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.

Very few methods address the problem of predicting beta-barrel membrane proteins directly from sequence. One reason is that only very few high-resolution structures for transmembrane beta-barrel (TMB) proteins have been determined thus far. Here we introduced the design, statistics and results of a novel profile-based hidden Markov model for the prediction and discrimination of TMBs. The method carefully attempts to avoid over-fitting the sparse experimental data. While our model training and scoring procedures were very similar to a recently published work, the architecture and structure-based labelling were significantly different. In particular, we introduced a new definition of beta- hairpin motifs, explicit state modelling of transmembrane strands, and a log-odds whole-protein discrimination score. The resulting method reached an overall four-state (up-, down-strand, periplasmic-, outer-loop) accuracy as high as 86%. Furthermore, accurately discriminated TMB from non-TMB proteins (45% coverage at 100% accuracy). This high precision enabled the application to 72 entirely sequenced Gram-negative bacteria. We found over 164 previously uncharacterized TMB proteins at high confidence. Database searches did not implicate any of these proteins with membranes. We challenge that the vast majority of our 164 predictions will eventually be verified experimentally. All proteome predictions and the PROFtmb prediction method are available at http://www.rostlab.org/ services/PROFtmb/.

We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. Overall, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling.

Whole-genome sequencing (WGS) of organisms displaying a specific mutant phenotype is a powerful approach to identify the genetic determinants of a plethora of biological processes. We have previously validated the feasibility of this approach by identifying a point-mutated locus responsible for a specific phenotype, observed in an ethyl methanesulfonate (EMS)-mutagenized Caenorhabditis elegans strain. Here we describe the genome-wide mutational profile of 17 EMS-mutagenized genomes as assessed with a bioinformatic pipeline, called MAQGene. Surprisingly, we find that while outcrossing mutagenized strains does reduce the total number of mutations, a striking mutational load is still observed even in outcrossed strains. Such genetic complexity has to be taken into account when establishing a causative relationship between genotype and phenotype. Even though unintentional, the 17 sequenced strains described here provide a resource of allelic variants in almost 1000 genes, including 62 premature stop codons, which represent candidate knockout alleles that will be of further use for the C. elegans community to study gene function.