The Genetic Basis of Mutation Rate Variation in Yeast

The Rapid Evolution of De Novo Proteins in Structure and Complex

Recent studies in the rice genome-wide have established that de novo genes, evolving from noncoding sequences, enhance protein diversity through a stepwise process. However, the pattern and rate of their evolution in protein structure over time remain unclear. Here, we addressed these issues within a surprisingly short evolutionary timescale (<1 million years for 97% of Oryza de novo genes) with comparative approaches to gene duplicates. We found that de novo genes evolve faster than gene duplicates in the intrinsically disordered regions (such as random coils), secondary structure elements (such as α helix and β strand), hydrophobicity, and molecular recognition features. In de novo proteins, specifically, we observed an 8% to 14% decay in random coils and intrinsically disordered region lengths and a 2.3% to 6.5% increase in structured elements, hydrophobicity, and molecular recognition features, per million years on average. These patterns of structural evolution align with changes in amino acid composition over time as well. We also revealed higher positive charges but smaller molecular weights for de novo proteins than duplicates. Tertiary structure predictions showed that most de novo proteins, though not typically well folded on their own, readily form low-energy and compact complexes with other proteins facilitated by extensive residue contacts and conformational flexibility, suggesting a faster-binding scenario in de novo proteins to promote interaction. These analyses illuminate a rapid evolution of protein structure in de novo genes in rice genomes, originating from noncoding sequences, highlighting their quick transformation into active, protein complex-forming components within a remarkably short evolutionary timeframe.

Modular and integrative activity reporters enhance biochemical studies in the yeast ER

The yeast endoplasmic reticulum sequestration and screening (YESS) system is a broadly applicable platform to perform high-throughput biochemical studies of post-translational modification enzymes (PTM-enzymes). This system enables researchers to profile and engineer the activity and substrate specificity of PTM-enzymes and to discover inhibitor-resistant enzyme mutants. In this study, we expand the capabilities of YESS by transferring its functional components to integrative plasmids. The YESS integrative system yields uniform protein expression and protease activities in various configurations, allows one to integrate activity reporters at two independent loci and to split the system between integrative and centromeric plasmids. We characterize these integrative reporters with two viral proteases, Tobacco etch virus (TEVp) and 3-chymotrypsin like protease (3CLpro), in terms of coefficient of variance, signal-to-noise ratio and fold-activation. Overall, we provide a framework for chromosomal-based studies that is modular, enabling rigorous high-throughput assays of PTM-enzymes in yeast.

Fitness effects of a demography-dispersal trade-off in expandingSaccharomyces cerevisiaemats

Fungi expand in space and time to form complex multicellular communities. The mechanisms by which they do so can vary dramatically and determine the life-history and dispersal traits of expanding populations. These traits influence deterministic and stochastic components of evolution, resulting in complex eco-evolutionary dynamics during colony expansion. We perform experiments on budding yeast strains genetically engineered to display rough-surface and smooth-surface phenotypes in colony-like structures called 'mats'. Previously, it was shown that the rough-surface strain has a competitive advantage over the smooth-surface strain when grown on semi-solid media. We experimentally observe the emergence and expansion of segments with a distinct smooth-surface phenotype during rough-surface mat development. We propose a trade-off between dispersal and local carrying capacity to explain the relative fitness of these two phenotypes. Using a modified stepping-stone model, we demonstrate that this trade-off gives the high-dispersing, rough-surface phenotype a competitive advantage from standing variation, but that it inhibits this phenotype's ability to invade a resident smooth-surface population via mutation. However, the trade-off improves the ability of the smooth-surface phenotype to invade in rough-surface mats, replicating the frequent emergence of smooth-surface segments in experiments. Together, these computational and experimental findings advance our understanding of the complex eco-evolutionary dynamics of fungal mat expansion.

