Measurements of spontaneous rates of mutations in the recent past and the near future

The Emerging Role of Natural Products in Cancer Treatment

The exploration of natural products as potential agents for cancer treatment has garnered significant attention in recent years. In this comprehensive review, we delve into the diverse array of natural compounds, including alkaloids, carbohydrates, flavonoids, lignans, polyketides, saponins, tannins, and terpenoids, highlighting their emerging roles in cancer therapy. These compounds, derived from various botanical sources, exhibit a wide range of mechanisms of action, targeting critical pathways involved in cancer progression such as cell proliferation, apoptosis, angiogenesis, and metastasis. Through a meticulous examination of preclinical and clinical studies, we provide insights into the therapeutic potential of these natural products across different cancer types. Furthermore, we discuss the advantages and challenges associated with their use in cancer treatment, emphasizing the need for further research to optimize their efficacy, pharmacokinetics, and delivery methods. Overall, this review underscores the importance of natural products in advancing cancer therapeutics and paves the way for future investigations into their clinical applications.

Monoterpenoids: An upcoming class of therapeutic agents for modulating cancer metastasis

Monoterpenoids, a sub-class of terpenoids, are secondary metabolites frequently extracted from the essential oils of aromatic plants. Their antitumor properties including antiproliferative, apoptotic, antiangiogenic, and antimetastatic effects along with other biological activities have been the subject of extensive study due to their diverse characteristics. In recent years, numerous investigations have been conducted to understand its potential anticancer impacts, specifically focusing on antiproliferative and apoptotic mechanisms. Metastasis, a malignancy hallmark, can exert either protective or destructive influences on tumor cells. Despite this, the potential antimetastatic and antiangiogenic attributes of monoterpenoids need further exploration. This review focuses on specific monoterpenoids, examining their effects on metastasis and relevant signaling pathways. The monoterpenoids exhibit a high level of complexity as natural products that regulate metastatic proteins through various signaling pathways, including phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin, mitogen-activated protein kinase/extracellular signal-regulated kinase/jun N-terminal kinase, nuclear factor kappa B, vascular endothelial growth factor, and epithelial mesenchymal transition process. Additionally, this review delves into the biosynthesis and classification of monoterpenoids, their potential antitumor impacts on cell lines, the plant sources of monoterpenoids, and the current status of limited clinical trials investigating their efficacy against cancer. Moreover, monoterpenoids depict promising potential in preventing cancer metastasis, however, inadequate clinical trials limit their drug usage. State-of-the-art techniques and technologies are being employed to overcome the challenges of utilizing monoterpenoids as an anticancer agent.

Deleterious and Adaptive Mutations in Plant Germplasm Conserved Ex Situ

Conserving more than 7 million plant germplasm accessions in 1,750 genebanks worldwide raises the hope of securing the food supply for humanity for future generations. However, there is a genetic cost for such long-term germplasm conservation, which has been largely unaccounted for before. We investigated the extent and variation of deleterious and adaptive mutations in 490 individual plants representing barley, wheat, oat, soybean, maize, rapa, and sunflower collections in a seed genebank using RNA-Seq technology. These collections were found to have a range of deleterious mutations detected from 125 (maize) to 83,695 (oat) with a mean of 13,537 and of the averaged sample-wise mutation burden per deleterious locus from 0.069 to 0.357 with a mean of 0.200. Soybean and sunflower collections showed that accessions acquired earlier had increased mutation burdens. The germplasm with more years of storage in several collections carried more deleterious and fewer adaptive mutations. The samples with more cycles of germplasm regeneration revealed fewer deleterious and more adaptive mutations. These findings are significant for understanding mutational dynamics and genetic cost in conserved germplasm and have implications for long-term germplasm management and conservation.

Validation of machine learning approach for direct mutation rate estimation

Mutations are the primary source of all genetic variation. Knowledge about their rates is critical for any evolutionary genetic analyses, but for a long time, that knowledge has remained elusive and indirectly inferred. In recent years, parent-offspring comparisons have yielded the first direct mutation rate estimates. The analyses are, however, challenging due to high rate of false positives and no consensus regarding standardized filtering of candidate de novo mutations. Here, we validate the application of a machine learning approach for such a task and estimate the mutation rate for the guppy (Poecilia reticulata), a model species in eco-evolutionary studies. We sequenced 4 parents and 20 offspring, followed by screening their genomes for de novo mutations. The initial large number of candidate de novo mutations was hard-filtered to remove false-positive results. These results were compared with mutation rate estimated with a supervised machine learning approach. Both approaches were followed by molecular validation of all candidate de novo mutations and yielded similar results. The ML method uniquely identified three mutations, but overall required more hands-on curation and had higher rates of false positives and false negatives. Both methods concordantly showed no difference in mutation rates between families. Estimated here the guppy mutation rate is among the lowest directly estimated mutation rates in vertebrates; however, previous research has also found low estimated rates in other teleost fishes. We discuss potential explanations for such a pattern, as well as future utility and limitations of machine learning approaches.

The rate of de novo structural variation is increased in in vitro-produced offspring and preferentially affects the paternal genome

Assisted reproductive technologies (ARTs), including in vitro maturation and fertilization (IVF), are increasingly used in human and animal reproduction. Whether these technologies directly affect the rate of de novo mutation (DNM), and to what extent, has been a matter of debate. Here we take advantage of domestic cattle, characterized by complex pedigrees that are ideally suited to detect DNMs and by the systematic use of ART, to study the rate of de novo structural variation (dnSV) in this species and how it is impacted by IVF. By exploiting features of associated de novo point mutations (dnPMs) and dnSVs in clustered DNMs, we provide strong evidence that (1) IVF increases the rate of dnSV approximately fivefold, and (2) the corresponding mutations occur during the very early stages of embryonic development (one- and two-cell stage), yet primarily affect the paternal genome.

