BMC Infectious Diseases (Oct 2016)
Deep, multi-stage transcriptome of the schistosomiasis vector Biomphalaria glabrata provides platform for understanding molluscan disease-related pathways
Abstract
Abstract Background The gastropod mollusc Biomphalaria glabrata is well known as a vector for the tropical disease schistosomiasis, which affects nearly 200 million people worldwide. Despite intensive study, our understanding of the genetic basis of B. glabrata development, growth and disease resistance is constrained by limited genetic resources, constraints for which next-generation sequencing methods provide a ready solution. Methods Illumina sequencing and de novo assembly using the Trinity program was used to generate a high-quality transcriptomic dataset spanning the entirety of in ovo development in schistosomiasis-free B. glabrata. This was subjected to automated (KEGG, BLAST2GO) and manual annotation efforts, allowing insight into the gene complements of this species in a number of contexts. Results Excellent dataset recovery was observed, with 133,084 contigs produced of mean size 2219.48 bp. 80,952 (60.8 %) returned a BLASTx hit with an E value of less than 10-3, and 74,492 (55.97 %) were either mapped or assigned a GO identity using the BLAST2GO program. The CEGMA set of core eukaryotic genes was found to be 99.6 % present, indicating exceptional transcriptome completeness. We were able to identify a wealth of disease-pathway related genes within our dataset, including the Wnt, apoptosis and Notch pathways. This provides an invaluable reference point for further work into molluscan development and evolution, for studying the impact of schistosomiasis in this species, and perhaps providing targets for the treatment of this widespread disease. Conclusions Here we present a deep transcriptome of an embryonic sample of schistosomiasis-free B. glabrata, presenting a comprehensive dataset for comparison to disease-affected specimens and from which conclusions can be drawn about the genetics of this widespread medical model. Furthermore, the dataset provided by this sequencing provides a useful reference point for comparison to other mollusc species, which can be used to better understand the evolution of this commercially, ecologically and medically important phylum.
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