Parameter Estimation and Species Tree Rooting Using ALE and GeneRax
Williams, T.A.; Davín, A.A.; Morel, B.; Szánthó, L.L.; Spang, A.; Stamatakis, A.; Hugenholtz, P.; Szöllosi, G.J. (2023). Parameter Estimation and Species Tree Rooting Using ALE and GeneRax. Genome Biology and Evolution 15(7). https://dx.doi.org/10.1093/gbe/evad134
Additional data:
In: Genome Biology and Evolution. Oxford University Press: Oxford. ISSN 1759-6653; e-ISSN 1759-6653, more
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| Author keywords |
phylogenetics; gene tree–species tree reconciliation; comparative genomics; microbial evolution |
| Authors | | Top |
- Williams, T.A.
- Davín, A.A.
- Morel, B.
- Szánthó, L.L.
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- Spang, A., more
- Stamatakis, A.
- Hugenholtz, P.
- Szöllosi, G.J.
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| 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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