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Understanding how genetic and ecological effects can interact to shape genetic loads within and across local populations is key to understanding ongoing persistence of systems that should otherwise be susceptible to extinction through mutational meltdown. Classic theory predicts short persistence times for metapopulations comprising small local populations with low connectivity, due to accumulation of deleterious mutations. Yet, some such systems have persisted over evolutionary time, implying the existence of mechanisms that allow metapopulations to avoid mutational meltdown. We first hypothesize a mechanism by which the combination of stochasticity in the numbers and types of mutations arising locally (genetic stochasticity), resulting local extinction, and recolonization through evolving dispersal facilitates metapopulation persistence. We then test this mechanism using a spatially and genetically explicit individual-based model. We show that genetic stochasticity in highly structured metapopulations can result in local extinctions, which can favor increased dispersal, thus allowing recolonization of empty habitat patches. This causes fluctuations in metapopulation size and transient gene flow, which reduces genetic load and increases metapopulation persistence over evolutionary time. Our suggested mechanism and simulation results provide an explanation for the conundrum presented by the continued persistence of highly structured populations with inbreeding mating systems that occur in diverse taxa.

Following widespread infections of the most recent coronavirus known to infect humans, SARS‐CoV‐2, attention has turned to potential therapeutic options. With no drug or vaccine yet approved, one focal point of research is to evaluate the potential value of repurposing existing antiviral treatments, with the logical strategy being to identify at least a short‐term intervention to prevent within‐patient progression, while long‐term vaccine strategies unfold. Here, we offer an evolutionary/population‐genetic perspective on one approach that may overwhelm the capacity for pathogen defense (i.e., adaptation) – induced mutational meltdown – providing an overview of key concepts, review of previous theoretical and experimental work of relevance, and guidance for future research. Applied with appropriate care, including target specificity, induced mutational meltdown may provide a general, rapidly implemented approach for the within‐patient eradication of a wide range of pathogens or other undesirable microorganisms.

RNA viruses comprise vast populations of closely related, but highly genetically diverse, entities known as quasispecies. Understanding the mechanisms by which this extreme diversity is generated and maintained is fundamental when approaching viral persistence and pathobiology in infected hosts. In this paper, we access quasispecies theory through a mathematical model based on the theory of multitype branching processes, to better understand the roles of mechanisms resulting in viral diversity, persistence and extinction. We accomplish this understanding by a combination of computational simulations and the theoretical analysis of the model. In order to perform the simulations, we have implemented the mathematical model into a computational platform capable of running simulations and presenting the results in a graphical format in real time. Among other things, we show that the establishment of virus populations may display four distinct regimes from its introduction into new hosts until achieving equilibrium or undergoing extinction. Also, we were able to simulate different fitness distributions representing distinct environments within a host which could either be favorable or hostile to the viral success. We addressed the most used mechanisms for explaining the extinction of RNA virus populations called lethal mutagenesis and mutational meltdown. We were able to demonstrate a correspondence between these two mechanisms implying the existence of a unifying principle leading to the extinction of RNA viruses., 34 pages, 10 figures, 4 tables, 1 appendix

An immense scientific effort has been made worldwide due to Covid-19’s pandemic magnitude. It has made possible to identify almost 300,000 SARS-CoV-2 different genetic variants, connecting them with clinical and epidemiological findings. Among this immense data collection, that constitutes the biggest evolutionary experiment in history, is buried the answer to what will happen in the future. Will new strains, more contagious than the current ones or resistant to the vaccines, arise by mutation? Although theoretic population genetics is, by far, the most powerful tool we have to do an accurate prediction, it has been barely used for the study of SARS-CoV-2 due to its conceptual difficulty. Having in mind that the size of the SARS-CoV-2 population is astronomical we can apply a discrete treatment, based on the branching process method, Fokker-Plank equations and Kolmogoroff’s forward equations, to calculate the survival likelihood through time, to elucidate the likelihood to become dominant genotypes and how long will this take, for new SARS-CoV-2 mutants depending on their selective advantage. Results show that most of the new mutants that will arise in the SARS-CoV-2 meta-population will stay at very low frequencies. However, some few new mutants, significantly more infectious than current ones, will still emerge and become dominant in the population favoured by a great selective advantage. Far from showing a “mutational meltdown”, SARS-CoV-2 meta-population will increase its fitness becoming more infective. There is a probability, small but finite, that new mutants arise resistant to some vaccines. High infected numbers and slow vaccination programs will significantly increase this likelihood.

