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Urbanization is one of the most significant contributors to the Anthropocene, and urban evolutionary ecology has become an important field of research. While it is commonly assumed that cities impose new and stronger selection, the contradictory assertion that selection may be relaxed in cities is also frequently mentioned, and overall, our understanding of the effects of urbanization on natural selection is incomplete.In this review, we first conduct a literature search to find evidence for patterns of natural selection on phenotypic traits including morphology, physiology, behaviour and life history, in urban and non‐urban populations of animals and plants. This search reveals that coefficients of natural selection in the context of urbanization are scarce (n = 8 studies providing selection gradients/differentials that include a total of n = 200 coefficients) and a lack of standardized methods hinders quantitative comparisons across studies (e.g. with meta‐analysis). These studies, however, provide interesting insight on the agents shaping natural selection in cities and improve our mechanistic understanding of selection processes at different spatial scales.We then perform a second literature search to review genomic studies assessing selection intensity in cities, on the genome of non‐human natural populations. While this search returns 383 articles, only 34 of these truly investigate footprints of selection associated with urbanization, and only one study provides urban genetic selection coefficients. Here again, we find highly heterogeneous approaches, yet some studies provide strong evidence of genomic footprints of urban adaptation.In neither the phenotypic nor genomic literature review were we able to quantitatively assess natural selection across urban versus non‐urban habitats. Thus, we propose a roadmap of how future studies should provide standardized metrics to facilitate mega‐ or meta‐analyses and explore generalized effects of urbanization on selection. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Recent positive selection can result in an excess of long identity-by-descent (IBD) haplotype segments overlapping a locus. The statistical methods that we propose here address three major objectives in studying selective sweeps: scanning for regions of interest, identifying possible sweeping alleles, and estimating a selection coefficient s. First, we implement a selection scan to locate regions with excess IBD rates. Second, we estimate the allele frequency and location of an unknown sweeping allele by aggregating over variants that are more abundant in an inferred outgroup with excess IBD rate versus the rest of the sample. Third, we propose an estimator for the selection coefficient and quantify uncertainty using the parametric bootstrap. Comparing against state-of-the-art methods in extensive simulations, we show that our methods are more precise at estimating s when s ≥ 0.015. We also show that our 95% confidence intervals contain s in nearly 95% of our simulations. We apply these methods to study positive selection in European ancestry samples from the Trans-Omics for Precision Medicine project. We analyze eight loci where IBD rates are more than four standard deviations above the genome-wide median, including LCT where the maximum IBD rate is 35 standard deviations above the genome-wide median. Overall, we present robust and accurate approaches to study recent adaptive evolution without knowing the identity of the causal allele or using time series data. Around locations of strong and recent selective sweeps, long identity-by-descent segments should be unusually abundant. Based on this expectation, we develop methods to detect putatively selected loci, infer frequencies and locations of unknown sweeping alleles, and estimate selection coefficients with valid confidence intervals supported by extensive simulations. [ABSTRACT FROM AUTHOR]

An understanding of biological fitness is central to theory and practice in ecology and evolution, yet fitness remains an elusive concept to define and is challenging to measure accurately. Fitness reflects an individual's ability to pass its alleles on to subsequent generations. Researchers often quantify proxies for fitness, such as survival, growth, or reproductive success. However, it can be difficult to determine lifetime fitness, especially for species with long life spans. The abiotic and biotic environment strongly affects the expression of fitness, which means that fitness components can vary through both space and time. This spatial and temporal heterogeneity results in the impressive range of adaptations that we see in nature. Here, we review definitions of fitness and approaches to measuring fitness at the level of genes, individuals, genotypes, and populations and highlight that fitness is a key concept linking ecological and evolutionary thought. [ABSTRACT FROM AUTHOR]

In this article, we present a method for designing, executing, and analyzing data from a microbial competition experiment. We use fluorescent reporters to label different competing strains and resolve individual growth curves using a fluorescent spectrophotometer. Our comprehensive data analysis pipeline integrates multiple experiments to simultaneously infer sources of variation, extract selection coefficients, and estimate the genetic contributions to fitness for various synthetic genetic cassettes (SGCs). To demonstrate the method, we employ a synthetic biological system based on Escherichia coli. Strains carry 1 of 10 different plasmids and one of three genomically integrated fluorescent markers. All strains are co-cultured to obtain real-time measurements of optical density (total population density) and fluorescence (sub-population densities). We identify challenges in calibrating between fluorescence and density and of fluorescent proteins maturing at different rates. To resolve these issues, we compare two methods of fluorescence calibration and correct for maturation by measuring in vivo maturation times. We provide evidence of genetic interactions occurring between our SGCs and further show how to use our statistical model to test some hypotheses about microbial growth and the costs of protein expression. [ABSTRACT FROM AUTHOR]

