Branching structure of genealogies in spatially growing populations and its implications for population genetics inference

TL;DR

This paper analyzes the genealogical structure of spatially growing populations using the Eden model, revealing key properties of cell lineages and implications for population genetics inference, especially in microbial colonies and tumors.

Contribution

It provides the first detailed characterization of coalescence processes in spatial growth models, linking physical analogies with population genetics insights.

Findings

Quantitative estimates for clone size distribution and segregating sites.

Identification of features that could be mistaken for selection in non-spatial models.

Insights into genealogical structures during spatial expansion.

Abstract

Spatial models where growth is limited to the edge of the expansions have been instrumental to understand the population dynamics and the clone size distribution in growing cellular populations, such as microbial colonies and avascular tumours. A complete characterization of the coalescence process generated by spatial growth is still lacking, limiting our ability to apply classic population genetics inference to spatially growing populations. Here, we start filling this gap by investigating the statistical properties of the cell lineages generated by the two dimensional Eden model, leveraging their physical analogy with directed polymers. Our analysis provides quantitative estimates for population measurements that can easily be assessed via sequencing, such as the average number of segregating sites and the clone size distribution of a subsample of the population. Our results not only reveal remarkable features of the genealogies generated during growth, but also highlight new properties that can be misinterpreted as signs of selection if non-spatial models are inappropriately applied.