Mitochondrial DNA (mtDNA) and plastid DNA (ptDNA) encode vital bioenergetic apparatus, and mutations in these organelle DNA (oDNA) molecules can be devastating. In the germline of several animals, a genetic “bottleneck” increases cell-to-cell variance in mtDNA heteroplasmy, allowing purifying selection to act to maintain low proportions of mutant mtDNA. However, most eukaryotes do not sequester a germline early in development, and even the animal bottleneck remains poorly understood. How then do eukaryotic organelles avoid Muller’s ratchet—the gradual buildup of deleterious oDNA mutations? Here, we construct a comprehensive and predictive genetic model, quantitatively describing how different mechanisms segregate and decrease oDNA damage across eukaryotes. We apply this comprehensive theory to characterise the animal bottleneck with recent single-cell observations in diverse mouse models. Further, we show that gene conversion is a particularly powerful mechanism to increase beneficial cell-to-cell variance without depleting oDNA copy number, explaining the benefit of observed oDNA recombination in diverse organisms which do not sequester animal-like germlines (for example, sponges, corals, fungi, and plants). Genomic, transcriptomic, and structural datasets across eukaryotes support this mechanism for generating beneficial variance without a germline bottleneck. This framework explains puzzling oDNA differences across taxa, suggesting how Muller’s ratchet is avoided in different eukaryotes., A comprehensive model for mitochondrial and plasmid DNA segregation, supported by with genomic, transcriptomic, and single-cell data, shows how the attritional effects of Muller’s ratchet can be avoided in the organelles of diverse eukaryotes.

In colonies of the filamentous multicellular bacterium Streptomyces coelicolor, a sub-population of cells arise that hyper-produce metabolically costly antibiotics, resulting in a division of labor that maximizes colony fitness. Because these cells contain large genomic deletions that cause massive reductions to individual fitness, their behavior is altruistic, much like worker castes in eusocial insects. To understand the reproductive and genomic fate of these mutant cells after their emergence, we use experimental evolution by serially transferring populations via spore-to-spore transfer for 25 cycles, reflective of the natural mode of bottlenecked transmission for these spore-forming bacteria. We show that, in contrast to wild-type cells, altruistic mutant cells continue to significantly decline in fitness during transfer while they delete larger and larger fragments from their chromosome ends. In addition, altruistic mutants acquire a roughly 10-fold increase in their base-substitution rates due to mutations in genes for DNA replication and repair. Ecological damage, caused by reduced sporulation, coupled with irreversible DNA damage due to point mutation and deletions, leads to an inevitable and irreversible type of mutational meltdown in these cells. Taken together, these results suggest that the altruistic cells arising in this division of labor are equivalent to reproductively sterile castes of social insects.

The dire need of effective preventive measures and treatment approaches against SARS-CoV-2 virus, causing COVID-19 pandemic, calls for an in-depth understanding of its evolutionary dynamics with attention to specific geographic locations, since lockdown and social distancing to prevent the virus spread could lead to distinct localized dynamics of virus evolution within and between countries owing to different environmental and host-specific selection pressures. To decipher any correlation between SARS-CoV-2 evolution and its epidemiology in India, we studied the mutational diversity of spike glycoprotein, the key player for the attachment, fusion and entry of virus to the host cell. For this, we analyzed the sequences of 630 Indian isolates as available in GISAID database till June 07, 2020, and detected the spike protein variants to emerge from two major ancestors – Wuhan-Hu-1/2019 and its D614G variant. Average stability of the docked spike protein – host receptor (S-R) complexes for these variants correlated strongly (R2=0.96) with the fatality rates across Indian states. However, while more than half of the variants were found unique to India, 67% of all variants showed lower stability of S-R complex than the respective ancestral variants, indicating a possible fitness loss in recently emerged variants, despite a continuous increase in mutation rate. These results conform to the sharply declining fatality rate countrywide (>7-fold during April 11 – June 28, 2020). Altogether, while we propose the potential of S-R complex stability to track disease severity, we urge an immediate need to explore if SARS-CoV-2 is approaching mutational meltdown in India.Author summaryEpidemiological features are intricately linked to evolutionary diversity of rapidly evolving pathogens, and SARS-CoV-2 is no exception. Our work suggests the potential of average stability of complexes formed by the circulating spike mutational variants and the human host receptor to track the severity of SARS-CoV-2 infection in a given region. In India, the stability of these complexes for recent variants tend to decrease relative to their ancestral ones, following countrywide declining fatality rate, in contrast to an increasing mutation rate. We hypothesize such a scenario as nascent footprints of Muller’s ratchet, proposing large-scale population genomics study for its validation, since this understanding could lead to therapeutic approaches for facilitating mutational meltdown of SARS-CoV-2, as experienced earlier for influenza A virus.

