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Mutations are the ultimate source of all genetic variation. However, few direct estimates of the contribution of mutation to molecular genetic variation are available. To address this issue, we first analyzed the rate and spectrum of mutations in the Arabidopsis thaliana reference accession after 25 generations of single-seed descent. We then compared the mutation profile in these mutation accumulation (MA) lines against genetic variation observed in the 1001 Genomes Project. The estimated haploid single nucleotide mutation (SNM) rate for A. thaliana is 6.95 × 10−9 (SE ± 2.68 × 10−10) per site per generation, with SNMs having higher frequency in transposable elements (TEs) and centromeric regions. The estimated indel mutation rate is 1.30 × 10−9 (±1.07 × 10−10) per site per generation, with deletions being more frequent and larger than insertions. Among the 1694 unique SNMs identified in the MA lines, the positions of 389 SNMs (23%) coincide with biallelic SNPs from the 1001 Genomes population, and in 289 (17%) cases the changes are identical. Of the 329 unique indels identified in the MA lines, 96 (29%) overlap with indels from the 1001 Genomes dataset, and 16 indels (5% of the total) are identical. These overlap frequencies are significantly higher than expected, suggesting that de novo mutations are not uniformly distributed and arise at polymorphic sites more frequently than assumed. These results suggest that high mutation rate potentially contributes to high polymorphism and low mutation rate to reduced polymorphism in natural populations providing insights of mutational inputs in generating natural genetic diversity.

Experimental investigations into the rates and fitness effects of spontaneous mutations are fundamental to our understanding of the evolutionary process. To gain insights into the molecular and fitness consequences of spontaneous mutations, we conducted a mutation accumulation (MA) experiment at varying population sizes in the nematode Caenorhabditis elegans, evolving 35 lines in parallel for 409 generations at three population sizes (N = 1, 10, and 100 individuals). Here, we focus on nuclear SNPs and small insertion/deletions (indels) under minimal influence of selection, as well as their accrual rates in larger populations under greater selection efficacy. The spontaneous rates of base substitutions and small indels are 1.84 (95% C.I. ± 0.14) × 10−9 substitutions and 6.84 (95% C.I. ± 0.97) × 10−10 changes/site/generation, respectively. Small indels exhibit a deletion bias with deletions exceeding insertions by threefold. Notably, there was no correlation between the frequency of base substitutions, nonsynonymous substitutions, or small indels with population size. These results contrast with our previous analysis of mitochondrial DNA mutations and nuclear copy-number changes in these MA lines, and suggest that nuclear base substitutions and small indels are under less stringent purifying selection compared to the former mutational classes. A transition bias was observed in exons as was a near universal base substitution bias toward A/T. Strongly context-dependent base substitutions, where 5′−Ts and 3′−As increase the frequency of A/T → T/A transversions, especially at the boundaries of A or T homopolymeric runs, manifest as higher mutation rates in (i) introns and intergenic regions relative to exons, (ii) chromosomal cores vs. arms and tips, and (iii) germline-expressed genes.

Accurate estimates of mutation rates derived from genome‐wide mutation accumulation (MA) data are fundamental to understanding basic evolutionary processes. The rapidly improving high‐throughput sequencing technologies provide unprecedented opportunities to identify single nucleotide mutations across genomes. However, such MA derived data are often difficult to analyze and the performance of the available methods of analysis is not well understood. In this study, we used the existing Bayesian Genotype Caller adapted for MA data that we refer to as Bayesian Mutation Finder (BMF) for identifying single nucleotide mutations while considering the characteristics of the data. We compared the performance of BMF with the widely used Genome Analysis Toolkit (GATK) by applying these two methods to time‐series MA data as well as simulated data. The time‐series data were obtained by propagating Daphnia pulex over an average of 188 generations and performing whole‐genome sequencing of 14 MA lines across three time points. The results indicate that BMF enables more accurate identification of single nucleotide mutations than GATK especially when applied to the empirical data. Furthermore, BMF involves the use of fewer parameters and is more computationally efficient than GATK. Both BMF and GATK found surprisingly many candidate mutations that were not confirmed at later time points. We systematically infer causes of the unconfirmed candidate mutations, introduce a framework for estimating mutation rates based on genome‐wide candidate mutations confirmed by subsequent sequencing, and provide an improved mutation rate estimate for D. pulex. Considering the characteristics of mutation accumulation (MA) data, we adapted the existing Bayesian Genotype Caller and we call this Bayesian Mutation Finder (BMF). The performance comparison of BMF and the currently widely used Genome Analysis Toolkit (GATK) using empirical time‐series and simulated MA data indicates that BMF enables more accurate mutation calling than GATK especially when applied to empirical data.

