Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects.

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of 2 common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (approximately 0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Associations with other cancer-related biomarkers might contribute to poor outcomes in RAS-altered, younger patients with colorectal cancer.

Colorectal cancer (CRC) is a common cancer in younger adults. In patients undergoing liver resection with RAS-altered CRCs, there is evidence suggesting younger patients have worse outcomes than older patients. To explain this pattern, differences in associations between RAS status and other cancer-related biomarkers in tumors from younger versus older patients with CRC were evaluated in a cohort of 925 patients with CRC, 277 (30.0%) of whom were ≤50 years old, and 454 (49.1%) who had RAS-altered tumors. For 3 biomarkers, RNF43, APC, and microsatellite instability (MSI), the association with RAS status was significantly modified by age after adjustment for multiple testing. Specifically, younger patients with RAS-altered tumors were more likely to be MSI-high, RNF43 mutated, and APC wild type. These differences might contribute to the observed pattern of diminished survival in younger versus older patients with CRC with RAS-mutated tumors undergoing liver metastasis resection.

Fitness consequences of a non-recombining sex-ratio drive chromosome can explain its prevalence in the wild.

Understanding the pleiotropic consequences of gene drive systems on host fitness is essential to predict their spread through a host population. Here, we study sex-ratio (SR) X-chromosome drive in the fly Drosophila recens, where SR causes the death of Y-bearing sperm in male carriers. SR males only sire daughters, which all carry SR, thus giving the chromosome a transmission advantage. The prevalence of the SR chromosome appears stable, suggesting pleiotropic costs. It was previously shown that females homozygous for SR are sterile, and here, we test for additional fitness costs of SR. We found that females heterozygous for SR have reduced fecundity and that male SR carriers have reduced fertility in conditions of sperm competition. We then use our fitness estimates to parametrize theoretical models of SR drive and show that the decrease in fecundity and sperm competition performance can account for the observed prevalence of SR in natural populations. In addition, we found that the expected equilibrium frequency of the SR chromosome is particularly sensitive to the degree of multiple mating and performance in sperm competition. Together, our data suggest that the mating system of the organism should be carefully considered during the development of gene drive systems.

Selection Transforms the Landscape of Genetic Variation Interacting with Hsp90.

The protein-folding chaperone Hsp90 has been proposed to buffer the phenotypic effects of mutations. The potential for Hsp90 and other putative buffers to increase robustness to mutation has had major impact on disease models, quantitative genetics, and evolutionary theory. But Hsp90 sometimes contradicts expectations for a buffer by potentiating rapid phenotypic changes that would otherwise not occur. Here, we quantify Hsp90's ability to buffer or potentiate (i.e., diminish or enhance) the effects of genetic variation on single-cell morphological features in budding yeast. We corroborate reports that Hsp90 tends to buffer the effects of standing genetic variation in natural populations. However, we demonstrate that Hsp90 tends to have the opposite effect on genetic variation that has experienced reduced selection pressure. Specifically, Hsp90 tends to enhance, rather than diminish, the effects of spontaneous mutations and recombinations. This result implies that Hsp90 does not make phenotypes more robust to the effects of genetic perturbation. Instead, natural selection preferentially allows buffered alleles to persist and thereby creates the false impression that Hsp90 confers greater robustness.

Molecular variation across populations of a widespread North American firefly, Photinus pyralis, reveals that coding changes do not underlie flash color variation or associated visual sensitivity.