Understanding why some species accumulate more deleterious substitutions than others is an important question relevant in evolutionary biology and conservation sciences. Previous studies conducted in terrestrial taxa suggest that life history traits correlate with the efficiency of purifying selection and accumulation of deleterious mutations. Using a large genome data set of 76 species of teleostean fishes, we show that species with life history traits associated with vulnerability to fishing have an increased rate of deleterious mutation accumulation (measured via dN/dS, i.e., nonsynonymous over synonymous substitution rate). Our results, focusing on a large clade of aquatic species, generalize previous patterns found so far in few clades of terrestrial vertebrates. These results also show that vulnerable species to fishing inherently accumulate more deleterious substitutions than nonthreatened ones, which illustrates the potential links among population genetics, ecology, and fishing policies to prevent species extinction.

Cellular populations such as avascular tumors and microbial biofilms may ‘invade’ or grow into surrounding populations. The invading population is often comprised of a heterogeneous mixture of cells with varying growth rates. The population may also exhibit mutational instabilities, such as a heavy deleterious mutation load in a cancerous growth. We study the dynamics of a heterogeneous, mutating population competing with a surrounding homogeneous population, as one might find in a cancerous invasion of healthy tissue. We find that the shape of the population interface serves as an indicator for the evolutionary dynamics within the heterogeneous population. In particular, invasion front undulations become enhanced when the invading population is near a mutational meltdown transition or when the surrounding ‘bystander’ population is barely able to reinvade the mutating population. We characterize these interface undulations and the effective fitness of the heterogeneous population in one- and two-dimensional systems.

The dire need of effective preventive measures and treatment approaches against SARS-CoV-2 virus, causing COVID-19 pandemic, calls for an in-depth understanding of its evolutionary dynamics with attention to specific geographic locations, since lockdown and social distancing to prevent the virus spread could lead to distinct localized dynamics of virus evolution within and between countries owing to different environmental and host-specific selection pressures. To decipher any correlation between SARS-CoV-2 evolution and its epidemiology in India, we studied the mutational diversity of spike glycoprotein, the key player for the attachment, fusion and entry of virus to the host cell. For this, we analyzed the sequences of 630 Indian isolates as available in GISAID database till June 07, 2020 (during the time-period before the start of Unlock 1.0 in India on and from June 08, 2020), and detected the spike protein variants to emerge from two major ancestors – Wuhan-Hu-1/2019 and its D614G variant. Average stability of the docked spike protein – host receptor (S-R) complexes for these variants correlated strongly (R2 = 0.96) with the fatality rates across Indian states. However, while more than half of the variants were found unique to India, 67% of all variants showed lower stability of S-R complex than the respective ancestral variants, indicating a possible fitness loss in recently emerged variants, despite a continuous increase in mutation rate. These results conform to the sharply declining fatality rate countrywide (>7-fold during April 11 – June 28, 2020). Altogether, while we propose the potential of S-R complex stability to track disease severity, we urge an immediate need to explore if SARS-CoV-2 is approaching mutational meltdown in India.

The mutation–selection process is the most fundamental mechanism of evolution. In 1935, R. A. Fisher proved his fundamental theorem of natural selection, providing a model in which the rate of change of mean fitness is equal to the genetic variance of a species. Fisher did not include mutations in his model, but believed that mutations would provide a continual supply of variance resulting in perpetual increase in mean fitness, thus providing a foundation for neo-Darwinian theory. In this paper we re-examine Fisher’s Theorem, showing that because it disregards mutations, and because it is invalid beyond one instant in time, it has limited biological relevance. We build a differential equations model from Fisher’s first principles with mutations added, and prove a revised theorem showing the rate of change in mean fitness is equal to genetic variance plus a mutational effects term. We refer to our revised theorem as the fundamental theorem of natural selection with mutations. Our expanded theorem, and our associated analyses (analytic computation, numerical simulation, and visualization), provide a clearer understanding of the mutation–selection process, and allow application of biologically realistic parameters such as mutational effects. The expanded theorem has biological implications significantly different from what Fisher had envisioned.

