Cargando…

MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India

BACKGROUND: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are X-linked recessive disorders caused by mutations in the DMD gene. The aim of this study was to predict the effect of gene mutations on the dystrophin protein and study its impact on clinical phenotype. METHODS: In...

Descripción completa

Detalles Bibliográficos
Autores principales: Deepha, Sekar, Vengalil, Seena, Preethish-Kumar, Veeramani, Polavarapu, Kiran, Nalini, Atchayaram, Gayathri, Narayanappa, Purushottam, Meera
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470271/
https://www.ncbi.nlm.nih.gov/pubmed/28610567
http://dx.doi.org/10.1186/s12881-017-0431-6
_version_ 1783243744507592704
author Deepha, Sekar
Vengalil, Seena
Preethish-Kumar, Veeramani
Polavarapu, Kiran
Nalini, Atchayaram
Gayathri, Narayanappa
Purushottam, Meera
author_facet Deepha, Sekar
Vengalil, Seena
Preethish-Kumar, Veeramani
Polavarapu, Kiran
Nalini, Atchayaram
Gayathri, Narayanappa
Purushottam, Meera
author_sort Deepha, Sekar
collection PubMed
description BACKGROUND: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are X-linked recessive disorders caused by mutations in the DMD gene. The aim of this study was to predict the effect of gene mutations on the dystrophin protein and study its impact on clinical phenotype. METHODS: In this study, 415 clinically diagnosed patients were tested for mutations by Multiplex ligation dependent probe amplification (MLPA). Muscle biopsy was performed in 34 patients with negative MLPA. Phenotype-genotype correlation was done using PROVEAN, hydrophobicity and eDystrophin analysis. We have utilized bioinformatics tools in order to evaluate the observed mutations both at the level of primary as well as secondary structure. RESULTS: Mutations were identified in 75.42% cases, of which there were deletions in 91.6% and duplications in 8.30%. As per the reading frame rule, 84.6% out-of frame and 15.3% in-frame mutations were noted. Exon 50 was the most frequently deleted exon and the exon 45–52 region was the hot-spot for deletions in this cohort. There was no correlation noted between age of onset or creatine kinase (CK) values with extent of gene mutation. The PROVEAN analysis showed a deleterious effect in 94.5% cases and a neutral effect in 5.09% cases. Mutations in exon 45–54 (out of frame) and exon 46–54 (in-frame) regions in the central rod domain of dystrophin showed more negative scores compared to other domains in the present study. Hydrophobicity profile analysis showed that the hydrophobic regions I & III were equally affected. Analysis of deletions in hinge III hydrophobic region by the eDystrophin programme also predicted a hybrid repeat seen to be associated with a BMD like disease progression, thus making the hinge III region relatively tolerant to mutations. CONCLUSIONS: We found that, while the predictions made by the software utilized might have overall significance, the results were not convincing on a case by case basis. This reflects the inadequacy of the currently available tools and also underlines the possible inadequacy of MLPA to detect other minor mutations that might enhance or suppress the effect of the primary mutation in this large gene. Next Generation Sequencing or targeted Sanger sequencing on a case by case basis might improve phenotype- genotype correlation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12881-017-0431-6) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5470271
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-54702712017-06-19 MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India Deepha, Sekar Vengalil, Seena Preethish-Kumar, Veeramani Polavarapu, Kiran Nalini, Atchayaram Gayathri, Narayanappa Purushottam, Meera BMC Med Genet Research Article BACKGROUND: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are X-linked recessive disorders caused by mutations in the DMD gene. The aim of this study was to predict the effect of gene mutations on the dystrophin protein and study its impact on clinical phenotype. METHODS: In this study, 415 clinically diagnosed patients were tested for mutations by Multiplex ligation dependent probe amplification (MLPA). Muscle biopsy was performed in 34 patients with negative MLPA. Phenotype-genotype correlation was done using PROVEAN, hydrophobicity and eDystrophin analysis. We have utilized bioinformatics tools in order to evaluate the observed mutations both at the level of primary as well as secondary structure. RESULTS: Mutations were identified in 75.42% cases, of which there were deletions in 91.6% and duplications in 8.30%. As per the reading frame rule, 84.6% out-of frame and 15.3% in-frame mutations were noted. Exon 50 was the most frequently deleted exon and the exon 45–52 region was the hot-spot for deletions in this cohort. There was no correlation noted between age of onset or creatine kinase (CK) values with extent of gene mutation. The PROVEAN analysis showed a deleterious effect in 94.5% cases and a neutral effect in 5.09% cases. Mutations in exon 45–54 (out of frame) and exon 46–54 (in-frame) regions in the central rod domain of dystrophin showed more negative scores compared to other domains in the present study. Hydrophobicity profile analysis showed that the hydrophobic regions I & III were equally affected. Analysis of deletions in hinge III hydrophobic region by the eDystrophin programme also predicted a hybrid repeat seen to be associated with a BMD like disease progression, thus making the hinge III region relatively tolerant to mutations. CONCLUSIONS: We found that, while the predictions made by the software utilized might have overall significance, the results were not convincing on a case by case basis. This reflects the inadequacy of the currently available tools and also underlines the possible inadequacy of MLPA to detect other minor mutations that might enhance or suppress the effect of the primary mutation in this large gene. Next Generation Sequencing or targeted Sanger sequencing on a case by case basis might improve phenotype- genotype correlation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12881-017-0431-6) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-13 /pmc/articles/PMC5470271/ /pubmed/28610567 http://dx.doi.org/10.1186/s12881-017-0431-6 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Deepha, Sekar
Vengalil, Seena
Preethish-Kumar, Veeramani
Polavarapu, Kiran
Nalini, Atchayaram
Gayathri, Narayanappa
Purushottam, Meera
MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
title MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
title_full MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
title_fullStr MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
title_full_unstemmed MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
title_short MLPA identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from India
title_sort mlpa identification of dystrophin mutations and in silico evaluation of the predicted protein in dystrophinopathy cases from india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470271/
https://www.ncbi.nlm.nih.gov/pubmed/28610567
http://dx.doi.org/10.1186/s12881-017-0431-6
work_keys_str_mv AT deephasekar mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia
AT vengalilseena mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia
AT preethishkumarveeramani mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia
AT polavarapukiran mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia
AT naliniatchayaram mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia
AT gayathrinarayanappa mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia
AT purushottammeera mlpaidentificationofdystrophinmutationsandinsilicoevaluationofthepredictedproteinindystrophinopathycasesfromindia