BACKGROUND: Genes underlying signal production and reception are expected to evolve to maximize signal detection in specific environments. Fireflies vary in their light signal color both within and between species, and thus provide an excellent system in which to study signal production and reception in the context of signaling environments. Differences in signal color have been hypothesized to be due to variation in the sequence of luciferase, the enzyme that catalyzes the light reaction. Similarly, differences in visual sensitivity, which are expected to match signal color, have been hypothesized to be due to variation in the sequence of opsins, the protein component of visual pigments. Here we investigated (1) whether sequence variation in luciferase correlates with variation in signal color and (2) whether sequence variation in opsins correlates with inferred matching visual sensitivity across populations of a widespread North American firefly species, Photinus pyralis. We further tested (3) whether selection has acted on these loci by examining their population-level differentiation relative to the distribution of differentiation derived from a genome-wide sample of loci generated by double-digest RADseq. RESULTS: We found virtually no coding variation in luciferase or opsins. However, there was extreme divergence in non-coding variation in luciferase across populations relative to a panel of random genomic loci. CONCLUSIONS: The absence of protein variation at both loci challenges the paradigm that variation in signal color and visual sensitivity in fireflies is exclusively due to coding variation in luciferase and opsin genes. Instead, flash color variation within species must involve other mechanisms, such as abdominal pigmentation or regulation of light organ physiology. Evidence for selection at non-coding variation in luciferase suggests that selection is targeting luciferase regulation and may favor differ expression levels across populations.

The evolution of sexual signal modes and associated sensor morphology in fireflies (Lampyridae, Coleoptera).

Animals employ different sexual signal modes (e.g. visual, acoustic, chemical) in different environments and behavioural contexts. If sensory structures are costly, then evolutionary shifts in primary signal mode should be associated with changes in sensor morphology. Further, sex differences are expected if male and female signalling behaviours differ. Fireflies are known for their light displays, but many species communicate exclusively with pheromones, including species that recently lost their light signals. We performed phylogenetically controlled analyses of male eye and antenna size in 46 North American taxa, and found that light signals are associated with larger eyes and shorter antennae. In addition, following a transition from nocturnal light displays to diurnal pheromones, eye size reductions occur more rapidly than antenna size increases. In agreement with the North American taxa, across 101 worldwide firefly taxa in 32 genera, we found light displays are associated with larger eye and smaller antenna sizes in both males and females. For those taxa with both male and female data, we found sex differences in eye size and, for diurnal species, in antenna size.

Precise estimates of mutation rate and spectrum in yeast.

Mutation is the ultimate source of genetic variation. The most direct and unbiased method of studying spontaneous mutations is via mutation accumulation (MA) lines. Until recently, MA experiments were limited by the cost of sequencing and thus provided us with small numbers of mutational events and therefore imprecise estimates of rates and patterns of mutation. We used whole-genome sequencing to identify nearly 1,000 spontaneous mutation events accumulated over ∼311,000 generations in 145 diploid MA lines of the budding yeast Saccharomyces cerevisiae. MA experiments are usually assumed to have negligible levels of selection, but even mild selection will remove strongly deleterious events. We take advantage of such patterns of selection and show that mutation classes such as indels and aneuploidies (especially monosomies) are proportionately much more likely to contribute mutations of large effect. We also provide conservative estimates of indel, aneuploidy, environment-dependent dominant lethal, and recessive lethal mutation rates. To our knowledge, for the first time in yeast MA data, we identified a sufficiently large number of single-nucleotide mutations to measure context-dependent mutation rates and were able to (i) confirm strong AT bias of mutation in yeast driven by high rate of mutations from C/G to T/A and (ii) detect a higher rate of mutation at C/G nucleotides in two specific contexts consistent with cytosine methylation in S. cerevisiae.

The repeatability of genome-wide mutation rate and spectrum estimates.

Over the last decade, mutation studies have grown in popularity due to the affordability and accessibility of whole genome sequencing. As the number of species in which spontaneous mutation has been directly estimated approaches 20 across two domains of life, questions arise over the repeatability of results in such experiments. Five species were identified in which duplicate mutation studies have been performed. Across these studies the difference in estimated spontaneous mutation rate is at most, weakly significant (p < 0.01). However, a highly significant (p < 10(-5)), threefold difference in the rate of insertions/deletions (indels) exists between two recent studies in Schizosaccharomyces pombe. Upon investigation of the ancestral genome sequence for both studies, a possible anti-mutator allele was identified. The observed variation in indel rate may imply that the use of indel markers, such as microsatellites, for the investigation of genetic diversity within and among populations may be inappropriate because of the assumption of uniform mutation rate within a species.

Modelling the multidimensional niche by linking functional traits to competitive performance.

