# Not Just Ne  Ne-More: New Applications for SMC from Ecology to Phylogenies

## TL;DR

This paper explores new uses of the SMC model in genetics, expanding its application to include ecological and evolutionary factors.

## Contribution

The paper introduces recent extensions to the SMC model, enabling it to account for gene flow, structural variation, and ecological traits.

## Key findings

- SMC-based methods now incorporate isolation with migration and multi-species coalescent models.
- Recent computational advances allow SMC to better handle ecological life history traits like selfing and dormancy.
- The paper highlights biological discoveries made possible by these extended SMC methods.

## 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.