What question did this study set out to answer?

To assess the validity of the rare mutation assumption in molecular phylogenetics and quantify its impact on evolutionary inferences in rapidly mutating pathogens.

August 20, 2026Systematic BiologyOpen Access

Phylogenetic inference with not-so-rare mutations and tiny organisms

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Authors

RBRui Borges JHJoseph Hughes

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Overview

Computational modeling reveals compromised branch lengths and selection estimates under rare-mutation assumptions in viruses, highlighting the necessity of accounting for recurrent mutations.

Key Points

To assess the validity of the rare mutation assumption in molecular phylogenetics and quantify its impact on evolutionary inferences in rapidly mutating pathogens.
Compared two mathematical mutation models: one incorporating recurrent mutations and another restricted to boundary (infrequent) mutations.
Evaluated both models using synthetic simulation data as well as empirical viral genomic sequences from HIV, hepatitis C virus (HCV), and influenza A virus (IAV).
Tree topologies remained largely unaffected when comparing recurrent mutation models to boundary mutation models.
Branch lengths and quantitative estimates of mutation bias and natural selection were substantially compromised under the rare mutation assumption across both simulated and empirical viral datasets.

Cite This Study

Borges et al. (2026) studied this question.

synapsesocial.com/papers/6a86b5eb8a91293e6a1cd7f5 https://doi.org/10.1093/sysbio/syag065

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August 20, 2026Systematic BiologyOpen Access

Phylogenetic inference with not-so-rare mutations and tiny organisms

View Full Paper

Ask AI

Bookmark

Authors

RBRui Borges JHJoseph Hughes

Discussion

Member takes

Overview

Computational modeling reveals compromised branch lengths and selection estimates under rare-mutation assumptions in viruses, highlighting the necessity of accounting for recurrent mutations.

Key Points

To assess the validity of the rare mutation assumption in molecular phylogenetics and quantify its impact on evolutionary inferences in rapidly mutating pathogens.
Compared two mathematical mutation models: one incorporating recurrent mutations and another restricted to boundary (infrequent) mutations.
Evaluated both models using synthetic simulation data as well as empirical viral genomic sequences from HIV, hepatitis C virus (HCV), and influenza A virus (IAV).
Tree topologies remained largely unaffected when comparing recurrent mutation models to boundary mutation models.
Branch lengths and quantitative estimates of mutation bias and natural selection were substantially compromised under the rare mutation assumption across both simulated and empirical viral datasets.

Cite This Study

Borges et al. (2026) studied this question.

synapsesocial.com/papers/6a86b5eb8a91293e6a1cd7f5 https://doi.org/10.1093/sysbio/syag065

View Full Paper

Ask AI

Bookmark