Summary: Inbreeding depression plays a fundamental role in evolution. To help detect and characterize the loci that underlie inbreeding depression, we used bud pollination and salt treatments to circumvent self‐incompatibility (SI) in plants from populations of Leavenworthia alabamica and produced families of progeny that were then genotyped at genetically mapped single‐nucleotide polymorphism (SNP) loci.Using Bayesian inference, the segregation patterns for each SNP were used to explore support for different dominance and selection coefficients at linked viability loci in different genomic regions.There was support for several partially recessive viability loci in one of the populations, and one such locus mapped to the genomic region of the novel SI locus in L. alabamica.These results are consistent with earlier findings that showed purging of inbreeding depression for germination rate in L. alabamica. They are also consistent with expectations from evolutionary genetic theory that recessive, deleterious alleles linked to loci under balancing selection can be sheltered from selection. [ABSTRACT FROM AUTHOR]

Abstract Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals’ haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al. (Advances in bioinformatics and computational biology: 11th Brazilian symposium on bioinformatics, BSB 2018, Niterói, Brazil, October 30 - November 1, 2018, Proceedings, 2018. https://doi.org/10.1007/978-3-030-01722-4_3 ) suggested the maximal perfect haplotype block as a very simple combinatorial pattern, forming the basis of a new method to perform rapid genome-wide selection scans. The algorithm they presented for identifying these blocks, however, had a worst-case running time quadratic in the genome length. It was posed as an open problem whether an optimal, linear-time algorithm exists. In this paper we give two algorithms that achieve this time bound, one conceptually very simple one using suffix trees and a second one using the positional Burrows–Wheeler Transform, that is very efficient also in practice.

Abstract By changing the genetic background available for selection at subsequent life stages, stage‐specific selection can define adaptive potential across the life cycle. We propose and evaluate here a neutrality test and a Bayesian method to infer stage‐specific viability selection coefficients using sequential random genotypic samples drawn from a longitudinal cohort mortality study, within a generation. The approach is suitable for investigating selective mortality in large natural or experimental cohorts of any organism in which individual tagging and tracking are unfeasible. Numerical simulation results indicate that the method can discriminate loci under strong viability selection, and provided samples are large, yield accurate estimates of the corresponding selection coefficients. Genotypic frequency changes are largely driven by sampling noise under weak selection, however, compromising inference in that case. We apply the proposed methods to analyze viability selection operating at early recruitment stages in a natural maritime pine (Pinus pinaster Ait.) population. We measured temporal genotypic frequency changes at 384 candidate‐gene SNP loci among seedlings sampled from the time of emergence in autumn until the summer of the following year, a period with high elimination rates. We detected five loci undergoing allele frequency changes larger than expected from stochastic mortality and sampling, with putative functions that could influence survival at early seedling stages. Our results illustrate how new statistical and sampling schemes can be used to conduct genomic scans of contemporary selection on specific life stages.

The ability to obtain genome-wide sequences of very large numbers of individuals from natural populations raises questions about optimal sampling designs and the limits to extracting information on key population-genetic parameters from temporal-survey data. Methods are introduced for evaluating whether observed temporal fluctuations in allele frequencies are consistent with the hypothesis of random genetic drift, and expressions for the expected sampling variances for the relevant statistics are given in terms of sample sizes and numbers. Estimation methods and aspects of statistical reliability are also presented for the mean and temporal variance of selection coefficients. For nucleotide sites that pass the test of neutrality, the current effective population size can be estimated by a method of moments, and expressions for its sampling variance provide insight into the degree to which such methodology can yield meaningful results under alternative sampling schemes. Finally, some caveats are raised regarding the use of the temporal covariance of allele-frequency change to infer selection. Taken together, these results provide a statistical view of the limits to population-genetic inference in even the simplest case of a closed population. [ABSTRACT FROM AUTHOR]

Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals' haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al. (Advances in bioinformatics and computational biology: 11th Brazilian symposium on bioinformatics, BSB 2018, Niterói, Brazil, October 30 - November 1, 2018, Proceedings, 2018. 10.1007/978-3-030-01722-4_3) suggested the maximal perfect haplotype block as a very simple combinatorial pattern, forming the basis of a new method to perform rapid genome-wide selection scans. The algorithm they presented for identifying these blocks, however, had a worst-case running time quadratic in the genome length. It was posed as an open problem whether an optimal, linear-time algorithm exists. In this paper we give two algorithms that achieve this time bound, one conceptually very simple one using suffix trees and a second one using the positional Burrows–Wheeler Transform, that is very efficient also in practice. [ABSTRACT FROM AUTHOR]

