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08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
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A unifying model of genome evolution under parsimony.
Benedict Paten1, Daniel R Zerbino, Glenn Hickey
1University of California, Santa Cruz, 1156 High St, 95064 Santa Cruz, USA. benedict@soe.ucsc.edu.
BMC Bioinformatics
|June 21, 2014
Summary
We introduce history graphs to unify phylogenetic tree estimation and genome rearrangement analysis under parsimony. This approach simplifies studying evolutionary histories by integrating substitutions and double cut and join (DCJ) rearrangements.
Area of Science:
- Computational Biology
- Evolutionary Biology
- Bioinformatics
Background:
- Phylogenetic tree estimation and genome rearrangement analysis are crucial for understanding genome evolution.
- Current methods for these analyses, such as parsimony and maximum likelihood, are often studied independently.
Purpose of the Study:
- To present a unified theoretical framework for analyzing genome evolution.
- To introduce a novel data structure, the history graph, for parsimonious analysis of evolutionary histories.
Main Methods:
- Development of the history graph data structure to represent substitutions and double cut and join (DCJ) rearrangements.
- Introduction of tractable functions to establish bounds on evolutionary operations.
- Definition and utilization of ancestral variation graphs (AVGs) for precise parsimonious interpretations.
Main Results:
- History graphs simplify the study of parsimonious evolutionary histories, encompassing both substitutions and DCJ rearrangements with duplications.
- Upper and lower bounds for the minimum number of substitutions and DCJ rearrangements were established.
- A finite set of AVGs can describe all parsimonious interpretations of a given history graph.
Conclusions:
- This work provides a theoretical model unifying genome rearrangement and phylogenetic inference under the principle of parsimony.
- The history graph and AVG framework offer a new computational approach to evolutionary studies.
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