Molecular Evolution of the Transmembrane Domains of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of integral membrane proteins vital for signaling and are important targets for pharmaceutical intervention in humans. Previously, we identified a group of ten amino acid positions (called key positions), within the seven transmembrane domain (7TM) interhelical region, which had high mutual information with each other and many other positions in the 7TM. Here, we estimated the evolutionary selection pressure at those key positions. We found that the key positions of receptors for small molecule natural ligands were under strong negative selection. Receptors naturally activated by lipids had weaker negative selection in general when compared to small molecule-activated receptors. Selection pressure varied widely in peptide-activated receptors. We used this observation to predict that a subgroup of orphan GPCRs not under strong selection may not possess a natural small-molecule ligand. In the subgroup of MRGX1-type GPCRs, we identified a key position, along with two non-key positions, under statistically significant positive selection

Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families

Ion Torrent sequencing for conducting genome-wide scans for mutation mapping analysis

Mutation mapping in mice can be readily accomplished by genome wide segregation analysis of polymorphic DNA markers. In this study, we showed the efficacy of Ion Torrent next generation sequencing for conducting genome-wide scans to map and identify a mutation causing congenital heart disease in a mouse mutant, Bishu, recovered from a mouse mutagenesis screen. The Bishu mutant line generated in a C57BL/6J (B6) background was intercrossed with another inbred strain, C57BL/10J (B10), and the resulting B6/B10 hybrid offspring were intercrossed to generate mutants used for the mapping analysis. For each mutant sample, a panel of 123 B6/B10 polymorphic SNPs distributed throughout the mouse genome was PCR amplified, bar coded, and then pooled to generate a single library used for Ion Torrent sequencing. Sequencing carried out using the 314 chip yielded > 600,000 usable reads. These were aligned and mapped using a custom bioinformatics pipeline. Each SNP was sequenced to a depth > 500x, allowing accurate automated calling of the B6/B10 genotypes. This analysis mapped the mutation in Bishu to an interval on the proximal region of mouse chromosome 4. This was confirmed by parallel capillary sequencing of the 123 polymorphic SNPs. Further analysis of genes in the map interval identified a splicing mutation in Dnaic1 (c.204+1G > A), an intermediate chain dynein, as the disease causing mutation in Bishu. Overall, our experience shows Ion Torrent amplicon sequencing is high throughput and cost effective for conducting genome-wide mapping analysis and is easily scalable for other high volume genotyping analyses