Upper Bound on the Mutational Burden Imposed by a CRISPR-Cas9 Gene-Drive Element

CRISPR-Cas9 gene drives (CCGDs) are powerful tools for genetic control of wild populations, useful for eradication of disease vectors, conservation of endangered species and other applications. However, Cas9 alone and in a complex with gRNA can cause double-stranded DNA breaks at off-target sites, which could increase the mutational load and lead to loss of heterozygosity (LOH). These undesired effects raise potential concerns about the long-term evolutionary safety of CCGDs, but the magnitude of these effects is unknown. To estimate how the presence of a CCGD or a Cas9 alone in the genome affects the rates of LOH events and de novo mutations, we carried out a mutation accumulation experiment in yeast Saccharomyces cerevisiae. Despite its substantial statistical power, our experiment revealed no detectable effect of CCGD or Cas9 alone on the genome-wide rates of mutations or LOH events, suggesting that these rates are affected by less than 30%. Nevertheless, we found that Cas9 caused a slight but significant shift towards more interstitial and fewer terminal LOH events, and the CCGD caused a significant difference in the distribution of LOH events on Chromosome V. Taken together, our results show that these genetic elements impose a weak and likely localized additional mutational burden in the yeast model. Although the mutagenic effects of CCGDs need to be further evaluated in other systems, our results suggest that the effect of CCGDs on off-target mutation rates and genetic diversity may be acceptable.

Genome instability footprint under rapamycin and hydroxyurea treatments

The mutational processes dictating the accumulation of mutations in genomes are shaped by genetic background, environment and their interactions. Accurate quantification of mutation rates and spectra under drugs has important implications in disease treatment. Here, we used whole-genome sequencing and time-resolved growth phenotyping of yeast mutation accumulation lines to give a detailed view of the mutagenic effects of rapamycin and hydroxyurea on the genome and cell growth. Mutation rates depended on the genetic backgrounds but were only marginally affected by rapamycin. As a remarkable exception, rapamycin treatment was associated with frequent chromosome XII amplifications, which compensated for rapamycin induced rDNA repeat contraction on this chromosome and served to maintain rDNA content homeostasis and fitness. In hydroxyurea, a wide range of mutation rates were elevated regardless of the genetic backgrounds, with a particularly high occurrence of aneuploidy that associated with dramatic fitness loss. Hydroxyurea also induced a high T-to-G and low C-to-A transversion rate that reversed the common G/C-to-A/T bias in yeast and gave rise to a broad range of structural variants, including mtDNA deletions. The hydroxyurea mutation footprint was consistent with the activation of error-prone DNA polymerase activities and non-homologues end joining repair pathways. Taken together, our study provides an in-depth view of mutation rates and signatures in rapamycin and hydroxyurea and their impact on cell fitness, which brings insights for assessing their chronic effects on genome integrity.

Two independent DNA repair pathways cause mutagenesis in template switching deficient Saccharomyces cerevisiae

Upon DNA replication stress, cells utilize the postreplication repair pathway to repair single-stranded DNA and maintain genome integrity. Postreplication repair is divided into 2 branches: error-prone translesion synthesis, signaled by proliferating cell nuclear antigen (PCNA) monoubiquitination, and error-free template switching, signaled by PCNA polyubiquitination. In Saccharomyces cerevisiae, Rad5 is involved in both branches of repair during DNA replication stress. When the PCNA polyubiquitination function of Rad5 s disrupted, Rad5 recruits translesion synthesis polymerases to stalled replication forks, resulting in mutagenic repair. Details of how mutagenic repair is carried out, as well as the relationship between Rad5-mediated mutagenic repair and the canonical PCNA-mediated mutagenic repair, remain to be understood. We find that Rad5-mediated mutagenic repair requires the translesion synthesis polymerase ζ but does not require other yeast translesion polymerase activities. Furthermore, we show that Rad5-mediated mutagenic repair is independent of PCNA binding by Rev1 and so is separable from canonical mutagenic repair. In the absence of error-free template switching, both modes of mutagenic repair contribute additively to replication stress response in a replication timing-independent manner. Cellular contexts where error-free template switching is compromised are not simply laboratory phenomena, as we find that a natural variant in RAD5 is defective in PCNA polyubiquitination and therefore defective in error-free repair, resulting in Rad5- and PCNA-mediated mutagenic repair. Our results highlight the importance of Rad5 in regulating spontaneous mutagenesis and genetic diversity in S. cerevisiae through different modes of postreplication repair.

