five

Expression QTL mapping of Toxoplasma gondii genes, Tachyzoite array

收藏
NIAID Data Ecosystem2026-03-07 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11514
下载链接
链接失效反馈
官方服务:
资源简介:
Toxoplasma gondii is an intracellular parasite with a significant impact on human health, especially in cases where individuals are immunocompromised (e.g., due to HIV/AIDS). In Europe and North America only a few clonal genotypes appear to be responsible for the vast majority of Toxoplasma infections, and these clonotypes have been intensely studied to identify strain-specific phenotypes that may play a role in the manifestation of more severe disease. To identify and genetically map strain-specific differences in gene expression, we have carried out expression quantitative trait locus (eQTL) analysis on Toxoplasma gene expression phenotypes using spotted cDNA microarrays. This led to the identification of 16 Toxoplasma genes that had significant and mappable strain-specific variation in hybridization intensity. While the analysis should identify both cis and trans-mapping hybridization profiles, we only identified loci with strain-specific hybridization differences that are most likely due to differences in the locus itself (i.e., cis-mapping). Interestingly, a larger number of these cis-mapping genes than would be expected by chance encode either confirmed or predicted secreted proteins, many of which are known to localize to the specialized secretory organelles characteristic of members of the phylum Apicomplexa. For 6 of the cis-mapping loci we determined if the strain-specific hybridization differences were due to true transcriptional differences or rather strain-specific differences in hybridization efficiency because of extreme polymorphism and/or deletion, and we found examples of both scenarios. Keywords: eQTL mapping; virulence; Toxoplasma gondii 19 F1 progeny from a cross between a type II parent (PDS) and a type III parent (CTG) were used in RNA hybridizations to identify cis and trans-mapping loci regulating gene expression
创建时间:
2012-03-19
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