Genome destabilizing mutator alleles drive specific mutational trajectories in Saccharomyces cerevisiae

Instability throughout the Saccharomyces cerevisiae genome resulting from Pms1 endonuclease deficiency

The endonuclease activity of Pms1 directs mismatch repair by generating a nick in the newly replicated DNA strand. Inactivating Pms2, the human homologue of yeast Pms1, increases the chances of colorectal and uterine cancers. Here we use whole genome sequencing to show that loss of this endonuclease activity, via the pms1-DE variant, results in strong mutator effects throughout the Saccharomyces cerevisiae genome. Mutation rates are strongly increased for mutations resulting from all types of single-base substitutions and for a wide variety of single- and multi-base indel mutations. Rates for these events are further increased in strains combining pms1-DE with mutator variants of each of the three major leading and lagging strand replicases. In all cases, mutation rates, spectra, biases, and context preferences are statistically indistinguishable from strains with equivalent polymerases but lacking initial mismatch recognition due to deletion of MSH2. This implies that, across the nuclear genome, strand discrimination via the Pms1 endonuclease is as important for MMR as is initial mismatch recognition by Msh2 heterodimers.

Signification and Application of Mutator and Antimutator Phenotype-Induced Genetic Variations in Evolutionary Adaptation and Cancer Therapeutics

Mutations present a dichotomy in their implications for cellular processes. They primarily arise from DNA replication errors or damage repair processes induced by environmental challenges. Cumulative mutations underlie genetic variations and drive evolution, yet also contribute to degenerative diseases such as cancer and aging. The mutator phenotype elucidates the heightened mutation rates observed in malignant tumors. Evolutionary adaptation, analogous to bacterial and eukaryotic systems, manifests through mutator phenotypes during changing environmental conditions, highlighting the delicate balance between advantageous mutations and their potentially detrimental consequences. Leveraging the genetic tractability of Saccharomyces cerevisiae offers unique insights into mutator phenotypes and genome instability akin to human cancers. Innovative reporter assays in yeast model organisms enable the detection of diverse genome alterations, aiding a comprehensive analysis of mutator phenotypes. Despite significant advancements, our understanding of the intricate mechanisms governing spontaneous mutation rates and preserving genetic integrity remains incomplete. This review outlines various cellular pathways affecting mutation rates and explores the role of mutator genes and mutation-derived phenotypes, particularly prevalent in malignant tumor cells. An in-depth comprehension of mutator and antimutator activities in yeast and higher eukaryotes holds promise for effective cancer control strategies.

Adaptation of the yeast gene knockout collection is near-perfectly predicted by fitness and diminishing return epistasis

Adaptive evolution of clonally dividing cells and microbes is the ultimate cause of cancer and infectious diseases. The possibility of constraining the adaptation of cell populations, by inhibiting proteins enhancing the evolvability, has therefore attracted interest. However, our current understanding of how genes influence adaptation kinetics is limited, partly because accurately measuring adaptation for many cell populations is challenging. We used a high-throughput adaptive laboratory evolution platform to track the adaptation of >18,000 cell populations corresponding to single-gene deletion strains in the haploid yeast deletion collection. We report that the preadaptation fitness of gene knockouts near-perfectly (R2= 0.91) predicts their adaptation to arsenic, leaving at the most a marginal role for dedicated evolvability gene functions. We tracked the adaptation of another >23,000 gene knockout populations to a diverse range of selection pressures and generalized the almost perfect (R2=0.72-0.98) capacity of preadaptation fitness to predict adaptation. We also reconstructed mutations in FPS1, ASK10, and ARR3, which together account for almost all arsenic adaptation in wild-type cells, in gene deletions covering a broad fitness range and show that the predictability of arsenic adaptation can be understood as a by global epistasis, where excluding arsenic is more beneficial to arsenic unfit cells. The paucity of genes with a meaningful evolvability effect on adaptation diminishes the prospects of developing adjuvant drugs aiming to slow antimicrobial and chemotherapy resistance.

