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Predicting candidate genes for human deafness disorders: a bioinformatics approach

BACKGROUND: There are more than 50 genes for autosomal dominant and autosomal recessive nonsyndromic hereditary deafness that are yet to be cloned. The human genome sequence and expression profiles of transcripts in the inner ear have aided positional cloning approaches. The knowledge of protein int...

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Autores principales: Alsaber, Rami, Tabone, Christopher J, Kandpal, Raj P
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1564145/
https://www.ncbi.nlm.nih.gov/pubmed/16854223
http://dx.doi.org/10.1186/1471-2164-7-180
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author Alsaber, Rami
Tabone, Christopher J
Kandpal, Raj P
author_facet Alsaber, Rami
Tabone, Christopher J
Kandpal, Raj P
author_sort Alsaber, Rami
collection PubMed
description BACKGROUND: There are more than 50 genes for autosomal dominant and autosomal recessive nonsyndromic hereditary deafness that are yet to be cloned. The human genome sequence and expression profiles of transcripts in the inner ear have aided positional cloning approaches. The knowledge of protein interactions offers additional advantages in selecting candidate genes within a mapped region. RESULTS: We have employed a bioinformatic approach to assemble the genes encoded by genomic regions that harbor various deafness loci. The genes were then in silico analyzed for their candidacy by expression pattern and ability to interact with other proteins. Such analyses have narrowed a list of 2400 genes from suspected regions of the genome to a manageable number of about 140 for further analysis. CONCLUSION: We have established a list of strong candidate genes encoded by the regions linked to various nonsyndromic hereditary hearing loss phenotypes by using a novel bioinformatic approach. The candidates presented here provide a starting point for mutational analysis in well-characterized families along with genetic linkage to refine the loci. The advantages and shortcomings of this bioinformatic approach are discussed.
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spelling pubmed-15641452006-09-13 Predicting candidate genes for human deafness disorders: a bioinformatics approach Alsaber, Rami Tabone, Christopher J Kandpal, Raj P BMC Genomics Methodology Article BACKGROUND: There are more than 50 genes for autosomal dominant and autosomal recessive nonsyndromic hereditary deafness that are yet to be cloned. The human genome sequence and expression profiles of transcripts in the inner ear have aided positional cloning approaches. The knowledge of protein interactions offers additional advantages in selecting candidate genes within a mapped region. RESULTS: We have employed a bioinformatic approach to assemble the genes encoded by genomic regions that harbor various deafness loci. The genes were then in silico analyzed for their candidacy by expression pattern and ability to interact with other proteins. Such analyses have narrowed a list of 2400 genes from suspected regions of the genome to a manageable number of about 140 for further analysis. CONCLUSION: We have established a list of strong candidate genes encoded by the regions linked to various nonsyndromic hereditary hearing loss phenotypes by using a novel bioinformatic approach. The candidates presented here provide a starting point for mutational analysis in well-characterized families along with genetic linkage to refine the loci. The advantages and shortcomings of this bioinformatic approach are discussed. BioMed Central 2006-07-19 /pmc/articles/PMC1564145/ /pubmed/16854223 http://dx.doi.org/10.1186/1471-2164-7-180 Text en Copyright © 2006 Alsaber et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Alsaber, Rami
Tabone, Christopher J
Kandpal, Raj P
Predicting candidate genes for human deafness disorders: a bioinformatics approach
title Predicting candidate genes for human deafness disorders: a bioinformatics approach
title_full Predicting candidate genes for human deafness disorders: a bioinformatics approach
title_fullStr Predicting candidate genes for human deafness disorders: a bioinformatics approach
title_full_unstemmed Predicting candidate genes for human deafness disorders: a bioinformatics approach
title_short Predicting candidate genes for human deafness disorders: a bioinformatics approach
title_sort predicting candidate genes for human deafness disorders: a bioinformatics approach
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1564145/
https://www.ncbi.nlm.nih.gov/pubmed/16854223
http://dx.doi.org/10.1186/1471-2164-7-180
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