Characterization of nuclear DNA diversity in an individual Leymus chinensis

Intraorganismal genetic heterogeneity (IGH) exists when an individual organism harbors more than one genotype among its cells. In general, intercellular DNA diversity occurs at a very low frequency and cannot be directly detected by DNA sequencing from bulk tissue. In this study, based on Sanger and high-throughput sequencing, different species, different organs, different DNA segments and a single cell were employed to characterize nucleotide mutations in Leymus chinensis. The results demonstrated that 1) the nuclear DNA showed excessive genetic heterogeneity among cells of an individual leaf or seed but the chloroplast genes remained consistent; 2) a high density of SNPs was found in the variants of the unique DNA sequence, and the similar SNP profile shared between the leaf and seed suggested that nucleotide mutation followed a certain rule and was not random; and 3) the mutation rate decreased from the genomic DNA sequence to the corresponding protein sequence. Our results suggested that Leymus chinensis seemed to consist of a collection of cells with different genetic backgrounds.

Very Low Rates of Spontaneous Gene Deletions and Gene Duplications in Dictyostelium discoideum

The study of spontaneous mutation rates has revealed a wide range of heritable point mutation rates across species, but there are comparatively few estimates for large-scale deletion and duplication rates. The handful of studies that have directly calculated spontaneous rates of deletion and duplication using mutation accumulation lines have estimated that genes are duplicated and deleted at orders of magnitude greater rates than the spontaneous point mutation rate. In our study, we tested whether spontaneous gene deletion and gene duplication rates are also high in Dictyostelium discoideum, a eukaryote with among the lowest point mutation rates (2.5 × 10-11 per site per generation) and an AT-rich genome (GC content of 22%). We calculated mutation rates of gene deletions and duplications using whole-genome sequencing data originating from a mutation accumulation experiment and determined the association between the copy number mutations and GC content. Overall, we estimated an average of 3.93 × 10-8 gene deletions and 1.18 × 10-8 gene duplications per gene per generation. While orders of magnitude greater than their point mutation rate, these rates are much lower compared to gene deletion and duplication rates estimated from mutation accumulation lines in other organisms (that are on the order of ~ 10-6 per gene/generation). The deletions and duplications were enriched in regions that were AT-rich even compared to the genomic background, in contrast to our expectations if low GC content was contributing to low mutation rates. The low deletion and duplication mutation rates in D. discoideum compared to other eukaryotes mirror their low point mutation rates, supporting previous work suggesting that this organism has high replication fidelity and effective molecular machinery to avoid the accumulation of mutations in their genome.

Phytochemical Compounds and Anticancer Activity of Cladanthus mixtus Extracts from Northern Morocco

Many of the chemotherapeutic drugs for the treatment of cancer are molecules identified and isolated from plants or their synthetic derivatives. This work aimed to identify the bioactive compounds using LC-MS and GC-MS and to evaluate the anticancer activity of the methanolic extracts of roots, stems, leaves, and flowers from Cladanthus mixtus. The anticancer activity was evaluated in vitro against two cancer cell lines: human breast carcinoma (MCF-7) and human prostate carcinoma (PC-3), using the MTT assay and microscopic observation. A human normal lung fibroblast (MRC-5) was included to determine the extract's safety for non-tumoral cells. The chemical composition results by LC-MS analysis revealed the presence of 24 phenolic compounds. Furthermore, GC-MS analysis allowed the identification of many biomolecules belonging to terpenoids, esters, alcohols, alkanes, fatty acids, organic acids, benzenes, phenols, ketones, carbonyls, amines, sterols, and other groups. The findings suggest that the majority of C. mixtus extracts have antiproliferative activity against two cancer cell lines, MCF-7 and PC-3, and one non-tumoral cell line, MRC-5. The activity was dose-dependent, and the highest effect was obtained with leaf extract in the two cancer cell lines. Moreover, these extracts demonstrated an acceptable toxicological profile against normal cells. Overall, C. mixtus extracts revealed promising antitumor properties provided by their phytochemical composition.

Comparative overview of emerging RNA viruses: Epidemiology, pathogenesis, diagnosis and current treatment

From many decades, emerging infections have threatened humanity. The pandemics caused by different CoVs have already claimed and will continue to claim millions of lives. The SARS, Ebola, MERS epidemics and the most recent emergence of COVID-19 pandemic have threatened populations across borders. Since a highly pathogenic CoV has been evolved into the human population in the twenty-first century known as SARS, scientific advancements and innovative methods to tackle these viruses have increased in order to improve response preparedness towards the unpredictable threat posed by these rapidly emerging pathogens. Recently published review articles on SARS-CoV-2 have mainly focused on its pathogenesis, epidemiology and available treatments. However, in this review, we have done a systematic comparison of all three CoVs i.e., SARS, MERS and SARS-CoV-2 along with Ebola and Zika in terms of their epidemiology, virology, clinical features and current treatment strategies. This review focuses on important emerging RNA viruses starting from Zika, Ebola and the CoVs which include SARS, MERS and SARS-CoV-2. Each of these viruses has been elaborated on the basis of their epidemiology, virulence, transmission and treatment. However, special attention has been given to SARS-CoV-2 and the disease caused by it i.e., COVID-19 due to current havoc caused worldwide. At the end, insights into the current understanding of the lessons learned from previous epidemics to combat emerging CoVs have been described. The travel-related viral spread, the unprecedented nosocomial outbreaks and the high case-fatality rates associated with these highly transmissible and pathogenic viruses highlight the need for new prophylactic and therapeutic actions which include but are not limited to clinical indicators, contact tracing, and laboratory investigations as important factors that need to be taken into account in order to arrive at the final conclusion.

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Recently published review articles on SARS-CoV-2 have mainly focused on its pathogenesis, epidemiology and available treatments.

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The pandemics caused by different CoVs have already claimed and will continue to claim millions of lives.

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This review focuses on important emerging RNA viruses starting from Zika, Ebola and the CoVs which include SARS, MERS and SARS-CoV-2.

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Globally, numerous studies and researchers have recently started fighting this virus.