Heterogeneous Mutation Rates and Spectra in Yeast Hybrids

Mutation rates and spectra vary between species and among populations. Hybridization can contribute to this variation, but its role remains poorly understood. Estimating mutation rates requires controlled conditions where the effect of natural selection can be minimized. One way to achieve this is through mutation accumulation experiments coupled with genome sequencing. Here, we investigate 400 mutation accumulation lines initiated from 11 genotypes spanning intralineage, interlineage, and interspecific crosses of the yeasts Saccharomyces paradoxus and S. cerevisiae and propagated for 770 generations. We find significant differences in mutation rates and spectra among crosses, which are not related to the level of divergence of parental strains but are specific to some genotype combinations. Differences in number of generations and departures from neutrality play a minor role, whereas polyploidy and loss of heterozygosity impact mutation rates in some of the hybrid crosses in an opposite way.

A modified fluctuation assay reveals a natural mutator phenotype that drives mutation spectrum variation within Saccharomyces cerevisiae

Although studies of Saccharomyces cerevisiae have provided many insights into mutagenesis and DNA repair, most of this work has focused on a few laboratory strains. Much less is known about the phenotypic effects of natural variation within S. cerevisiae’s DNA repair pathways. Here, we use natural polymorphisms to detect historical mutation spectrum differences among several wild and domesticated S. cerevisiae strains. To determine whether these differences are likely caused by genetic mutation rate modifiers, we use a modified fluctuation assay with a CAN1 reporter to measure de novo mutation rates and spectra in 16 of the analyzed strains. We measure a 10-fold range of mutation rates and identify two strains with distinctive mutation spectra. These strains, known as AEQ and AAR, come from the panel’s ‘Mosaic beer’ clade and share an enrichment for C > A mutations that is also observed in rare variation segregating throughout the genomes of several Mosaic beer and Mixed origin strains. Both AEQ and AAR are haploid derivatives of the diploid natural isolate CBS 1782, whose rare polymorphisms are enriched for C > A as well, suggesting that the underlying mutator allele is likely active in nature. We use a plasmid complementation test to show that AAR and AEQ share a mutator allele in the DNA repair gene OGG1, which excises 8-oxoguanine lesions that can cause C > A mutations if left unrepaired.

Stability across the Whole Nuclear Genome in the Presence and Absence of DNA Mismatch Repair

We describe the contribution of DNA mismatch repair (MMR) to the stability of the eukaryotic nuclear genome as determined by whole-genome sequencing. To date, wild-type nuclear genome mutation rates are known for over 40 eukaryotic species, while measurements in mismatch repair-defective organisms are fewer in number and are concentrated on Saccharomyces cerevisiae and human tumors. Well-studied organisms include Drosophila melanogaster and Mus musculus, while less genetically tractable species include great apes and long-lived trees. A variety of techniques have been developed to gather mutation rates, either per generation or per cell division. Generational rates are described through whole-organism mutation accumulation experiments and through offspring–parent sequencing, or they have been identified by descent. Rates per somatic cell division have been estimated from cell line mutation accumulation experiments, from systemic variant allele frequencies, and from widely spaced samples with known cell divisions per unit of tissue growth. The latter methods are also used to estimate generational mutation rates for large organisms that lack dedicated germlines, such as trees and hyphal fungi. Mechanistic studies involving genetic manipulation of MMR genes prior to mutation rate determination are thus far confined to yeast, Arabidopsis thaliana, Caenorhabditis elegans, and one chicken cell line. A great deal of work in wild-type organisms has begun to establish a sound baseline, but far more work is needed to uncover the variety of MMR across eukaryotes. Nonetheless, the few MMR studies reported to date indicate that MMR contributes 100-fold or more to genome stability, and they have uncovered insights that would have been impossible to obtain using reporter gene assays.

Slow Growth and Increased Spontaneous Mutation Frequency in Respiratory Deficient afo1- Yeast Suppressed by a Dominant Mutation in ATP3

A yeast deletion mutation in the nuclear-encoded gene, AFO1, which codes for a mitochondrial ribosomal protein, led to slow growth on glucose, the inability to grow on glycerol or ethanol, and loss of mitochondrial DNA and respiration. We noticed that afo1- yeast readily obtains secondary mutations that suppress aspects of this phenotype, including its growth defect. We characterized and identified a dominant missense suppressor mutation in the ATP3 gene. Comparing isogenic slowly growing rho-zero and rapidly growing suppressed afo1- strains under carefully controlled fermentation conditions showed that energy charge was not significantly different between strains and was not causal for the observed growth properties. Surprisingly, in a wild-type background, the dominant suppressor allele of ATP3 still allowed respiratory growth but increased the petite frequency. Similarly, a slow-growing respiratory deficient afo1- strain displayed an about twofold increase in spontaneous frequency of point mutations (comparable to the rho-zero strain) while the suppressed strain showed mutation frequency comparable to the respiratory-competent WT strain. We conclude, that phenotypes that result from afo1- are mostly explained by rapidly emerging mutations that compensate for the slow growth that typically follows respiratory deficiency.

