Large scale in silico prediction of putative rhodopsin and secretin G-coupled protein receptors (GPCRs) across multiple decapod species using a hybrid clustering/phylogenetics approach

Abstract

Order Decapoda consists of more than 8,000 species of crustaceans (phylum Arthropoda) that include shrimps, lobsters, crayfish, crab.... Despite their importance in terms of economic as well as ecological value, decapod crustacean’s neuropeptidergic components are currently not well characterized. The advancement of next generation sequencing technology has given the research community a tool to predict neuropeptides with an unprecedented pace. On the contrary, for neuropeptide’s receptors, specifically G protein-coupled receptors (GPCRs), the characterization process is hindered due to the complexity of their structure. The traditional approach using molecular phylogenetics has several weaknesses including (1): manual curated GPCRs list that might bias the result, (2) is time and computationally demanding in increment of data size. In the current study, we present a hybrid approach of clustering and phylogenetics analysis to annotate the putative GPCRs in 10 different decapod species including Cancer borealis, Carcinus maenas, Cherax quadricarinatus, Eriochier sinensis, Gecarcinus lateralis, Homarus americanus, Nephrops norvegicus, Palinurus ornatus, Penaeus monodon, and Procambarus clarkii. This approach included clustering of GPCRs based on similarity, then validating the results at a finer resolution using phylogenetic analysis. A web browser that allow data mining (which includes the sequence of GPCRs, expression pattern, as well as gene ontology annotation) is also presented. This study provides a framework to further understand the roles of GPCRs in decapod crustaceans. Given that identification and annotation of GPCRs is hindered by the complexity of this large gene family, our hybrid approach can streamline further discovery at a greater pace and higher accuracy