Since the Origin of Species , it has been known that evolution depends on what Darwin called the "strong principle of inheritance." Highly accurate replication of cellular phenotype is a universal phenomenon in all of life since LUCA and is often taken for granted as a constant in evolutionary theory. It is not known how self-replication arose during the origin of life. In this report I use the simple mathematics of evolutionary theory to investigate the dynamics of self-replication accuracy and allelic selection. Results indicate that the degree of self-replication accuracy must be greater than a threshold related to the selection coefficients of the alleles in a population in order for evolution to occur. Accurate replication of cellular phenotype and of the molecules involved in genotype/phenotype linkage is necessary for the origin of evolution and may be considered the fundamental principle of life. [ABSTRACT FROM AUTHOR]

Within‐individual trait variation – otherwise known as sub‐individual variation – is an important component of phenotypic variation, with both a genetic and epigenetic basis. We explore its adaptive value and the effects of ontogeny and the environment on sub‐individual variability.We conducted a field study to analyse the effects of tree age, soil pH, soil water content and soil nutrients on sub‐individual variability in fruit size of hawthorn (Crataegus monogyna) in three sites in northwest Spain. Additionally, we examined how bird‐mediated selection influences average and sub‐individual variation in fruit size.Results show that average and sub‐individual variations in fruit size were related to fitness affecting seed dispersal. Older trees produced larger fruits, but tree age did not affect sub‐individual variation in fruit size. Abiotic environmental factors differently affected sub‐individual variation and average fruit size. Seed‐dispersing birds exerted correlated selection on average and variation in fruit size, favouring trees with larger and less variable fruit size at one site.Our work suggests that the fruit size variation within individual trees, the sub‐individual variation, is modified by abiotic environmental factors and, additionally, is an adaptive trait that responds to natural selection. [ABSTRACT FROM AUTHOR]

Evolutionary biologists commonly seek explanations for how selection drives the emergence of novel traits. Although trait loss is also predicted to occur frequently, few contemporary examples exist. In Hawaii, the Pacific field cricket (Teleogryllus oceanicus) is undergoing adaptive sexual signal loss due to natural selection imposed by eavesdropping parasitoids. Mutant male crickets ("flatwings") cannot sing. We measured the intensity of sexual selection on wing phenotype in a wild population. First, we surveyed the relative abundance of flatwings and "normal‐wings" (nonmutants) on Oahu. Then, we bred wild‐mated females' offspring to determine both female genotype with respect to the flatwing mutation and the proportion of flatwing males that sired their offspring. We found evidence of strong sexual selection favoring the production of song: females were predominantly homozygous normal‐wing, their offspring were sired disproportionately by singing males, and at the population level, flatwing males became less common following a single sexual selection event. We report a selection coefficient describing the total (pre‐ and postcopulatory) sexual selection favoring normal‐wing males in nature. Given the maintenance of the flatwing phenotype in Hawaii in recent years, this substantial sexual selection additionally suggests an approximate strength of opposing natural selection that favors silent males. [ABSTRACT FROM AUTHOR]

By changing the genetic background available for selection at subsequent life stages, stage‐specific selection can define adaptive potential across the life cycle. We propose and evaluate here a neutrality test and a Bayesian method to infer stage‐specific viability selection coefficients using sequential random genotypic samples drawn from a longitudinal cohort mortality study, within a generation. The approach is suitable for investigating selective mortality in large natural or experimental cohorts of any organism in which individual tagging and tracking are unfeasible. Numerical simulation results indicate that the method can discriminate loci under strong viability selection, and provided samples are large, yield accurate estimates of the corresponding selection coefficients. Genotypic frequency changes are largely driven by sampling noise under weak selection, however, compromising inference in that case. We apply the proposed methods to analyze viability selection operating at early recruitment stages in a natural maritime pine (Pinus pinaster Ait.) population. We measured temporal genotypic frequency changes at 384 candidate‐gene SNP loci among seedlings sampled from the time of emergence in autumn until the summer of the following year, a period with high elimination rates. We detected five loci undergoing allele frequency changes larger than expected from stochastic mortality and sampling, with putative functions that could influence survival at early seedling stages. Our results illustrate how new statistical and sampling schemes can be used to conduct genomic scans of contemporary selection on specific life stages. [ABSTRACT FROM AUTHOR]