The divergence of mutation rates and spectra across the Tree of Life

Owing to advances in genome sequencing, genome stability has become one of the most scrutinized cellular traits across the Tree of Life. Despite its centrality to all things biological, the mutation rate (per nucleotide site per generation) ranges over three orders of magnitude among species and several-fold within individual phylogenetic lineages. Within all major organismal groups, mutation rates scale negatively with the effective population size of a species and with the amount of functional DNA in the genome. This relationship is most parsimoniously explained by the drift-barrier hypothesis, which postulates that natural selection typically operates to reduce mutation rates until further improvement is thwarted by the power of random genetic drift. Despite this constraint, the molecular mechanisms underlying DNA replication fidelity and repair are free to wander, provided the performance of the entire system is maintained at the prevailing level. The evolutionary flexibility of the mutation rate bears on the resolution of several prior conundrums in phylogenetic and population-genetic analysis and raises challenges for future applications in these areas.

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.

What Has Genomics Taught An Evolutionary Biologist?

Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.

High-throughput approaches to functional characterization of genetic variation in yeast

Expansion of sequencing efforts to include thousands of genomes is providing a fundamental resource for determining the genetic diversity that exists in a population. Now, high-throughput approaches are necessary to begin to understand the role these genotypic changes play in affecting phenotypic variation. Saccharomyces cerevisiae maintains its position as an excellent model system to determine the function of unknown variants with its exceptional genetic diversity, phenotypic diversity, and reliable genetic manipulation tools. Here, we review strategies and techniques developed in yeast that scale classic approaches of assessing variant function. These approaches improve our ability to better map quantitative trait loci at a higher resolution, even for rare variants, and are already providing greater insight into the role that different types of mutations play in phenotypic variation and evolution not just in yeast but across taxa.

Recent insights into the evolution of mutation rates in yeast

Mutation is the origin of all genetic variation, good and bad. The mutation process can evolve in response to mutations, positive or negative selection, and genetic drift, but how these forces contribute to mutation-rate variation is an unsolved problem at the heart of genetics research. Mutations can be challenging to measure, but genome sequencing and other tools have allowed for the collection of larger and more detailed datasets, particularly in the yeast-model system. We review key hypotheses for the evolution of mutation rates and describe recent advances in understanding variation in mutational properties within and among yeast species. The multidimensional spectrum of mutations is increasingly recognized as holding valuable clues about how this important process evolves.

A natural mutator allele shapes mutation spectrum variation in mice

Although germline mutation rates and spectra can vary within and between species, common genetic modifiers of the mutation rate have not been identified in nature¹. Here we searched for loci that influence germline mutagenesis using a uniquely powerful resource: a panel of recombinant inbred mouse lines known as the BXD, descended from the laboratory strains C57BL/6J (B haplotype) and DBA/2J (D haplotype). Each BXD lineage has been maintained by brother-sister mating in the near absence of natural selection, accumulating de novo mutations for up to 50 years on a known genetic background that is a unique linear mosaic of B and D haplotypes². We show that mice inheriting D haplotypes at a quantitative trait locus on chromosome 4 accumulate C>A germline mutations at a 50% higher rate than those inheriting B haplotypes, primarily owing to the activity of a C>A-dominated mutational signature known as SBS18. The B and D quantitative trait locus haplotypes encode different alleles of Mutyh, a DNA repair gene that underlies the heritable cancer predisposition syndrome that causes colorectal tumors with a high SBS18 mutation load^3,4. Both B and D Mutyh alleles are present in wild populations of Mus musculus domesticus, providing evidence that common genetic variation modulates germline mutagenesis in a model mammalian species.

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.