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values. Copy number variants (CNVs) are a pervasive source of heritable variation that can facilitate rapid adaptive evolution. Previously, we developed a locus-specific fluorescent CNV reporter to quantify CNV dynamics in evolving populations maintained in nutrient-limiting conditions using chemostats. Here, we use CNV adaptation dynamics to estimate the rate at which beneficial CNVs are introduced through de novo mutation and their fitness effects using simulation-based likelihood-free inference approaches. We tested the suitability of 2 evolutionary models: a standard Wright-Fisher model and a chemostat model. We evaluated 2 likelihood-free inference algorithms: the well-established Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC) algorithm, and the recently developed Neural Posterior Estimation (NPE) algorithm, which applies an artificial neural network to directly estimate the posterior distribution. By systematically evaluating the suitability of different inference methods and models, we show that NPE has several advantages over ABC-SMC and that a Wright-Fisher evolutionary model suffices in most cases. Using our validated inference framework, we estimate the CNV formation rate at the GAP1 locus in the yeast Saccharomyces cerevisiae to be 10-4.7 to 10-4 CNVs per cell division and a fitness coefficient of 0.04 to 0.1 per generation for GAP1 CNVs in glutamine-limited chemostats. We experimentally validated our inference-based estimates using 2 distinct experimental methods-barcode lineage tracking and pairwise fitness assays-which provide independent confirmation of the accuracy of our approach. Our results are consistent with a beneficial CNV supply rate that is 10-fold greater than the estimated rates of beneficial single-nucleotide mutations, explaining the outsized importance of CNVs in rapid adaptive evolution. More generally, our study demonstrates the utility of novel neural network-based likelihood-free inference methods for inferring the rates and effects of evolutionary processes from empirical data with possible applications ranging from tumor to viral evolution.

Therapeutic Potential of Certain Terpenoids as Anticancer Agents: A Scoping Review

Cancer is a life-threatening disease and is considered to be among the leading causes of death worldwide. Chemoresistance, severe toxicity, relapse and metastasis are the major obstacles in cancer therapy. Therefore, introducing new therapeutic agents for cancer remains a priority to increase the range of effective treatments. Terpenoids, a large group of secondary metabolites, are derived from plant sources and are composed of several isoprene units. The high diversity of terpenoids has drawn attention to their potential anticancer and pharmacological activities. Some terpenoids exhibit an anticancer effect by triggering various stages of cancer progression, for example, suppressing the early stage of tumorigenesis via induction of cell cycle arrest, inhibiting cancer cell differentiation and activating apoptosis. At the late stage of cancer development, certain terpenoids are able to inhibit angiogenesis and metastasis via modulation of different intracellular signaling pathways. Significant progress in the identification of the mechanism of action and signaling pathways through which terpenoids exert their anticancer effects has been highlighted. Hence, in this review, the anticancer activities of twenty-five terpenoids are discussed in detail. In addition, this review provides insights on the current clinical trials and future directions towards the development of certain terpenoids as potential anticancer agents.

Is there still evolution in the human population?

It is often claimed that humanity has stopped evolving because modern medicine erased all selection on survival. Even if that would be true, and it is not, there would be other mechanisms of evolution which could still led to changes in allelic frequencies. Here I show, by applying basic evolutionary genetics knowledge, that we expect humanity to evolve. The results from genome sequencing projects have repeatedly affirmed that there are still recent signs of selection in our genomes. I give some examples of such adaptation. Then I briefly discuss what our evolutionary future has in store for us.

Major population splits coincide with episodes of rapid climate change in a forest-dependent bird

Climate change influences population demography by altering patterns of gene flow and reproductive isolation. Direct mutation rates offer the possibility for accurate dating on the within-species level but are currently only available for a handful of vertebrate species. Here, we use the first directly estimated mutation rate in birds to study the evolutionary history of pied flycatchers (Ficedula hypoleuca). Using a combination of demographic inference and species distribution modelling, we show that all major population splits in this forest-dependent system occurred during periods of increased climate instability and rapid global temperature change. We show that the divergent Spanish subspecies originated during the Eemian-Weichselian transition 115-104 thousand years ago (kya), and not during the last glacial maximum (26.5-19 kya), as previously suggested. The magnitude and rates of climate change during the glacial-interglacial transitions that preceded population splits in pied flycatchers were similar to, or exceeded, those predicted to occur in the course of the current, human-induced climate crisis. As such, our results provide a timely reminder of the strong impact that episodes of climate instability and rapid temperature changes can have on species' evolutionary trajectories, with important implications for the natural world in the Anthropocene.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Quantifying the relationship between genetic diversity and population size suggests natural selection cannot explain Lewontin's Paradox

Neutral theory predicts that genetic diversity increases with population size, yet observed levels of diversity across metazoans vary only two orders of magnitude while population sizes vary over several. This unexpectedly narrow range of diversity is known as Lewontin's Paradox of Variation (1974). While some have suggested selection constrains diversity, tests of this hypothesis seem to fall short. Here, I revisit Lewontin's Paradox to assess whether current models of linked selection are capable of reducing diversity to this extent. To quantify the discrepancy between pairwise diversity and census population sizes across species, I combine previously-published estimates of pairwise diversity from 172 metazoan taxa with newly derived estimates of census sizes. Using phylogenetic comparative methods, I show this relationship is significant accounting for phylogeny, but with high phylogenetic signal and evidence that some lineages experience shifts in the evolutionary rate of diversity deep in the past. Additionally, I find a negative relationship between recombination map length and census size, suggesting abundant species have less recombination and experience greater reductions in diversity due to linked selection. However, I show that even assuming strong and abundant selection, models of linked selection are unlikely to explain the observed relationship between diversity and census sizes across species.

Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur

Mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum of de novo mutations have been directly characterized in relatively few lineages. Our study provides the first direct mutation-rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprises nearly half of the primate clade. Using high-coverage linked-read sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be among the highest calculated for a mammal at 1.52 × 10-8 (95% credible interval: 1.28 × 10-8-1.78 × 10-8) mutations/site/generation. Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG sites. Despite the surprising nature of these results, we found both the rate and spectrum to be robust to the manipulation of a wide range of computational filtering criteria. We also sequenced a technical replicate to estimate a false-negative and false-positive rate for our data and show that any point estimate of a de novo mutation rate should be considered with a large degree of uncertainty. For validation, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species for which de novo mutation rates have also been estimated. These comparisons revealed general consistency of the mutation spectrum between the pedigree-based and the substitution-rate analyses for all species compared.