This deposit is composed by the main article plus the supplementary materials of the publication. Influenza virus inflicts a heavy death toll annually and resistance to existing antiviral drugs has generated interest in the development of agents with novel mechanisms of action. Favipiravir is an antiviral drug that acts by increasing the genome-wide mutation rate of influenza A virus (IAV). Potential synergistic benefits of combining oseltamivir and favipiravir have been demonstrated in animal models of influenza, but the population-level effects of combining the drugs are unknown. In order to elucidate the underlying evolutionary processes at play, we performed genome-wide sequencing of IAV experimental populations subjected to serial passaging in vitro under a combined protocol of oseltamivir and favipiravir. We describe the interplay between mutation, selection, and genetic drift that ultimately culminates in population extinction. In particular, selective sweeps around oseltamivir resistance mutations reduce genome-wide variation while deleterious mutations hitchhike to fixation given the increased mutational load generated by favipiravir. This latter effect reduces viral fitness and accelerates extinction compared with IAV populations treated with favipiravir alone, but risks spreading both established and newly emerging mutations, including possible drug resistance mutations, if transmission occurs before the viral populations are eradicated. Office of the Assistant Secretary of Defense for Health Affairs - Peer Reviewed Medical Research Program grant: (W81XWH-15-1-0317); Defense Advanced Research Projects Agency (DARPA) Prophecy Program; Defense Sciences Office (DSO), Contract No. HR0011-11-C-0095, and D13AP00041; MediVector; European Research Council (ERC); Fuji Films; Department of Defense. info:eu-repo/semantics/publishedVersion

The cross-species transmission of viruses into new host populations, termed virus emergence, is a significant issue in public health, agriculture, wildlife management, and related fields. Virus emergence requires overlap between host populations, alterations in virus genetics to permit infection of new hosts, and adaptation to novel hosts such that between-host transmission is sustainable, all of which are the purview of the fields of ecology and evolution. A firm understanding of the ecology of viruses and how they evolve is required for understanding how and why viruses emerge. In this paper, I address the evolutionary mechanisms of virus emergence and how they relate to virus ecology. I argue that, while virus acquisition of the ability to infect new hosts is not difficult, limited evolutionary trajectories to sustained virus between-host transmission and the combined effects of mutational meltdown, bottlenecking, demographic stochasticity, density dependence, and genetic erosion in ecological sinks limit most emergence events to dead-end spillover infections. Despite the relative rarity of pandemic emerging viruses, the potential of viruses to search evolutionary space and find means to spread epidemically and the consequences of pandemic viruses that do emerge necessitate sustained attention to virus research, surveillance, prophylaxis, and treatment.

High mutation rates select for the evolution of mutational robustness where populations inhabit flat fitness peaks with little epistasis, protecting them from a mutational meltdown. Recent evidence suggests that a different effect protects small populations from extinction via the accumulation of deleterious mutations. In drift robustness, populations tend to occupy peaks with steep flanks and positive epistasis between mutations. However, it is not known what happens when mutation rates are high and population sizes are small at the same time. Using a simple fitness model with both variable epistasis and variable mutational effect size, we show that the equilibrium fitness has a minimum as a function of the parameter that tunes epistasis, implying that this critical point is an unstable fixed point for evolutionary trajectories. In agent-based simulations of evolution at finite mutation rate, we demonstrate that when mutations can change epistasis, trajectories with a subcritical value of epistasis evolve to decrease epistasis, while those with supercritical initial points evolve towards higher epistasis. These two fixed points can be identified with mutational and drift robustness, respectively.

