Event inference in multidomain families with phylogenetic reconciliation

BMC Bioinformatics

Research

Maureen Stolzer¹  Minli Xu¹  Han Lai¹  Dannie Durand²  Katherine Siewert³ 

[1] Department of Biological Sciences, Carnegie Mellon University, Forbes Ave, 15213, Pittsburgh, PA, USA;Department of Biological Sciences, Carnegie Mellon University, Forbes Ave, 15213, Pittsburgh, PA, USA;Department of Computer Science, Carnegie Mellon University, Forbes Ave, 15213, Pittsburgh, PA, USA;Department of Biological Sciences, Carnegie Mellon University, Forbes Ave, 15213, Pittsburgh, PA, USA;School of Medicine, University of Pennsylvania, Curie Blvd, 19104, Philadelphia, PA, USA;

关键词: domains;    evolution;    phylogenetics;    multidomain;    reconstruction;    domain shuffling;   

DOI  :  10.1186/1471-2105-16-S14-S8

来源: Springer

【 摘 要 】

BackgroundReconstructing evolution provides valuable insights into the processes of gene evolution and function. However, while there have been great advances in algorithms and software to reconstruct the history of gene families, these tools do not model the domain shuffling events (domain duplication, insertion, transfer, and deletion) that drive the evolution of multidomain protein families. Protein evolution through domain shuffling events allows for rapid exploration of functions by introducing new combinations of existing folds. This powerful mechanism was key to some significant evolutionary innovations, such as multicellularity and the vertebrate immune system. A method for reconstructing this important evolutionary process is urgently needed.ResultsHere, we introduce a novel, event-based framework for studying multidomain evolution by reconciling a domain tree with a gene tree, with additional information provided by the species tree. In the context of this framework, we present the first reconciliation algorithms to infer domain shuffling events, while addressing the challenges inherent in the inference of evolution across three levels of organization.ConclusionsWe apply these methods to the evolution of domains in the Membrane associated Guanylate Kinase family. These case studies reveal a more vivid and detailed evolutionary history than previously provided. Our algorithms have been implemented in software, freely available at http://www.cs.cmu.edu/~durand/Notung.

【 授权许可】

Unknown   
© Stolzer et al. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.