Fitness inference tested by in silico population genetics

Fuente: arXiv
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Hauptverfasser: Zeng, Hong-Li, Huang, Yu-Han, Barton, John, Aurell, Erik
Format: Preprint
Veröffentlicht: 2025
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author Zeng, Hong-Li
Huang, Yu-Han
Barton, John
Aurell, Erik
author_facet Zeng, Hong-Li
Huang, Yu-Han
Barton, John
Aurell, Erik
contents We consider populations evolving according to natural selection, mutation, and recombination, and assume that the genomes of all or a representative selection of individuals are known. We pose the problem if it is possible to infer fitness parameters and genotype fitness order from such data. We tested this hypothesis in simulated populations. We delineate parameter ranges where this is possible and other ranges where it is not.Our work provides a framework for determining when fitness inference is feasible from population-wide, whole-genome, time-stratified data and highlights settings where it is not. We give a brief survey of biological model organisms and human pathogens that fit into this framework.
format Preprint
id arxiv_https___arxiv_org_abs_2510_20500
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fitness inference tested by in silico population genetics
Zeng, Hong-Li
Huang, Yu-Han
Barton, John
Aurell, Erik
Populations and Evolution
Biological Physics
We consider populations evolving according to natural selection, mutation, and recombination, and assume that the genomes of all or a representative selection of individuals are known. We pose the problem if it is possible to infer fitness parameters and genotype fitness order from such data. We tested this hypothesis in simulated populations. We delineate parameter ranges where this is possible and other ranges where it is not.Our work provides a framework for determining when fitness inference is feasible from population-wide, whole-genome, time-stratified data and highlights settings where it is not. We give a brief survey of biological model organisms and human pathogens that fit into this framework.
title Fitness inference tested by in silico population genetics
topic Populations and Evolution
Biological Physics
url https://arxiv.org/abs/2510.20500