Tandemly repeated DNA is known to be highly abundant and highly divergent between species, but the genome-wide mutation rates in these mostly unmappable... A long-standing evolutionary puzzle is that all eukaryotic genomes contain large amounts of tandemly-repeated DNA whose sequence motifs and abundance vary greatly among even closely related species. To elucidate the evolutionary forces governing tandem repeat dynamics, quantification of the rates and patterns of mutations in repeat copy number and tests of its selective neutrality are necessary. Here, we used whole-genome sequences of 28 mutation accumulation (MA) lines of Daphnia pulex, in addition to six isolates from a non-MA population originating from the same progenitor, to both estimate mutation rates of abundances of repeat sequences and evaluate the selective regime acting upon them. We found that mutation rates of individual repeats were both high and highly variable, ranging from additions/deletions of 0.29–105 copies per generation (reflecting changes of 0.12–0.80% per generation). Our results also provide evidence that new repeat sequences are often formed from existing ones. The non-MA population isolates showed a signal of either purifying or stabilizing selection, with 33% lower variation in repeat copy number on average than the MA lines, although the level of selective constraint was not evenly distributed across all repeats. The changes between many pairs of repeats were correlated, and the pattern of correlations was significantly different between the MA lines and the non-MA population. Our study demonstrates that tandem repeats can experience extremely rapid evolution in copy number, which can lead to high levels of divergence in genome-wide repeat composition between closely related species.

When addressing a genomic question, having a reliable and adequate reference genome is of utmost importance. This drives the necessity to refine and customize reference genomes (RGs). Our laboratory has recently developed a strategy, the Perfect Match Genomic Landscape (PMGL), to detect variation between genomes [K. Palacios-Flores et al.. Genetics 208, 1631–1641 (2018)]. The PMGL is precise and sensitive and, in contrast to most currently used algorithms, is nonstatistical in nature. Here we demonstrate the power of PMGL to refine and customize RGs. As a proof-of-concept, we refined different versions of the Saccharomyces cerevisiae RG. We applied the automatic PMGL pipeline to refine the genomes of microorganisms belonging to the three domains of life: the archaea Methanococcus maripaludis and Pyrococcus furiosus; the bacteria Escherichia coli, Staphylococcus aureus, and Bacillus subtilis; and the eukarya Schizosaccharomyces pombe, Aspergillus oryzae, and several strains of Saccharomyces paradoxus. We analyzed the reference genome of the virus SARS-CoV-2 and previously published viral genomes from patients’ samples with COVID-19. We performed a mutation-accumulation experiment in E. coli and show that the PMGL strategy can detect specific mutations generated at any desired step of the whole procedure. We propose that PMGL can be used as a final step for the refinement and customization of any haploid genome, independently of the strategies and algorithms used in its assembly.

The release of heavy metals from industrial, agricultural, and mining activities poses significant risks to aquatic ecosystems by degrading water quality and generating reactive oxygen species that can damage DNA in aquatic organisms. Daphnia is a widespread keystone species in freshwater ecosystems that is routinely exposed to a range of anthropogenic and natural stressors. With a fully sequenced genome, a well-understood life history and ecology, and an extensive library of responses to toxicity, Daphnia serves as an ideal model organism for studying the impact of environmental stressors on genomic stability. Ribosomal DNA (rDNA) encodes ribosomal RNA (rRNA), which is essential for protein synthesis, and the spacers that separate the rRNA genes contain regulatory elements. However, the effects of heavy metals on this region of the genome are not well documented. We used short-read whole-genome sequences to analyze copy number and sequence variation in Daphnia pulex mutation accumulation lines exposed to nickel and copper, both individually and in combination, at concentrations that mimic levels often found at contaminated sites. We found no significant direct effect of chronic exposure to either metal on rDNA copy number or sequence variation. However, the results suggest that nickel and copper exposure may indirectly influence rDNA by altering recombination rates. We also emphasize the importance of interval length between generational samples for accurately assessing the frequency and magnitude of rDNA copy number changes. In addition, we observed differential expansion of rDNA haplotypes, suggesting that they may be clustered within the rDNA array.

Using a mechanistic spatially explicit trait-based neighborhood-model, we quantify the impact of mutations on intraspecific spatial interactions to better understand mechanisms underlying the maintenance of genetic variation and the potential effects of these evolved interactions on the population dynamics of Arabidopsis thaliana. We use 100 twenty-fifth generation mutation accumulation (MA) lines (genotypes) derived from one founder genotype to study mutational effects on neighbor responses in a field experiment. We created individual-based maps (15,000 individuals), including phenotypic variation, to quantify mutational effects within genotypes versus between genotypes on reproduction and survival. At small-scale (within 80 cm of the focal plant), survival is enhanced but seed-set is decreased when a genotype is surrounded by different genotypes. At large-scale (within 200 cm of the focal plant), seed set is facilitated by different genotypes while the same genotype has either no effect or negative effects. The direction of the interactions among MA lines suggests that at small scale these interactions may contribute to the maintenance of genetic variation and at large scale contribute to the survival of the population. This may suggest, that, mutations potentially have immediate effects on population and community dynamics by influencing the outcome of competitive and faciliatory interactions among conspecifics.

