An update on mutant identification by combined SNP mapping/whole genome sequencing and CloudMap data analysis

Our lab has previously developed a combination of single-step SNP mapping and whole ge-nome sequencing (WGS) methods to pinpoint phenotype-causing sequence variants (Doitsidou et al., 2010). The mapping part of the single-step procedure is essential to separate the phenotype-causing, mutagen-induced sequence variant from background sequence variants. WGS data can be analyzed with CloudMap, a free, cloud-based software analysis tool that we recently developed (Minevich et al., 2012). We have previously provided proof-of-concept studies for the use of CloudMap, and we report here our experience with using CloudMap on a routine basis. We have found over the last two years that the SNP/WGS strategy and ensuing CloudMap-based data analysis can reproducibly and accurately pinpoint phenotype-causing mutations to mapping regions as small as 0.5 Mb and that the method can work with very few recombinants. Fig. 1 shows the mapping plots from a selection of 16 EMS mutagenized strains from 8 different EMS-induced screens for loss of neuronal identity (thanks to many members of the Hobert lab for providing the mapping data). The talles