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

项目总结/摘要 HIV中的重组事件比点突变更频繁地发生， 流行病学上重要的创始菌株在不同的地理区域，并造成至少20 - 30%的 全球艾滋病毒感染。然而，在认识到艾滋病毒重组33年后，两个关键问题仍然存在， 关于HIV重组事件是如何发生的以及如何预测出现的重组， 集群，以更好地为公共卫生决策提供信息。基于近20年的艾滋病经验，我们认为， 这两个问题都与目前HIV重组家族分类系统的固有缺陷有关 （CRF），其没有充分认识到重组家族内和重组家族之间的快速病毒进化。 因此，CRF的这种静态定义不仅对大多数CRF产生了小样本量问题，而且 这使得很难以动态的方式跟踪病毒的进化;而这两个问题对公共卫生至关重要 监测和改进针对HIV重组体的疫苗和抗病毒药物设计。在这项研究中， 我们的目标是：1）战略性地填补CRF信息的不足和缺失，以克服小- CRF定义造成的样本量问题，以及2）提供沿着HIV基因组的全球概况， 基于基因组学的HIV重组发生和进化 丰富的CRF信息。我们的中心假设是，不充分和缺失的CRF信息， 考虑到大多数CRF的样本量有限以及缺乏CRF的动态视图，可以从战略上 通过添加来自HIV片段序列的信息（即，非全长序列），其由超过 90%已发表的HIV数据保存在GenBank中。我们的假设是基于几条重要的 证据，包括我们的研究结果。我们提出这项研究的理由是， 缺失CRF信息将提高我们监测和追踪现有HIV的能力 重组体和改进对新出现的HIV重组体簇的预测。利用我们近20个 在HIV数据挖掘，统计方法开发，统计机器学习方面有多年的经验， 统计遗传学，我们将开发和验证三个目标的两种新方法。截至本建议结束时， 项目，我们希望获得新的方法和新的发现，以促进我们对CRF的理解（例如， 重组机制和演变），并改善对现有和新出现的 通用报告格式组群。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

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.