Putting a price on the powerhouse Mitochondria—the so-called powerhouse of the cell—are derived from bacterial endosymbionts. This history provides opportunities and challenges for their host cells, particularly metazoans, including humans. Youle reviews the interplay between host and mitochondrial biology and highlights how mitochondrial ancestry has influenced innate immune responses. Keeping mitochondria both healthy and in check is key to organismal health and, when perturbed, leads to a variety of pathologies, including Parkinson's disease and inflammation. Science , this issue p. eaaw9855

Self-fertilisation has consequences for variation across the genome as it reduces effective population size, effect recombination rates and pollen flow, with implications for local adaptation. We conducted simulations of divergent stabilising selection on a quantitative trait with drift, pollen flow, mutation, recombination and different outcrossing rates. We quantified trait divergence and the genetic architecture of adaptation. We conducted an FST outlier analysis to identify candidate loci and quantified the impact of mating system on detectability. Selfing promoted trait divergence mainly through reductions in pollen flow. Moreover, trait architecture became more diffuse with selfing. Average effect size of trait loci was lower, while the number of loci, and their clustering distance increased. The genetic architecture of selfers was also more diffuse than outcrossers for equivalent migration rates. However, when deleterious alleles were included, architectures became more concentrated in selfers, likely to be because of reductions in population size caused by mutational meltdown and impacts of background selection on Ne . Our simulations demonstrate that mating system has important impacts on adaptive divergence of traits and the genetic landscape underlying that divergence. Selfing has a significant effect on detectability of regions of the genome important for adaptation because of neutral divergence and diffuse trait architecture.

Large genomes with elevated mutation rates are prone to accumulating deleterious mutations more rapidly than natural selection can purge (Muller's ratchet). As a consequence, it may lead to the extinction of small populations. Relative to most unicellular organisms, cancer cells, with large and nonrecombining genome and high mutation rate, could be particularly susceptible to such "mutational meltdown." However, the most common type of mutation in organismal evolution, namely, deleterious mutation, has received relatively little attention in the cancer biology literature. Here, by monitoring single-cell clones from HeLa cell lines, we characterize deleterious mutations that retard the rate of cell proliferation. The main mutation events are copy number variations (CNVs), which, estimated from fitness data, happen at a rate of 0.29 event per cell division on average. The mean fitness reduction, estimated reaching 18% per mutation, is very high. HeLa cell populations therefore have very substantial genetic load and, at this level, natural population would likely face mutational meltdown. We suspect that HeLa cell populations may avoid extinction only after the population size becomes large enough. Because CNVs are common in most cell lines and tumor tissues, the observations hint at cancer cells' vulnerability, which could be exploited by therapeutic strategies.

Mutation, genetic drift, and selection are considered the main factors shaping genetic variation in nature. There is a lack, however, of general predictions accounting for the mutual interrelation between these factors. In the context of the background selection model, we provide a set of equations for the joint prediction of the effective population size and the rate of fixation of deleterious mutations, which are applicable both to sexual and asexual species. For a population of N haploid individuals and a model of deleterious mutations with effect s appearing with rate U in a genome L Morgans long, the asymptotic effective population size ( N e ) and the average number of generations ( T ) between consecutive fixations can be approximated by N e ≈ N exp [ − 2 U / ( 2 s + L ) ( 1 − 1 / UT ) 3 ] and T ≈ [ exp ( 2 s N e ) − 1 ] / [ 2 Us N e ] . The solution is applicable to Muller’s ratchet, providing satisfactory approximations to the rate of accumulation of mutations for a wide range of parameters. We also obtain predictions of the effective size accounting for the expected nucleotide diversity. Predictions for sexual populations allow for outlining the general conditions where mutational meltdown occurs. The equations can be extended to any distribution of mutational effects and the consideration of hotspots of recombination, showing that N e is rather insensitive and not proportional to changes in N for many combinations of parameters. This could contribute to explain the observed small differences in levels of polymorphism between species with very different census sizes.

The rapid evolution of drug resistance remains a critical public health concern. The treatment of influenza A virus (IAV) has proven particularly challenging, due to the ability of the virus to develop resistance against current antivirals and vaccines. Here, we evaluate a novel antiviral drug therapy, favipiravir, for which the mechanism of action in IAV involves an interaction with the viral RNA-dependent RNA polymerase resulting in an effective increase in the viral mutation rate. We used an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across 15 time points under multiple drug concentrations and in controls, we present the first evidence for the ability of IAV populations to effectively adapt to low concentrations of favipiravir. In contrast, under high concentrations, we observe population extinction, indicative of mutational meltdown. We discuss the observed dynamics with respect to the evolutionary forces at play and emphasize the utility of evolutionary theory to inform drug development.