Linking competitive outcomes to environmental conditions is necessary for understanding species' distributions and responses to environmental change. Despite this importance, generalizable approaches for predicting competitive outcomes across abiotic gradients are lacking, driven largely by the highly complex and context-dependent nature of biotic interactions. Here, we present and empirically test a novel niche model that uses functional traits to model the niche space of organisms and predict competitive outcomes of co-occurring populations across multiple resource gradients. The model makes no assumptions about the underlying mode of competition and instead applies to those settings where relative competitive ability across environments correlates with a quantifiable performance metric. To test the model, a series of controlled microcosm experiments were conducted using genetically related strains of a widespread microbe. The model identified trait microevolution and performance differences among strains, with the predicted competitive ability of each organism mapped across a two-dimensional carbon and nitrogen resource space. Areas of coexistence and competitive dominance between strains were identified,and the predicted competitive outcomes were validated in approximately 95% of the pairings. By linking trait variation to competitive ability, our work demonstrates a generalizable approach for predicting and modelling competitive outcomes across changing environmental contexts.

Value of next generation sequencing (NGS) testing in advanced cancer patients.

OBJECTIVE: The availability of targeted therapies for oncology patients is increasing. Available genomic tests to identify treatment-eligible patients include single gene tests and gene panel tests, including the whole-exome, whole-transcriptome OncoExTra test. We assessed the costs and clinical benefits of test choice. METHODS: A Microsoft Excel-based model was developed to evaluate test choice in patients with advanced/metastatic non-small cell lung cancer (NSCLC), breast, prostate, and colorectal cancer. Treatment pathways were based on NCCN guidelines and medical expert opinion. Inputs were derived from published literature. Annual economic results and lifetime clinical results with OncoExTra testing were projected per-tested-patient and compared with single gene testing and no testing. Separately, results were estimated for a US health plan without the OncoExTra test and with its use in 5% of patients. RESULTS: Compared with no genomic testing, OncoExTra test use increased costs by $4,915 per patient; however, 82%-92% of individuals across tumour types were identified as eligible for targeted therapy or a clinical trial. Compared with single gene testing, OncoExTra test use decreased costs by $9,966 per-patient-tested while increasing use of approved or investigational targeted therapies by 20%. When considering a hypothetical health plan with 1 million members, 858 patients were eligible for genomic testing. Using the OncoExTra test in 5% of those eligible, per-member per-month costs decreased by $0.003, ranging from cost-savings of $0.026 in NSCLC patients to a $0.009 increase in prostate cancer patients. Cost-savings were driven by reduced treatment costs with increased clinical trial enrolment and reduced direct and indirect medical costs associated with targeted treatments. LIMITATIONS: Limitations include the required simplifications in modelling complex conditions that may not fully reflect evolving real-world testing and treatment patterns. CONCLUSIONS: Compared to single-gene testing, results indicate that using next generation sequencing test such as OncoExTra identified more actionable alterations, leading to improved outcomes and reduced costs.

Approximate Bayesian estimation of extinction rate in the Finnish Daphnia magna metapopulation.

Approximate Bayesian computation (ABC) is useful for parameterizing complex models in population genetics. In this study, ABC was applied to simultaneously estimate parameter values for a model of metapopulation coalescence and test two alternatives to a strict metapopulation model in the well-studied network of Daphnia magna populations in Finland. The models shared four free parameters: the subpopulation genetic diversity (θS), the rate of gene flow among patches (4Nm), the founding population size (N0) and the metapopulation extinction rate (e) but differed in the distribution of extinction rates across habitat patches in the system. The three models had either a constant extinction rate in all populations (strict metapopulation), one population that was protected from local extinction (i.e. a persistent source), or habitat-specific extinction rates drawn from a distribution with specified mean and variance. Our model selection analysis favoured the model including a persistent source population over the two alternative models. Of the closest 750,000 data sets in Euclidean space, 78% were simulated under the persistent source model (estimated posterior probability = 0.769). This fraction increased to more than 85% when only the closest 150,000 data sets were considered (estimated posterior probability = 0.774). Approximate Bayesian computation was then used to estimate parameter values that might produce the observed set of summary statistics. Our analysis provided posterior distributions for e that included the point estimate obtained from previous data from the Finnish D. magna metapopulation. Our results support the use of ABC and population genetic data for testing the strict metapopulation model and parameterizing complex models of demography.

