High-throughput phenotyping using parallel sequencing of RNA interference targets in the African trypanosome
High-throughput phenotyping using parallel sequencing of RNA interference targets in the African trypanosome
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DOI：
10.1101/gr.115089.110
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发表时间：
2011-06-01
期刊：
影响因子：
7
通讯作者：
Horn, David
中科院分区：
文献类型：
--
作者：
Alsford, Sam;Turner, Daniel J.;Horn, David
非洲锥虫是人类和牲畜的主要病原体，是研究不同寻常的原生动物生物学的一种模式。我们描述了一种高通量表型方法，称为RNA干扰（RNAi）靶测序，或RIT-seq，使用Illumina测序，绘制与RNAi相关的适应度成本。我们在诱导RNAi之前和之后对从锥虫文库中回收的bb90000个整合RNAi靶标的丰度进行了评分。数据显示了7435个蛋白质编码序列，约占布鲁氏锥虫基因组非冗余序列的99%。对血液和昆虫生命周期阶段以及不同文库的分析揭示了基因组规模的生长和发育敲低图谱，将数千个以前未被表征和“假设”的基因与基本功能联系起来。强调了锥虫生物学中突出特征的基因，包括转录后基因表达控制，鞭毛运动和血液中糖酵解的重要性，以及从血液到昆虫阶段分化过程中羧酸代谢和磷酸化的重要性。目前的数据集还提供了急需的基因验证，以确定新的药物靶点。RIT-seq代表了基因组规模功能分析和基因组序列数据开发的多功能新工具。
African trypanosomes are major pathogens of humans and livestock and represent a model for studies of unusual protozoal biology. We describe a high-throughput phenotyping approach termed RNA interference (RNAi) target sequencing, or RIT-seq that, using Illumina sequencing, maps fitness-costs associated with RNAi. We scored the abundance of >90,000 integrated RNAi targets recovered from trypanosome libraries before and after induction of RNAi. Data are presented for 7435 protein coding sequences, >99% of a non-redundant set in the Trypanosoma brucei genome. Analysis of bloodstream and insect life-cycle stages and differentiated libraries revealed genome-scale knockdown profiles of growth and development, linking thousands of previously uncharacterized and "hypothetical'' genes to essential functions. Genes underlying prominent features of trypanosome biology are highlighted, including the constitutive emphasis on post-transcriptional gene expression control, the importance of flagellar motility and glycolysis in the bloodstream, and of carboxylic acid metabolism and phosphorylation during differentiation from the bloodstream to the insect stage. The current data set also provides much needed genetic validation to identify new drug targets. RIT-seq represents a versatile new tool for genome-scale functional analyses and for the exploitation of genome sequence data.