AI Article Synopsis

  • - ALE and GeneRax are tools designed for analyzing how gene trees relate to species trees, using statistical models to understand events like gene duplication, transfer, and loss, while also helping to determine the origins of gene families and root species trees.
  • - Despite recent criticisms regarding their reliability in estimating gene duplication and transfer events, a study found that ALE and GeneRax perform well on both simulated data and real-world empirical data.
  • - Specifically, ALE demonstrates a consistent ability to capture variations in gene event frequencies according to known biological contexts, successfully rooting species trees in plants and opisthokonts, while providing comparable insights for Bacteria.

Article Abstract

ALE and GeneRax are tools for probabilistic gene tree-species tree reconciliation. Based on a common underlying statistical model of how gene trees evolve along species trees, these methods rely on gene vs. species tree discordance to infer gene duplication, transfer, and loss events, map gene family origins, and root species trees. Published analyses have used these methods to root species trees of Archaea, Bacteria, and several eukaryotic groups, as well as to infer ancestral gene repertoires. However, it was recently suggested that reconciliation-based estimates of duplication and transfer events using the ALE/GeneRax model were unreliable, with potential implications for species tree rooting. Here, we assess these criticisms and find that the methods are accurate when applied to simulated data and in generally good agreement with alternative methodological approaches on empirical data. In particular, ALE recovers variation in gene duplication and transfer frequencies across lineages that is consistent with the known biology of studied clades. In plants and opisthokonts, ALE recovers the consensus species tree root; in Bacteria-where there is less certainty about the root position-ALE agrees with alternative approaches on the most likely root region. Overall, ALE and related approaches are promising tools for studying genome evolution.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373948PMC
http://dx.doi.org/10.1093/gbe/evad134DOI Listing

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