Kin selection, genomics and caste-antagonistic pleiotropy.

Kin selection is a fundamentally important process that affects the evolution of social behaviours. The genomics revolution now provides the opportunity to test kin selection theory using genomic data. In this commentary, we discuss previous studies that explored the link between kin selection and patterns of variation within the genome. We then present a new theory aimed at understanding the evolution of genes involved in the development of social insects. Specifically, we investigate caste-antagonistic pleiotropy, which occurs when the phenotypes of distinct castes are optimized by different genotypes at a single locus. We find that caste-antagonistic pleiotropy leads to narrow regions where polymorphism can be maintained. Furthermore, multiple mating by queens reduces the region in which worker-favoured alleles fix, which suggests that multiple mating impedes worker caste evolution. We conclude by discussing ways to test these and other facets of kin selection using newly emerging genomic data.

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects: Distributions of fitness effects of spontaneous mutations.

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of two common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (~0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Comprehensive Review on the Clinical Impact of Next-Generation Sequencing Tests for the Management of Advanced Cancer.

PURPOSE: This review summarizes the published evidence on the clinical impact of using next-generation sequencing (NGS) tests to guide management of patients with cancer in the United States. METHODS: We performed a comprehensive literature review to identify recent English language publications that presented progression-free survival (PFS) and overall survival (OS) of patients with advanced cancer receiving NGS testing. RESULTS: Among 6,475 publications identified, 31 evaluated PFS and OS among subgroups of patients who received NGS-informed cancer management. PFS and OS were significantly longer among patients who were matched to targeted treatment in 11 and 16 publications across tumor types, respectively. CONCLUSION: Our review indicates that NGS-informed treatment can have an impact on survival across tumor types.

Genetic estimates of population age in the water flea, Daphnia magna.

Genetic datasets can be used to date evolutionary events, even on recent time scales if sufficient data are available. We used statistics calculated from multilocus microsatellite datasets to estimate population ages in data generated through coalescent simulations and in samples from populations of known age in a metapopulation of Daphnia magna in Finland. Our simulation results show that age estimates improve with additional loci and define a time frame over which these statistics are most useful. On the most recent time scales, assumptions regarding the model of mutation (infinite sites vs. stepwise mutation) have little influence on estimated ages. In older populations, size homoplasy among microsatellite alleles results in a downwards bias for estimates based on the infinite sites model (ISM). In the Finnish D. magna metapopulation, our genetically derived estimated ages were biased upwards. Potential sources of this bias include the underlying model of mutation, gene flow, founder size, and the possibility of persistent source populations in the system. Our simulated data show that genetic age estimation is possible, even for very young populations, but our empirical data highlight the importance of factors such as migration when these statistics are applied in natural populations.

Tumor-Type Agnostic, Targeted Therapies: BRAF Inhibitors Join the Group.

In the present review, we briefly discuss the breakthrough advances in precision medicine using a tumor-agnostic approach and focus on BRAF treatment modalities, the mechanisms of resistance and the diagnostic approach in cancers with BRAF mutations. Tumor-type agnostic drug therapies work across cancer types and present a significant novel shift in precision cancer medicine. They are the consequence of carefully designed clinical trials that showed the value of tumor biomarkers, not just in diagnosis but in therapy guidance. Six tumor-agnostic drugs (with seven indications) have been approved through October 2022 by FDA. The first tumor-agnostic treatment modality was pembrolizumab for MSI-H/dMMR solid tumors, approved in 2017. This was followed by approvals of larotrectinib and entrectinib for cancers with NTRK fusions without a known acquired resistance mutation. In 2020, pembrolizumab was approved for all TMB-high solid cancers, while a PD-L1 inhibitor dostarlimab-gxly was approved for dMMR solid cancers in 2021. A combination of BRAF/MEK inhibitors (dabrafenib/trametinib) was approved as a tumor-agnostic therapy in June 2022 for all histologic types of solid metastatic cancers harboring BRAFV600E mutations. In September 2022, RET inhibitor selpercatinib was approved for solid cancers with RET gene fusions. CONCLUSION: Precision cancer medicine has substantially improved cancer diagnostics and treatment. Tissue type-agnostic drug therapies present a novel shift in precision cancer medicine. This approach rapidly expands to provide treatments for patients with different cancers harboring the same molecular alteration.

