Population Genetics Inference for Longitudinally-Sampled Mutants Under Strong Selection

Longitudinal allele frequency data are becoming increasingly prevalent. Such samples permit statistical inference of the population genetics parameters that influence the fate of mutant variants. To infer these parameters by maximum likelihood, the mutant frequency is often assumed to evolve according to the Wright–Fisher model. For computational reasons, this discrete model is commonly approximated by a diffusion process that requires the assumption that the forces of natural selection and mutation are weak. This assumption is not always appropriate. For example, mutations that impart drug resistance in pathogens may evolve under strong selective pressure. Here, we present an alternative approximation to the mutant-frequency distribution that does not make any assumptions about the magnitude of selection or mutation and is much more computationally efficient than the standard diffusion approximation. Simulation studies are used to compare the performance of our method to that of the Wright–Fisher and Gaussian diffusion approximations. For large populations, our method is found to provide a much better approximation to the mutant-frequency distribution when selection is strong, while all three methods perform comparably when selection is weak. Importantly, maximum-likelihood estimates of the selection coefficient are severely attenuated when selection is strong under the two diffusion models, but not when our method is used. This is further demonstrated with an application to mutant-frequency data from an experimental study of bacteriophage evolution. We therefore recommend our method for estimating the selection coefficient when the effective population size is too large to utilize the discrete Wright–Fisher model.     

Identifying Signatures of Selection in Genetic Time Series

Both genetic drift and natural selection cause the frequencies of alleles in a population to vary over time. Discriminating between these two evolutionary forces, based on a time series of samples from a population, remains an outstanding problem with increasing relevance to modern data sets. Even in the idealized situation when the sampled locus is independent of all other loci, this problem is difficult to solve, especially when the size of the population from which the samples are drawn is unknown. A standard χ²-based likelihood-ratio test was previously proposed to address this problem. Here we show that the χ²-test of selection substantially underestimates the probability of type I error, leading to more false positives than indicated by its P-value, especially at stringent P-values. We introduce two methods to correct this bias. The empirical likelihood-ratio test (ELRT) rejects neutrality when the likelihood-ratio statistic falls in the tail of the empirical distribution obtained under the most likely neutral population size. The frequency increment test (FIT) rejects neutrality if the distribution of normalized allele-frequency increments exhibits a mean that deviates significantly from zero. We characterize the statistical power of these two tests for selection, and we apply them to three experimental data sets. We demonstrate that both ELRT and FIT have power to detect selection in practical parameter regimes, such as those encountered in microbial evolution experiments. Our analysis applies to a single diallelic locus, assumed independent of all other loci, which is most relevant to full-genome selection scans in sexual organisms, and also to evolution experiments in asexual organisms as long as clonal interference is weak. Different techniques will be required to detect selection in time series of cosegregating linked loci.     

Genetic Variability Under the Seedbank Coalescent

We analyze patterns of genetic variability of populations in the presence of a large seedbank with the help of a new coalescent structure called the seedbank coalescent. This ancestral process appears naturally as a scaling limit of the genealogy of large populations that sustain seedbanks, if the seedbank size and individual dormancy times are of the same order as those of the active population. Mutations appear as Poisson processes on the active lineages and potentially at reduced rate also on the dormant lineages. The presence of “dormant” lineages leads to qualitatively altered times to the most recent common ancestor and nonclassical patterns of genetic diversity. To illustrate this we provide a Wright–Fisher model with a seedbank component and mutation, motivated from recent models of microbial dormancy, whose genealogy can be described by the seedbank coalescent. Based on our coalescent model, we derive recursions for the expectation and variance of the time to most recent common ancestor, number of segregating sites, pairwise differences, and singletons. Estimates (obtained by simulations) of the distributions of commonly employed distance statistics, in the presence and absence of a seedbank, are compared. The effect of a seedbank on the expected site-frequency spectrum is also investigated using simulations. Our results indicate that the presence of a large seedbank considerably alters the distribution of some distance statistics, as well as the site-frequency spectrum. Thus, one should be able to detect from genetic data the presence of a large seedbank in natural populations.     

