# Extensive de novo mutation rate variation between individuals and across the genome of Chlamydomonas reinhardtii

## TL;DR

This study reveals significant variation in mutation rates among individuals and across the genome of a green alga, shedding light on how spontaneous mutations occur.

## Contribution

The study reports the largest dataset of spontaneous mutations in Chlamydomonas reinhardtii and identifies factors influencing mutation rates.

## Key findings

- Mutation rates varied seven-fold among different strains of Chlamydomonas reinhardtii.
- Mutator genotypes caused dramatic increases in mutation rates in some replicates.
- A predictive model accurately estimated mutation rates based on genomic features like GC content and gene expression.

## Abstract

Describing the process of spontaneous mutation is fundamental for understanding the genetic basis of disease, the threat posed by declining population size in conservation biology, and in much evolutionary biology. However, directly studying spontaneous mutation is difficult because of the rarity of de novo mutations. Mutation accumulation (MA) experiments overcome this by allowing mutations to build up over many generations in the near absence of natural selection. In this study, we sequenced the genomes of 85 MA lines derived from six genetically diverse wild strains of the green alga Chlamydomonas reinhardtii. We identified 6,843 spontaneous mutations, more than any other study of spontaneous mutation. We observed seven-fold variation in the mutation rate among strains and that mutator genotypes arose, increasing the mutation rate dramatically in some replicates. We also found evidence for fine-scale heterogeneity in the mutation rate, driven largely by the sequence flanking mutated sites, and by clusters of multiple mutations at closely linked sites. There was little evidence, however, for mutation rate heterogeneity between chromosomes or over large genomic regions of 200Kbp. Using logistic regression, we generated a predictive model of the mutability of sites based on their genomic properties, including local GC content, gene expression level and local sequence context. Our model accurately predicted the average mutation rate and natural levels of genetic diversity of sites across the genome. Notably, trinucleotides vary 17-fold in rate between the most mutable and least mutable sites. Our results uncover a rich heterogeneity in the process of spontaneous mutation both among individuals and across the genome.