Variation Across Mitochondrial Gene Trees Provides Evidence for Systematic Error: How Much Gene Tree Variation Is Biological?
Author(s) -
Emilie J. Richards,
Jeremy M. Brown,
Anthony J. Barley,
Rebecca A. Chong,
Robert C. Thomson
Publication year - 2018
Publication title -
systematic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.128
H-Index - 182
eISSN - 1076-836X
pISSN - 1063-5157
DOI - 10.1093/sysbio/syy013
Subject(s) - variation (astronomy) , biology , phylogenetic tree , tree (set theory) , evolutionary biology , phylogenetics , similarity (geometry) , gene , inference , mitochondrial dna , computational biology , genetic variation , genetics , computer science , mathematics , artificial intelligence , mathematical analysis , physics , astrophysics , image (mathematics)
The use of large genomic data sets in phylogenetics has highlighted extensive topological variation across genes. Much of this discordance is assumed to result from biological processes. However, variation among gene trees can also be a consequence of systematic error driven by poor model fit, and the relative importance of biological vs. methodological factors in explaining gene tree variation is a major unresolved question. Using mitochondrial genomes to control for biological causes of gene tree variation, we estimate the extent of gene tree discordance driven by systematic error and employ posterior prediction to highlight the role of model fit in producing this discordance. We find that the amount of discordance among mitochondrial gene trees is similar to the amount of discordance found in other studies that assume only biological causes of variation. This similarity suggests that the role of systematic error in generating gene tree variation is underappreciated and critical evaluation of fit between assumed models and the data used for inference is important for the resolution of unresolved phylogenetic questions.
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