Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We pr...

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Autores principales:	Eric Letouzé, Aliou Sow, Fabien Petel, Roberto Rosati, Bonald C Figueiredo, Nelly Burnichon, Anne-Paule Gimenez-Roqueplo, Enzo Lalli, Aurélien de Reyniès
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/59cabf94aff54422bcd59728db3dbfc8
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id	oai:doaj.org-article:59cabf94aff54422bcd59728db3dbfc8
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spelling	oai:doaj.org-article:59cabf94aff54422bcd59728db3dbfc82021-11-18T07:19:56ZIdentity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.1932-620310.1371/journal.pone.0035897https://doaj.org/article/59cabf94aff54422bcd59728db3dbfc82012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22567117/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the "missing" heritability in cancer. This method is freely available and can be used online at the FounderTracker website.Eric LetouzéAliou SowFabien PetelRoberto RosatiBonald C FigueiredoNelly BurnichonAnne-Paule Gimenez-RoqueploEnzo LalliAurélien de ReynièsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 5, p e35897 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Eric Letouzé Aliou Sow Fabien Petel Roberto Rosati Bonald C Figueiredo Nelly Burnichon Anne-Paule Gimenez-Roqueplo Enzo Lalli Aurélien de Reyniès Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.
description	Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the "missing" heritability in cancer. This method is freely available and can be used online at the FounderTracker website.
format	article
author	Eric Letouzé Aliou Sow Fabien Petel Roberto Rosati Bonald C Figueiredo Nelly Burnichon Anne-Paule Gimenez-Roqueplo Enzo Lalli Aurélien de Reyniès
author_facet	Eric Letouzé Aliou Sow Fabien Petel Roberto Rosati Bonald C Figueiredo Nelly Burnichon Anne-Paule Gimenez-Roqueplo Enzo Lalli Aurélien de Reyniès
author_sort	Eric Letouzé
title	Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.
title_short	Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.
title_full	Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.
title_fullStr	Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.
title_full_unstemmed	Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.
title_sort	identity by descent mapping of founder mutations in cancer using high-resolution tumor snp data.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/59cabf94aff54422bcd59728db3dbfc8
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Identity by descent mapping of founder mutations in cancer using high-resolution tumor SNP data.

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