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Comparing two Bayesian methods for gene tree/species tree reconstruction: simulations with incomplete lineage sorting and horizontal gene transfer.

机译:比较两种用于基因树/物种树重建的贝叶斯方法:具有不完整谱系排序和水平基因转移的模拟。

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With the increasing interest in recognizing the discordance between gene genealogies, various gene tree/species tree reconciliation methods have been developed. We present here the first attempt to assess and compare two such Bayesian methods, Bayesian estimation of species trees (BEST) and BUCKy (Bayesian untangling of concordance knots), in the presence of several known processes of gene tree discordance. DNA alignments were simulated under the influence of incomplete lineage sorting (ILS) and of horizontal gene transfer (HGT). BEST and BUCKy both account for uncertainty in gene tree estimation but differ substantially in their assumptions of what caused gene tree discordance. BEST estimates a species tree using the coalescent model, assuming that all gene tree discordance is due to ILS. BUCKy does not assume any specific biological process of gene tree discordance through the use of a nonparametric clustering of concordant genes. BUCKy estimates the concordance factor (CF) of a clade, which is defined as the proportion of genes that truly have the clade in their trees. The estimated concordance tree is then built from clades with the highest estimated CFs. Because of their different assumptions, it was expected that BEST would perform better in the presence of ILS and that BUCKy would perform better in the presence of HGT. As expected, the species tree was more accurately reconstructed by BUCKy in the presence of HGT, when the HGT events were unevenly placed across the species tree. BUCKy and BEST performed similarly in most other cases, including in the presence of strong ILS and of HGT events that were evenly placed across the tree. However, BUCKy was shown to underestimate the uncertainty in CF estimation, with short credibility intervals. Despite this, the discordance pattern estimated by BUCKy could be compared with the signature of ILS. The resulting test for the adequacy of the coalescent model proved to have low Type I error. It was powerful when HGT was the major source of discordance and when HGT events were unevenly placed across the species tree.
机译:随着人们越来越认识到基因谱系之间的矛盾,已经开发了各种基因树/物种树协调方法。在此,我们提出了在几种已知的基因树不一致过程中,评估和比较两种贝叶斯方法的首次尝试,即贝叶斯物种树估计(BEST)和BUCKy(贝叶斯一致结的贝叶斯解缠)。 DNA比对在不完全谱系分选(ILS)和水平基因转移(HGT)的影响下进行模拟。 BEST和BUCKy都考虑了基因树估计中的不确定性,但是它们对导致基因树不一致的原因的假设存在很大差异。 BEST假设所有基因树不一致是由于ILS造成的,BEST使用合并模型估计了物种树。 BUCKy不假设通过使用非一致基因的非参数聚类来进行基因树不一致的任何特定生物学过程。 BUCKy估算进化枝的一致性因子(CF),定义为树木中真正具有进化枝的基因的比例。然后从具有最高估计CF的进化枝中建立估计的一致性树。由于它们的假设不同,因此可以预期,在ILS存在的情况下BEST会表现更好,在HGT存在的情况下BUCKy会表现更好。不出所料,当HGT事件在种树上分布不均时,在HGT存在下BUCKy可以更准确地重建种树。在大多数其他情况下,BUCKy和BEST的表现相似,包括在树上均匀放置的强ILS和HGT事件的情况下。但是,BUCKy被证明低估了CF估计中的不确定性,并且可信区间很短。尽管如此,可以将BUCKy估计的不一致模式与ILS的签名进行比较。对合并模型的充分性进行的测试证明具有低的I型误差。当HGT是引起不和谐的主要根源,并且当HGT事件在物种树上的位置不均匀时,此功能非常强大。

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