Linking Branch Lengths Across Loci Provides the Best Fit for Phylogenetic Inference

BioRxiv : the Preprint Server for Biology
David A DucheneSimon Y.W. Ho

Abstract

Evolution leaves heterogeneous patterns of nucleotide variation across the genome, with different loci subject to varying degrees of mutation, selection, and drift. Appropriately modelling this heterogeneity is important for reliable phylogenetic inference. One modelling approach in statistical phylogenetics is to apply independent models of molecular evolution to different groups of sites, where the groups are usually defined by locus, codon position, or combinations of the two. The potential impacts of partitioning data for the assignment of substitution models are well appreciated. Meanwhile, the treatment of branch lengths has received far less attention. In this study, we examined the effects of linking and unlinking branch-length parameters across loci. By analysing a range of empirical data sets, we find that the best-fitting model for phylogenetic inference is consistently one in which branch lengths are proportionally linked: gene trees have the same pattern of branch-length variation, but with varying absolute tree lengths. This model provided a substantially better fit than those that either assumed identical branch lengths across gene trees or that allowed each gene tree to have its own distinct set of branch length...Continue Reading

Related Concepts

Attention
Base Sequence
Codon (Nucleotide Sequence)
Genes
Genome
Trees (plant)
Site
Branching (Qualifier Value)
Evolution, Molecular
Genetic Loci

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

Related Papers

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
Mark Pagel, Andrew Meade
BioRxiv : the Preprint Server for Biology
SANCHITA BHADRAA. Ellington
Developmental and Comparative Immunology
David H Bos, D Posada
© 2021 Meta ULC. All rights reserved