Genome-wide DNA mutations in Arabidopsis plants after multigenerational exposure to high temperatures

BACKGROUND

Elevated temperatures can cause physiological, biochemical, and molecular responses in plants that can greatly affect their growth and development. Mutations are the most fundamental force driving biological evolution. However, how long-term elevations in temperature influence the accumulation of mutations in plants remains unknown.

RESULTS

Multigenerational exposure of Arabidopsis MA (mutation accumulation) lines and MA populations to extreme heat and moderate warming results in significantly increased mutation rates in single-nucleotide variants (SNVs) and small indels. We observe distinctive mutational spectra under extreme and moderately elevated temperatures, with significant increases in transition and transversion frequencies. Mutation occurs more frequently in intergenic regions, coding regions, and transposable elements in plants grown under elevated temperatures. At elevated temperatures, more mutations accumulate in genes associated with defense responses, DNA repair, and signaling. Notably, the distribution patterns of mutations among all progeny differ between MA populations and MA lines, suggesting that stronger selection effects occurred in populations. Methylation is observed more frequently at mutation sites, indicating its contribution to the mutation process at elevated temperatures. Mutations occurring within the same genome under elevated temperatures are significantly biased toward low gene density regions, special trinucleotides, tandem repeats, and adjacent simple repeats. Additionally, mutations found in all progeny overlap significantly with genetic variations reported in 1001 Genomes, suggesting non-uniform distribution of de novo mutations through the genome.

CONCLUSION

Collectively, our results suggest that elevated temperatures can accelerate the accumulation, and alter the molecular profiles, of DNA mutations in plants, thus providing significant insight into how environmental temperatures fuel plant evolution.

The insertion of a mitochondrial selfish element into the nuclear genome and its consequences

Homing endonucleases (HE) are enzymes capable of cutting DNA at highly specific target sequences, the repair of the generated double-strand break resulting in the insertion of the HE-encoding gene ("homing" mechanism). HEs are present in all three domains of life and viruses; in eukaryotes, they are mostly found in the genomes of mitochondria and chloroplasts, as well as nuclear ribosomal RNAs. We here report the case of a HE that accidentally integrated into a telomeric region of the nuclear genome of the fungal maize pathogen Ustilago maydis. We show that the gene has a mitochondrial origin, but its original copy is absent from the U. maydis mitochondrial genome, suggesting a subsequent loss or a horizontal transfer from a different species. The telomeric HE underwent mutations in its active site and lost its original start codon. A potential other start codon was retained downstream, but we did not detect any significant transcription of the newly created open reading frame, suggesting that the inserted gene is not functional. Besides, the insertion site is located in a putative RecQ helicase gene, truncating the C-terminal domain of the protein. The truncated helicase is expressed during infection of the host, together with other homologous telomeric helicases. This unusual mutational event altered two genes: The integrated HE gene subsequently lost its homing activity, while its insertion created a truncated version of an existing gene, possibly altering its function. As the insertion is absent in other field isolates, suggesting that it is recent, the U. maydis 521 reference strain offers a snapshot of this singular mutational event.

Modelling persistence over generations in biological and cultural evolution based on differential paces of change

Paces of change are faster in cultural evolution than in biological evolution due to different levels of stability in information storage. This study develops mathematical models to investigate the consequences of differential mutation rates on the ability of groups of information units to survive over many generations. We examined the ability of groups composed of connected units to live on despite the occurrence of deleterious mutations that occur at probabilities ranging from 10^-1 to 10^-6. It appears that the degree of connection between units should be high enough for groups to persist across generations, but this alone did not ensure their survival; when groups of units were limited in size and subjected to high mutation rates, they did not survive for very long. By contrast, a significant proportion of groups were able to survive numerous generations if mutation rates were low and/or group size was large. The results revealed that the mean number of surviving generations was minimized for certain sizes of groups. When allowing information units to duplicate at each generation, simulation showed that a great number of groups avoided extinction even when mutating at the rate of cultural change if the initial group size was large and the duplication rate was high enough to counteract the consequences of environmental perturbations. The modelling described in this study sets out the conditions under which groups of units can survive along generations. It should serve as a basis for further investigations about the links between processes of biological and cultural changes.

Metabolic cost of rapid adaptation of single yeast cells

Cells can rapidly adapt to changing environments through nongenetic processes; however, the metabolic cost of such adaptation has never been considered. Here we demonstrate metabolic coupling in a remarkable, rapid adaptation process (1 in 1,000 cells adapt per hour) by simultaneously measuring metabolism and division of thousands of individual Saccharomyces cerevisiae cells using a droplet microfluidic system: droplets containing single cells are immobilized in a two-dimensional (2D) array, with osmotically induced changes in droplet volume being used to measure cell metabolism, while simultaneously imaging the cells to measure division. Following a severe challenge, most cells, while not dividing, continue to metabolize, displaying a remarkably wide diversity of metabolic trajectories from which adaptation events can be anticipated. Adaptation requires a characteristic amount of energy, indicating that it is an active process. The demonstration that metabolic trajectories predict a priori adaptation events provides evidence of tight energetic coupling between metabolism and regulatory reorganization in adaptation. This process allows S. cerevisiae to adapt on a physiological timescale, but related phenomena may also be important in other processes, such as cellular differentiation, cellular reprogramming, and the emergence of drug resistance in cancer.

Somatic Mutation and Evolution in Plants

Somatic mutations are common in plants, and they may accumulate and be passed on to gametes. The determinants of somatic mutation accumulation include the intraorganismal selective effect of mutations, the number of cell divisions that separate the zygote from the formation of gametes, and shoot apical meristem structure and branching. Somatic mutations can promote the evolution of diploidy, polyploidy, sexual recombination, outcrossing, clonality, and separate sexes, and they may contribute genetic variability in many other traits. The amplification of beneficial mutations via intraorganismal selection may relax selection to reduce the genomic mutation rate or to protect the germline in plants. The total rate of somatic mutation, the distribution of selective effects and fates in the plant body, and the degree to which the germline is sheltered from somatic mutations are still poorly understood. Our knowledge can be improved through empirical estimates of mutation rates and effects on cell lineages and whole organisms, such as estimates of the reduction in fitness of progeny produced by within- versus between-flower crosses on the same plant, mutation coalescent studies within the canopy, and incorporation of somatic mutation into theoretical models of plant evolutionary genetics.

