Moran Process Version of the Tug-of-War Model: Complex Behavior Revealed by Mathematical Analysis and Simulation Studies

In a series of publications McFarland and co-authors introduced the tug-of-warmodel of evolution of cancer cell populations. The model is explaining the joint effect ofrare advantageous and frequent slightly deleterious mutations, which may be identifiable withdriver and passenger mutations in cancer. In this paper, we put the Tug-of-War model inthe framework of a denumerable-type Moran process and use mathematics and simulationsto understand its behavior. The model is associated with a time-continuous Markov Chain(MC), with a generator that can be split into a sum of the drift and selection process partand of the mutation process part. Operator semigroup theory is then employed to prove thatthe MC does not explode, as well as to characterize a strong-drift limit version of the MCwhich displays instant fixation effect, which was an assumption in the original McFarlandsmodel. Mathematical results are fully confirmed by simulations of the complete and limitversions. They also visualize complex stochastic transients and genealogies of clones arising inthe model.

Genomics of a killifish from the Seychelles islands supports transoceanic island colonization and reveals relaxed selection of developmental genes

How freshwater fish colonize remote islands remains an evolutionary puzzle. Tectonic drift and trans-oceanic dispersal models have been proposed as possible alternative mechanisms. Integrating dating of known tectonic events with population genetics and experimental test of salinity tolerance in the Seychelles islands golden panchax (Pachypanchax playfairii), we found support for trans-oceanic dispersal being the most likely scenario. At the macroevolutionary scale, the non-annual killifish golden panchax shows stronger genome-wide purifying selection compared to annual killifishes from continental Africa. Reconstructing past demographies in isolated golden panchax populations provides support for decline in effective population size, which could have allowed slightly deleterious mutations to segregate in the population. Unlike annual killifishes, where relaxed selection preferentially targets aging-related genes, relaxation of purifying selection in golden panchax affects genes involved in developmental processes, including fgf10.

Parental population range expansion before secondary contact promotes heterosis

Population genomic analysis of hybrid zones is instrumental to our understanding of the evolution of reproductive isolation. Many temperate hybrid zones are formed by the secondary contact between two parental populations that had undergone post-glacial range expansion. Here we show that explicitly accounting for historical parental isolation followed by range expansion prior to secondary contact is fundamental for explaining genetic and fitness patterns in these hybrid zones. Specifically, ancestral population expansion can result in allele surfing, neutral or slightly deleterious mutations drift high frequency at the front of the expansion. If these surfed deleterious alleles are recessive, they can contribute to substantial heterosis in hybrids produced at secondary contact, counteracting negative-epistatic interactions between BDMI loci and hence can deteriorate reproductive isolation. Similarly, surfing at neutral loci can alter the expected pattern of population ancestry and suggests that accounting for historical population expansion is necessary to develop accurate null genomic models in secondary-contact hybrid zones. Furthermore, this process should be incorporated in macroevolutionary models of divergence as well, since such heterosis facilitated by parental-range expansion could dampen genomic divergence established in the past.

GENOME-WIDE RELAXATION OF SELECTIVE CONSTRAINTS UNDERLIES THE EVOLUTION OF SHORT LIFE SPAN IN AFRICAN KILLIFISHES

African killifishes independently evolved annual life cycles at least three times, offering a unique natural experiment of diversification of life history strategies. Using a comprehensive whole-genome sampling of 46 species of African killifishes, we found that genome size correlates with annual life style and climate. Annual species underwent genome-wide expansion of transposable elements, higher gene family turn-over rates and relaxed selection in genes in known aging pathways, such as mitochondrial replication and translation, mTOR pathway and DNA repair. Whole-genome resequencing in wild Nothobranchius populations showed bottle-necks and a genome-wide signature of relaxation of selection in populations evolved in dryer climates. In conclusion, evolution in ephemeral environments in African killifishes caused an extensive relaxation of selective constraints at genome-wide level. We discovered that, in African killifishes, ecology drove the evolution of short life span, associated to tens of thousands of slightly deleterious mutations driven to intermediate to high frequencies.

Compensatory coevolution

In most eukaryotes, mitochondrial genes mutate at a higher rate than nuclear genes. In addition, mitochondrial genes are transmitted without recombination, so slightly deleterious mutations are predicted to perpetually accumulate in mt genes. Accumulation of deleterious mutations in mt genes can potentially lead to loss of mitonuclear coadaptation. There is growing evidence that variant nuclear genes evolve so as to compensate for mitochondrial mutations and restore mitochondrial function. This is compensatory coevolution and is the focus of this chapter. The chapter also explores the idea that the many nuclear-encoded subunits in eukaryotic electron transport system enzymes were recruited to regulate and control the core catalytic reactions undertaken by the core mitochondrial subunits. It will also consider the evidence that when mutational erosion occurs, corrupted mitochondrial genotypes can be rescued by introgression of entire mitochondrial genomes. Compensatory coevolution has important implications for speciation, sexual selection, and adaptation.

