Not Just <i>N</i> <i>e</i>   <i>N</i> <i>e</i> -More: New Applications for SMC from Ecology to Phylogenies

Genomes contain the mutational footprint of an organism's evolutionary history, shaped by diverse forces including ecological factors, selective pressures, and life history traits. The sequentially Markovian coalescent (SMC) is a versatile and tractable model for the genetic genealogy of a sample of genomes, which captures this shared history. Methods that utilize the SMC, such as PSMC and MSMC, have been widely used in evolution and ecology to infer demographic histories. However, these methods ignore common biological features, such as gene flow events and structural variation. Recently, there have been several advancements that widen the applicability of SMC-based methods: inclusion of an isolation with migration model, integration with the multi-species coalescent, incorporation of ecological life history traits (such as selfing and dormancy), and many computational advances in applying these models to data. We give an overview of the SMC model and its various recent extensions, discuss examples of biological discoveries through SMC-based inference, and comment on the assumptions, benefits and drawbacks of various methods.

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Publication Details

Journal
Genome Biology and Evolution
Published
2025-11-28
DOI
https://doi.org/10.1093/gbe/evaf229
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
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article

Not Just N e   N e -More: New Applications for SMC from Ecology to Phylogenies

Elizabeth T. Chevy, Toby G. L. Kovacs, A. Nieto, Arun Durvasula et al.
Genome Biology and Evolution
Evolution and Genetic Dynamics
article

Not Just N e   N e -More: New Applications for SMC from Ecology to Phylogenies

Elizabeth T. Chevy, Toby G. L. Kovacs, A. Nieto, Arun Durvasula, Trevor Cousins, Anastasia Ignatieva, Emily E. Puckett, David Peede
article en

Abstract

Genomes contain the mutational footprint of an organism's evolutionary history, shaped by diverse forces including ecological factors, selective pressures, and life history traits. The sequentially Markovian coalescent (SMC) is a versatile and tractable model for the genetic genealogy of a sample of genomes, which captures this shared history. Methods that utilize the SMC, such as PSMC and MSMC, have been widely used in evolution and ecology to infer demographic histories. However, these methods ignore common biological features, such as gene flow events and structural variation. Recently, there have been several advancements that widen the applicability of SMC-based methods: inclusion of an isolation with migration model, integration with the multi-species coalescent, incorporation of ecological life history traits (such as selfing and dormancy), and many computational advances in applying these models to data. We give an overview of the SMC model and its various recent extensions, discuss examples of biological discoveries through SMC-based inference, and comment on the assumptions, benefits and drawbacks of various methods.

Genome Biology and EvolutionVol. 18(1)
University of Southern California (US), Centre National de la Recherche Scientifique (FR), The University of Sydney (AU), École Pratique des Hautes Études (FR), University of Cambridge (GB), Université Paris Sciences et Lettres (FR), Brown University (US), Sorbonne Université (FR), University of Oxford (GB), Institut de Systématique, Évolution, Biodiversité (FR), Institut de Recherche pour le Développement (FR), University of Memphis (US)
Openalex Percentile: Top 61%
Evolution and Genetic Dynamics
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