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Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map
Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2813264/ https://www.ncbi.nlm.nih.gov/pubmed/20126534 http://dx.doi.org/10.1371/journal.pgen.1000831 |
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author | Khil, Pavel P. Camerini-Otero, R. Daniel |
author_facet | Khil, Pavel P. Camerini-Otero, R. Daniel |
author_sort | Khil, Pavel P. |
collection | PubMed |
description | Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers. |
format | Text |
id | pubmed-2813264 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28132642010-02-03 Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map Khil, Pavel P. Camerini-Otero, R. Daniel PLoS Genet Research Article Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers. Public Library of Science 2010-01-29 /pmc/articles/PMC2813264/ /pubmed/20126534 http://dx.doi.org/10.1371/journal.pgen.1000831 Text en This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Khil, Pavel P. Camerini-Otero, R. Daniel Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map |
title | Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map |
title_full | Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map |
title_fullStr | Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map |
title_full_unstemmed | Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map |
title_short | Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map |
title_sort | genetic crossovers are predicted accurately by the computed human recombination map |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2813264/ https://www.ncbi.nlm.nih.gov/pubmed/20126534 http://dx.doi.org/10.1371/journal.pgen.1000831 |
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