Impact of the tree prior on estimating clock rates during epidemic outbreaks

Bayesian phylogenetics aims at estimating phylogenetic trees together with evolutionary and population dynamic parameters based on genetic sequences. It has been noted that the clock rate, one of the evolutionary parameters, decreases with an increase in the sampling period of sequences. In particular, clock rates of epidemic outbreaks are often estimated to be higher compared with the long-term clock rate. Purifying selection has been suggested as a biological factor that contributes to this phenomenon, since it purges slightly deleterious mutations from a population over time. However, other factors such as methodological biases may also play a role and make a biological interpretation of results difficult. In this paper, we identify methodological biases originating from the choice of tree prior, that is, the model specifying epidemiological dynamics. With a simulation study we demonstrate that a misspecification of the tree prior can upwardly bias the inferred clock rate and that the interplay of the different models involved in the inference can be complex and nonintuitive. We also show that the choice of tree prior can influence the inference of clock rate on real-world Ebola virus (EBOV) datasets. While commonly used tree priors result in very high clock-rate estimates for sequences from the initial phase of the epidemic in Sierra Leone, tree priors allowing for population structure lead to estimates agreeing with the long-term rate for EBOV.

Integrating ecology and evolution to study hypothetical dynamics of algal blooms and Muller’s ratchet using Evolvix

Algal blooms have been the subject of considerable research as they occur over various spatial and temporal scales and can produce toxins that disrupt their ecosystem. Algal blooms are often governed by nutrient availability however other limitations exist. Algae are primary producers and therefore subject to predation which can keep populations below levels supported by nutrient availability. If algae as prey mutate to gain the ability to produce toxins deterring predators, they may increase their survival rates and form blooms unless other factors counter their effective increase in growth rate. Where might such mutations come from? Clearly, large populations of algae will repeatedly experience mutations knocking-out DNA repair genes, increasing mutation rates, and with them the chance of acquiring de-novo mutations producing a toxin against predators. We investigate this hypothetical scenario by simulation in the Evolvix modeling language. We modeled a sequence of steps that in principle can allow a typical asexual algal population to escape predation pressure and form a bloom with the help of mutators. We then turn our attention to the unavoidable side effect of generally increased mutation rates, many slightly deleterious mutations. If these accumulate at sufficient speed, their combined impact on fitness might place upper limits on the duration of algal blooms. These steps are required: (1) Random mutations result in the loss of DNA repair mechanisms. (2) Increased mutation rates make it more likely to acquire the ability to produce toxins by altering metabolism. (3) Toxins deter predators providing algae with growth advantages that can mask linked slightly deleterious mutational effects. (4) Reduced predation pressure enables blooms if algae have sufficient nutrients. (5) Lack of recombination results in the accumulation of slightly deleterious mutations as predicted by Muller’s ratchet. (6) If fast enough, deleterious mutation accumulation eventually leads to mutational meltdown of toxic blooming algae. (7) Non-mutator algal populations are not affected due to ongoing predation pressure. Our simulation models integrate ecological continuous-time dynamics of predator-prey systems with the population genetics of a simplified Muller’s ratchet model using Evolvix. Evolvix maps these models to Continuous-Time Markov Chain models that can be simulated deterministically or stochastically depending on the question. The current model is incomplete; we plan to investigate many parameter combinations to produce a more robust model ensemble with stable links to reasonable parameter estimates. However, our model already has several intriguing features that may allow for the eventual development of observation methods for monitoring ecosystem health. Our work also highlights a growing need to simulate integrated models combining ecological processes, multi-level population dynamics, and evolutionary genetics in a single computational run.

