TY  - JOUR
A1  - Leshchiner, Ignat
A1  - Alexa, Kristen
A1  - Kelsey, Peter
A1  - Adzhubei, Ivan
A1  - Austin, Christina
A1  - Cooney, Jeffrey
A1  - Anderson, Heidi
A1  - King, Matthew
A1  - Stottmann, Rolf W
A1  - Ha, Seungshin
A1  - Drummond, Ian
A1  - Paw, Barry H.
A1  - North, Trista
A1  - Beier, David
A1  - Goessling, Wolfram
A1  - Sunyaev, Shamil
T1  - Mutation mapping and identification by whole genome sequencing
Y1  - 2012/05/03 
JF  - Genome Research 
JO  - Genome Research 
DO  - 10.1101/gr.135541.111 
SP  - gr.135541.111 
UR  - http://genome.cshlp.org/content/early/2012/06/14/gr.135541.111.abstract 
N2  - 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. 
ER  -