English

Quantifying Genetic Innovation: Mathematical Foundations for the Topological Study of Reticulate Evolution

Algebraic Topology 2020-01-17 v2 Computational Geometry Populations and Evolution Quantitative Methods

Abstract

A topological approach to the study of genetic recombination, based on persistent homology, was introduced by Chan, Carlsson, and Rabad\'an in 2013. This associates a sequence of signatures called barcodes to genomic data sampled from an evolutionary history. In this paper, we develop theoretical foundations for this approach. First, we present a novel formulation of the underlying inference problem. Specifically, we introduce and study the novelty profile, a simple, stable statistic of an evolutionary history which not only counts recombination events but also quantifies how recombination creates genetic diversity. We propose that the (hitherto implicit) goal of the topological approach to recombination is the estimation of novelty profiles. We then study the problem of obtaining a lower bound on the novelty profile using barcodes. We focus on a low-recombination regime, where the evolutionary history can be described by a directed acyclic graph called a galled tree, which differs from a tree only by isolated topological defects. We show that in this regime, under a complete sampling assumption, the 1st1^\mathrm{st} barcode yields a lower bound on the novelty profile, and hence on the number of recombination events. For i>1i>1, the ithi^{\mathrm{th}} barcode is empty. In addition, we use a stability principle to strengthen these results to ones which hold for any subsample of an arbitrary evolutionary history. To establish these results, we describe the topology of the Vietoris--Rips filtrations arising from evolutionary histories indexed by galled trees. As a step towards a probabilistic theory, we also show that for a random history indexed by a fixed galled tree and satisfying biologically reasonable conditions, the intervals of the 1st1^{\mathrm{st}} barcode are independent random variables. Using simulations, we explore the sensitivity of these intervals to recombination.

Keywords

Cite

@article{arxiv.1804.01398,
  title  = {Quantifying Genetic Innovation: Mathematical Foundations for the Topological Study of Reticulate Evolution},
  author = {Michael Lesnick and Raúl Rabadán and Daniel I. S. Rosenbloom},
  journal= {arXiv preprint arXiv:1804.01398},
  year   = {2020}
}

Comments

Expository improvements and minor corrections. To appear in the SIAM Journal on Applied Algebra and Geometry. 47 pages

R2 v1 2026-06-23T01:13:43.063Z