De novo transcriptome assembly of a facultative parasitic nematode Pelodera (syn. Rhabditis) strongyloides
Zhang, M., Heikkinen, L., Knott, E., & Wong, G. (2019). De novo transcriptome assembly of a facultative parasitic nematode Pelodera (syn. Rhabditis) strongyloides. Gene, 710, 30-38. https://doi.org/10.1016/j.gene.2019.05.041
© 2019 Elsevier B.V.
Pelodera strongyloides is a generally free-living gonochoristic facultative nematode. The whole genomic sequence of P. strongyloides remains unknown but 4 small subunit ribosomal RNA (ssrRNA) gene sequences are available. This project launched a de novo transcriptome assembly with 100 bp paired-end RNA-seq reads from normal, starved and wet-plate cultured animals. Trinity assembly tool generated 104,634 transcript contigs with N50 contig being 2195 bp and average contig length at 1103 bp. Transcriptome BLASTX matching results of five nematodes (C. elegans, Strongyloides stercoralis, Necator americanus, Trichuris trichiura, and Pristionchus pacificus) were consistent with their evolutionary relationships. Sixteen genes were identified to be homologous to key elements of the C. elegans RNA interference system, such as Dicer, Argonaute, RNA-dependent RNA polymerase and double strand RNA transport proteins. In starved samples, we observed up-regulation of cuticle related genes and 3 dauer formation genes. Dauer morphology was captured with enlarged phasmid under light microscopy, and dauer and normal larvae counts in clumps had a Pearson's product-moment correlation of 0.805 with P-value = 0.0088. Our results demonstrate that P. strongyloides could be used for studying nematode-related human or pet parasitic diseases. The sequenced assembled transcriptome reported here may be useful to understand the evolution of parasitism in Nematoda. ...
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Related funder(s)Academy of Finland
Funding program(s)Research post as Academy Research Fellow, AoF
Additional information about fundingThis research was supported by the Faculty of Health Sciences, Universidade de Macau (MYRG2016-00101-FHS) and the Academy of Finland (Project 258365 to KEK). Computational analyses were supported by High Performance Computing Cluster (HPC Cluster) in University of Macau and super cluster taito in CSC, Finnish IT Center for Science.
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