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Abstract Detail


Carruthers, Tom [1].

The implications of lineage-specific rates for divergence time estimation.

Molecular evolutionary rate variation adds considerable complexity to divergence time estimation in molecular phylogenies. Here, we evaluate the impact of lineage-specific rates – which we define as among-branch-rate-variation that acts consistently across the entire genome. We compare its impact to residual rates – defined as among-branch-rate-variation that shows a different pattern of rate variation at each sampled locus, and gene-specific rates – defined as variation in the average rate across all branches at each sampled locus. We show that lineage-specific rates lead to erroneous divergence time estimates, regardless of how many loci are sampled. Further, we show that stronger lineage-specific rates lead to increasing error. This contrasts to residual rates and gene-specific rates, where sampling more loci significantly reduces error. If divergence times are inferred in a Bayesian framework, we highlight that error caused by lineage-specific rates significantly reduces the probability that the 95% highest posterior density (HPD) includes the correct value, and leads to sensitivity to the prior. Use of a more complex rate prior – which has recently been proposed to model rate variation more accurately – does not affect these conclusions. Finally, we show that the scale of lineage-specific rates used in our simulation experiments is comparable to that of an empirical dataset for the angiosperm genus Ipomoea. Taken together, our findings demonstrate that lineage-specific rates cause error in divergence time estimates, and that this error is not overcome by analysing genomic scale multi-locus datasets. Given the fundamental importance of divergence time estimation to macro-evolutionary research, these findings have far-reaching implications.

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1 - University of Oxford, Plant Sciences, Wolfson College, Linton Road, Oxford, OX2 6UD, UK

divergence time estimation
substitution rate analyses.

Presentation Type: Oral Paper
Session: MACRO1, Macroevolution I
Location: Tucson B/Starr Pass
Date: Tuesday, July 30th, 2019
Time: 9:00 AM
Number: MACRO1005
Abstract ID:609
Candidate for Awards:None

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