Genome scale resolution for linkage mapping

用于连锁图谱的基因组尺度分辨率

• 批准号: 9751191
• 负责人: Ian Harry Cheeseman
• 金额: $ 32.49万
• 依托单位: UNIVERSITY OF NOTRE DAME
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9751191
• 关键词: Antimalarials; Artemisinins; Chromosome Mapping; Communities; Data; Data Analyses; Databases; Drug resistance; Experimental Genetics; Expression Profiling; Falciparum Malaria; Genetic; Genetic Crosses; Genetic Determinism; Genetic Markers; Genetic Recombination; Genetic Transcription; Genome; Genomics; Goals; Hour; Inheritance Patterns; Life Cycle Stages; Malaria; Mass Fragmentography; Metabolic; Metadata; Mutation; Output; Parasites; Phenotype; Plasmodium falciparum; Proteins; Proteome; Proteomics; Quantitative Trait Loci; RNA; Research; Research Personnel; Resistance; Resolution; Series; Single Nucleotide Polymorphism; System; Systems Biology; Technology; Time; Translating; Work; data integration; data warehouse; genome analysis; genome sequencing; genome-wide; humanized mouse; malaria infection; metabolome; metabolomics; mouse model; pathogen; protein metabolite; skills; transcriptome; transcriptome sequencing; transcriptomics; whole genome

ABSTRACT Plasmodium falciparum resistance to the antimalarial artemisinin threatens the great steps forward made in the last decade to control malaria infection. We lack a comprehensive understanding on the genetic determinants of drug resistance, and how the emergence of resistance conferring mutations impacts the cellular state of the P. falciparum malaria parasite. Experimental genetic crosses are an extremely precise means to identify the genetic determinants of resistance, and a powerful framework to examine the consequences of acquiring resistance at a genetic, transcriptional, proteomic and metabolomic level. By performing a series of inter-related genetic crosses in a groundbreaking humanized mouse model we will interrogate the systems biology of artemisinin resistance. The Genomics Core will further this goal by generating `omics data for this P01 (broadly combining genomics, transcriptomics, proteomics and metabolomics). We will perform whole genome sequencing of each of the progeny of the genetic crosses, mapping short reads to the 23 megabase genome of this eukaryotic pathogen to identify genetic markers for examining patterns of inheritance in P. falciparum (RP01), and quantitative trait loci (QTL) analysis of drug resistance phenotypes (RP02). Additionally, we will perform time course analyses of expression profiles and metabolite levels to identify expression QTLs and metabolite QTLs, and proteomic profiling to identify protein QTLs (RP03). Each of these disparate technologies has independent pitfalls and require highly specialized skills to generate reliable data. We have assembled a team of experts in genome and transcriptome sequencing, proteomics and metabolomics. This team will collaboratively tackle the formidable technical challenge of profiling malaria parasites across the `omics landscape. To translate these technologies into a usable output for the investigators across the P01, and for the malaria community at large, we will work closely with the Data Integration and Analysis Core (Core B) to generate an “analysis-ready” database containing the phenotypic, genetic, transcriptomic, proteomic and metabolic data for each of the progeny, and carry with it essential metadata and detailed workflows for robust flow of information throughout the project.

摘要 恶性疟原虫对抗疟药物青蒿素的抗药性威胁着在疟疾防治方面取得的重大进展。 在过去十年中，控制疟疾感染。我们缺乏对遗传因素的全面了解， 耐药性，以及耐药突变的出现如何影响P. 恶性疟原虫实验遗传杂交是鉴定遗传的一种极其精确的手段 抵抗的决定因素，以及一个强有力的框架来检查获得抵抗的后果， 遗传、转录、蛋白质组和代谢组水平。通过执行一系列相互关联的遗传 在一个开创性的人源化小鼠模型中进行杂交，我们将研究青蒿素的系统生物学 阻力基因组学核心将通过生成此P01的“组学数据”（广泛结合 基因组学、转录组学、蛋白质组学和代谢组学）。我们将对每一个人进行全基因组测序， 基因杂交的后代，将短读段映射到这个真核生物的23兆碱基基因组， 病原体以鉴定用于检查恶性疟原虫（RP 01）中的遗传模式的遗传标记，以及 耐药表型的数量性状基因座（QTL）分析（RP 02）。此外，我们将执行时间 对表达谱和代谢物水平进行过程分析，以鉴定表达QTL和代谢物QTL， 和蛋白质组学分析以鉴定蛋白质QTL（RP 03）。这些不同的技术中的每一种都有独立的 这是一个陷阱，需要高度专业化的技能来生成可靠的数据。我们召集了一个专家小组， 基因组和转录组测序、蛋白质组学和代谢组学。该团队将共同解决 在"组学“领域对疟疾寄生虫进行分析的巨大技术挑战。翻译这些 技术转化为P01研究人员和整个疟疾社区的可用输出， 我们将与数据集成和分析核心（核心B）密切合作，以生成“分析就绪” 数据库，其包含每一种的表型、遗传、转录组、蛋白质组和代谢数据。 并携带基本的元数据和详细的工作流程，以便在整个过程中实现强大的信息流 该项目