Old Trade, New Tricks: Insights into the Spontaneous Mutation Process from the Partnering of Classical Mutation Accumulation Experiments with High-Throughput Genomic Approaches

Mutations spawn genetic variation which, in turn, fuels evolution. Hence, experimental investigations into the rate and fitness effects of spontaneous mutations are central to the study of evolution. Mutation accumulation (MA) experiments have served as a cornerstone for furthering our understanding of spontaneous mutations for four decades. In the pregenomic era, phenotypic measurements of fitness-related traits in MA lines were used to indirectly estimate key mutational parameters, such as the genomic mutation rate, new mutational variance per generation, and the average fitness effect of mutations. Rapidly emerging next-generating sequencing technology has supplanted this phenotype-dependent approach, enabling direct empirical estimates of the mutation rate and a more nuanced understanding of the relative contributions of different classes of mutations to the standing genetic variation. Whole-genome sequencing of MA lines bears immense potential to provide a unified account of the evolutionary process at multiple levels-the genetic basis of variation, and the evolutionary dynamics of mutations under the forces of selection and drift. In this review, we have attempted to synthesize key insights into the spontaneous mutation process that are rapidly emerging from the partnering of classical MA experiments with high-throughput sequencing, with particular emphasis on the spontaneous rates and molecular properties of different mutational classes in nuclear and mitochondrial genomes of diverse taxa, the contribution of mutations to the evolution of gene expression, and the rate and stability of transgenerational epigenetic modifications. Future advances in sequencing technologies will enable greater species representation to further refine our understanding of mutational parameters and their functional consequences.

Adaptive Evolution under Extreme Genetic Drift in Oxidatively Stressed Caenorhabditis elegans

A mutation-accumulation (MA) experiment with Caenorhabditis elegans nematodes was conducted in which replicate, independently evolving lines were initiated from a low-fitness mitochondrial electron transport chain mutant, gas-1. The original intent of the study was to assess the effect of electron transport chain dysfunction involving elevated reactive oxygen species production on patterns of spontaneous germline mutation. In contrast to results of standard MA experiments, gas-1 MA lines evolved slightly higher mean fitness alongside reduced among-line genetic variance compared with their ancestor. Likewise, the gas-1 MA lines experienced partial recovery to wildtype reactive oxygen species levels. Whole-genome sequencing and analysis revealed that the molecular spectrum but not the overall rate of nuclear DNA mutation differed from wildtype patterns. Further analysis revealed an enrichment of mutations in loci that occur in a gas-1-centric region of the C. elegans interactome, and could be classified into a small number of functional-genomic categories. Characterization of a backcrossed four-mutation set isolated from one gas-1 MA line revealed this combination to be beneficial on both gas-1 mutant and wildtype genetic backgrounds. Our combined results suggest that selection favoring beneficial mutations can be powerful even under unfavorable population genetic conditions, and agree with fitness landscape theory predicting an inverse relationship between population fitness and the likelihood of adaptation.

The molecular clock and evolutionary timescales

The molecular clock provides a valuable means of estimating evolutionary timescales from genetic and biochemical data. Proposed in the early 1960s, it was first applied to amino acid sequences and immunological measures of genetic distances between species. The molecular clock has undergone considerable development over the years, and it retains profound relevance in the genomic era. In this mini-review, we describe the history of the molecular clock, its impact on evolutionary theory, the challenges brought by evidence of evolutionary rate variation among species, and the statistical models that have been developed to account for these heterogeneous rates of genetic change. We explain how the molecular clock can be used to infer rates and timescales of evolution, and we list some of the key findings that have been obtained when molecular clocks have been applied to genomic data. Despite the numerous challenges that it has faced over the decades, the molecular clock continues to offer the most effective method of resolving the details of the evolutionary timescale of the Tree of Life.

Temperature responses of mutation rate and mutational spectrum in an Escherichia coli strain and the correlation with metabolic rate

Background

Temperature is a major determinant of spontaneous mutation, but the precise mode, and the underlying mechanisms, of the temperature influences remain less clear. Here we used a mutation accumulation approach combined with whole-genome sequencing to investigate the temperature dependence of spontaneous mutation in an Escherichia coli strain. Experiments were performed under aerobic conditions at 25, 28 and 37 °C, three temperatures that were non-stressful for the bacterium but caused significantly different bacterial growth rates.

Results

Mutation rate did not differ between 25 and 28 °C, but was higher at 37 °C. Detailed analyses of the molecular spectrum of mutations were performed; and a particularly interesting finding is that higher temperature led to a bias of mutation to coding, relative to noncoding, DNA. Furthermore, the temperature response of mutation rate was extremely similar to that of metabolic rate, consistent with an idea that metabolic rate predicts mutation rate.

Conclusions

Temperature affects mutation rate and the types of mutation supply, both being crucial for the opportunity of natural selection. Our results help understand how temperature drives evolutionary speed of organisms and thus the global patterns of biodiversity. This study also lend support to the metabolic theory of ecology for linking metabolic rate and molecular evolution rate.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1252-8) contains supplementary material, which is available to authorized users.

