Systems genetics of artemisinin resistance

青蒿素抗性的系统遗传学

• 批准号: 10216649
• 负责人: Tim J Anderson
• 金额: $ 43.82万
• 依托单位: UNIVERSITY OF NOTRE DAME
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10216649
• 关键词: Address; Alleles; Animal Model; Artemisinins; Automobile Driving; Biochemical Pathway; Biology; CRISPR/Cas technology; Chromosome Mapping; Collaborations; Communities; Complement; Copy Number Polymorphism; Data; Data Analyses; Data Set; Distant; Drug resistance; E protein; Evolution; Experimental Genetics; Feedback; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Crosses; Genetic Polymorphism; Genetic Recombination; Genetic Transcription; Genetic Variation; Genome; Genomic approach; Genomics; Genotype; Harvest; Knowledge; Link; Location; Malaria; Maps; Measures; Messenger RNA; Methods; Microsatellite Repeats; Modeling; Nature; Network-based; Parasites; Parents; Pathway interactions; Pattern; Pharmaceutical Preparations; Phenotype; Phosphatidylinositols; Plasmodium; Plasmodium falciparum; Play; Population; Production; Proteins; Proteomics; Quantitative Trait Loci; RNA; Recording of previous events; Research; Resistance; Role; Study models; System; Systems Biology; Testing; Time; Trans-Activators; Transcript; Translations; Work; asexual; base; cost; data integration; design; fitness; genetic analysis; genetic approach; genetic information; genetic linkage analysis; genome-wide; genome-wide linkage; humanized mouse; improved; insight; metabolomics; protein metabolism; protein metabolite; resistance mechanism; response; transcription factor; transcriptome sequencing

ABSTRACT The ability to conduct experimental genetic crosses in malaria using humanized mice provides exciting opportunities for genetic analysis of Plasmodium falciparum. Systems genetics approaches can complement these efforts, because transcription of RNA, translation into proteins and metabolism of these proteins, provide the critical intermediate steps that link genotype and phenotype. We will characterize the transcriptional, proteomic and metabolomic signatures of both parental parasites and progeny from three genetic crosses generated by Core A (Experimental Genetic Crosses). To generate the material needed, we will grow and harvest tightly synchronized parasite cultures (2 replicates) at 6 hr intervals throughout the parasites lifecycle for extraction of mRNA, proteins and metabolites: RNAseq, proteomic and metabolomic characterization will then be conducted by Core C (Genomics). The systems datasets generated will be used to ask both applied and fundamental questions about parasite biology: (i) We hypothesis that `omic' data collected will provide key insights into the mechanism of resistance, the metabolic networks involved in resistance and cost of resistance. Systems genetic analyses in a linkage mapping framework will show how additional loci impact artemisinin resistance, and the reasons that kelch13 alleles vary in level of resistance observed. (ii) we hypothesize that the systems biology paradigms emerging from studies of model organism will fit poorly for malaria. P. falciparum is fundamentally different from models organism in having just-in-time cascades of mRNA production across the lifecycle and few encoded transcription factors. We will conduct genome wide QTL analyses of mRNA, proteins and metabolites to investigate the interplay and feedback between genes, mRNA, proteins and metabolites to test this hypothesis. These analyses will explore the level at which protein abundance is regulated, and the relative importance of SNPs, microsatellites and copy number variation in driving regulatory evolution. These analyses will involve strong collaboration with Core B (Data Integration and Analysis Core) and RP02 (Drug Resistance Profiling and QTL mapping) in Notre Dame. The RNAseq, proteomics and metabolomics data will be made publically available for use by the malaria research community.

摘要 利用人源化小鼠进行疟疾实验遗传杂交的能力提供了令人兴奋的结果 恶性疟原虫遗传分析的机会。系统遗传学方法可以补充 这些努力，因为RNA的转录，翻译成蛋白质和这些蛋白质的新陈代谢，提供 连接基因和表型的关键中间步骤。我们将描述转录的， 三个遗传组合的双亲寄生虫和后代的蛋白质组和代谢组学特征 由核心A(实验遗传杂交)产生。为了生产所需的材料，我们将发展和 在寄生虫生命周期中每隔6小时采集紧密同步的寄生虫培养物(2个重复)，用于 提取信使核糖核酸、蛋白质和代谢物：RNAseq、蛋白质组和代谢组学鉴定 由Core C(基因组学)进行。生成的系统数据集将用于询问应用程序和 关于寄生虫生物学的基本问题：(I)我们假设收集到的‘基因组’数据将提供关键 对耐药机制、参与耐药的代谢网络和耐药成本的洞察。 连锁图谱框架中的系统遗传分析将显示额外的基因座如何影响青蒿素 抗性，以及观察到的kelch13等位基因抗性水平不同的原因。(Ii)我们假设 从模式生物研究中产生的系统生物学范式将不太适合疟疾。恶性疟原虫是 与模型生物体的根本不同之处在于，在整个 生命周期和很少的编码转录因子。我们将对mrna、蛋白质进行全基因组qtl分析。 和代谢物来研究基因、mRNA、蛋白质和代谢物之间的相互作用和反馈 检验这一假设。这些分析将探索蛋白质丰度受到调控的水平，以及 SNPs、微卫星和拷贝数变化在推动调控进化中的相对重要性。这些 分析将涉及与核心B(数据集成和分析核心)和RP02(药物)的密切合作 抗性图谱和QTL定位)。RNAseq、蛋白质组学和代谢组学数据将 供疟疾研究界公开使用。