A novel approach to pinpoint predisposed recombination regions in HIV for a global profile of HIV recombinants' occurrence and evolution

一种查明 HIV 中易发生重组区域的新方法，以了解 HIV 重组体发生和进化的全球概况

基本信息

批准号：
10762779
负责人：
Hanwen Huang
金额：
$ 18.88万
依托单位：
UNIVERSITY OF GEORGIA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-01 至 2025-05-31
项目状态：
未结题

项目摘要

Project Summary/Abstract Occurring more frequent than point mutations, the recombination events in HIV have resulted in epidemiologically important founder strains in various geographic regions and contribute to at least 20-30% of global HIV infections. However, after 33 years of recognizing HIV recombination, two critical questions still remain elusive as to how HIV recombination events have occurred and how to predict emerging recombinant clusters to better inform public health decision making. Based on nearly 20 years of HIV experience, we believe that both questions relate to the flaws inherent in the current classification system for HIV recombinant families (CRFs), which has inadequately appreciated the rapid virus evolution within and between recombinant families. As a result, this static definition of CRFs not only creates a small-sample-size problem for most CRFs, but also makes it difficult to track viral evolution in a dynamic means; while both issues are essential for public health surveillance and for improved vaccine and antivirals design targeting HIV recombinants. In this proposed study, our objectives are to: 1) strategically fulfill the inadequate and missing CRF information to overcome the small- sample-size problem created by the CRF definition, and 2) provide a global profile along the HIV genome about HIV’s recombination occurrence and evolution via pinpointing HIV predisposed recombination regions based on the enriched CRF information. Our central hypothesis is that the inadequate and missing CRF information, which accounts for the limited sample size for most CRFs and the lack of a dynamic view of CRFs, can be strategically fulfilled by adding information from HIV fragment sequences (i.e., non-full-length sequences) that consist of over 90% of all published HIV data deposited in GenBank. Our hypothesis is based on several important lines of evidence, including results from our studies. Our rationale for this proposed study is that fulfilling the inadequate and missing CRF information will increase our capabilities in the surveillance and tracking of existing HIV recombinants and for improved prediction of emerging HIV recombinants’ clusters. Leveraged by our nearly 20 years of experience in HIV data mining, statistical method development, statistical machine learning, and statistical genetics, we will develop and validate two new methods in three Aims. By the end of this proposed project, we expect to obtain new methods and new findings to advance our understanding of the CRFs (e.g., recombination mechanisms and evolution) and for improved public health surveillance for existing and emerging CRF clusters. Finally, our methods and results will be released for free to facilitate other viruses’ research in recombination.

项目概要/摘要 HIV 中的重组事件比点突变发生得更频繁，导致不同地理区域中具有流行病学重要意义的始祖菌株，至少占 20-30% 然而，在认识到 HIV 重组 33 年后，仍然存在两个关键问题。关于 HIV 重组事件是如何发生的以及如何预测新出现的重组事件仍然难以捉摸我们认为，基于近 20 年的艾滋病毒经验，我们认为这些集群可以更好地为公共卫生决策提供信息。这两个问题都与当前艾滋病毒重组家庭分类系统固有的缺陷有关（CRF），它没有充分认识到重组家族内部和之间的病毒快速进化。因此，这种 CRF 的静态定义不仅给大多数 CRF 带来了小样本问题，而且使得以动态方式追踪病毒进化变得困难，而这两个问题对于公共卫生都是至关重要的；监测以及改进针对 HIV 重组体的疫苗和抗病毒设计。我们的目标是： 1) 战略性地填补 CRF 信息不足和缺失的问题，以克服小问题 CRF 定义产生的样本量问题，以及 2) 提供有关 HIV 基因组的全局概况通过精确定位 HIV 易感重组区域来了解 HIV 重组的发生和进化我们的中心假设是 CRF 信息不充分和缺失。考虑到大多数 CRF 的样本量有限以及缺乏 CRF 的动态视图，可以从策略上进行解决通过添加来自 HIV 片段序列（即非全长序列）的信息来实现，该序列由超过 GenBank 中 90% 的已发表 HIV 数据均基于以下几个重要方面。证据，包括我们的研究结果，我们提出这项研究的理由是弥补不足。缺失的 CRF 信息将提高我们监测和追踪现有 HIV 的能力我们近 20 个研究人员利用该技术改进了对新兴 HIV 重组体簇的预测。在 HIV 数据挖掘、统计方法开发、统计机器学习和统计遗传学，我们将在三个目标中开发和验证两种新方法。项目中，我们期望获得新方法和新发现来增进我们对 CRF 的理解（例如，重组机制和进化）以及改善现有和新兴的公共卫生监测最后，我们的方法和结果将免费发布，以方便其他病毒的研究。重组。