Population growth enhances the mean fixation time of neutral mutations and the persistence of neutral variation

A fundamental result of population genetics states that a new mutation, at an unlinked neutral locus in a randomly mating diploid population, has a mean time of fixation of ～4N(e) generations, where N(e) is the effective population size. This result is based on an assumption of fixed population size, which does not universally hold in natural populations. Here, we analyze such neutral fixations in populations of changing size within the framework of the diffusion approximation. General expressions are derived for the mean and variance of the fixation time in changing populations. Some explicit results are given for two cases: (i) the effective population size undergoes a sudden change, representing a sudden population expansion or a sudden bottleneck; (ii) the effective population changes linearly for a limited period of time and then remains constant. Additionally, a lower bound for the mean time of fixation is obtained for an effective population size that increases with time, and this is applied to exponentially growing populations. The results obtained in this work show, among other things, that for populations that increase in size, the mean time of fixation can be enhanced, sometimes substantially so, over 4N(e,0) generations, where N(e,0) is the effective population size at the time the mutation arises. Such an enhancement is associated with (i) an increased probability of neutral polymorphism in a population and (ii) an enhanced persistence of high-frequency neutral variation, which is the variation most likely to be observed.     

Low temperature delays timing and enhances the cost of nitrogen fixation in the unicellular cyanobacterium Cyanothece

Marine nitrogen-fixing cyanobacteria are largely confined to the tropical and subtropical ocean. It has been argued that their global biogeographical distribution reflects the physiologically feasible temperature range at which they can perform nitrogen fixation. In this study we refine this line of argumentation for the globally important group of unicellular diazotrophic cyanobacteria, and pose the following two hypotheses: (i) nitrogen fixation is limited by nitrogenase activity at low temperature and by oxygen diffusion at high temperature, which is manifested by a shift from strong to weak temperature dependence of nitrogenase activity, and (ii) high respiration rates are required to maintain very low levels of oxygen for nitrogenase, which results in enhanced respiratory cost per molecule of fixed nitrogen at low temperature. We tested these hypotheses in laboratory experiments with the unicellular cyanobacterium Cyanothece sp. {"type":"entrez-nucleotide","attrs":{"text":"BG043511","term_id":"12489990","term_text":"BG043511"}}BG043511. In line with the first hypothesis, the specific growth rate increased strongly with temperature from 18 to 30 °C, but leveled off at higher temperature under nitrogen-fixing conditions. As predicted by the second hypothesis, the respiratory cost of nitrogen fixation and also the cellular C:N ratio rose sharply at temperatures below 21 °C. In addition, we found that low temperature caused a strong delay in the onset of the nocturnal nitrogenase activity, which shortened the remaining nighttime available for nitrogen fixation. Together, these results point at a lower temperature limit for unicellular nitrogen-fixing cyanobacteria, which offers an explanation for their (sub)tropical distribution and suggests expansion of their biogeographical range by global warming.     

Climate‐induced habitat suitability changes intensify fishing impacts on the life history of large yellow croaker (Larimichthys crocea)

Intense fishing pressure and climate change are major threats to the fish population and coastal fisheries. Larimichthys crocea (large yellow croaker) is a long‐lived fish, which performs seasonal migrations from its spawning and nursery grounds along the coast of the East China Sea (ECS) to overwintering grounds offshore. This study used length‐based analysis and habitat suitability index (HSI) model to evaluate the current life‐history parameters and overwintering habitat suitability of L. crocea, respectively. We compared recent (2019) and historical (1971–1982) life‐history parameters and overwintering HSI to analyze the fishing pressure and climate change effects on the overall population and overwintering phase of L. crocea. The length‐based analysis indicated serious overfishing of L. crocea, characterized by reduced catch, size truncation, constrained distribution, and advanced maturation causing a recruitment bottleneck. The overwintering HSI modeling results indicated that climate change has led to decreased sea surface temperature during L. crocea overwintering phase over the last half‐century, which in turn led to area decrease and an offshore‐oriented shifting of optimal overwintering habitat of L. crocea. The fishing‐caused size truncation may have constrained the migratory ability, and distribution of L. crocea subsequently led to the mismatch of the optimal overwintering habitat against climate change background, namely habitat bottleneck. Hence, while heavy fishing was the major cause of L. crocea collapse, climate‐induced overwintering habitat suitability may have intensified the fishery collapse of L. crocea population. It is important for management to consider both overfishing and climate change issues when developing stock enhancement activities and policy regulations, particularly for migratory long‐lived fish that share a similar life history to L. crocea. Combined with China''s current restocking and stock enhancement initiatives, we propose recommendations for the future restocking of L. crocea in China.