Integrating ecology and evolution to study hypothetical dynamics of algal blooms and Muller’s ratchet using Evolvix

Algal blooms have been the subject of considerable research as they occur over various spatial and temporal scales and can produce toxins that disrupt their ecosystem. Algal blooms are often governed by nutrient availability however other limitations exist. Algae are primary producers and therefore subject to predation which can keep populations below levels supported by nutrient availability. If algae as prey mutate to gain the ability to produce toxins deterring predators, they may increase their survival rates and form blooms unless other factors counter their effective increase in growth rate. Where might such mutations come from? Clearly, large populations of algae will repeatedly experience mutations knocking-out DNA repair genes, increasing mutation rates, and with them the chance of acquiring de-novo mutations producing a toxin against predators. We investigate this hypothetical scenario by simulation in the Evolvix modeling language. We modeled a sequence of steps that in principle can allow a typical asexual algal population to escape predation pressure and form a bloom with the help of mutators. We then turn our attention to the unavoidable side effect of generally increased mutation rates, many slightly deleterious mutations. If these accumulate at sufficient speed, their combined impact on fitness might place upper limits on the duration of algal blooms. These steps are required: (1) Random mutations result in the loss of DNA repair mechanisms. (2) Increased mutation rates make it more likely to acquire the ability to produce toxins by altering metabolism. (3) Toxins deter predators providing algae with growth advantages that can mask linked slightly deleterious mutational effects. (4) Reduced predation pressure enables blooms if algae have sufficient nutrients. (5) Lack of recombination results in the accumulation of slightly deleterious mutations as predicted by Muller’s ratchet. (6) If fast enough, deleterious mutation accumulation eventually leads to mutational meltdown of toxic blooming algae. (7) Non-mutator algal populations are not affected due to ongoing predation pressure. Our simulation models integrate ecological continuous-time dynamics of predator-prey systems with the population genetics of a simplified Muller’s ratchet model using Evolvix. Evolvix maps these models to Continuous-Time Markov Chain models that can be simulated deterministically or stochastically depending on the question. The current model is incomplete; we plan to investigate many parameter combinations to produce a more robust model ensemble with stable links to reasonable parameter estimates. However, our model already has several intriguing features that may allow for the eventual development of observation methods for monitoring ecosystem health. Our work also highlights a growing need to simulate integrated models combining ecological processes, multi-level population dynamics, and evolutionary genetics in a single computational run.

Functional Bias and Demographic History Obscure Patterns of Selection among Single-Copy Genes in a Fungal Species Complex

Many different evolutionary processes may be responsible for explaining natural variation within genomes, some of which include natural selection at the molecular level and changes in population size. Fungi are highly adaptable organisms, and their relatively small genomes and short generation times make them pliable for evolutionary genomic studies. However, adaptation in wild populations has been relatively less documented compared to experimental or clinical studies. Here, we analyzed DNA sequences from 502 putative single-copy orthologous genes in 63 samples that represent seven recently diverged North American Amanita (jacksonii-complex) lineages. For each gene and each species, we measured the genealogical sorting index (gsi) and infinite-site-based summary statistics, such as , and DTaj in coding and intron regions. MKT-based approaches and likelihood-ratio-test Kn/Ks models were used to measure natural selection in all coding sequences. Multi-locus (Extended) Bayesian Skyline Plots (eBSP) were used to model intraspecific demographic changes through time based on unlinked, putative neutral regions (introns). Most genes show evidence of long-term purifying selection, likely reflecting a functional bias implicit in single-copy genes. We find that two species have strongly negatively skewed Tajima’s D, while three other have a positive skew, corresponding well with patterns of demographic expansion and contraction. Standard MKT analyses resulted in a high incidence of near-zero α with a tendency towards negative values. In contrast, α estimates based on the distribution of fitness effects (DFE), which accounts for demographic effects and slightly deleterious mutations, suggest a higher proportion of sites fixed by positive selection. The difference was more notorious in species with expansion signatures or with historically low population sizes, evidencing the concealing effects of specific demographic histories. Finally, we attempt to mitigate Gene Ontology term overrepresentation, highlighting the potential adaptive or ecological roles of some genes under positive selection.

asymptoticMK: A web-based tool for the asymptotic McDonald–Kreitman test

ABSTRACTThe McDonald–Kreitman (MK) test is a widely used method for quantifying the role of positive selection in molecular evolution. One key shortcoming of this test lies in its sensitivity to the presence of slightly deleterious mutations, which can severely bias its estimates. An asymptotic version of the MK test was recently introduced that addresses this problem by evaluating polymorphism levels for different mutation frequencies separately, and then extrapolating a function fitted to that data. Here we present asymptoticMK, a web-based implementation of this asymptotic McDonald–Kreitman test. Our web service provides a simple R-based interface into which the user can upload the required data (polymorphism and divergence data for the genomic test region and a neutrally evolving reference region). The web service then analyzes the data and provides plots of the test results. This service is free to use, open-source, and available at http://benhaller.com/messerlab/asymptoticMK.html.