Possible Role for Allelic Variation in Yeast MED15 in Ecological Adaptation

The propensity for Saccharomyces cerevisiae yeast to ferment sugars into ethanol and CO₂ has long been useful in the production of a wide range of food and drink. In the production of alcoholic beverages, the yeast strain selected for fermentation is crucial because not all strains are equally proficient in tolerating fermentation stresses. One potential mechanism by which domesticated yeast may have adapted to fermentation stresses is through changes in the expression of stress response genes. MED15 is a general transcriptional regulator and RNA Pol II Mediator complex subunit which modulates the expression of many metabolic and stress response genes. In this study, we explore the role of MED15 in alcoholic fermentation. In addition, we ask whether MED15 alleles from wine, sake or palm wine yeast improve fermentation activity and grape juice fermentation stress responses. And last, we investigate to what extent any differences in activity are due to allelic differences in the lengths of three polyglutamine tracts in MED15. We find that strains lacking MED15 are deficient in fermentation and fermentation stress responses and that MED15 alleles from alcoholic beverage yeast strains can improve both the fermentation capacity and the response to ethanol stresses when transplanted into a standard laboratory strain. Finally, we find that polyglutamine tract length in the Med15 protein is one determinant in the efficiency of the alcoholic fermentation process. These data lead to a working model in which polyglutamine tract length and other types of variability within transcriptional hubs like the Mediator subunit, Med15, may contribute to a reservoir of transcriptional profiles that may provide a fitness benefit in the face of environmental fluctuations.

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.

The rate and molecular spectrum of mutation are selectively maintained in yeast

What determines the rate (μ) and molecular spectrum of mutation is a fundamental question. The prevailing hypothesis asserts that natural selection against deleterious mutations has pushed μ to the minimum achievable in the presence of genetic drift, or the drift barrier. Here we show that, contrasting this hypothesis, μ substantially exceeds the drift barrier in diverse organisms. Random mutation accumulation (MA) in yeast frequently reduces μ, and deleting the newly discovered mutator gene PSP2 nearly halves μ. These results, along with a comparison between the MA and natural yeast strains, demonstrate that μ is maintained above the drift barrier by stabilizing selection. Similar comparisons show that the mutation spectrum such as the universal AT mutational bias is not intrinsic but has been selectively preserved. These findings blur the separation of mutation from selection as distinct evolutionary forces but open the door to alleviating mutagenesis in various organisms by genome editing.

How natural selection shapes the rate and molecular spectrum of mutations is debated. Yeast mutation accumulation experiments identify a gene promoting mutagenesis and show stabilizing selection maintaining the mutation rate above the drift barrier. Selection also preserves the mutation spectrum.

Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time-consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway. Loss-of-function mutations in MSH2 are associated with hereditary nonpolyposis colorectal cancer, an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbrück fluctuation tests using a collection of published MSH2 missense variants. Our pooled screen successfully identified previously characterized nonfunctional alleles as high mutators. We then created an additional 185 human missense variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVar's classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the frequency of antibiotic resistance emergence.

Population genomic analysis of Cryptococcus Brazilian isolates reveals an African type subclade distribution

The genomes of a large number of Cryptococcus neoformans isolates have been sequenced and analyzed in recent years. These genomes have been used to understand the global population structure of this opportunistic pathogen. However, only a small number of South American isolates have been considered in these studies, and the population structure of C. neoformans in this part of the world remains elusive. Here, we analyzed the genomic sequences of 53 Brazilian Cryptococcus isolates and deciphered the C. neoformans population structure in this country. Our data reveal an African-like structure that suggested repeated intercontinental transports from Africa to South America. We also identified a mutator phenotype in one VNBII Brazilian isolate, exemplifying how fast-evolving isolates can shape the Cryptococcus population structure. Finally, phenotypic analyses revealed wide diversity but not lineage specificity in the expression of classical virulence traits within the set of isolates.

High and Highly Variable Spontaneous Mutation Rates in Daphnia

The rate and spectrum of spontaneous mutations are critical parameters in basic and applied biology because they dictate the pace and character of genetic variation introduced into populations, which is a prerequisite for evolution. We use a mutation–accumulation approach to estimate mutation parameters from whole-genome sequence data from multiple genotypes from multiple populations of Daphnia magna, an ecological and evolutionary model system. We report extremely high base substitution mutation rates (µ-n,bs = 8.96 × 10⁻⁹/bp/generation [95% CI: 6.66–11.97 × 10⁻⁹/bp/generation] in the nuclear genome and µ-m,bs = 8.7 × 10⁻⁷/bp/generation [95% CI: 4.40–15.12 × 10⁻⁷/bp/generation] in the mtDNA), the highest of any eukaryote examined using this approach. Levels of intraspecific variation based on the range of estimates from the nine genotypes collected from three populations (Finland, Germany, and Israel) span 1 and 3 orders of magnitude, respectively, resulting in up to a ∼300-fold difference in rates among genomic partitions within the same lineage. In contrast, mutation spectra exhibit very consistent patterns across genotypes and populations, suggesting the mechanisms underlying the mutational process may be similar, even when the rates at which they occur differ. We discuss the implications of high levels of intraspecific variation in rates, the importance of estimating gene conversion rates using a mutation–accumulation approach, and the interacting factors influencing the evolution of mutation parameters. Our findings deepen our knowledge about mutation and provide both challenges to and support for current theories aimed at explaining the evolution of the mutation rate, as a trait, across taxa.

