five

Gene Atlasing of Digestive and Reproductive Tissues in Schistosoma mansoni

收藏
Figshare2016-01-18 更新2026-04-29 收录
下载链接:
https://figshare.com/articles/dataset/Gene_Atlasing_of_Digestive_and_Reproductive_Tissues_in____Schistosoma_mansoni_/137349
下载链接
链接失效反馈
官方服务:
资源简介:
BackgroundWhile considerable genomic and transcriptomic data are available for Schistosoma mansoni, many of its genes lack significant annotation. A transcriptomic study of individual tissues and organs of schistosomes could play an important role in functional annotation of the unknown genes, particularly by providing rapid localisation data and thus giving insight into the potential roles of these molecules in parasite development, reproduction and homeostasis, and in the complex host-parasite interaction. Methodology/Principal FindingsQuantification of gene expression in tissues of S. mansoni was achieved by a combination of laser microdissection microscopy (LMM) and oligonucleotide microarray analysis. We compared the gene expression profile of the adult female gastrodermis and male and female reproductive tissues with whole worm controls. The results revealed a total of 393 genes (contigs) that were up-regulated two-fold or more in the gastrodermis, 4,450 in the ovary, 384 in the vitelline tissues of female parasites, and 2,171 in the testes. We have also supplemented these data with the identification of highly expressed genes in different regions of manually dissected male and female S. mansoni. Though relatively crude, this dissection strategy provides low resolution localisation data for critical regions of the adult parasites that are not amenable to LMM isolation. ConclusionsThis is the first detailed transcriptomic study of the reproductive tissues and gastrodermis of S. mansoni. The results obtained will help direct future research on the functional aspects of these tissues, expediting the characterisation of currently unannotated gene products of S. mansoni and the discovery of new drug and vaccine targets.
创建时间:
2016-01-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作