An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.
An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.
复制标题
DOI：
10.1371/journal.pcbi.1000581
复制
发表时间：
2009-11
影响因子：
4.3
通讯作者：
Frost SD
中科院分区：
文献类型：
--
作者：
Kosakovsky Pond SL;Posada D;Stawiski E;Chappey C;Poon AF;Hughes G;Fearnhill E;Gravenor MB;Leigh Brown AJ;Frost SD
遗传多样性病原体（如人类免疫缺陷病毒1型，HIV-1）经常被分为遗传学或免疫学定义的亚型进行分类。这些亚型的计算鉴定有助于监测、流行病学分析和新变体的检测，例如，HIV-1的循环重组形式。已经提出了许多概念上和技术上不同的技术来确定查询序列的子类型，但没有一个普遍的最佳方法。我们提出了一种基于模型的系统发育方法，用于自动分型HIV-1（或其他病毒或细菌）序列，映射断点的位置和分配重组株中的亲本序列以及计算推断量的置信水平。我们的子类型分类使用进化AL出租（SCUEAL）的过程中表现非常好，在各种模拟情况下，并行运行时，多个序列被筛选，并匹配或超过现有的方法对典型的经验案例的性能。我们将SCUEAL应用于来自两个大型数据库（斯坦福大学耐药性数据库和英国HIV耐药性数据库）的所有可用聚合酶（pol）序列。与之前指定的亚型进行比较显示，纯亚型序列中的一小部分但很大一部分（约5%）实际上可能是亚型内或亚型间重组体。SCUEAL的免费实现是作为HyPhy包和Datamonkey Web服务器的模块提供的。当需要对未知菌株进行准确的自动分类时，我们的方法特别有用，并且定位于补充和扩展更快但不太准确的方法。鉴于艾滋病毒亚型信息在侧重于亚型对治疗、临床结果、致病性和疫苗设计的影响的研究中的使用越来越频繁，准确、稳健和可扩展的亚型分型程序的重要性是显而易见的。HIV-1的主要组有九种不同的亚型，每种亚型都起源于HIV-1的不同亚流行病。亚型的分布往往是世界上特定地理区域所特有的，是一种有用的流行病学和监测资源。病毒亚型对疾病进展、治疗结果和疫苗设计的影响正在积极研究中，准确的亚型分型程序的重要性显而易见。在HIV-1中，亚型分配因共同传播的毒株之间频繁重组而变得复杂，产生了新的遗传镶嵌或重组形式：迄今为止已经鉴定了43种，并且可能存在更多。我们提出了一种自动系统发育方法（SCUEAL），以准确地描述简单和复杂的HIV-1嵌合体。使用计算机模拟和生物数据，我们证明了SCUEAL在各种条件下表现非常好，特别是当一些现有的分类程序失败。此外，我们表明，一个小的，但值得注意的比例亚型表征存储在公共数据库中可能是不完整或不正确的。这里介绍的计算技术应该提供一个更准确的表征HIV-1株，特别是新的重组，并导致新的见解的分子历史，流行病学和地理分布的病毒。
Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (≈5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear. There are nine different subtypes of the main group of HIV-1, each originating as a distinct subepidemic of HIV-1. The distribution of subtypes is often unique to a given geographic region of the world and constitutes a useful epidemiological and surveillance resource. The effects of viral subtype on disease progression, treatment outcome and vaccine design are being actively researched, and the importance of accurate subtyping procedures is clear. In HIV-1, subtype assignment is complicated by frequent recombination among co-circulating strains, creating new genetic mosaics or recombinant forms: 43 have been characterized to date, and many more likely exist. We present an automated phylogenetic method (SCUEAL) to accurately characterize both simple and complex HIV-1 mosaics. Using computer simulations and biological data we demonstrate that SCUEAL performs very well under various conditions, especially when some of the existing classification procedures fail. Furthermore, we show that a small, but noticeable proportion of subtype characterization stored in public databases may be incomplete or incorrect. The computational technique introduced here should provide a much more accurate characterization of HIV-1 strains, especially novel recombinants, and lead to new insights into molecular history, epidemiology and geographical distribution of the virus.
登录
查看更多内容
影响因子：
3.8
作者：
Gifford, Robert;de Oliveira, Tulio;Pillay, Deenan
通讯作者：
Pillay, Deenan
影响因子：
1.5
作者：
Baker, Chris A. R.;McEvers, Kimberly;Cao, Huyen
通讯作者：
Cao, Huyen
影响因子：
1.5
作者：
Gómez-Carrillo, M;Quarleri, JF;Salomón, H
通讯作者：
Salomón, H
影响因子：
3.7
作者：
Bennett DE;Camacho RJ;Otelea D;Kuritzkes DR;Fleury H;Kiuchi M;Heneine W;Kantor R;Jordan MR;Schapiro JM;Vandamme AM;Sandstrom P;Boucher CA;van de Vijver D;Rhee SY;Liu TF;Pillay D;Shafer RW
通讯作者：
Shafer RW
影响因子：
6.8
作者：
AKAIKE, H
通讯作者：
AKAIKE, H