| author | Murat KAYA |
| author_facet | Murat KAYA |
| author_sort | Murat KAYA |
| collection | DOAJ |
| description | Purpose: Infertility affects nearly 12% of couples worldwide, with a male factor being the primary or contributory reason in around 50% of cases. MicroRNAs (miRNAs) are essential post-transcriptional regulators in the spermatogenesis process, and dysregulated miRNAs have been shown to have harmful effects on male fertility. However, it is unclear which miRNAs are associated with infertility-related genes. The aim of this study is, to identify miRNAs that may be involved in the regulation of infertility-related genes using various bioinformatics approaches.
Materials and Methods: The study first selected genes associated with infertility from the Male Infertility Knowledge Base (MIK) database. Pathway analysis of the defined genes, protein-protein interaction (PPI), and hub proteins related to these genes were revealed by the Elsevier pathway collection database and Enrichr tool. Following that, miRNAs that can influence infertility-related genes were determined, and the influence of the miRNA-target gene connection on male infertility was established bioinformatically using various in silico tools such as miRPathDB 2.0 tool, StarmiR, and miRNet.
Results: 21 male infertility associated genes were selected from the MIK database and 15 miRNAs that are most likely to regulate these genes were identified bioinformatically. 10 hub proteins related to defined male infertility genes were analyzed.
Conclusion: Our bioinformatic study results indicate that miR-34a-5p dysregulation may contribute to infertility through CREM, LAMP3, AGBL5, FOXM1 genes and also miR-335-5p may cause infertility via the CFAP65, CFTR, and GAPDHS genes. |
| first_indexed | 2024-03-08T18:59:15Z |
| format | Article |
| id | doaj.art-c092af21d3cb4a3e8fca00eed2fddfe1 |
| institution | Directory Open Access Journal |
| issn | 2619-9203 |
| language | English |
| last_indexed | 2024-03-08T18:59:15Z |
| publishDate | 2023-12-01 |
| publisher | Kirsehir Ahi Evran University |
| record_format | Article |
| series | Ahi Evran Medical Journal |
| spelling | doaj.art-c092af21d3cb4a3e8fca00eed2fddfe12023-12-28T07:50:16ZengKirsehir Ahi Evran UniversityAhi Evran Medical Journal2619-92032023-12-017329630310.46332/aemj.1198311A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted GenesMurat KAYA0https://orcid.org/0000-0003-2241-7088ISTANBUL UNIVERSITY, İSTANBUL FACULTY OF MEDICINE, DEPARTMENT OF INTERNAL MEDICINE, DEPARTMENT OF MEDICAL GENETICSPurpose: Infertility affects nearly 12% of couples worldwide, with a male factor being the primary or contributory reason in around 50% of cases. MicroRNAs (miRNAs) are essential post-transcriptional regulators in the spermatogenesis process, and dysregulated miRNAs have been shown to have harmful effects on male fertility. However, it is unclear which miRNAs are associated with infertility-related genes. The aim of this study is, to identify miRNAs that may be involved in the regulation of infertility-related genes using various bioinformatics approaches. Materials and Methods: The study first selected genes associated with infertility from the Male Infertility Knowledge Base (MIK) database. Pathway analysis of the defined genes, protein-protein interaction (PPI), and hub proteins related to these genes were revealed by the Elsevier pathway collection database and Enrichr tool. Following that, miRNAs that can influence infertility-related genes were determined, and the influence of the miRNA-target gene connection on male infertility was established bioinformatically using various in silico tools such as miRPathDB 2.0 tool, StarmiR, and miRNet. Results: 21 male infertility associated genes were selected from the MIK database and 15 miRNAs that are most likely to regulate these genes were identified bioinformatically. 10 hub proteins related to defined male infertility genes were analyzed. Conclusion: Our bioinformatic study results indicate that miR-34a-5p dysregulation may contribute to infertility through CREM, LAMP3, AGBL5, FOXM1 genes and also miR-335-5p may cause infertility via the CFAP65, CFTR, and GAPDHS genes.https://dergipark.org.tr/tr/download/article-file/2746351male infertilitymir-335-5pmir-34a-5p |
| spellingShingle | Murat KAYA A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes Ahi Evran Medical Journal male infertility mir-335-5p mir-34a-5p |
| title | A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes |
| title_full | A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes |
| title_fullStr | A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes |
| title_full_unstemmed | A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes |
| title_short | A Bioinformatics Approach to Male Infertility, MicroRNAs, and Targeted Genes |
| title_sort | bioinformatics approach to male infertility micrornas and targeted genes |
| topic | male infertility mir-335-5p mir-34a-5p |
| url | https://dergipark.org.tr/tr/download/article-file/2746351 |
| work_keys_str_mv | AT muratkaya abioinformaticsapproachtomaleinfertilitymicrornasandtargetedgenes AT muratkaya bioinformaticsapproachtomaleinfertilitymicrornasandtargetedgenes |