Almost all cellular life forms are hosts to diverse genetic parasites with various levels of autonomy including plasmids, transposons and viruses. Theoretical modeling of the evolution of primordial replicators indicates that parasites (cheaters) necessarily evolve in such systems and can be kept at bay primarily via compartmentalization. Given the (near) ubiquity, abundance and diversity of genetic parasites, the question becomes pertinent: are such parasites intrinsic to life? At least in prokaryotes, the persistence of parasites is linked to the rate of horizontal gene transfer (HGT). We mathematically derive the threshold value of the minimal transfer rate required for selfish element persistence, depending on the element duplication and loss rates as well as the cost to the host. Estimation of the characteristic gene duplication, loss and transfer rates for transposons, plasmids and virus-related elements in multiple groups of diverse bacteria and archaea indicates that most of these rates are compatible with the long term persistence of parasites. Notably, a small but non-zero rate of HGT is also required for the persistence of non-parasitic genes. We hypothesize that cells cannot tune their horizontal transfer rates to be below the threshold required for parasite persistence without experiencing highly detrimental side-effects. As a lower boundary to the minimum DNA transfer rate that a cell can withstand, we consider the process of genome degradation and mutational meltdown of populations through Muller’s ratchet. A numerical assessment of this hypothesis suggests that microbial populations cannot purge parasites while escaping Muller’s ratchet. Thus, genetic parasites appear to be virtually inevitable in cellular organisms.

Summary The lifespan of plants ranges from a few weeks in annuals to thousands of years in trees. It is hard to explain such extreme longevity considering that DNA replication errors inevitably cause mutations. Without purging through meiotic recombination, the accumulation of somatic mutations will eventually result in mutational meltdown, a phenomenon known as Muller's ratchet. Nevertheless, the lifespan of trees is limited more often by incidental disease or structural damage than by genetic aging. The key determinants of tree architecture are the axillary meristems, which form in the axils of leaves and grow out to form branches. The number of branches is low in annual plants, but in perennial plants iterative branching can result in thousands of terminal branches. Here, we use stem cell ablation and quantitative cell-lineage analysis to show that axillary meristems are set aside early, analogous to the metazoan germline. While neighboring cells divide vigorously, axillary meristem precursors maintain a quiescent state, with only 7–9 cell divisions occurring between the apical and axillary meristem. During iterative branching, the number of branches increases exponentially, while the number of cell divisions increases linearly. Moreover, computational modeling shows that stem cell arrangement and positioning of axillary meristems distribute somatic mutations around the main shoot, preventing their fixation and maximizing genetic heterogeneity. These features slow down Muller's ratchet and thereby extend lifespan.

Asexual populations are expected to accumulate deleterious mutations through a process known as Muller's Ratchet. Lynch, Gabriel, and colleagues have proposed that the Ratchet eventually results in a vicious cycle of mutation accumulation and population decline that drives populations to extinction. They called this phenomenon mutational meltdown. Here, we analyze the meltdown using a multitype branching process model where, in the presence of mutation, populations are doomed to extinction. We find that extinction occurs more quickly in small populations, experiencing a high deleterious mutation rate, and mutations with more severe deleterious effects. The effects of mutational parameters on extinction time in doomed populations differ from those on the severity of Muller's Ratchet in populations of constant size. We also find that mutational meltdown, although it does occur in our model, does not determine extinction time. Rather, extinction time is determined by the expected impact of deleterious mutations on fitness.

Sex is ancestral in eukaryotes. Meiotic sex differs from bacterial ways of exchanging genetic material by involving the fusion of two cells. We examine the hypothesis that fusion evolved in early eukaryotes because it was directly beneficial, rather than a passive side effect of meiotic sex. We assume that the uptake of (proto)mitochondria into eukaryotes preceded the evolution of cell fusion and that Muller's ratchet operating within symbiont lineages led to the accumulation of lineage-specific sets of mutations in asexual host cells. We examine whether cell fusion, and the consequent biparental inheritance of symbionts, helps to mitigate the effects of this mutational meltdown of mitochondria. In our model, host cell fitness improves when two independently evolved mitochondrial strains co-inhabit a single cytoplasm, mirroring mitochondrial complementation found in modern eukaryotes. If fusion incurs no cost, we find that an allele coding for fusion can invade a population of nonfusers. If fusion is costly, there are two thresholds. The first describes a maximal fusing rate (probability of fusion per round of cell division) that is able to fix. An allele that codes for a rate above this threshold can reach a polymorphic equilibrium with nonfusers, as long as the rate is below the second threshold, above which the fusion allele is counter-selected. Whenever it evolves, fusion increases the population-wide level of heteroplasmy, which allows mitochondrial complementation and increases population fitness. We conclude that beneficial interactions between mitochondria are a potential factor that selected for cell fusion in early eukaryotes.

