Whole genome sequencing (WGS) allows researchers to pinpoint genetic differences between individuals and significantly shortcuts the costly and time-consuming part of forward genetic analysis in model organism systems. Currently, the most effortintensive part of WGS is the bioinformatic analysis of the relatively short reads generated by second generation sequencing platforms. We describe here a novel, easily accessible and cloud-based pipeline, called CloudMap, which greatly simplifies the analysis of mutant genome sequences. Available on the Galaxy web platform, CloudMap requires no software installation when run on the cloud, but it can also be run locally or via Amazon's Elastic Compute Cloud (EC2) service. CloudMap uses a series of predefined workflows to pinpoint sequence variations in animal genomes, such as those of premutagenized and mutagenized Caenorhabditis elegans strains. In combination with a variant-based mapping procedure, CloudMap allows users to sharply define genetic map intervals graphically and to retrieve very short lists of candidate variants with a few simple clicks. Automated workflows and extensive video user guides are available to detail the individual analysis steps performed (http://usegalaxy.org/cloudmap). We demonstrate the utility of CloudMap for WGS analysis of C. elegans and Arabidopsis genomes and describe how other organisms (e.g., Zebrafish and Drosophila) can easily be accommodated by this software platform. To accommodate rapid analysis of many mutants from large-scale genetic screens, CloudMap contains an in silico complementation testing tool that allows users to rapidly identify instances where multiple alleles of the same gene are present in the mutant collection. Lastly, we describe the application of a novel mapping/WGS method ("Variant Discovery Mapping") that does not rely on a defined polymorphic mapping strain, and we integrate the application of this method into CloudMap. CloudMap tools and documentation are continually updated at http://usegalaxy.org/cloudmap. W HOLE genome sequencing (WGS) represents the fastest and most cost-effective way to map phenotypecausing mutations in model organisms such as Caenorhabditis elegans (Hobert 2010). However, analysis of the resulting data is complex and requires specialized bioinformatics knowledge not readily available in most labs. Furthermore, the flood of WGS data has raised new concerns about both computing power needs and data storage capacities. Researchers may be unwilling to commit resources to computers or software in the fear that they may be quickly replaced or will not be interoperable with existing or future systems. As WGS costs continue to plummet and the technology becomes pervasive, all laboratories that use genetic analysis will be faced with these problems.The basic premise of genetic mapping is simple: out of the millions of base positions in a mutagenized, sequenced genome, we aim to find the region of genome that is linked to the phenotype-causing mutation and identify the causal variant. O...

The choice of using one of many possible neurotransmitter systems is a critical step in defining the identity of an individual neuron type. We show here that the key defining feature of glutamatergic neurons, the vesicular glutamate transporter EAT-4/VGLUT is expressed in 38 of the 118 anatomically defined neuron classes of the C.elegans nervous system. We show that eat-4/VGLUT expression is controlled in a modular manner, with distinct cis-regulatory modules driving expression in distinct glutamatergic neuron classes. We identify 13 different transcription factors, 11 of them homeodomain proteins, that act in specific combinations in 25 different glutamatergic neuron classes to initiate and maintain eat-4/VGLUT expression. We show that the adoption of a glutamatergic phenotype is linked to the adoption of other terminal identity features of a neuron, including cotransmitter phenotypes. Examination of mouse orthologs of these homeodomain proteins resulted in the identification of mouse LHX1 as a regulator of glutamatergic neurons in the brainstem.

Whole-genome sequencing (WGS) is becoming a fast and cost-effective method to pinpoint molecular lesions in mutagenized genetic model systems, such as Caenorhabditis elegans. As mutagenized strains contain a significant mutational load, it is often still necessary to map mutations to a chromosomal interval to elucidate which of the WGS-identified sequence variants is the phenotype-causing one. We describe here our experience in setting up and testing a simple strategy that incorporates a rapid SNP-based mapping step into the WGS procedure. In this strategy, a mutant retrieved from a genetic screen is crossed with a polymorphic C. elegans strain, individual F2 progeny from this cross is selected for the mutant phenotype, the progeny of these F2 animals are pooled and then whole-genome-sequenced. The density of polymorphic SNP markers is decreased in the region of the phenotype-causing sequence variant and therefore enables its identification in the WGS data. As a proof of principle, we use this strategy to identify the molecular lesion in a mutant strain that produces an excess of dopaminergic neurons. We find that the molecular lesion resides in the Pax-6/Eyeless ortholog vab-3. The strategy described here will further reduce the time between mutant isolation and identification of the molecular lesion.