G3 Genes Genomes GeneticsGenomicsPeer-reviewed journal article
De novo transcriptome characterization of a sterilizing trematode parasite (Microphallus sp.) from two species of New Zealand snails
Abstract
Snail-borne trematodes represent a large, diverse, and evolutionarily, ecologically, and medically important group of parasites, often imposing strong selection on their hosts and causing host morbidity and mortality. Even so, there are very few genomic and transcriptomic resources available for this important animal group. We help to fill this gap by providing transcriptome resources from trematode metacercariae infecting two congeneric snail species, Potamopyrgus antipodarum and P. estuarinus. This genus of New Zealand snails has gained prominence in large part through the development of P. antipodarum and its sterilizing trematode parasite Microphallus livelyi into a textbook model for host-parasite coevolutionary interactions in nature. By contrast, the interactions between Microphallus trematodes and P. estuarinus, an estuary-inhabiting species closely related to the freshwater P. antipodarum, are relatively unstudied. Here, we provide the first annotated transcriptome assemblies from Microphallus isolated from P. antipodarum and P. estuarinus. We also use these transcriptomes to produce genomic resources that will be broadly useful to those interested in host-parasite coevolution, local adaption, and molecular evolution and phylogenetics of this and other snail-trematode systems. Analyses of the two Microphallus transcriptomes revealed that the two trematode isolates are more genetically differentiated from one another than are M. livelyi infecting different populations of P. antipodarum, suggesting that the Microphallus infecting P. estuarinus represent a distinct lineage. We also provide a promising set of candidate genes likely involved in parasitic infection and response to salinity stress.
- organism: mouse
- organism: rat
- organism: zebrafish
- assay: bulk RNA-seq
- research focus: database / resource
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
- approach: experimental assay
- Citations
- 7
- FWCI
- 1.03
- Field percentile
- top 23%
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