期刊
SYSTEMATIC BIOLOGY
卷 57, 期 5, 页码 772-784出版社
OXFORD UNIV PRESS
DOI: 10.1080/10635150802434394
关键词
Alternative splicing evolution; Bayesian phylogenetic inference; immigration-mutation-death process; intron conservation; stochastic Dollo
资金
- NIH [GM008185, U54-RR021813]
- DOE [DE-fC02-02ER63421]
- Dreyfus Foundation Teacher-Scholar
- Alfred P. Sloan Research
- NATIONAL CENTER FOR RESEARCH RESOURCES [U54RR021813] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [T32GM008185, R01GM086887] Funding Source: NIH RePORTER
New contributions toward generalizing evolutionary models expand greatly our ability to analyze complex evolutionary characters and advance phylogeny reconstruction. In this article, we extend the binary stochastic Dollo model to allow for multi-state characters. In doing so, we align previously incompatible Wagner and Dollo parsimony principles under a common probabilistic framework by embedding arbitrary continuous-time Markov chains into the binary stochastic Dollo model. This approach enables us to analyze character traits that exhibit both Dollo and Wagner characteristics throughout their evolutionary histories. Utilizing Bayesian inference, we apply our novel model to analyze intron conservation patterns and the evolution of alternatively spliced exons. The generalized framework we develop demonstrates potential in distinguishing between phylogenetic hypotheses and providing robust estimates of evolutionary rates. Moreover, for the two applications analyzed here, our framework is the first to provide an adequate stochastic process for the data. We discuss possible extensions to the framework from both theoretical and applied perspectives.
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