Scientific ReportsBioinformaticsPeer-reviewed journal article
Analysis of ovarian transcriptomes reveals thousands of novel genes in the insect vector Rhodnius prolixus
Vitor Lima CoelhoiD, Tarcísio Fontenele de BritoiD, Ingrid Alexandre de Abreu BritoiD, Maira Arruda CardosoiD, Mateus Antonio BerniiD, Helena Marcolla AraujoiD, Michael SammethiD, Attilio PaneiD
Abstract
Rhodnius prolixus is a Triatominae insect species and a primary vector of Chagas disease. The genome of R. prolixus has been recently sequenced and partially assembled, but few transcriptome analyses have been performed to date. In this study, we describe the stage-specific transcriptomes obtained from previtellogenic stages of oogenesis and from mature eggs. By analyzing ~228 million paired-end RNA-Seq reads, we significantly improved the current genome annotations for 9,206 genes. We provide extended 5 and 3 UTRs, complete Open Reading Frames, and alternative transcript variants. Strikingly, using a combination of genome-guided and de novo transcriptome assembly we found more than two thousand novel genes, thus increasing the number of genes in R. prolixus from 15,738 to 17,864. We used the improved transcriptome to investigate stage-specific gene expression profiles during R. prolixus oogenesis. Our data reveal that 11,127 genes are expressed in the early previtellogenic stage of oogenesis and their transcripts are deposited in the developing egg including key factors regulating germline development, genome integrity, and the maternal-zygotic transition. In addition, GO term analyses show that transcripts encoding components of the steroid hormone receptor pathway, cytoskeleton, and intracellular signaling are abundant in the mature eggs, where they likely control early embryonic development upon fertilization. Our results significantly improve the R. prolixus genome and transcriptome and provide novel insight into oogenesis and early embryogenesis in this medically relevant insect.
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- approach: matrix factorization
- Citations
- 29
- FWCI
- 1.65
- Field percentile
- top 16%
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