RAPID: Methods for Estimating Genetic Diversity of the Ebola Virus

更广泛的意义：埃博拉病毒是一种以高突变率为特征的RNA病毒。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不断繁殖。估计病毒的遗传多样性对于了解它们的来源和变异模式以及开发有效的药物治疗方法至关重要。病毒种群的特征是组成它的基因组的序列和频率。高通量DNA测序技术使快速和负担得起的病毒基因组分析成为可能。然而，高通量测序平台的错误和有限的读取长度给估计病毒遗传多样性带来了挑战。技术描述：本研究的目的是开发新的算法来确定和分析RNA病毒的遗传多样性，并将其应用于埃博拉病毒的分析。研究人员的具体目标是：(1)开发相关聚类框架和计算高效的方法，从高通量测序数据中估计病毒的遗传多样性。在这方面的研究中，病毒基因组的重建被转化为最大-k割问题，并利用半定规划有效地求解。(2)利用高通量测序技术，设计图形模型和置信度传播算法，用于推断不同集合中的病毒基因组。这项研究的重点是可扩展的消息传递方法，用于估计病毒遗传多样性。(3)依托所开发的方法，利用公开的高通量测序数据分析埃博拉病毒的多样性。预计上述工作的结果将对了解埃博拉疫情暴发机制和病毒变异模式产生立竿见影的影响。

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.