Causes and evolutionary consequences of primordial germ-cell specification mode in metazoans

In animals, primordial germ cells (PGCs) give rise to the germ lines, the cell lineages that produce sperm and eggs. PGCs form in embryogenesis, typically by one of two modes: a likely ancestral mode wherein germ cells are induced during embryogenesis by cell-cell signaling (induction) or a derived mechanism whereby germ cells are specified by using germ plasm-that is, maternally specified germ-line determinants (inheritance). The causes of the shift to germ plasm for PGC specification in some animal clades remain largely unknown, but its repeated convergent evolution raises the question of whether it may result from or confer an innate selective advantage. It has been hypothesized that the acquisition of germ plasm confers enhanced evolvability, resulting from the release of selective constraint on somatic gene networks in embryogenesis, thus leading to acceleration of an organism's protein-sequence evolution, particularly for genes expressed at early developmental stages, and resulting in high speciation rates in germ plasm-containing lineages (denoted herein as the "PGC-specification hypothesis"). Although that hypothesis, if supported, could have major implications for animal evolution, our recent large-scale coding-sequence analyses from vertebrates and invertebrates provided important examples of genera that do not support the hypothesis of liberated constraint under germ plasm. Here, we consider reasons why germ plasm might be neither a direct target of selection nor causally linked to accelerated animal evolution. We explore alternate scenarios that could explain the repeated evolution of germ plasm and propose potential consequences of the inheritance and induction modes to animal evolutionary biology.

Potential and limits for rapid genetic adaptation to warming in a Great Barrier Reef coral

Can genetic adaptation in reef-building corals keep pace with the current rate of sea surface warming? Here we combine population genomics, biophysical modeling, and evolutionary simulations to predict future adaptation of the common coral Acropora millepora on the Great Barrier Reef (GBR). Genomics-derived migration rates were high (0.1–1% of immigrants per generation across half the latitudinal range of the GBR) and closely matched the biophysical model of larval dispersal. Both genetic and biophysical models indicated the prevalence of southward migration along the GBR that would facilitate the spread of heat-tolerant alleles to higher latitudes as the climate warms. We developed an individual-based metapopulation model of polygenic adaptation and parameterized it with population sizes and migration rates derived from the genomic analysis. We find that high migration rates do not disrupt local thermal adaptation, and that the resulting standing genetic variation should be sufficient to fuel rapid region-wide adaptation of A. millepora populations to gradual warming over the next 20–50 coral generations (100–250 years). Further adaptation based on novel mutations might also be possible, but this depends on the currently unknown genetic parameters underlying coral thermal tolerance and the rate of warming realized. Despite this capacity for adaptation, our model predicts that coral populations would become increasingly sensitive to random thermal fluctuations such as ENSO cycles or heat waves, which corresponds well with the recent increase in frequency of catastrophic coral bleaching events.

Coral reefs worldwide are suffering high mortality from severe thermal stress episodes induced by acute ocean warming events. Under the current rate of warming, will corals be gone before the end of this century? Here we combine population genomics with biophysical and evolutionary modeling to investigate adaptive potential of a common reef-building coral from the Great Barrier Reef. To approach this task, we have developed a predictive model of polygenic adaptation in a system of multiple inter-connected populations that exist in a heterogeneous and changing environment. Applying this model to our coral species, we find that populations successfully adapt to diverse local temperatures along the range of the Great Barrier Reef despite high migrant exchange and should collectively harbor enough adaptive genetic variants to fuel region-wide thermal adaptation for another century and perhaps longer. In the same time, the model predicts that random thermal fluctuations will induce increasingly severe coral mortality episodes, which aligns well with observations over the last few decades.

Key issues review: evolution on rugged adaptive landscapes

Adaptive landscapes represent a mapping between genotype and fitness. Rugged adaptive landscapes contain two or more adaptive peaks: allele combinations with higher fitness than any of their neighbors in the genetic space. How do populations evolve on such rugged landscapes? Evolutionary biologists have struggled with this question since it was first introduced in the 1930s by Sewall Wright. Discoveries in the fields of genetics and biochemistry inspired various mathematical models of adaptive landscapes. The development of landscape models led to numerous theoretical studies analyzing evolution on rugged landscapes under different biological conditions. The large body of theoretical work suggests that adaptive landscapes are major determinants of the progress and outcome of evolutionary processes. Recent technological advances in molecular biology and microbiology allow experimenters to measure adaptive values of large sets of allele combinations and construct empirical adaptive landscapes for the first time. Such empirical landscapes have already been generated in bacteria, yeast, viruses, and fungi, and are contributing to new insights about evolution on adaptive landscapes. In this Key Issues Review we will: (i) introduce the concept of adaptive landscapes; (ii) review the major theoretical studies of evolution on rugged landscapes; (iii) review some of the recently obtained empirical adaptive landscapes; (iv) discuss recent mathematical and statistical analyses motivated by empirical adaptive landscapes, as well as provide the reader with instructions and source code to implement simulations of evolution on adaptive landscapes; and (v) discuss possible future directions for this exciting field.

Are RNA Viruses Candidate Agents for the Next Global Pandemic? A Review

Pathogenic RNA viruses are potentially the most important group involved in zoonotic disease transmission, and they represent a challenge for global disease control. Their biological diversity and rapid adaptive rates have proved to be difficult to overcome and to anticipate by modern medical technology. Also, the anthropogenic change of natural ecosystems and the continuous population growth are driving increased rates of interspecies contacts and the interchange of pathogens that can develop into global pandemics. The combination of molecular, epidemiological, and ecological knowledge of RNA viruses is therefore essential towards the proper control of these emergent pathogens. This review outlines, throughout different levels of complexity, the problems posed by RNA viral diseases, covering some of the molecular mechanisms allowing them to adapt to new host species-and to novel pharmaceutical developments-up to the known ecological processes involved in zoonotic transmission.

Overlooking the smallest matter: viruses impact biological invasions

Parasites and pathogens have recently received considerable attention for their ability to affect biological invasions, however, researchers have largely overlooked the distinct role of viruses afforded by their unique ability to rapidly mutate and adapt to new hosts. With high mutation and genomic substitution rates, RNA and single-stranded DNA (ssDNA) viruses may be important constituents of invaded ecosystems, and could potentially behave quite differently from other pathogens. We review evidence suggesting that rapidly evolving viruses impact invasion dynamics in three key ways: (1) Rapidly evolving viruses may prevent exotic species from establishing self-sustaining populations. (2) Viruses can cause population collapses of exotic species in the introduced range. (3) Viruses can alter the consequences of biological invasions by causing population collapses and extinctions of native species. The ubiquity and frequent host shifting of viruses make their ability to influence invasion events likely. Eludicating the viral ecology of biological invasions will lead to an improved understanding of the causes and consequences of invasions, particularly as regards establishment success and changes to community structure that cannot be explained by direct interspecific interactions among native and exotic species.

