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Practical guidance and workflows for identifying fast evolving non-coding genomic elements using PhyloAcc.
Thomas, Gregg W C; Gemmell, Patrick; Shakya, Subir B; Hu, Zhirui; Liu, Jun S; Sackton, Timothy B; Edwards, Scott V.
Affiliation
  • Thomas GWC; Informatics Group, Harvard University, Cambridge, MA, USA.
  • Gemmell P; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
  • Shakya SB; Department of Statistics, Harvard University, Cambridge, MA, USA.
  • Hu Z; Informatics Group, Harvard University, Cambridge, MA, USA.
  • Liu JS; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
  • Sackton TB; Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA.
  • Edwards SV; Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA.
Integr Comp Biol ; 2024 May 30.
Article in En | MEDLINE | ID: mdl-38816211
ABSTRACT
Comparative genomics provides ample ways to study genome evolution and its relationship to phenotypic traits. By developing and testing alternate models of evolution throughout a phylogeny, one can estimate rates of molecular evolution along different lineages in a phylogeny and link these rates with observations in extant species, such as convergent phenotypes. Pipelines for such work can help identify when and where genomic changes may be associated with, or possibly influence, phenotypic traits. We recently developed a set of models called PhyloAcc, using a Bayesian framework to estimate rates of nucleotide substitution on different branches a phylogenetic tree and evaluate their association with pre-defined or estimated phenotypic traits PhyloAcc-ST and PhyloAcc-GT both allow users to define a priori a set of target lineages and then compare different models to identify loci accelerating in one or more target lineages. Whereas ST considers only one species tree across all input loci, GT considers alternate topologies for every locus. PhyloAcc-C simultaneously models molecular rates and rates of continuous trait evolution,allowing the user to ask whether the two are associated. Here we describe these models and provide tips and workflows on how to prepare the input data and run PhyloAcc.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Integr Comp Biol Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Integr Comp Biol Year: 2024 Document type: Article