Significance How mutation and selection co-determine the course of cancer evolution remains an open, fundamental question. We construct a mutation-selection phase diagram, using tumor mutation load (ML) and selection strength (dN/dS) as key variables, and assess their association with clinical outcome. The results reveal a biphasic evolutionary regime whereby beyond a critical ML, tumor fitness decreases with the number of mutations, although the proteome evolves near neutrality—that is, without strong selection. Deviations from neutrality at extreme ML show how positive selection (at low ML) and purifying selection (at high ML) may act to maintain tumor fitness. These results corroborate the existence of a critical state in cancer evolution predicted by theory and have fundamental and likely clinical implications., How mutation and selection determine the fitness landscape of tumors and hence clinical outcome is an open fundamental question in cancer biology, crucial for the assessment of therapeutic strategies and resistance to treatment. Here we explore the mutation-selection phase diagram of 6,721 tumors representing 23 cancer types by quantifying the overall somatic point mutation load (ML) and selection (dN/dS) in the entire proteome of each tumor. We show that ML strongly correlates with patient survival, revealing two opposing regimes around a critical point. In low-ML cancers, a high number of mutations indicates poor prognosis, whereas high-ML cancers show the opposite trend, presumably due to mutational meltdown. Although the majority of cancers evolve near neutrality, deviations are observed at extreme MLs. Melanoma, with the highest ML, evolves under purifying selection, whereas in low-ML cancers, signatures of positive selection are observed, demonstrating how selection affects tumor fitness. Moreover, different cancers occupy specific positions on the ML–dN/dS plane, revealing a diversity of evolutionary trajectories. These results support and expand the theory of tumor evolution and its nonlinear effects on survival.

Sex is beneficial in the long term because it can prevent mutational meltdown through increased effectiveness of selection. This idea is supported by empirical evidence of deleterious mutation accumulation in species with a recent transition to asexuality. Here, we study the effectiveness of purifying selection in oribatid mites which have lost sex millions of years ago and diversified into different families and species while reproducing asexually. We compare the accumulation of deleterious nonsynonymous and synonymous mutations between three asexual and three sexual lineages using transcriptome data. Contrasting studies of young asexual lineages, we find evidence for strong purifying selection that is more effective in asexual as compared to sexual oribatid mite lineages. Our results suggest that large populations likely sustain effective purifying selection and facilitate the escape of mutational meltdown in the absence of sex. Thus, sex per se is not a prerequisite for the long-term persistence of animal lineages., Asexual reproduction is thought to be an evolutionary dead end in eukaryotes because deleterious mutations will not be purged effectively. Here, Brandt and colleagues show that anciently asexual oribatid mites in fact have reduced accumulation of deleterious mutations compared to their sexual relatives.

ABSRACTLarge and non-recombining genomes are prone to accumulating deleterious mutations faster than natural selection can purge (Muller’s ratchet). A possible consequence would then be the extinction of small populations. Relative to most single-cell organisms, cancer cells, with large and non-recombining genomes, could be particularly susceptible to such “mutational meltdown”. Curiously, deleterious mutations in cancer cells are rarely noticed despite the strong signals in cancer genome sequences. Here, by monitoring single-cell clones from HeLa cell lines, we characterize deleterious mutations that retard cell proliferation. The main mutational events are copy number variations (CNVs), which happen at an extraordinarily high rate of 0.29 events per cell division. The average fitness reduction, estimated to be 18% per mutation, is also very high. HeLa cell populations therefore have very substantial genetic load and, at this level, natural population would likely experience mutational meltdown. We suspect that HeLa cell populations may avoid extinction only after the population size becomes large. Because CNVs are common in most cell lines and cancer tissues, the observations hint at cancer cells’ vulnerability, which could be exploited by therapeutic strategies.