Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family

<p>Abstract</p> <p>Background</p> <p>The medical community requires computational tools that distinguish missense genetic differences having phenotypic impact within the vast number of sense mutations that do not. Tools that do this will become increasingly important fo...

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Main Authors: De Kee Danny W, Gaucher Eric A, Benner Steven A
Format: Article
Language:English
Published: BMC 2006-03-01
Series:BMC Genomics
Online Access:http://www.biomedcentral.com/1471-2164/7/44
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spelling doaj-1215c053d4f24595adb25e2593b4cf8c2020-11-24T22:38:20ZengBMCBMC Genomics1471-21642006-03-01714410.1186/1471-2164-7-44Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene familyDe Kee Danny WGaucher Eric ABenner Steven A<p>Abstract</p> <p>Background</p> <p>The medical community requires computational tools that distinguish missense genetic differences having phenotypic impact within the vast number of sense mutations that do not. Tools that do this will become increasingly important for those seeking to use human genome sequence data to predict disease, make prognoses, and customize therapy to individual patients.</p> <p>Results</p> <p>An approach, termed DETECTER, is proposed to identify sites in a protein sequence where amino acid replacements are likely to have a significant effect on phenotype, including causing genetic disease. This approach uses a model-dependent tool to estimate the normalized replacement rate at individual sites in a protein sequence, based on a history of those sites extracted from an evolutionary analysis of the corresponding protein family. This tool identifies sites that have higher-than-average, average, or lower-than-average rates of change in the lineage leading to the sequence in the population of interest. The rates are then combined with sequence data to determine the likelihoods that particular amino acids were present at individual sites in the evolutionary history of the gene family. These likelihoods are used to predict whether any specific amino acid replacements, if introduced at the site in a modern human population, would have a significant impact on fitness. The DETECTER tool is used to analyze the cystic fibrosis transmembrane conductance regulator (CFTR) gene family.</p> <p>Conclusion</p> <p>In this system, DETECTER retrodicts amino acid replacements associated with the cystic fibrosis disease with greater accuracy than alternative approaches. While this result validates this approach for this particular family of proteins only, the approach may be applicable to the analysis of polymorphisms generally, including SNPs in a human population.</p> http://www.biomedcentral.com/1471-2164/7/44
collection DOAJ
language English
format Article
sources DOAJ
author De Kee Danny W
Gaucher Eric A
Benner Steven A
spellingShingle De Kee Danny W
Gaucher Eric A
Benner Steven A
Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
BMC Genomics
author_facet De Kee Danny W
Gaucher Eric A
Benner Steven A
author_sort De Kee Danny W
title Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
title_short Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
title_full Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
title_fullStr Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
title_full_unstemmed Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
title_sort application of detecter, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2006-03-01
description <p>Abstract</p> <p>Background</p> <p>The medical community requires computational tools that distinguish missense genetic differences having phenotypic impact within the vast number of sense mutations that do not. Tools that do this will become increasingly important for those seeking to use human genome sequence data to predict disease, make prognoses, and customize therapy to individual patients.</p> <p>Results</p> <p>An approach, termed DETECTER, is proposed to identify sites in a protein sequence where amino acid replacements are likely to have a significant effect on phenotype, including causing genetic disease. This approach uses a model-dependent tool to estimate the normalized replacement rate at individual sites in a protein sequence, based on a history of those sites extracted from an evolutionary analysis of the corresponding protein family. This tool identifies sites that have higher-than-average, average, or lower-than-average rates of change in the lineage leading to the sequence in the population of interest. The rates are then combined with sequence data to determine the likelihoods that particular amino acids were present at individual sites in the evolutionary history of the gene family. These likelihoods are used to predict whether any specific amino acid replacements, if introduced at the site in a modern human population, would have a significant impact on fitness. The DETECTER tool is used to analyze the cystic fibrosis transmembrane conductance regulator (CFTR) gene family.</p> <p>Conclusion</p> <p>In this system, DETECTER retrodicts amino acid replacements associated with the cystic fibrosis disease with greater accuracy than alternative approaches. While this result validates this approach for this particular family of proteins only, the approach may be applicable to the analysis of polymorphisms generally, including SNPs in a human population.</p>
url http://www.biomedcentral.com/1471-2164/7/44
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