Identification of novel genes involved in neutral lipid storage by quantitative trait loci analysis of Saccharomyces cerevisiae

BACKGROUND

The accumulation of intracellular fat depots is a polygenic trait. Therefore, the extent of lipid storage in the individuals of a species covers a broad range and is determined by many genetic factors. Quantitative trait loci analysis can be used to identify those genetic differences between two strains of the same species that are responsible for the differences in a given phenotype. We used this method and complementary approaches to identify genes in the yeast Saccharomyces cerevisiae that are involved in neutral lipid storage.

RESULTS

We selected two yeast strains, the laboratory strain BY4741 and the wine yeast AWRI1631, with a more than two-fold difference in neutral lipid content. After crossing, sporulation and germination, we used fluorescence activated cell sorting to isolate a subpopulation of cells with the highest neutral lipid content from the pool of segregants. Whole genome sequencing of this subpopulation and of the unsorted pool of segregants implicated several loci that are involved in lipid accumulation. Three of the identified genes, PIG1, PHO23 and RML2, were investigated in more detail. Deletions of these genes and the exchange of the alleles between the two parental strains confirmed that the encoded proteins contribute to neutral lipid storage in S. cerevisiae and that PIG1, PHO23 and RML2 are the major causative genes. Backcrossing of one of the segregants with the parental strains for seven generations revealed additional regions in the genomes of both strains with potential causative genes for the high lipid accumulation phenotype.

CONCLUSIONS

We identified several genes that contribute to the phenotype of lipid accumulation in an allele-specific manner. Surprisingly, no allelic variations of genes with known functions in lipid metabolism were found, indicating that the level of storage lipid accumulation is determined by many cellular processes that are not directly related to lipid metabolism.

Cancer cells employ an evolutionarily conserved polyploidization program to resist therapy

Unusually large cancer cells with abnormal nuclei have been documented in the cancer literature since 1858. For more than 100 years, they have been generally disregarded as irreversibly senescent or dying cells, too morphologically misshapen and chromatin too disorganized to be functional. Cell enlargement, accompanied by whole genome doubling or more, is observed across organisms, often associated with mitigation strategies against environmental change, severe stress, or the lack of nutrients. Our comparison of the mechanisms for polyploidization in other organisms and non-transformed tissues suggest that cancer cells draw from a conserved program for their survival, utilizing whole genome doubling and pausing proliferation to survive stress. These polyaneuploid cancer cells (PACCs) are the source of therapeutic resistance, responsible for cancer recurrence and, ultimately, cancer lethality.

Loss of Heterozygosity and Base Mutation Rates Vary Among Saccharomyces cerevisiae Hybrid Strains

A growing body of evidence suggests that mutation rates exhibit intra-species specific variation. We estimated genome-wide loss of heterozygosity (LOH), gross chromosomal changes, and single nucleotide mutation rates to determine intra-species specific differences in hybrid and homozygous strains of Saccharomyces cerevisiae. The mutation accumulation lines of the S. cerevisiae hybrid backgrounds - S288c/YJM789 (S/Y) and S288c/RM11-1a (S/R) were analyzed along with the homozygous diploids RM11, S288c, and YJM145. LOH was extensive in both S/Y and S/R hybrid backgrounds. The S/Y background also showed longer LOH tracts, gross chromosomal changes, and aneuploidy. Short copy number aberrations were observed in the S/R background. LOH data from the S/Y and S/R hybrids were used to construct a LOH map for S288c to identify hotspots. Further, we observe up to a sixfold difference in single nucleotide mutation rates among the S. cerevisiae S/Y and S/R genetic backgrounds. Our results demonstrate LOH is common during mitotic divisions in S. cerevisiae hybrids and also highlight genome-wide differences in LOH patterns and rates of single nucleotide mutations between commonly used S. cerevisiae hybrid genetic backgrounds.

