RAPID: Methods for Estimating Genetic Diversity of the Ebola Virus

RAPID：估计埃博拉病毒遗传多样性的方法

• 批准号: 1507998
• 负责人: Haris Vikalo
• 金额: $ 20万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2016-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1507998&HistoricalAwards=false
• 关键词: RAPID; Methods; Estimating; Genetic; Diversity

Broader Significance:Ebola is an RNA virus characterized by a high mutation rate. The genetic diversity of RNA viruses enables them to adapt to varying conditions over the course of infection and keep proliferating. Estimating viral genetic diversity is essential for the understanding of their origin and mutation patterns, and for the development of effective drug treatments. A viral population is characterized by the sequences and frequencies of the genomes that comprise it. High-throughput DNA sequencing technologies enable fast and affordable analysis of viral genomes. However, errors and limited read lengths of high-throughput sequencing platforms render the problem of estimating viral genetic diversity challenging.Technical Description:The aim of this research is to develop novel algorithms for determining and analyzing genetic diversity of RNA viruses and applying them to the analysis of the Ebola virus. The investigator specifically aims to: (1) Develop correlation clustering framework and computationally efficient methods for estimating viral genetic diversity from high-throughput sequencing data. In this line of research, reconstruction of viral genomes is cast as the max-k-cut problem and efficiently solved using semi-definite programming. (2) Design graphical models and belief propagation algorithms for inferring viral genomes in a diverse set analyzed with high-throughput sequencing technologies. The focus of this research thrust is on scalable message-passing methods for estimating viral genetic diversity. (3) Relying on the developed methods, analyze the diversity of the Ebola virus using publicly available high-throughput sequencing data. The results of the outlined work are expected to have an immediate impact on the understanding of the Ebola outbreak mechanisms and virus mutation patterns.

更广泛的意义：埃博拉病毒是一种RNA病毒，其特征是高突变率。RNA病毒的遗传多样性使它们能够在感染过程中适应不同的条件并保持增殖。估计病毒的遗传多样性对于了解其起源和突变模式以及开发有效的药物治疗至关重要。病毒群体的特征在于组成它的基因组的序列和频率。高通量DNA测序技术可以快速且经济地分析病毒基因组。然而，高通量测序平台的错误和有限的读取长度使得估计病毒遗传多样性的问题具有挑战性。技术描述：本研究的目的是开发用于确定和分析RNA病毒遗传多样性的新算法，并将其应用于埃博拉病毒的分析。研究者的具体目标是：（1）开发相关聚类框架和计算效率高的方法，用于从高通量测序数据中估计病毒遗传多样性。在这条研究路线中，病毒基因组的重建被转换为最大k-割问题，并使用半定规划有效地解决。(2)设计图形模型和置信度传播算法，用于推断使用高通量测序技术分析的不同集合中的病毒基因组。这项研究的重点是可扩展的信息传递方法估计病毒的遗传多样性。(3)依靠开发的方法，使用公开的高通量测序数据分析埃博拉病毒的多样性。所概述的工作成果预计将对了解埃博拉疫情机制和病毒突变模式产生直接影响。