Inference and characterization of horizontally transferred gene families using stochastic mapping.
Inference and characterization of horizontally transferred gene families using stochastic mapping.
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DOI：
10.1093/molbev/msp240
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发表时间：
2010-03
影响因子：
10.7
通讯作者：
Pupko T
中科院分区：
文献类型：
--
作者：
Cohen O;Pupko T
基因获得和丢失的大基因组事件在微生物进化中起着关键的进化作用。然而，描述这些事件的概率进化模型及其稳健推理方法远不如现有的分析特定位点序列进化的方法发达。在这里，我们提出了一种新的方法来推断基因家族的得失。首先，我们开发了描述基因家族内容动态的概率进化模型，这比以前提出的模型在生物学上更现实。在我们基于可能性的模型中，考虑到潜在的系统发育，收益和损失由存在和不存在之间的转换表示。我们采用混合模型方法，其中我们允许增益率和损失率在基因家族之间变化。其次，我们使用这些模型和随机映射的分析实现来推断特定于分支的事件。我们的新方法使我们能够推断和量化水平基因转移（HGT）事件。这使我们能够根据它们的得失倾向对各种基因家族和谱系进行排序。将该方法应用于4873个基因家族，结果表明：1)该混合模型能较好地描述微生物间基因家族含量的差异；2)随机映射方法能够基于模拟准确地推断增益和损失事件；3)至少34%的基因家族在其进化过程中至少经历过一次HGT；4)推断经历HGT的基因家族在特定功能类别中既丰富又缺失。
Macrogenomic events, in which genes are gained and lost, play a pivotal evolutionary role in microbial evolution. Nevertheless, probabilistic-evolutionary models describing such events and methods for their robust inference are considerably less developed than existing methodologies for analyzing site-specific sequence evolution. Here, we present a novel method for the inference of gains and losses of gene families. First, we develop probabilistic-evolutionary models describing the dynamics of gene-family content, which are more biologically realistic than previously suggested models. In our likelihood-based models, gains and losses are represented by transitions between presence and absence, given an underlying phylogeny. We employ a mixture-model approach in which we allow both the gain rate and the loss rate to vary among gene families. Second, we use these models together with the analytic implementation of stochastic mapping to infer branch-specific events. Our novel methodology allows us to infer and quantify horizontal gene transfer (HGT) events. This enables us to rank various gene families and lineages according to their propensity to undergo gains and losses. Applying our methodology to 4,873 gene families shows that: 1) the novel mixture models describe the observed variability in gene-family content among microbes significantly better than previous models; 2) The stochastic mapping approach enables accurate inference of gain and loss events based on simulations; 3) At least 34% of the gene families analyzed are inferred to have experienced HGT at least once during their evolution; and 4) Gene families that were inferred to experience HGT are both enriched and depleted with respect to specific functional categories.
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