Chromatin Structure and Drug Resistance in Candida spp

Anti-microbial resistance (AMR) is currently one of the most serious threats to global human health and, appropriately, research to tackle AMR garnishes significant investment and extensive attention from the scientific community. However, most of this effort focuses on antibiotics, and research into anti-fungal resistance (AFR) is vastly under-represented in comparison. Given the growing number of vulnerable, immunocompromised individuals, as well as the positive impact global warming has on fungal growth, there is an immediate urgency to tackle fungal disease, and the disturbing rise in AFR. Chromatin structure and gene expression regulation play pivotal roles in the adaptation of fungal species to anti-fungal stress, suggesting a potential therapeutic avenue to tackle AFR. In this review we discuss both the genetic and epigenetic mechanisms by which chromatin structure can dictate AFR mechanisms and will present evidence of how pathogenic yeast, specifically from the Candida genus, modify chromatin structure to promote survival in the presence of anti-fungal drugs. We also discuss the mechanisms by which anti-chromatin therapy, specifically lysine deacetylase inhibitors, influence the acquisition and phenotypic expression of AFR in Candida spp. and their potential as effective adjuvants to mitigate against AFR.

Advances in understanding the evolution of fungal genome architecture

Diversity within the fungal kingdom is evident from the wide range of morphologies fungi display as well as the various ecological roles and industrial purposes they serve. Technological advances, particularly in long-read sequencing, coupled with the increasing efficiency and decreasing costs across sequencing platforms have enabled robust characterization of fungal genomes. These sequencing efforts continue to reveal the rampant diversity in fungi at the genome level. Here, we discuss studies that have furthered our understanding of fungal genetic diversity and genomic evolution. These studies revealed the presence of both small-scale and large-scale genomic changes. In fungi, research has recently focused on many small-scale changes, such as how hypermutation and allelic transmission impact genome evolution as well as how and why a few specific genomic regions are more susceptible to rapid evolution than others. High-throughput sequencing of a diverse set of fungal genomes has also illuminated the frequency, mechanisms, and impacts of large-scale changes, which include chromosome structural variation and changes in chromosome number, such as aneuploidy, polyploidy, and the presence of supernumerary chromosomes. The studies discussed herein have provided great insight into how the architecture of the fungal genome varies within species and across the kingdom and how modern fungi may have evolved from the last common fungal ancestor and might also pave the way for understanding how genomic diversity has evolved in all domains of life.

The RNA-associated proteins MKT1 and MKT1L form alternative PBP1-containing complexes in Trypanosoma brucei

Control of gene expression in kinetoplastids such as trypanosomes depends heavily on RNA-binding proteins that influence mRNA decay and translation. We previously showed that the trypanosome protein MKT1 forms a multicomponent protein complex: MKT1 interacts with PBP1, which in turn recruits LSM12 and poly(A)-binding protein. MKT1 is recruited to mRNAs by sequence-specific RNA-binding proteins, resulting in stabilization of the bound mRNA. We here show that PBP1, LSM12, and a 117-residue protein, XAC1 (Tb927.7.2780), are present in complexes that contain either MKT1 or an MKT1-like protein, MKT1L (Tb927.10.1490). All five proteins are present predominantly in the complexes, and we found evidence for a minor subset of complexes containing both MKT1 and MKT1L. XAC1-containing complexes reproducibly contained RNA-binding proteins that were previously found associated with MKT1. Moreover, XAC1- or MKT1-containing complexes specifically recruited one of the two poly(A)-binding proteins, PABP2, and one of the six cap-binding translation initiation complexes, EIF4E6-EIF4G5. Yeast two-hybrid assay results indicated that MKT1 directly interacts with EIF4G5. MKT1-PBP1 complexes can therefore interact with mRNAs via their poly(A) tails and caps, as well as through sequence-specific RNA-binding proteins. Correspondingly, MKT1 is associated with many mRNAs, although not with those encoding ribosomal proteins. Meanwhile, MKT1L resembles MKT1 at the C terminus but additionally features an N-terminal extension with low-complexity regions. Although MKT1L depletion inhibited cell proliferation, we found no evidence that it specifically interacts with RNA-binding proteins or mRNA. We speculate that MKT1L may compete with MKT1 for PBP1 binding and thereby modulate the function of MKT1-containing complexes.

