Improving the gene structure annotation of the apicomplexan parasite Neospora caninum fulfils a vital requirement towards an in silico-derived vaccine.
Neospora caninum is an apicomplexan parasite which can cause abortion in cattle, instigating major economic burden. Vaccination has been proposed as the most cost-effective control measure to alleviate this burden. Consequently the overriding aspiration for N. caninum research is the identification and subsequent evaluation of vaccine candidates in animal models. To save time, cost and effort, it is now feasible to use an in silico approach for vaccine candidate prediction. Precise protein sequences, derived from the correct open reading frame, are paramount and arguably the most important factor determining the success or failure of this approach. The challenge is that publicly available N. caninum sequences are mostly derived from gene predictions. Annotated inaccuracies can lead to erroneously predicted vaccine candidates by bioinformatics programs. This study evaluates the current N. caninum annotation for potential inaccuracies. Comparisons with annotation from a closely related pathogen, Toxoplasma gondii, are also made to distinguish patterns of inconsistency. More importantly, a mRNA sequencing (RNA-Seq) experiment is used to validate the annotation. Potential discrepancies originating from a questionable start codon context and exon boundaries were identified in 1943 protein coding sequences. We conclude, where experimental data were available, that the majority of N. caninum gene sequences were reliably predicted. Nevertheless, almost 28% of genes were identified as questionable. Given the limitations of RNA-Seq, the intention of this study was not to replace the existing annotation but to support or oppose particular aspects of it. Ideally, many studies aimed at improving the annotation are required to build a consensus. We believe this study, in providing a new resource on gene structure and annotation, is a worthy contributor to this endeavour.
School of Medical and Molecular Sciences, University of Technology Sydney (UTS), 15 Broadway, Ultimo, NSW 2007, Australia. Electronic address: StephenJames.Goodswen@student.uts.edu.au.
Stephen J
SJ
Goodswen
School of Medical and Molecular Sciences, University of Technology Sydney (UTS), 15 Broadway, Ultimo, NSW 2007, Australia.
Joel L N
JL
Barratt
School of Software, Faculty of Engineering and Information Technology and the Centre for Quantum Computation and Intelligent Systems at the University of Technology Sydney (UTS), 15 Broadway, Ultimo, NSW 2007, Australia.
Paul J
PJ
Kennedy
School of Medical and Molecular Sciences, University of Technology Sydney (UTS), 15 Broadway, Ultimo, NSW 2007, Australia.
John T
JT
Ellis
D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000469:parasitology* / Q000517:prevention & control; D003048:Coccidiosis / Q000469:parasitology / Q000517:prevention & control / Q000662:veterinary*; D003198:Computer Simulation; D058977:Molecular Sequence Annotation; D018688:Neospora / Q000235:genetics* / Q000276:immunology; D015800:Protozoan Proteins / Q000235:genetics* / Q000276:immunology; D016052:Protozoan Vaccines / Q000235:genetics* / Q000276:immunology
D015800:Protozoan Proteins; D016052:Protozoan Vaccines
Comparative genomics; Gene annotation; In silico vaccine discovery; Neospora caninum; RNA-Seq; Toxoplasma gondii