Exonuclease domain mutants of yeast DIS3 display genome instability

The exosome functions to regulate the cellular transcriptome through RNA biogenesis, surveillance, and decay. Mutations in Dis3, a catalytic subunit of the RNA exosome with separable endonuclease and exonuclease activities, are linked to multiple myeloma. Here we report that a cancer-associated DIS3 allele, dis3^E729K, provides evidence for DIS3 functioning in mitotic fidelity in yeast. This dis3^E729K allele does not induce defects in 7S→5.8S rRNA processing, although it elicits a requirement for P-body function. While it does not significantly influence cell cycle progression alone, the allele reduces the efficiency of cell cycle arrest in strains with defects in kinetochore assembly. Finally, point mutations in the exonuclease domains of yeast Dis3 elicit genome instability phenotypes; however, these DIS3 mutations do not increase DNA damage or RNA processing defects that lead to the accumulation of polyadenylated RNA in the nucleus. These data suggest that specific DIS3 activities support mitotic fidelity in yeast.

Muver, a computational framework for accurately calling accumulated mutations

BACKGROUND

Identification of mutations from next-generation sequencing data typically requires a balance between sensitivity and accuracy. This is particularly true of DNA insertions and deletions (indels), that can impart significant phenotypic consequences on cells but are harder to call than substitution mutations from whole genome mutation accumulation experiments. To overcome these difficulties, we present muver, a computational framework that integrates established bioinformatics tools with novel analytical methods to generate mutation calls with the extremely low false positive rates and high sensitivity required for accurate mutation rate determination and comparison.

RESULTS

Muver uses statistical comparison of ancestral and descendant allelic frequencies to identify variant loci and assigns genotypes with models that include per-sample assessments of sequencing errors by mutation type and repeat context. Muver identifies maximally parsimonious mutation pathways that connect these genotypes, differentiating potential allelic conversion events and delineating ambiguities in mutation location, type, and size. Benchmarking with a human gold standard father-son pair demonstrates muver's sensitivity and low false positive rates. In DNA mismatch repair (MMR) deficient Saccharomyces cerevisiae, muver detects multi-base deletions in homopolymers longer than the replicative polymerase footprint at rates greater than predicted for sequential single-base deletions, implying a novel multi-repeat-unit slippage mechanism.

CONCLUSIONS

Benchmarking results demonstrate the high accuracy and sensitivity achieved with muver, particularly for indels, relative to available tools. Applied to an MMR-deficient Saccharomyces cerevisiae system, muver mutation calls facilitate mechanistic insights into DNA replication fidelity.

RECQ-like helicases Sgs1 and BLM regulate R-loop-associated genome instability

Sgs1, the orthologue of human Bloom's syndrome helicase BLM, is a yeast DNA helicase functioning in DNA replication and repair. We show that SGS1 loss increases R-loop accumulation and sensitizes cells to transcription-replication collisions. Yeast lacking SGS1 accumulate R-loops and γ-H2A at sites of Sgs1 binding, replication pausing regions, and long genes. The mutation signature of sgs1Δ reveals copy number changes flanked by repetitive regions with high R-loop-forming potential. Analysis of BLM in Bloom's syndrome fibroblasts or by depletion of BLM from human cancer cells confirms a role for Sgs1/BLM in suppressing R-loop-associated genome instability across species. In support of a potential direct effect, BLM is found physically proximal to DNA:RNA hybrids in human cells, and can efficiently unwind R-loops in vitro. Together, our data describe a conserved role for Sgs1/BLM in R-loop suppression and support an increasingly broad view of DNA repair and replication fork stabilizing proteins as modulators of R-loop-mediated genome instability.

