Comparative genomics studies are growing in number partly because of their unique ability to provide insight into shared and divergent biology between species. Of particular interest is the use of phylogenetic methods to infer the evolutionary history of cis-regulatory sequence features, which contribute strongly to phenotypic divergence and are frequently gained and lost in eutherian genomes. Understanding the mechanisms by which cis-regulatory element turnover generate emergent phenotypes is crucial to our understanding of adaptive evolution. Ancestral reconstruction methods can place species-specific cis-regulatory features in their evolutionary context, thus increasing our understanding of the process of regulatory sequence turnover. However, applying these methods to gain and loss of cis-regulatory features historically required complex workflows, preventing widespread adoption by the broad scientific community. MapGL simplifies phylogenetic inference of the evolutionary history of short genomic sequence features by combining the necessary steps into a single piece of software with a simple set of inputs and outputs. We show that MapGL can reliably disambiguate the mechanisms underlying differential regulatory sequence content across a broad range of phylogenetic topologies and evolutionary distances. Thus, MapGL provides the necessary context to evaluate how genomic sequence gain and loss contribute to species-specific divergence. MapGL makes phylogenetic inference of species-specific sequence gain and loss easy for both expert and non-expert users, making it a powerful tool for gaining novel insights into genome evolution.

中文翻译：

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MapGL：通过系统发育最大简约性推断短基因组序列特征的进化增益和缺失。

比较基因组学的研究之所以在数量上有所增长，部分原因是它们具有独特的能力，可以洞察物种之间共享和不同的生物学。特别重要的是，使用系统发育方法来推断顺式调控序列特征的进化历史，这些特征极大地促进了表型差异，并在欧亚基因组中频繁获得和丢失。理解顺式调控元件更新产生新兴表型的机制对于我们对适应性进化的理解至关重要。祖先的重建方法可以将物种特有的顺式调控特性置于其进化背景下，从而增加了我们对调控序列更新过程的理解。然而，从历史上讲，使用这些方法来获得和失去顺式调节特性需要复杂的工作流程，从而阻止了广泛的科学界的广泛采用。MapGL通过将必要的步骤组合到具有一组简单的输入和输出的单个软件中，简化了短基因组序列特征进化史的系统发育推断。我们表明，MapGL可以可靠地消除各种系统发育拓扑和进化距离中差异调控序列内容的潜在机制。因此，MapGL提供了必要的背景信息，以评估基因组序列的得失如何导致物种特异性差异。通过MapGL，无论是专业用户还是非专业用户，都可以轻松地进行物种特定序列得失的系统发育推断，