Controlling for life-history traits in vertebrates reveals that effective population size does not affect mutation rate or genome size
Abstract
Why mutation rates ( μ ) and genome sizes (GS) vary among species remains a central question in evolutionary genetics. Two influential models, the drift-barrier hypothesis (DBH) and the mutational-hazard hypothesis, propose that effective population size ( N e ) shapes these traits via the efficiency of selection, predicting higher μ and larger genomes in small populations. A recent comparative analysis of vertebrates reported a significant negative correlation between N e and μ , interpreted as support for the DBH. Using phylogenetic path analysis, we reanalyze the same dataset of 55 vertebrate species spanning mammals, birds, reptiles, and fishes, in which μ was estimated from high-coverage parent–offspring trios, while explicitly controlling for six life-history traits within a causal framework that tests model-implied conditional independencies. We show that the reported N e - μ association is entirely mediated by generation time (GT), which independently influences both variables; once this “back-door” path is blocked, N e has no detectable effect on μ . Once GT is accounted for, mating system shows the largest association with μ . Parallel analyses of GS within the same validated life-history framework reveal that GS is unrelated to N e , μ , or their interaction and is decoupled from the life-history covariation that strongly structures μ . These results are robust to alternative N e estimators and causal model formulations. Together, our findings indicate that N e provides little explanatory power for variation in μ or GS across vertebrates, challenging the presumed universality of drift-limited genome evolution.
Fields of Study & Subjects
Genetic diversity and population structure
Evolution and Genetic Dynamics
Cancer Genomics and Diagnostics
Publication details
- Journal / source
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Volume
- 123
- Issue
- 6
- Pages
- e2519649123–e2519649123
- Publication date
- 3 February 2026
- Language
- EN