AI Article Synopsis

  • To understand gene evolution effectively, researchers should use a broad range of coding sequences from many species to track gene duplications and losses.
  • As the number of sequences increases, visualizing and interpreting the resulting phylogenetic trees becomes challenging, necessitating a way to simplify them.
  • The Phylogenetic Tree Collapser (PTC) program provides an automated solution for collapsing large phylogenetic trees based on user-defined taxonomic categories, making it accessible for researchers without heavy informatics expertise.

Article Abstract

When inferring the evolution of a gene/gene family, it is advisable to use all available coding sequences (CDS) from as many species genomes as possible in order to infer and date all gene duplications and losses. Nowadays, this means using hundreds or even thousands of CDSs, which makes the inferred phylogenetic trees difficult to visualize and interpret. Therefore, it is useful to have an automated way of collapsing large phylogenetic trees according to a taxonomic term decided by the user (family, class, or order, for instance), in order to highlight the minimal set of sequences that should be used to recapitulate the full history of the gene/gene family being studied at that taxonomic level, that can be refined using additional software. Here we present the Phylogenetic Tree Collapser (PTC) program (https://github.com/pegi3s/phylogenetic-tree-collapser), a flexible tool for automated tree collapsing using taxonomic information, that can be easily used by researchers without a background in informatics, since it only requires the installation of Docker, Podman or Singularity. The utility of PTC is demonstrated by addressing the evolution of the ascorbic acid synthesis pathway in insects. A Docker image is available at Docker Hub (https://hub.docker.com/r/pegi3s/phylogenetic-tree-collapser) with PTC installed and ready-to-run.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11377030PMC
http://dx.doi.org/10.1515/jib-2023-0051DOI Listing

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