Strong correlations between mutation rates and selective constraint in the human genome?
- 1University of Wisconsin-Madison
Abstract
The 21st century has seen repeated challenges to the premise that de novo mutations occur independently from their fitness effects. So far, these attempts have been dismissed as technical artifacts, restoring confidence in the null hypothesis. Yet the development of high-resolution genomic resources enables investigating the relationship between mutation rate variation and selective constraint with unprecedented detail. Here, we use state-of-the art genomic maps to test whether predicted mutation rates differ within and outside putatively constrained sites in humans. Contrary to the hypothesis that is typically put forward, but in agreement with another recent study, we find that protein-coding genes exhibit higher rates of mutation than the neutral genomic background. Conversely, mutation rates are lower in non-coding elements identified through sequence conservation. This can be attributed either to biases in the estimation of mutation rates in sites under selection, biases in scoring constraint in sites with low rates of mutation, or a genuine signal that would merit further investigation. Regardless of the underlying cause, our findings have broad implications for evolutionary genetics. Several studies rely on accurate mutation maps and identification of selection targets across the genome, which inherently confound each other. Caution is therefore warranted when interpreting results from currently available non-coding scores.
Related
- The VGLUT3-p.T8I Mutation Alters Striatal Acetylcholine Dynamics in Response to Social Stressors and Drives Selective Social Avoidance in Male Mice
- Recombination shapes the dynamics of selective constraint in global populations of human gut bacteria
- Epigenetic regulators partition the genome by evolutionary and developmental constraint
- Exploring the influence of mutation rates with stochastic perturbations on genome evolution
- Cellular mechanism of gain-of-function mutation I173M in sheep MC4R gene identified in year-round and seasonal estrus breeds through whole-genome resequencing
BibTeX
@misc{barroso2026strong,
title = {{Strong correlations between mutation rates and selective constraint in the human genome?}},
author = {G. V. Barroso and A. Ragsdale},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.08.757506},
url = {https://www.biorxiv.org/content/10.64898/2026.10.08.757506v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Strong correlations between mutation rates and selective constraint in the human genome?
AU - G. V. Barroso
AU - A. Ragsdale
PY - 2026
DA - 2026/10/08
PB - bioRxiv
DO - 10.64898/2026.10.08.757506
UR - https://www.biorxiv.org/content/10.64898/2026.10.08.757506v1
AB - The 21st century has seen repeated challenges to the premise that de novo mutations occur independently from their fitness effects. So far, these attempts have been dismissed as technical artifacts, restoring confidence in the null hypothesis. Yet the development of high-resolution genomic resources enables investigating the relationship between mutation rate variation and selective constraint with unprecedented detail. Here, we use state-of-the art genomic maps to test whether predicted mutation rates differ within and outside putatively constrained sites in humans. Contrary to the hypothesis that is typically put forward, but in agreement with another recent study, we find that protein-coding genes exhibit higher rates of mutation than the neutral genomic background. Conversely, mutation rates are lower in non-coding elements identified through sequence conservation. This can be attributed either to biases in the estimation of mutation rates in sites under selection, biases in scoring constraint in sites with low rates of mutation, or a genuine signal that would merit further investigation. Regardless of the underlying cause, our findings have broad implications for evolutionary genetics. Several studies rely on accurate mutation maps and identification of selection targets across the genome, which inherently confound each other. Caution is therefore warranted when interpreting results from currently available non-coding scores.
ER -