Genome Assembly of the Ty1-Less Saccharomyces paradoxus Strain DG1768.

Here, we report an essentially complete genome assembly for the Ty1-less Saccharomyces paradoxus strain DG1768 (derivative of strain 337) based on PacBio and Illumina shotgun sequence data. We also document the genetic alterations that make this yeast strain a key resource for Ty1 mobility studies.

The 17-gene Genomic Prostate Score assay as a predictor of biochemical recurrence in men with intermediate and high-risk prostate cancer.

The validated 17-gene Oncotype DX Genomic Prostate Score® (GPS™) assay risk-stratifies prostate-cancer patients with localized disease. The assay has primarily been utilized in lower risk patients deciding between active surveillance versus definitive therapy. In this retrospective cohort study, we analyze the association of the GPS result with time to biochemical recurrence post-prostatectomy in patients with National Comprehensive Cancer Network® (NCCN) intermediate and higher risk prostate cancer. The 141 patients included in the study were from the NorthShore University HealthSystem diagnosed 2014-2019 with NCCN intermediate (n = 109) or higher risk (n = 32) prostate cancer, treated with radical prostatectomy 2015-2019. The association of GPS result with time to biochemical recurrence was evaluated using univariable and multivariable Cox proportional hazards models in 120 patients with unfavorable intermediate or higher risk. Median (interquartile range) follow-up time was 28 (20 to 38) months. The GPS result was significantly associated with time to biochemical recurrence as both a continuous and dichotomous variable in univariable (hazard ratio [HR] per 20 GPS units 2.36, 95% CI 1.45-3.80, p < 0.001; HR for GPS result 41-100 vs 0-40 3.28, 95% CI 1.61-7.19, p < 0.001) and in multivariable models accounting for NCCN risk group (HR per 20 GPS units 2.14, 95% CI 1.31-3.46, p = 0.003; HR for GPS result 41-100 vs 0-40 3.00, 95% CI 1.43-6.72, p = 0.003) or biopsy Gleason Score and diagnostic PSA or PSA density. These results indicate that the GPS assay was a strong predictor of biochemical recurrence after radical prostatectomy in this unfavorable intermediate and higher risk prostate cancer patient population.

Fitness epistasis among 6 biosynthetic loci in the budding yeast Saccharomyces cerevisiae.

We generated all possible haploid and homozygous diploid genotypes at 6 biosynthetic loci in yeast and scored their fitness to examine whether there was any pattern of weak synergistic epistasis, which is a requirement of the deterministic mutation model for the evolution of sex. We measured 4 components of fitness: haploid growth rate, haploid mating efficiency, diploid growth rate, and diploid sporulation efficiency. We found that in agreement with previous work in yeast, epistasis tended to be small in magnitude and variable in sign, regardless of the fitness component measured. The number of background mutations had either no effect or no consistent effect on epistasis distributions. For every combination of 2 loci in a mutation-free background, we also generated all heterozygous genotypes so that we could partition diploid epistasis into additive x additive, additive x dominance, and dominance x dominance epistasis. Our main interest was in determining whether dominance by dominance epistasis was large and negative, which is a requirement of diploid models with inbreeding to explain high levels of recombination. Dominance by dominance epistasis estimates obtained by partitioning diploid epistasis for growth rates were both positive and negative. With the caveat that our results are based on only 6 biosynthetic loci, epistasis for fitness is not supported as an explanation for the maintenance of sex or the high rate of meiotic recombination in yeast.