Institute of Informatics, Warsaw University, Warsaw 02-097, Poland.
BMC Bioinformatics. 2011 Feb 15;12 Suppl 1(Suppl 1):S15. doi: 10.1186/1471-2105-12-S1-S15.
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.
大量新的基因组数据为在物种系统发育树上绘制基因复制和丢失事件的位置提供了机会。最初的基因复制和丢失映射方法基于简约准则，找到最小化复制和丢失事件数量的映射。基因复制和丢失的概率建模相对较新，并且主要集中在出生-死亡过程上。
我们引入了一种新的最大似然模型，该模型估计了在具有分支长度的物种树中的基因树内的物种形成和基因复制和丢失事件。我们还提供了一种在实践中有效的算法，用于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，并使用经验数据和模拟数据验证了其性能。
在测试数据集上，DrML 甚至在基因树包含来自数百个物种的序列的情况下，也可以在数分钟内找到最佳的基因复制和丢失场景。在许多情况下，这些最佳场景与基于简约的基因树协调产生的 lca-mapping 不同。因此，DrML 为研究基因复制提供了一个新的实用统计框架。