How and why to build a mathematical model: A case study using prion aggregation

Biological systems are inherently complex, and the increasing level of detail with which we are able to experimentally probe such systems continually reveals new complexity. Fortunately, mathematical models are uniquely positioned to provide a tool suitable for rigorous analysis, hypothesis generation, and connecting results from isolated in vitro experiments with results from in vivo and whole-organism studies. However, developing useful mathematical models is challenging because of the often different domains of knowledge required in both math and biology. In this work, we endeavor to provide a useful guide for researchers interested in incorporating mathematical modeling into their scientific process. We advocate for the use of conceptual diagrams as a starting place to anchor researchers from both domains. These diagrams are useful for simplifying the biological process in question and distinguishing the essential components. Not only do they serve as the basis for developing a variety of mathematical models, but they ensure that any mathematical formulation of the biological system is led primarily by scientific questions. We provide a specific example of this process from our own work in studying prion aggregation to show the power of mathematical models to synergistically interact with experiments and push forward biological understanding. Choosing the most suitable model also depends on many different factors, and we consider how to make these choices based on different scales of biological organization and available data. We close by discussing the many opportunities that abound for both experimentalists and modelers to take advantage of collaborative work in this field.

High frequency DNA rearrangement at qγ27 creates a novel allele for Quality Protein Maize breeding

Copy number variation (CNV) is a major source of genetic variation and often contributes to phenotypic variation in maize. The duplication at the 27-kDa γ-zein locus (qγ27) is essential to convert soft endosperm into hard endosperm in quality protein maize (QPM). This duplication is unstable and generally produces CNV at this locus. We conducted genetic experiments designed to directly measure DNA rearrangement frequencies occurring in males and females of different genetic backgrounds. The average frequency with which the duplication rearranges to single copies is 1.27 × 10-3 and varies among different lines. A triplication of γ27 gene was screened and showed a better potential than the duplication for the future QPM breeding. Our results highlight a novel approach to directly determine the frequency of DNA rearrangements, in this case resulting in CNV at the qγ27 locus. Furthermore, this provides a highly effective way to test suitable parents in QPM breeding.

Baker's Yeast Clinical Isolates Provide a Model for How Pathogenic Yeasts Adapt to Stress

Global outbreaks of drug-resistant fungi such as Candida auris are thought to be due at least in part to excessive use of antifungal drugs. Baker's yeast Saccharomyces cerevisiae has gained importance as an emerging opportunistic fungal pathogen that can cause infections in immunocompromised patients. Analyses of over 1000 S. cerevisiae isolates are providing rich resources to better understand how fungi can grow in human environments. A large percentage of clinical S. cerevisiae isolates are heterozygous across many nucleotide sites, and a significant proportion are of mixed ancestry and/or are aneuploid or polyploid. Such features potentially facilitate adaptation to new environments. These observations provide strong impetus for expanding genomic and molecular studies on clinical and wild isolates to understand the prevalence of genetic diversity and instability-generating mechanisms, and how they are selected for and maintained. Such work can also lead to the identification of new targets for antifungal drugs.

