Evolution of genome size in asexual populations

TL;DR

This study uses digital evolution to explore how mutation rates influence genome size in asexual populations, revealing a tradeoff between phenotypic innovation and mutational load that drives genome expansion or compression.

Contribution

It demonstrates how mutation rate affects genome size evolution in asexual organisms through digital simulations, linking mutation dynamics to phenotypic complexity.

Findings

Lower mutation rates promote genome expansion and phenotypic complexity.

Higher mutation rates lead to genome compression due to mutational load.

Mutation rate inversely correlates with genome size in asexual populations.

Abstract

Genome sizes have evolved to vary widely, from 250 bases in viroids to 670 billion bases in amoeba. This remarkable variation in genome size is the outcome of complex interactions between various evolutionary factors such as point mutation rate, population size, insertions and deletions, and genome editing mechanisms that may be specific to certain taxonomic lineages. While comparative genomics analyses have uncovered some of the relationships between these diverse evolutionary factors, we still do not understand what drives genome size evolution. Specifically, it is not clear how primordial mutational processes of base substitutions, insertions, and deletions influence genome size evolution in asexual organisms. Here, we use digital evolution to investigate genome size evolution by tracking genome edits and their fitness effects in real time. In agreement with empirical data, we find that mutation rate is inversely correlated with genome size in asexual populations. We show that at low point mutation rate, insertions are significantly more beneficial than deletions, driving genome expansion and acquisition of phenotypic complexity. Conversely, high mutational load experienced at high mutation rates inhibits genome growth, forcing the genomes to compress genetic information. Our analyses suggest that the inverse relationship between mutation rate and genome size is a result of the tradeoff between evolving phenotypic innovation and limiting the mutational load.