five

Epigenomic Modifications Predict Active Promoters and Gene Structure in Toxoplasma gondii

收藏
NIAID Data Ecosystem2026-03-06 收录
下载链接:
https://figshare.com/articles/dataset/Epigenomic_Modifications_Predict_Active_Promoters_and_Gene_Structure_in_Toxoplasma_gondii_/152164
下载链接
链接失效反馈
官方服务:
资源简介:
Mechanisms of gene regulation are poorly understood in Apicomplexa, a phylum that encompasses deadly human pathogens like Plasmodium and Toxoplasma. Initial studies suggest that epigenetic phenomena, including histone modifications and chromatin remodeling, have a profound effect upon gene expression and expression of virulence traits. Using the model organism Toxoplasma gondii, we characterized the epigenetic organization and transcription patterns of a contiguous 1% of the T. gondii genome using custom oligonucleotide microarrays. We show that methylation and acetylation of histones H3 and H4 are landmarks of active promoters in T. gondii that allow us to deduce the position and directionality of gene promoters with >95% accuracy. These histone methylation and acetylation “activation” marks are strongly associated with gene expression. We also demonstrate that the pattern of histone H3 arginine methylation distinguishes certain promoters, illustrating the complexity of the histone modification machinery in Toxoplasma. By integrating epigenetic data, gene prediction analysis, and gene expression data from the tachyzoite stage, we illustrate feasibility of creating an epigenomic map of T. gondii tachyzoite gene expression. Further, we illustrate the utility of the epigenomic map to empirically and biologically annotate the genome and show that this approach enables identification of previously unknown genes. Thus, our epigenomics approach provides novel insights into regulation of gene expression in the Apicomplexa. In addition, with its compact genome, genetic tractability, and discrete life cycle stages, T. gondii provides an important new model to study the evolutionarily conserved components of the histone code.
创建时间:
2007-06-08
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