Mutation mapping and identification by whole-genome sequencing
- Ignaty Leshchiner1,
- Kristen Alexa1,
- Peter Kelsey1,
- Ivan Adzhubei1,
- Christina A. Austin-Tse2,
- Jeffrey D. Cooney3,
- Heidi Anderson3,
- Matthew J. King3,
- Rolf W. Stottmann1,
- Maija K. Garnaas1,
- Seungshin Ha1,
- Iain A. Drummond2,
- Barry H. Paw3,
- Trista E. North4,5,
- David R. Beier1,
- Wolfram Goessling1,5,6,7,8,9 and
- Shamil R. Sunyaev1,6,8,9
- 1Genetics Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA;
- 2Department of Genetics, Massachusetts General Hospital, Boston, Massachusetts 02114, USA;
- 3Hematology Division, Brigham and Women's Hospital, Harvard Medical School, Karp Family Research Building, Boston, Massachusetts 02114, USA;
- 4Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02115, USA;
- 5Harvard Stem Cell Institute, Cambridge, Massachusetts 02138, USA;
- 6Harvard/MIT Division of Health Sciences and Technology, Cambridge, Massachusetts 02139, USA;
- 7Gastrointestinal Cancer Center, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA
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↵8 These authors contributed equally to this work.
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.
Footnotes
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↵9 Corresponding authors
E-mail ssunyaev{at}rics.bwh.harvard.edu
E-mail wgoessling{at}partners.org
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.135541.111.
- Received November 30, 2011.
- Accepted April 19, 2012.
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/.
