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

Authors: Guerrero, Felicito; KELLOGG, ANASTHASIA - University Of Texas - El Paso; OGREY, ALEXANDRIA - University Of Texas - El Paso; Heekin, Andrew; BARRERO, ROBERTO - Murdoch University; BELLGARD, MATTHEW - Murdoch University; DOWD, SCOT - Molecular Research Lp (MR DNA); LEUNG, MING-YING - University Of Texas - El Paso

Submitted to: Ticks and Tick Borne Diseases
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/18/2016
Publication Date: 7/1/2016
Citation: Guerrero, F., Kellogg, A., Ogrey, A., Heekin, A.M., Barrero, R., Bellgard, M., Dowd, S., Leung, M. 2016. Prediction of G protein-coupled receptor encoding sequences from the synganglion transcriptome of the cattle tick, Rhipicephalus microplus. Ticks and Tick Borne Diseases. 7(5):670-677.

Interpretive Summary: The cattle tick, Rhipicephalus (Boophilus) microplus, is a pest which causes multiple health complications in cattle. G-protein coupled receptors (GPCR) are members of a large family of proteins that are present in all higher organisms, including ticks. GPCRs are common active sites for drug compounds in human medicine and are good targets for developing novel tick control methods. However, GPCRs are difficult to identify using generally available methods of protein identification. GPCRs share only limited amino acid sequence similarity among comparative family members. However, all GPCRs share a common structure consisting of seven regions composed of helical structures that cross the cell membrane. Arthropod nervous systems are the target of many pesticides and GPCRs are common in neural tissues. We present an analysis of the transcriptome of cattle tick neural tissue, using various methods of identifying amino acid sequences that encode GPCRs.

Technical Abstract: 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 an interesting 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 from sequence data. TMHMM predicts the number of transmembrane helices in a protein sequence. GPCRpred predicts GPCRs using the dipeptide composition of the sequence. These two bioinformatic tools were applied to our transcriptome assembly of the cattle tick synganglion. Together, BLAST and Pfam identified 64 unique contigs as encoding partial or full length candidate cattle tick GPCRs. Collectively, TMHMM and GPCRpred identified a greater number of prospective GPCR candidates than BLAST and Pfam alone. This demonstrates that the addition of structurally-based and alignment-free bioinformatic approaches to a transcriptome analysis produces a greater collection of prospective GPCRs than an analysis based solely upon methodologies dependent upon sequence alignment and similarity.