The fitness cost of mismatch repair mutators in Saccharomyces cerevisiae: partitioning the mutational load

Mutational load is the depression in a population's mean fitness that results from the continual influx of deleterious mutations. Here, we directly estimate the mutational load in a population of haploid Saccharomyces cerevisiae that are deficient for mismatch repair. We partition the load in haploids into two components. To estimate the load due to nonlethal mutations, we measure the competitive fitness of hundreds of randomly selected clones from both mismatch-repair-deficient and -proficient populations. Computation of the mean clone fitness for the mismatch-repair-deficient strain permits an estimation of the nonlethal load, and the histogram of fitness provides an interesting visualization of a loaded population. In a separate experiment, in order to estimate the load due to lethal mutations (i.e. the lethal mutation rate), we manipulate thousands of individual pairs of mother and daughter cells and track their fates. These two approaches yield point estimates for the two contributors to load, and the addition of these estimates is nearly equal to the separately measured short-term competitive fitness deficit for the mismatch-repair-deficient strain. This correspondence suggests that there is no need to invoke direct fitness effects to explain the fitness difference between mismatch-repair-deficient and -proficient strains. Assays in diploids are consistent with deleterious mutations in diploids tending towards recessivity. These results enhance our understanding of mutational load, a central population genetics concept, and we discuss their implications for the evolution of mutation rates.

Superloser: A Plasmid Shuffling Vector for Saccharomyces cerevisiae with Exceedingly Low Background

Here we report a new plasmid shuffle vector for forcing budding yeast (Saccharomyces cerevisiae) to incorporate a new genetic pathway in place of a native pathway - even an essential one - while maintaining low false positive rates (less than 1 in 108 per cell). This plasmid, dubbed "Superloser," was designed with reduced sequence similarity to commonly used yeast plasmids (i.e., pRS400 series) to limit recombination, a process that in our experience leads to retention of the yeast gene(s) instead of the desired gene(s). In addition, Superloser utilizes two orthogonal copies of the counter-selectable marker URA3 to reduce spontaneous 5-fluoroorotic acid resistance. Finally, the CEN/ARS sequence is fused to the GAL1-10 promoter, which disrupts plasmid segregation in the presence of the sugar galactose, causing Superloser to rapidly be removed from a population of cells. We show one proof-of-concept shuffling experiment: swapping yeast's core histones out for their human counterparts. Superloser is especially useful for forcing yeast to use highly unfavorable genes, such as human histones, as it enables plating a large number of cells (1.4x109) on a single 10 cm petri dish while maintaining a very low background. Therefore, Superloser is a useful tool for yeast geneticists to effectively shuffle low viability genes and/or pathways in yeast that may arise in as few as 1 in 108 cells.

Interspecies association mapping links reduced CG to TG substitution rates to the loss of gene-body methylation

Comparative genomics can unravel the genetic basis of species differences; however, successful reports on quantitative traits are still scarce. Here we present genome assemblies of 31 so-far unassembled Brassicaceae plant species and combine them with 16 previously published assemblies to establish the Brassicaceae Diversity Panel. Using a new interspecies association strategy for quantitative traits, we found a so-far unknown association between the unexpectedly high variation in CG to TG substitution rates in genes and the absence of CHROMOMETHYLASE3 (CMT3) orthologues. Low substitution rates were associated with the loss of CMT3, while species with conserved CMT3 orthologues showed high substitution rates. Species without CMT3 also lacked gene-body methylation (gbM), suggesting an evolutionary trade-off between the unknown function of gbM and low substitution rates in Brassicaceae, possibly due to low mutability of non-methylated cytosines.

Facilitators of adaptation and antifungal resistance mechanisms in clinically relevant fungi

Opportunistic fungal pathogens can cause a diverse range of diseases in humans. The increasing rate of fungal infections caused by strains that are resistant to commonly used antifungals results in difficulty to treat diseases, with accompanying high mortality rates. Existing and newly emerging molecular resistance mechanisms rapidly spread in fungal populations and need to be monitored. Fungi exhibit a diversity of mechanisms to maintain physiological resilience and create genetic variation; processes which eventually lead to the selection and spread of resistant fungal pathogens. To prevent and anticipate this dispersion, the role of evolutionary factors that drive fungal adaptation should be investigated. In this review, we provide an overview of resistance mechanisms against commonly used antifungal compounds in the clinic and for which fungal resistance has been reported. Furthermore, we aim to summarize and elucidate potent generators of genetic variability across the fungal kingdom that aid adaptation to stressful environments. This knowledge can lead to recognizing potential niches that facilitate fast resistance development and can provide leads for new management strategies to battle the emerging resistant populations in the clinic and the environment.