Mutation mapping and identification by whole genome sequencing
- Ignat Leshchiner1,
- Kristen Alexa1,
- Peter Kelsey1,
- Ivan Adzhubei1,
- Christina Austin2,
- Jeffrey Cooney1,
- Heidi Anderson1,
- Matthew King1,
- Rolf Stottman1,
- Seungshin Ha1,
- Ian Drummond3,
- Barry H. Paw1,
- Trista North4,
- David Beier5,
- Wolfram Goessling5 and
- Shamil Sunyaev1,6
- 1 Brigham & Women's Hospital, Harvard Medical School;
- 2 Massachusetts General Hospital, Harvard Medical School;
- 3 Massachusetts General Hospital;
- 4 Beth Israel Deaconess Medical Center, Harvard Medical School;
- 5 Brigham and Women's Hospital/Harvard Med Sch
- ↵* Corresponding author; email: ssunyaev{at}rics.bwh.harvard.edu
Abstract
Genetic mapping of mutations in model systems has facilitated the identification of genes contributing to fundamental biological processes, including human diseases. However, this approach has historically required the prior characterization of informative markers. Here, we report a fast and cost-effective method for genetic mapping using Next Generation Sequencing that combines single nucleotide polymorphism discovery, mutation localization, and potential identification of causal sequence variants. In contrast to prior approaches, we have developed a Hidden Markov Model to narrowly define the mutation area by inferring recombination breakpoints of chromosomes in the mutant pool. In addition, we created an interactive online software resource to facilitate automated analysis of sequencing data and demonstrate its utility in the zebrafish and mouse models. Our novel methodology and online tools will make Next Generation Sequencing an easily applicable resource for mutation mapping in all model systems.
- Received November 30, 2011.
- Accepted April 19, 2012.
- © 2012, Published by Cold Spring Harbor Laboratory Press
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/.