Selective aggregation of the splicing factor Hsh155 suppresses splicing upon genotoxic stress

Upon genotoxic stress, dynamic relocalization events control DNA repair as well as alterations of the transcriptome and proteome, enabling stress recovery. How these events may influence one another is only partly known. Beginning with a cytological screen of genome stability proteins, we find that the splicing factor Hsh155 disassembles from its partners and localizes to both intranuclear and cytoplasmic protein quality control (PQC) aggregates under alkylation stress. Aggregate sequestration of Hsh155 occurs at nuclear and then cytoplasmic sites in a manner that is regulated by molecular chaperones and requires TORC1 activity signaling through the Sfp1 transcription factor. This dynamic behavior is associated with intron retention in ribosomal protein gene transcripts, a decrease in splicing efficiency, and more rapid recovery from stress. Collectively, our analyses suggest a model in which some proteins evicted from chromatin and undergoing transcriptional remodeling during stress are targeted to PQC sites to influence gene expression changes and facilitate stress recovery.

Modelling Mutation Spectra of Human Carcinogens Using Experimental Systems

Mutation spectra in cancer genomes provide information on the disease aetiology and the causality underlying the evolution and progression of cancer. Genome-wide mutation patterns reflect the effects of mutagenic insults and can thus reveal past carcinogen-specific exposures and inform hypotheses on the causative factors for specific cancer types. To identify mutation profiles in human cancers, single-gene studies were first employed, focusing mainly on the tumour suppressor gene TP53. Furthermore, experimental studies had been developed in model organisms. They allowed the characterization of the mutation patterns specific to known human carcinogens, such as polycyclic aromatic hydrocarbons or ultraviolet light. With the advent of massively parallel sequencing, mutation landscapes become revealed on a large scale, in human primary tumours and in experimental models, enabling deeper investigations of the functional and structural impact of mutations on the genome, including exposure-specific base-change fingerprints known as mutational signatures. These studies can now accelerate the identification of aetiological factors, contribute to carcinogen evaluation and classification and ultimately inform cancer prevention measures.

Hypermutation signature reveals a slippage and realignment model of translesion synthesis by Rev3 polymerase in cisplatin-treated yeast

Gene-gene or gene-drug interactions are typically quantified using fitness as a readout because the data are continuous and easily measured in high throughput. However, to what extent fitness captures the range of other phenotypes that show synergistic effects is usually unknown. Using Saccharomyces cerevisiae and focusing on a matrix of DNA repair mutants and genotoxic drugs, we quantify 76 gene-drug interactions based on both mutation rate and fitness and find that these parameters are not connected. Independent of fitness defects, we identified six cases of synthetic hypermutation, where the combined effect of the drug and mutant on mutation rate was greater than predicted. One example occurred when yeast lacking RAD1 were exposed to cisplatin, and we characterized this interaction using whole-genome sequencing. Our sequencing results indicate mutagenesis by cisplatin in rad1Δ cells appeared to depend almost entirely on interstrand cross-links at GpCpN motifs. Interestingly, our data suggest that the following base on the template strand dictates the addition of the mutated base. This result differs from cisplatin mutation signatures in XPF-deficient Caenorhabditis elegans and supports a model in which translesion synthesis polymerases perform a slippage and realignment extension across from the damaged base. Accordingly, DNA polymerase ζ activity was essential for mutagenesis in cisplatin-treated rad1Δ cells. Together these data reveal the potential to gain new mechanistic insights from nonfitness measures of gene-drug interactions and extend the use of mutation accumulation and whole-genome sequencing analysis to define DNA repair mechanisms.

Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum

The characterization of mutational spectra is usually carried out in one of three ways-by direct observation through mutation accumulation (MA) experiments, through parent-offspring sequencing, or by indirect inference from sequence data. Direct observations of spontaneous mutations with MA experiments are limited, given (i) the rarity of spontaneous mutations, (ii) applicability only to laboratory model species with short generation times, and (iii) the possibility that mutational spectra under lab conditions might be different from those observed in nature. Trio sequencing is an elegant solution, but it is not applicable in all organisms. Indirect inference, usually from divergence data, faces no such technical limitations, but rely upon critical assumptions regarding the strength of natural selection that are likely to be violated. Ideally, new mutational events would be directly observed before the biased filter of selection, and without the technical limitations common to lab experiments. One approach is to identify very young mutations from population sequencing data. Here we do so by leveraging two characteristics common to all new mutations-new mutations are necessarily rare in the population, and absent in the genomes of immediate relatives. From 132 clinical yeast strains, we were able to identify 1,425 putatively new mutations and show that they exhibit extremely low signatures of selection, as well as display a mutational spectrum that is similar to that identified by a large scale MA experiment. We verify that population sequencing data are a potential wealth of information for inferring mutational spectra, and should be considered for analysis where MA experiments are infeasible or especially tedious.