Background and objectives: The rate of evolution of drug resistance depends on the fitness of resistant pathogens. The fitness of resistant pathogens is reduced by competition with sensitive pathogens in untreated hosts and so enhanced by competitive release in drug-treated hosts. We set out to estimate the magnitude of those effects on a variety of fitness measures, hypothesizing that competitive suppression and competitive release would have larger impacts when resistance was rarer to begin with. Methodology: We infected mice with varying densities of drug-resistant Plasmodium chabaudi malaria parasites in a fixed density of drug-sensitive parasites and followed infection dynamics using strain-specific quantitative PCR. Results: Competition with susceptible parasites reduced the absolute fitness of resistant parasites by 50-100%. Drug treatment increased the absolute fitness from 2- to>10 000-fold. The ecological context and choice of fitness measure was responsible for the wide variation in those estimates. Initial population growth rates poorly predicted parasite abundance and transmission probabilities. Conclusions and implications: (i) The sensitivity of estimates of pathogen fitness to ecological context and choice of fitness measure make it difficult to derive field-relevant estimates of the fitness costs and benefits of resistance from experimental settings. (ii) Competitive suppression can be a key force preventing resistance from emerging when it is rare, as it is when it first arises. (iii) Drug treatment profoundly affects the fitness of resistance. Resistance evolution could be slowed by developing drug use policies that consider in-host competition. [ABSTRACT FROM AUTHOR]

Individuals often interact more closely with some members of the population (e.g., offspring, siblings, or group members) than they do with other individuals. This structuring of interactions can lead to multilevel natural selection, where traits expressed at the group-level influence fitness alongside individual-level traits. Such multilevel selection can alter evolutionary trajectories, yet is rarely quantified in the wild, especially for species that do not interact in clearly demarcated groups. We quantified multilevel natural selection on two traits, postnatal growth rate and birth date, in a population of North American red squirrels ( Tamiasciurus hudsonicus). The strongest level of selection was typically within-acoustic social neighborhoods (within 130 m of the nest), where growing faster and being born earlier than nearby litters was key, while selection on growth rate was also apparent both within-litters and within-study areas. Higher population densities increased the strength of selection for earlier breeding, but did not influence selection on growth rates. Females experienced especially strong selection on growth rate at the within-litter level, possibly linked to the biased bequeathal of the maternal territory to daughters. Our results demonstrate the importance of considering multilevel and sex-specific selection in wild species, including those that are territorial and sexually monomorphic. [ABSTRACT FROM AUTHOR]

There are three different age-related changes in stand respiration (woody + foliage respiration) in an even-aged pure forest stand after canopy closure: (A) monotonous increase (Kira and Shidei, 1967; Odum, 1969), (B) constancy (Oohata and Shidei, 1974; Ogawa et al., 2010), and (C) monotonous decrease (Ryan et al., 1997; Drake et al., 2011). These contrasting views were based on observational data rather than on theoretical arguments. The present study was performed to model age-related changes in stand respiration to elucidate the mechanism of stand respiration dynamics after canopy closure in compliance with three concepts: (i) the self-thinning law, (ii) power scaling between mean individual annual respiration and mean individual mass, and (iii) the logistic function of stand density changes. Simulations showed that although the three hypotheses were tenable theoretically, that proposed by Kira and Shidei is a mathematically special case. Considering these modeling results, age-related stand respiration changes in plantations of hinoki ( Chamaecyparis obtusa ) (Ogawa et al., 1985) can be regarded as decreasing as well as constant after canopy closure. The present modeling revealed that there exists possibility of increasing stand respiration in Kira and Shidei’s hypothesis from the theoretical viewpoints, although no observed data support their hypothetical trend. However, from both of the empirical and theoretical viewpoints, we understood that possibilities of stand respiration constancy and decrease in forest stands were regarded to be reasonable after the canopy closure. [ABSTRACT FROM AUTHOR]

The selection coefficient, s, quantifies the strength of selection acting on a genetic variant. Despite this parameter's central importance to population genetic models, until recently we have known relatively little about the value of s in natural populations. With the development of molecular genetic techniques in the late 20th century and the sequencing technologies that followed, biologists are now able to identify genetic variants and directly relate them to organismal fitness. We reviewed the literature for published estimates of natural selection acting at the genetic level and found over 3000 estimates of selection coefficients from 79 studies. Selection coefficients were roughly exponentially distributed, suggesting that the impact of selection at the genetic level is generally weak but can occasionally be quite strong. We used both nonparametric statistics and formal random-effects meta-analysis to determine how selection varies across biological and methodological categories. Selection was stronger when measured over shorter timescales, with the mean magnitude of s greatest for studies that measured selection within a single generation. Our analyses found conflicting trends when considering how selection varies with the genetic scale (e.g., SNPs or haplotypes) at which it is measured, suggesting a need for further research. Besides these quantitative conclusions, we highlight key issues in the calculation, interpretation, and reporting of selection coefficients and provide recommendations for future research. [ABSTRACT FROM AUTHOR]