RecPD: A Recombination-aware measure of phylogenetic diversity.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
02 2022
Historique:
received: 04 10 2021
accepted: 07 02 2022
revised: 04 03 2022
pubmed: 23 2 2022
medline: 13 4 2022
entrez: 22 2 2022
Statut: epublish

Résumé

A critical step in studying biological features (e.g., genetic variants, gene families, metabolic capabilities, or taxa) is assessing their diversity and distribution among a sample of individuals. Accurate assessments of these patterns are essential for linking features to traits or outcomes of interest and understanding their functional impact. Consequently, it is of crucial importance that the measures employed for quantifying feature diversity can perform robustly under any evolutionary scenario. However, the standard measures used for quantifying and comparing the distribution of features, such as prevalence, phylogenetic diversity, and related approaches, either do not take into consideration evolutionary history, or assume strictly vertical patterns of inheritance. Consequently, these approaches cannot accurately assess diversity for features that have undergone recombination or horizontal transfer. To address this issue, we have devised RecPD, a novel recombination-aware phylogenetic-diversity statistic for measuring the distribution and diversity of features under all evolutionary scenarios. RecPD utilizes ancestral-state reconstruction to map the presence / absence of features onto ancestral nodes in a species tree, and then identifies potential recombination events in the evolutionary history of the feature. We also derive several related measures from RecPD that can be used to assess and quantify evolutionary dynamics and correlation of feature evolutionary histories. We used simulation studies to show that RecPD reliably reconstructs feature evolutionary histories under diverse recombination and loss scenarios. We then applied RecPD in two diverse real-world scenarios including a preliminary study type III effector protein families secreted by the plant pathogenic bacterium Pseudomonas syringae and growth phenotypes of the Pseudomonas genus and demonstrate that prevalence is an inadequate measure that obscures the potential impact of recombination. We believe RecPD will have broad utility for revealing and quantifying complex evolutionary processes for features at any biological level.

Identifiants

pubmed: 35192600
doi: 10.1371/journal.pcbi.1009899
pii: PCOMPBIOL-D-21-01774
pmc: PMC8896707
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1009899

Déclaration de conflit d'intérêts

The authors declare that they have no competing interests.

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Auteurs

Cedoljub Bundalovic-Torma (C)

Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.

Darrell Desveaux (D)

Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.
Centre for the Analysis of Genome Evolution & Function, University of Toronto, Toronto, Ontario, Canada.

David S Guttman (DS)

Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.
Centre for the Analysis of Genome Evolution & Function, University of Toronto, Toronto, Ontario, Canada.

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Classifications MeSH