Bioinformatic prediction of G protein-coupled receptor encoding sequences from the transcriptome of the foreleg, including the Haller's organ, of the cattle tick, Rhipicephalus australis.

The cattle tick of Australia, Rhipicephalus australis, is a vector for microbial parasites that cause serious bovine diseases. The Haller's organ, located in the tick's forelegs, is crucial for host detection and mating. To facilitate the development of new technologies for better control of this agricultural pest, we aimed to sequence and annotate the transcriptome of the R. australis forelegs and associated tissues, including the Haller's organ. As G protein-coupled receptors (GPCRs) are an important family of eukaryotic proteins studied as pharmaceutical targets in humans, we prioritized the identification and classification of the GPCRs expressed in the foreleg tissues. The two forelegs from adult R. australis were excised, RNA extracted, and pyrosequenced with 454 technology. Reads were assembled into unigenes and annotated by sequence similarity. Python scripts were written to find open reading frames (ORFs) from each unigene. These ORFs were analyzed by different GPCR prediction approaches based on sequence alignments, support vector machines, hidden Markov models, and principal component analysis. GPCRs consistently predicted by multiple methods were further studied by phylogenetic analysis and 3D homology modeling. From 4,782 assembled unigenes, 40,907 possible ORFs were predicted. Using Blastp, Pfam, GPCRpred, TMHMM, and PCA-GPCR, a basic set of 46 GPCR candidates were compiled and a phylogenetic tree was constructed. With further screening of tertiary structures predicted by RaptorX, 6 likely GPCRs emerged and the strongest candidate was classified by PCA-GPCR to be a GABAB receptor.

Prediction of G protein-coupled receptor encoding sequences from the synganglion transcriptome of the cattle tick, Rhipicephalus microplus.

The cattle tick, Rhipicephalus (Boophilus) microplus, is a pest which causes multiple health complications in cattle. The G protein-coupled receptor (GPCR) super-family presents a candidate target for developing novel tick control methods. However, GPCRs share limited sequence similarity among orthologous family members, and there is no reference genome available for R. microplus. This limits the effectiveness of alignment-dependent methods such as BLAST and Pfam for identifying GPCRs from R. microplus. However, GPCRs share a common structure consisting of seven transmembrane helices. We present an analysis of the R. microplus synganglion transcriptome using a combination of structurally-based and alignment-free methods which supplement the identification of GPCRs by sequence similarity. TMHMM predicts the number of transmembrane helices in a protein sequence. GPCRpred is a support vector machine-based method developed to predict and classify GPCRs using the dipeptide composition of a query amino acid sequence. These two bioinformatic tools were applied to our transcriptome assembly of the cattle tick synganglion. Together, BLAST and Pfam identified 85 unique contigs as encoding partial or full length candidate cattle tick GPCRs. Collectively, TMHMM and GPCRpred identified 27 additional GPCR candidates that BLAST and Pfam missed. This demonstrates that the addition of structurally-based and alignment-free bioinformatic approaches to transcriptome annotation and analysis produces a greater collection of prospective GPCRs than an analysis based solely upon methodologies dependent upon sequence alignment and similarity.