Revertant mosaicism in genodermatoses

Inherited monogenic skin disorders include blistering disorders, inflammatory disorders, and disorders of differentiation or development. In most cases, the skin is broadly involved throughout the affected individual's lifetime, but rarely, appearance of normal skin clones has been described. In these cases of revertant mosaicism, cells undergo spontaneous correction to ameliorate the effects of genetic mutation. While targeted reversion of genetic mutation would have tremendous therapeutic value, the mechanisms of reversion in the skin are poorly understood. In this review, we provide an overview of genodermatoses that demonstrate widespread reversion and their corrective mechanisms, as well as the current research aimed to understand this "natural gene therapy".

The effect of induced mutations on quantitative traits in Arabidopsis thaliana: Natural versus artificial conditions

Mutations are the ultimate source of all genetic variations. New mutations are expected to affect quantitative traits differently depending on the extent to which traits contribute to fitness and the environment in which they are tested. The dogma is that the preponderance of mutations affecting fitness will be skewed toward deleterious while their effects on nonfitness traits will be bidirectionally distributed. There are mixed views on the role of stress in modulating these effects. We quantify mutation effects by inducing mutations in Arabidopsis thaliana (Columbia accession) using the chemical ethylmethane sulfonate. We measured the effects of new mutations relative to a premutation founder for fitness components under both natural (field) and artificial (growth room) conditions. Additionally, we measured three other quantitative traits, not expected to contribute directly to fitness, under artificial conditions. We found that induced mutations were equally as likely to increase as decrease a trait when that trait was not closely related to fitness (traits that were neither survivorship nor reproduction). We also found that new mutations were more likely to decrease fitness or fitness‐related traits under more stressful field conditions than under relatively benign artificial conditions. In the benign condition, the effect of new mutations on fitness components was similar to traits not as closely related to fitness. These results highlight the importance of measuring the effects of new mutations on fitness and other traits under a range of conditions.

Human Germline Mutation and the Erratic Evolutionary Clock

Our understanding of the chronology of human evolution relies on the “molecular clock” provided by the steady accumulation of substitutions on an evolutionary lineage. Recent analyses of human pedigrees have called this understanding into question by revealing unexpectedly low germline mutation rates, which imply that substitutions accrue more slowly than previously believed. Translating mutation rates estimated from pedigrees into substitution rates is not as straightforward as it may seem, however. We dissect the steps involved, emphasizing that dating evolutionary events requires not “a mutation rate” but a precise characterization of how mutations accumulate in development in males and females—knowledge that remains elusive.

Transgenerational inheritance: Models and mechanisms of non-DNA sequence-based inheritance

Heritability has traditionally been thought to be a characteristic feature of the genetic material of an organism-notably, its DNA. However, it is now clear that inheritance not based on DNA sequence exists in multiple organisms, with examples found in microbes, plants, and invertebrate and vertebrate animals. In mammals, the molecular mechanisms have been challenging to elucidate, in part due to difficulties in designing robust models and approaches. Here we review some of the evidence, concepts, and potential mechanisms of non-DNA sequence-based transgenerational inheritance. We highlight model systems and discuss whether phenotypes are replicated or reconstructed over successive generations, as well as whether mechanisms operate at transcriptional and/or posttranscriptional levels. Finally, we explore the short- and long-term implications of non-DNA sequence-based inheritance. Understanding the effects of non-DNA sequence-based mechanisms is key to a full appreciation of heritability in health and disease.

Time-dependent estimates of molecular evolutionary rates: evidence and causes

We are writing in response to a recent critique by Emerson & Hickerson (2015), who challenge the evidence of a time-dependent bias in molecular rate estimates. This bias takes the form of a negative relationship between inferred evolutionary rates and the ages of the calibrations on which these estimates are based. Here, we present a summary of the evidence obtained from a broad range of taxa that supports a time-dependent bias in rate estimates, with a consideration of the potential causes of these observed trends. We also describe recent progress in improving the reliability of evolutionary rate estimation and respond to the concerns raised by Emerson & Hickerson (2015) about the validity of rates estimated from time-structured sequence data. In doing so, we hope to dispel some misconceptions and to highlight several research directions that will improve our understanding of time-dependent biases in rate estimates.

Mechanisms of Nuclear Export in Cancer and Resistance to Chemotherapy

Tumour suppressor proteins, such as p53, BRCA1, and ABC, play key roles in preventing the development of a malignant phenotype, but those that function as transcriptional regulators need to enter the nucleus in order to function. The export of proteins between the nucleus and cytoplasm is complex. It occurs through nuclear pores and exported proteins need a nuclear export signal (NES) to bind to nuclear exportin proteins, including CRM1 (Chromosomal Region Maintenance protein 1), and the energy for this process is provided by the RanGTP/RanGDP gradient. Due to the loss of DNA repair and cell cycle checkpoints, drug resistance is a major problem in cancer treatment, and often an initially successful treatment will fail due to the development of resistance. An important mechanism underlying resistance is nuclear export, and a number of strategies that can prevent nuclear export may reverse resistance. Examples include inhibitors of CRM1, antibodies to the nuclear export signal, and alteration of nuclear pore structure. Each of these are considered in this review.

In Genes We Trust: Germline Engineering, Eugenics, and the Future of the Human Genome

Liberal proponents of genetic engineering maintain that developing human germline modification technologies is morally desirable because it will result in a net improvement in human health and well-being. Skeptics of germline modification, in contrast, fear evolutionary harms that could flow from intervening in the human germline, and worry that such programs, even if well intentioned, could lead to a recapitulation of the scientifically and morally discredited projects of the old eugenics. Some bioconservatives have appealed as well to the value of retaining our "given" human biological nature as a reason for restraining the development and use of human genetic modification technologies even where they would tend to increase well-being. In this article, I argue that germline intervention will be necessary merely to sustain the levels of genetic health that we presently enjoy for future generations-a goal that should appeal to bioliberals and bioconservatives alike. This is due to the population-genetic consequences of relaxed selection pressures in human populations caused by the increasing efficacy and availability of conventional medicine. This heterodox conclusion, which I present as a problem of intergenerational justice, has been overlooked in medicine and bioethics due to certain misconceptions about human evolution, which I attempt to rectify, as well as the sordid history of Darwinian approaches to medicine and social policy, which I distinguish from the present argument.