Dosage Mutator Genes in Saccharomyces cerevisiae: A Novel Mutator Mode-of-Action of the Mph1 DNA Helicase

Mutations that cause genome instability are considered important predisposing events that contribute to initiation and progression of cancer. Genome instability arises either due to defects in genes that cause an increased mutation rate (mutator phenotype), or defects in genes that cause chromosome instability (CIN). To extend the catalog of genome instability genes, we systematically explored the effects of gene overexpression on mutation rate, using a forward-mutation screen in budding yeast. We screened ∼5100 plasmids, each overexpressing a unique single gene, and characterized the five strongest mutators, MPH1 (mutator phenotype 1), RRM3, UBP12, PIF1, and DNA2 We show that, for MPH1, the yeast homolog of Fanconi Anemia complementation group M (FANCM), the overexpression mutator phenotype is distinct from that of mph1Δ. Moreover, while four of our top hits encode DNA helicases, the overexpression of 48 other DNA helicases did not cause a mutator phenotype, suggesting this is not a general property of helicases. For Mph1 overexpression, helicase activity was not required for the mutator phenotype; in contrast Mph1 DEAH-box function was required for hypermutation. Mutagenesis by MPH1 overexpression was independent of translesion synthesis (TLS), but was suppressed by overexpression of RAD27, a conserved flap endonuclease. We propose that binding of DNA flap structures by excess Mph1 may block Rad27 action, creating a mutator phenotype that phenocopies rad27Δ. We believe this represents a novel mutator mode-of-action and opens up new prospects to understand how upregulation of DNA repair proteins may contribute to mutagenesis.

Genomic approaches to DNA repair and mutagenesis

DNA damage is a constant threat to cells, causing cytotoxicity as well as inducing genetic alterations. The steady-state abundance of DNA lesions in a cell is minimized by a variety of DNA repair mechanisms, including DNA strand break repair, mismatch repair, nucleotide excision repair, base excision repair, and ribonucleotide excision repair. The efficiencies and mechanisms by which these pathways remove damage from chromosomes have been primarily characterized by investigating the processing of lesions at defined genomic loci, among bulk genomic DNA, on episomal DNA constructs, or using in vitro substrates. However, the structure of a chromosome is heterogeneous, consisting of heavily protein-bound heterochromatic regions, open regulatory regions, actively transcribed genes, and even areas of transient single stranded DNA. Consequently, DNA repair pathways function in a much more diverse set of chromosomal contexts than can be readily assessed using previous methods. Recent efforts to develop whole genome maps of DNA damage, repair processes, and even mutations promise to greatly expand our understanding of DNA repair and mutagenesis. Here we review the current efforts to utilize whole genome maps of DNA damage and mutation to understand how different chromosomal contexts affect DNA excision repair pathways.

Navigating yeast genome maintenance with functional genomics

Maintenance of genome integrity is a fundamental requirement of all organisms. To address this, organisms have evolved extremely faithful modes of replication, DNA repair and chromosome segregation to combat the deleterious effects of an unstable genome. Nonetheless, a small amount of genome instability is the driver of evolutionary change and adaptation, and thus a low level of instability is permitted in populations. While defects in genome maintenance almost invariably reduce fitness in the short term, they can create an environment where beneficial mutations are more likely to occur. The importance of this fact is clearest in the development of human cancer, where genome instability is a well-established enabling characteristic of carcinogenesis. This raises the crucial question: what are the cellular pathways that promote genome maintenance and what are their mechanisms? Work in model organisms, in particular the yeast Saccharomyces cerevisiae, has provided the global foundations of genome maintenance mechanisms in eukaryotes. The development of pioneering genomic tools inS. cerevisiae, such as the systematic creation of mutants in all nonessential and essential genes, has enabled whole-genome approaches to identifying genes with roles in genome maintenance. Here, we review the extensive whole-genome approaches taken in yeast, with an emphasis on functional genomic screens, to understand the genetic basis of genome instability, highlighting a range of genetic and cytological screening modalities. By revealing the biological pathways and processes regulating genome integrity, these analyses contribute to the systems-level map of the yeast cell and inform studies of human disease, especially cancer.

Dissecting genetic and environmental mutation signatures with model organisms

Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon.