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Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes
FGF23, CYP24A1 and VDR altogether play a significant role in genetic susceptibility to chronic kidney disease (CKD). Identification of possible causative mutations may serve as therapeutic targets and diagnostic markers for CKD. Thus, we adopted both sequence and sequence-structure based SNP analysi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833053/ https://www.ncbi.nlm.nih.gov/pubmed/27114920 http://dx.doi.org/10.1016/j.mgene.2016.03.005 |
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author | Nagamani, Selvaraman Singh, Kh. Dhanachandra Muthusamy, Karthikeyan |
author_facet | Nagamani, Selvaraman Singh, Kh. Dhanachandra Muthusamy, Karthikeyan |
author_sort | Nagamani, Selvaraman |
collection | PubMed |
description | FGF23, CYP24A1 and VDR altogether play a significant role in genetic susceptibility to chronic kidney disease (CKD). Identification of possible causative mutations may serve as therapeutic targets and diagnostic markers for CKD. Thus, we adopted both sequence and sequence-structure based SNP analysis algorithm in order to overcome the limitations of both methods. We explore the functional significance towards the prediction of risky SNPs associated with CKD. We assessed the performance of four widely used pathogenicity prediction methods. We compared the performances of the programs using Mathews correlation Coefficient ranged from poor (MCC = 0.39) to reasonably good (MCC = 0.42). However, we got the best results for the combined sequence and structure based analysis method (MCC = 0.45). 4 SNPs from FGF23 gene, 8 SNPs from VDR gene and 13 SNPs from CYP24A1 gene were predicted to be the causative agents for human diseases. This study will be helpful in selecting potential SNPs for experimental study from the SNP pool and also will reduce the cost for identification of potential SNPs as a genetic marker. |
format | Online Article Text |
id | pubmed-4833053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-48330532016-04-25 Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes Nagamani, Selvaraman Singh, Kh. Dhanachandra Muthusamy, Karthikeyan Meta Gene Article FGF23, CYP24A1 and VDR altogether play a significant role in genetic susceptibility to chronic kidney disease (CKD). Identification of possible causative mutations may serve as therapeutic targets and diagnostic markers for CKD. Thus, we adopted both sequence and sequence-structure based SNP analysis algorithm in order to overcome the limitations of both methods. We explore the functional significance towards the prediction of risky SNPs associated with CKD. We assessed the performance of four widely used pathogenicity prediction methods. We compared the performances of the programs using Mathews correlation Coefficient ranged from poor (MCC = 0.39) to reasonably good (MCC = 0.42). However, we got the best results for the combined sequence and structure based analysis method (MCC = 0.45). 4 SNPs from FGF23 gene, 8 SNPs from VDR gene and 13 SNPs from CYP24A1 gene were predicted to be the causative agents for human diseases. This study will be helpful in selecting potential SNPs for experimental study from the SNP pool and also will reduce the cost for identification of potential SNPs as a genetic marker. Elsevier 2016-03-31 /pmc/articles/PMC4833053/ /pubmed/27114920 http://dx.doi.org/10.1016/j.mgene.2016.03.005 Text en © 2016 Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Nagamani, Selvaraman Singh, Kh. Dhanachandra Muthusamy, Karthikeyan Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes |
title | Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes |
title_full | Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes |
title_fullStr | Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes |
title_full_unstemmed | Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes |
title_short | Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes |
title_sort | combined sequence and sequence-structure based methods for analyzing fgf23, cyp24a1 and vdr genes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833053/ https://www.ncbi.nlm.nih.gov/pubmed/27114920 http://dx.doi.org/10.1016/j.mgene.2016.03.005 |
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