In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder
Abstract Background Single nucleotide polymorphism (SNP) is called changes in a single base sequence in DNA between individuals. Micro-RNAs (miRNAs) are short, non-coding RNA molecules that control gene expression after transcription. Today, SNPs and miRNAs are associated with many diseases, and one...
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SpringerOpen
2025-01-01
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| Series: | Egyptian Journal of Medical Human Genetics |
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| Online Access: | https://doi.org/10.1186/s43042-025-00644-4 |
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| author | Kübra Çoruh Kınalı Ebru Özkan Oktay Mesut Karahan |
| author_facet | Kübra Çoruh Kınalı Ebru Özkan Oktay Mesut Karahan |
| author_sort | Kübra Çoruh Kınalı |
| collection | DOAJ |
| description | Abstract Background Single nucleotide polymorphism (SNP) is called changes in a single base sequence in DNA between individuals. Micro-RNAs (miRNAs) are short, non-coding RNA molecules that control gene expression after transcription. Today, SNPs and miRNAs are associated with many diseases, and one of them is autism spectrum disorder (ASD). ASD is a neurodevelopmental condition identified by symptoms that reduce the quality of life such as stereotypical movements, lack of social interaction and communication skills, cognitive and language disorders. The objective of this study is to utilize in silico tools to predict the possible damaging impacts of SNPs (missense) in ASD-related KCTD13, CSDE1, and SLC6A1 genes that cause amino acid substitution on protein function, stability, structure, and miRNA target binding sites. Methods The SNPs and protein amino acid sequences were obtained from the NCBI dbSNP and UniProt databases. This data served as input for predictions, which were carried out using different computational tools like SIFT, PolyPhen-2, SNPs&GO, PROVEAN, MutationAssessor, PhD-SNP, PANTHER, SNAP-2, Meta-SNP, I-Mutant 2.0, MUpro, and Project HOPE. For miRNA analysis, the miRSNP and PolymiRTS tools were utilized. GeneMANIA and STRING were also employed to explore gene–gene and protein–protein interactions. Results A total of 16 variants in these three genes were estimated to be potentially harmful via in silico analysis. As a result of the miRSNP and PolymiRTS analyses, it was found that 407 miRNAs could affect the regulation of target genes through the identified SNP variations. Furthermore, the predictive impact of those SNPs on protein stabilization was examined and three-dimensional protein models were created. Conclusion This study revealed the potential effects of genetic variations on three genes associated with ASD. The findings suggest that computational analysis of miRNA and SNPs on these ASD-related genes could provide valuable insights into the genetic mechanisms underlying ASD. In addition, it is suggested to investigate through experimental research whether the findings can be utilized as potential biomarkers for diagnosing and treating autism. |
| format | Article |
| id | doaj-art-59251384d4ef49bbba98f7cd1e68db62 |
| institution | Kabale University |
| issn | 2090-2441 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Egyptian Journal of Medical Human Genetics |
| spelling | doaj-art-59251384d4ef49bbba98f7cd1e68db622025-02-02T12:27:45ZengSpringerOpenEgyptian Journal of Medical Human Genetics2090-24412025-01-0126111310.1186/s43042-025-00644-4In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorderKübra Çoruh Kınalı0Ebru Özkan Oktay1Mesut Karahan2Institute of Health Science, Üsküdar UniversityLaboratory Technology Program, Vocational School of Health Services, Üsküdar UniversityMedical Laboratory Techniques, Vocational School of Health Sciences, Üsküdar UniversityAbstract Background Single nucleotide polymorphism (SNP) is called changes in a single base sequence in DNA between individuals. Micro-RNAs (miRNAs) are short, non-coding RNA molecules that control gene expression after transcription. Today, SNPs and miRNAs are associated with many diseases, and one of them is autism spectrum disorder (ASD). ASD is a neurodevelopmental condition identified by symptoms that reduce the quality of life such as stereotypical movements, lack of social interaction and communication skills, cognitive and language disorders. The objective of this study is to utilize in silico tools to predict the possible damaging impacts of SNPs (missense) in ASD-related KCTD13, CSDE1, and SLC6A1 genes that cause amino acid substitution on protein function, stability, structure, and miRNA target binding sites. Methods The SNPs and protein amino acid sequences were obtained from the NCBI dbSNP and UniProt databases. This data served as input for predictions, which were carried out using different computational tools like SIFT, PolyPhen-2, SNPs&GO, PROVEAN, MutationAssessor, PhD-SNP, PANTHER, SNAP-2, Meta-SNP, I-Mutant 2.0, MUpro, and Project HOPE. For miRNA analysis, the miRSNP and PolymiRTS tools were utilized. GeneMANIA and STRING were also employed to explore gene–gene and protein–protein interactions. Results A total of 16 variants in these three genes were estimated to be potentially harmful via in silico analysis. As a result of the miRSNP and PolymiRTS analyses, it was found that 407 miRNAs could affect the regulation of target genes through the identified SNP variations. Furthermore, the predictive impact of those SNPs on protein stabilization was examined and three-dimensional protein models were created. Conclusion This study revealed the potential effects of genetic variations on three genes associated with ASD. The findings suggest that computational analysis of miRNA and SNPs on these ASD-related genes could provide valuable insights into the genetic mechanisms underlying ASD. In addition, it is suggested to investigate through experimental research whether the findings can be utilized as potential biomarkers for diagnosing and treating autism.https://doi.org/10.1186/s43042-025-00644-4BioinformaticsMolecular neuroscienceNeurodevelopmental disordersAutism spectrum disorderPolymorphismIn silico |
| spellingShingle | Kübra Çoruh Kınalı Ebru Özkan Oktay Mesut Karahan In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder Egyptian Journal of Medical Human Genetics Bioinformatics Molecular neuroscience Neurodevelopmental disorders Autism spectrum disorder Polymorphism In silico |
| title | In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder |
| title_full | In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder |
| title_fullStr | In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder |
| title_full_unstemmed | In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder |
| title_short | In silico analysis of SNPs and miRNAs of KCTD13, CSDE1, SLC6A1 genes associated with autism spectrum disorder |
| title_sort | in silico analysis of snps and mirnas of kctd13 csde1 slc6a1 genes associated with autism spectrum disorder |
| topic | Bioinformatics Molecular neuroscience Neurodevelopmental disorders Autism spectrum disorder Polymorphism In silico |
| url | https://doi.org/10.1186/s43042-025-00644-4 |
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