# mSphere of Influence: Predicting the evolution of pathogen populations

## TL;DR

This article discusses how genomic data can help predict the evolution of pathogen populations.

## Contribution

The paper highlights the novel use of genomic data to forecast pathogen evolution through frequency-dependent selection and pangenome analysis.

## Key findings

- Genomic data can forecast evolution in Streptococcus pneumoniae via frequency-dependent selection.
- Prokaryotic pangenome evolution reveals insights into contingency and predictability.
- These findings influence pathogen population genomics and evolutionary predictions.

## Abstract

Tatum D. Mortimer works in the field of pathogen population genomics and evolution. In this mSphere of Influence article, she reflects on how “Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae” by Azarian et al. and “Contingency, repeatability, and predictability in the evolution of a prokaryotic pangenome” by Beavan et al. made an impact on her by highlighting the ways in which genomic data can be used to predict pathogen evolution.