Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases
Suicide is multifactorial and polygenic phenotype, affected by environmental and genetic factors. Among epigenetic mechanisms, miRNAs have been studied, but so far no very concise results exist. To overcome limitations of candidate miRNA and whole genome sequencing approaches, we created an in silic...
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| Format: | Article |
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MDPI AG
2022-03-01
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| Series: | Genes |
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| Online Access: | https://www.mdpi.com/2073-4425/13/4/562 |
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| author | Alja Videtič Paska Urban Alič Tomaž Zupanc Katarina Kouter |
| author_facet | Alja Videtič Paska Urban Alič Tomaž Zupanc Katarina Kouter |
| author_sort | Alja Videtič Paska |
| collection | DOAJ |
| description | Suicide is multifactorial and polygenic phenotype, affected by environmental and genetic factors. Among epigenetic mechanisms, miRNAs have been studied, but so far no very concise results exist. To overcome limitations of candidate miRNA and whole genome sequencing approaches, we created an in silico analysis algorithm that would help select the best suitable miRNAs that target the most interesting genes associated with suicidality. We used databases/web algorithms DIANA microT, miRDB, miRmap, miRWalk, and TargetScan and candidate genes <i>SLC6A4</i>, <i>HTR1A</i>, <i>BDNF</i>, <i>NR3C1</i>, <i>ZNF714</i>, and <i>NRIP3</i>. Based on a prediction algorithm, we have chosen miRNAs that are targeting regulation of the genes listed, and are at the same time being expressed in the brain. The highest ranking scores were obtained for hsa-miR-4516, hsa-miR-3135b, hsa-miR-124-3p, hsa-miR-129-5p, hsa-miR-27b-3p, hsa-miR-381-3p, hsa-miR-4286. Expression of these miRNAs was tested in the brain tissue of 40 suicide completers and controls, and hsa-miR-4516 and hsa-miR-381-3p showed a trend for statistical significance. We also checked the expression of the target genes of these miRNAs, and for <i>NR3C1</i> expression was lower in suicide completers compared to controls, which is in accordance with the available literature results. To determine the miRNAs that are most suitable for further suicidality research, more studies, combining in silico analysis and wet lab experiments, should be performed. |
| first_indexed | 2024-03-09T13:38:30Z |
| format | Article |
| id | doaj.art-cac61e7923a749c1a4d3f1ba22841a06 |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-09T13:38:30Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-cac61e7923a749c1a4d3f1ba22841a062023-11-30T21:09:27ZengMDPI AGGenes2073-44252022-03-0113456210.3390/genes13040562Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA DatabasesAlja Videtič Paska0Urban Alič1Tomaž Zupanc2Katarina Kouter3Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, SloveniaFaculty of Medicine, University of Ljubljana, 1000 Ljubljana, SloveniaInstitute of Forensic Medicine, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, SloveniaInstitute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, SloveniaSuicide is multifactorial and polygenic phenotype, affected by environmental and genetic factors. Among epigenetic mechanisms, miRNAs have been studied, but so far no very concise results exist. To overcome limitations of candidate miRNA and whole genome sequencing approaches, we created an in silico analysis algorithm that would help select the best suitable miRNAs that target the most interesting genes associated with suicidality. We used databases/web algorithms DIANA microT, miRDB, miRmap, miRWalk, and TargetScan and candidate genes <i>SLC6A4</i>, <i>HTR1A</i>, <i>BDNF</i>, <i>NR3C1</i>, <i>ZNF714</i>, and <i>NRIP3</i>. Based on a prediction algorithm, we have chosen miRNAs that are targeting regulation of the genes listed, and are at the same time being expressed in the brain. The highest ranking scores were obtained for hsa-miR-4516, hsa-miR-3135b, hsa-miR-124-3p, hsa-miR-129-5p, hsa-miR-27b-3p, hsa-miR-381-3p, hsa-miR-4286. Expression of these miRNAs was tested in the brain tissue of 40 suicide completers and controls, and hsa-miR-4516 and hsa-miR-381-3p showed a trend for statistical significance. We also checked the expression of the target genes of these miRNAs, and for <i>NR3C1</i> expression was lower in suicide completers compared to controls, which is in accordance with the available literature results. To determine the miRNAs that are most suitable for further suicidality research, more studies, combining in silico analysis and wet lab experiments, should be performed.https://www.mdpi.com/2073-4425/13/4/562psychiatryepigeneticsBrodmann area 10non-coding RNAsuicidal behaviourmicro RNA |
| spellingShingle | Alja Videtič Paska Urban Alič Tomaž Zupanc Katarina Kouter Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases Genes psychiatry epigenetics Brodmann area 10 non-coding RNA suicidal behaviour micro RNA |
| title | Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases |
| title_full | Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases |
| title_fullStr | Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases |
| title_full_unstemmed | Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases |
| title_short | Suicide and Changes in Expression of Neuronal miRNA Predicted by an Algorithm Search through miRNA Databases |
| title_sort | suicide and changes in expression of neuronal mirna predicted by an algorithm search through mirna databases |
| topic | psychiatry epigenetics Brodmann area 10 non-coding RNA suicidal behaviour micro RNA |
| url | https://www.mdpi.com/2073-4425/13/4/562 |
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