To better understand the potential factors contributing to genome instability and phenotypic diversity, we conducted mutation accumulation (MA) experiments for 120 days for 7 diploid cryptococcal hybrids under fluconazole (10 MA lines each) and non-fluconazole conditions (10 MA lines each). The genomic DNA content, loss of heterozygosity (LOH) rate, growth ability, and fluconazole susceptibility were determined for all 140 evolved cultures. Compared to that of their ancestral clones, the evolved clones showed: (i) genomic DNA content changes ranging from ~22% less to ~27% more, and (ii) reduced, similar, and increased phenotypic values for each tested trait, with most evolved clones displaying increased growth at 40 °C and increased fluconazole resistance. Aside from the ancestral multi-locus genotypes (MLGs) and heterozygosity patterns (MHPs), 77 unique MLGs and 70 unique MPHs were identified among the 140 evolved cultures at day 120. The average LOH rates of the MA lines in the absence and presence of fluconazole were similar at 1.27 × 10−4 and 1.38 × 10−4 LOH events per MA line per mitotic division, respectively. While LOH rates varied among MA lines from different ancestors, there was no apparent correlation between the genetic divergence of the parental haploid genomes within ancestral clones and LOH rates. Together, our results suggest that hybrids between diverse lineages of the human pathogenic Cryptococcus can generate significant genotypic and phenotypic diversities during asexual reproduction.

Since the first half of the twentieth century, evolutionary theory has been dominated by the idea that mutations occur randomly with respect to their consequences 1 . Here we test this assumption with large surveys of de novo mutations in the plant Arabidopsis thaliana . In contrast to expectations, we find that mutations occur less often in functionally constrained regions of the genome—mutation frequency is reduced by half inside gene bodies and by two-thirds in essential genes. With independent genomic mutation datasets, including from the largest Arabidopsis mutation accumulation experiment conducted to date, we demonstrate that epigenomic and physical features explain over 90% of variance in the genome-wide pattern of mutation bias surrounding genes. Observed mutation frequencies around genes in turn accurately predict patterns of genetic polymorphisms in natural Arabidopsis accessions ( r  = 0.96). That mutation bias is the primary force behind patterns of sequence evolution around genes in natural accessions is supported by analyses of allele frequencies. Finally, we find that genes subject to stronger purifying selection have a lower mutation rate. We conclude that epigenome-associated mutation bias 2 reduces the occurrence of deleterious mutations in Arabidopsis , challenging the prevailing paradigm that mutation is a directionless force in evolution. Data on de novo mutations in Arabidopsis thaliana reveal that mutations do not occur randomly; instead, epigenome-associated mutation bias reduces the occurrence of deleterious mutations.

Stem cells of the liver, colon and small intestine gradually accumulate mutations throughout life at a similar rate even though cancer incidence varies greatly among these tissues. Accumulated mutations in adult stem cells Accumulation of mutations in human adult stem cells in the course of a lifetime has been associated with increase in cancer risk. But the actual mutation rates and patterns in these cells are currently unknown. Edwin Cuppen and colleagues have sequenced DNA from clonal organoids in culture derived from primary multipotent cells obtained from donors of aged between 3 and 87 years. They find that mutations accumulate at a similar rate of approximately 40 novel mutations per year in tissues with known variations in cancer incidence, but they also observe tissue-specific mutation spectra in the colon and small intestine compared to the liver. The gradual accumulation of genetic mutations in human adult stem cells (ASCs) during life is associated with various age-related diseases, including cancer 1 , 2 . Extreme variation in cancer risk across tissues was recently proposed to depend on the lifetime number of ASC divisions, owing to unavoidable random mutations that arise during DNA replication 1 . However, the rates and patterns of mutations in normal ASCs remain unknown. Here we determine genome-wide mutation patterns in ASCs of the small intestine, colon and liver of human donors with ages ranging from 3 to 87 years by sequencing clonal organoid cultures derived from primary multipotent cells 3 , 4 , 5 . Our results show that mutations accumulate steadily over time in all of the assessed tissue types, at a rate of approximately 40 novel mutations per year, despite the large variation in cancer incidence among these tissues 1 . Liver ASCs, however, have different mutation spectra compared to those of the colon and small intestine. Mutational signature analysis reveals that this difference can be attributed to spontaneous deamination of methylated cytosine residues in the colon and small intestine, probably reflecting their high ASC division rate. In liver, a signature with an as-yet-unknown underlying mechanism is predominant. Mutation spectra of driver genes in cancer show high similarity to the tissue-specific ASC mutation spectra, suggesting that intrinsic mutational processes in ASCs can initiate tumorigenesis. Notably, the inter-individual variation in mutation rate and spectra are low, suggesting tissue-specific activity of common mutational processes throughout life.