Maximum likelihood models and algorithms for gene tree evolution with duplications and losses.
Maximum likelihood models and algorithms for gene tree evolution with duplications and losses.
复制标题
基因树进化的最大似然模型和算法，并具有重复和损失。
DOI：
10.1186/1471-2105-12-s1-s15
复制
发表时间：
2011-02-15
影响因子：
3
通讯作者：
Eulenstein O
中科院分区：
文献类型：
--
作者：
Górecki P;Burleigh GJ;Eulenstein O
丰富的新基因组数据提供了绘制基因重复和丢失事件在物种系统发育中的位置的机会。第一个定位基因重复和丢失的方法是基于简约标准，找到最小化重复和丢失事件数量的定位。基因复制和丢失的概率模型是相对较新的，主要集中在出生-死亡过程。我们引入了一个新的最大似然模型，估计物种形成和基因复制和丢失事件在一个物种树内的分支长度。在实践中，我们还提供了一种高效的算法，可以计算该模型的最佳进化场景。我们在程序DrML中实现了该算法，并用经验和模拟数据验证了其性能。在测试数据集中，DrML可以在几分钟内找到最佳的基因重复和丢失情况，即使基因树包含来自数百个物种的序列。在许多情况下，这些最佳方案不同于简约基因树调和的lca映射。因此，DrML为研究基因重复提供了一个新的、实用的统计框架。
The abundance of new genomic data provides the opportunity to map the location of gene duplication and loss events on a species phylogeny. The first methods for mapping gene duplications and losses were based on a parsimony criterion, finding the mapping that minimizes the number of duplication and loss events. Probabilistic modeling of gene duplication and loss is relatively new and has largely focused on birth-death processes. We introduce a new maximum likelihood model that estimates the speciation and gene duplication and loss events in a gene tree within a species tree with branch lengths. We also provide an, in practice, efficient algorithm that computes optimal evolutionary scenarios for this model. We implemented the algorithm in the program DrML and verified its performance with empirical and simulated data. In test data sets, DrML finds optimal gene duplication and loss scenarios within minutes, even when the gene trees contain sequences from several hundred species. In many cases, these optimal scenarios differ from the lca-mapping that results from a parsimony gene tree reconciliation. Thus, DrML provides a new, practical statistical framework on which to study gene duplication.