Extraordinary Genetic Diversity in a Wood Decay Mushroom

Populations of different species vary in the amounts of genetic diversity they possess. Nucleotide diversity π, the fraction of nucleotides that are different between two randomly chosen genotypes, has been known to range in eukaryotes between 0.0001 in Lynx lynx and 0.16 in Caenorhabditis brenneri. Here, we report the results of a comparative analysis of 24 haploid genotypes (12 from the United States and 12 from European Russia) of a split-gill fungus Schizophyllum commune. The diversity at synonymous sites is 0.20 in the American population of S. commune and 0.13 in the Russian population. This exceptionally high level of nucleotide diversity also leads to extreme amino acid diversity of protein-coding genes. Using whole-genome resequencing of 2 parental and 17 offspring haploid genotypes, we estimate that the mutation rate in S. commune is high, at 2.0 × 10⁻⁸ (95% CI: 1.1 × 10⁻⁸ to 4.1 × 10⁻⁸) per nucleotide per generation. Therefore, the high diversity of S. commune is primarily determined by its elevated mutation rate, although high effective population size likely also plays a role. Small genome size, ease of cultivation and completion of the life cycle in the laboratory, free-living haploid life stages and exceptionally high variability of S. commune make it a promising model organism for population, quantitative, and evolutionary genetics.

The evolution of obligate sex: the roles of sexual selection and recombination

The evolution of sex is one of the greatest mysteries in evolutionary biology. An even greater mystery is the evolution of obligate sex, particularly when competing with facultative sex and not with complete asexuality. Here, we develop a stochastic simulation of an obligate allele invading a facultative population, where males are subject to sexual selection. We identify a range of parameters where sexual selection can contribute to the evolution of obligate sex: Especially when the cost of sex is low, mutation rate is high, and the facultative individuals do not reproduce sexually very often. The advantage of obligate sex becomes larger in the absence of recombination. Surprisingly, obligate sex can take over even when the population has a lower mean fitness as a result. We show that this is due to the high success of obligate males that can compensate the cost of sex.

Asymmetric Context-Dependent Mutation Patterns Revealed through Mutation-Accumulation Experiments

Despite the general assumption that site-specific mutation rates are independent of the local sequence context, a growing body of evidence suggests otherwise. To further examine context-dependent patterns of mutation, we amassed 5,645 spontaneous mutations in wild- type (WT) and mismatch-repair deficient (MMR(-)) mutation-accumulation (MA) lines of the gram-positive model organism Bacillus subtilis. We then analyzed>7,500 spontaneous base-substitution mutations across B. subtilis, Escherichia coli, and Mesoplasma florum WT and MMR(-) MA lines, finding a context-dependent mutation pattern that is asymmetric around the origin of replication. Different neighboring nucleotides can alter site-specific mutation rates by as much as 75-fold, with sites neighboring G:C base pairs or dimers involving alternating pyrimidine-purine and purine-pyrimidine nucleotides having significantly elevated mutation rates. The influence of context-dependent mutation on genome architecture is strongest in M. florum, consistent with the reduced efficiency of selection in organisms with low effective population size. If not properly accounted for, the disparities arising from patterns of context-dependent mutation can significantly influence interpretations of positive and purifying selection.

The unforeseen challenge: from genotype-to-phenotype in cell populations

Biological cells present a paradox, in that they show simultaneous stability and flexibility, allowing them to adapt to new environments and to evolve over time. The emergence of stable cell states depends on genotype-to-phenotype associations, which essentially reflect the organization of gene regulatory modes. The view taken here is that cell-state organization is a dynamical process in which the molecular disorder manifests itself in a macroscopic order. The genome does not determine the ordered cell state; rather, it participates in this process by providing a set of constraints on the spectrum of regulatory modes, analogous to boundary conditions in physical dynamical systems. We have developed an experimental framework, in which cell populations are exposed to unforeseen challenges; novel perturbations they had not encountered before along their evolutionary history. This approach allows an unbiased view of cell dynamics, uncovering the potential of cells to evolve and develop adapted stable states. In the last decade, our experiments have revealed a coherent set of observations within this framework, painting a picture of the living cell that in many ways is not aligned with the conventional one. Of particular importance here, is our finding that adaptation of cell-state organization is essentially an efficient exploratory dynamical process rather than one founded on random mutations. Based on our framework, a set of concepts underlying cell-state organization-exploration evolving by global, non-specific, dynamics of gene activity-is presented here. These concepts have significant consequences for our understanding of the emergence and stabilization of a cell phenotype in diverse biological contexts. Their implications are discussed for three major areas of biological inquiry: evolution, cell differentiation and cancer. There is currently no unified theoretical framework encompassing the emergence of order, a stable state, in the living cell. Hopefully, the integrated picture described here will provide a modest contribution towards a physics theory of the cell.

Induced mutations in yeast cell populations adapting to an unforeseen challenge

The modern evolutionary synthesis assumes that mutations occur at random, independently of the environment in which they confer an advantage. However, there are indications that cells facing challenging conditions can adapt rapidly, utilizing processes beyond selection of pre-existing genetic variation. Here, we show that a strong regulatory challenge can induce mutations in many independent yeast cells, in the absence of general mutagenesis. Whole genome sequencing of cell lineages reveals a repertoire of independent mutations within a single lineage that arose only after the cells were exposed to the challenging environment, while other cells in the same lineage adapted without any mutation in their genomes. Thus, our experiments uncovered multiple alternative routes for heritable adaptation that were all induced in the same lineage during a short time period. Our results demonstrate the existence of adaptation mechanisms beyond random mutation, suggesting a tight connection between physiological and genetic processes.