Modeling the evolution of recombination plasticity: A prospective review.

Meiotic recombination is one of the main sources of genetic variation, a fundamental factor in the evolutionary adaptation of sexual eukaryotes. Yet, the role of variation in recombination rate and other recombination features remains underexplored. In this review, we focus on the sensitivity of recombination rates to different extrinsic and intrinsic factors. We briefly present the empirical evidence for recombination plasticity in response to environmental perturbations and/or poor genetic background and discuss theoretical models developed to explain how such plasticity could have evolved and how it can affect important population characteristics. We highlight a gap between the evidence, which comes mostly from experiments with diploids, and theory, which typically assumes haploid selection. Finally, we formulate open questions whose solving would help to outline conditions favoring recombination plasticity. This will contribute to answering the long-standing question of why sexual recombination exists despite its costs, since plastic recombination may be evolutionary advantageous even in selection regimes rejecting any non-zero constant recombination.

Proactive response preparation contributes to contingency learning: novel evidence from force-sensitive keyboards.

Contingency learning can involve learning that the identity of one stimulus in a sequence predicts the identity of the next stimulus. It remains unclear, however, whether such learning speeds responses to the next stimulus only by reducing the threshold for triggering the expected response after stimulus onset or also by preparing the expected response before stimulus onset. To distinguish between these competing accounts, we manipulated the probabilities with which each of two prime arrows (Left and Right) were followed by each of two probe arrows (Up and Down) in a prime-probe task while using force-sensitive keyboards to monitor sub-threshold finger force. Consistent with the response preparation account, two experiments revealed greater force just before probe onset on the response key corresponding to the direction in which the probe was more (versus less) likely to point (e.g., Up vs. Down). Furthermore, mirroring sequential contingency effects in behavior, this pre-probe force effect vanished after a single low-probability trial. These findings favor the response preparation account over the threshold only account. They also suggest the possibility that contingency learning in our tasks indexes trial-by-trial expectations regarding the utility of the prime for predicting the upcoming probe.

Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes.

Bacterial genomes exhibit widespread horizontal gene transfer, resulting in highly variable genome content that complicates the inference of genetic interactions. In this study, we develop a method for detecting coevolving genes from large datasets of bacterial genomes based on pairwise comparisons of closely related individuals, analogous to a pedigree study in eukaryotic populations. We apply our method to pairs of genes from the Staphylococcus aureus accessory genome of over 75,000 annotated gene families using a database of over 40,000 whole genomes. We find many pairs of genes that appear to be gained or lost in a coordinated manner, as well as pairs where the gain of one gene is associated with the loss of the other. These pairs form networks of rapidly coevolving genes, primarily consisting of genes involved in virulence, mechanisms of horizontal gene transfer, and antibiotic resistance, particularly the SCCmec complex. While we focus on gene gain and loss, our method can also detect genes that tend to acquire substitutions in tandem, or genotype-phenotype or phenotype-phenotype coevolution. Finally, we present the R package DeCoTUR that allows for the computation of our method.

Fifty shades of greenbeard: robust evolution of altruism based on similarity of complex phenotypes.

We study the evolution of altruistic behaviour under a model where individuals choose to cooperate by comparing a set of continuous phenotype tags. Individuals play a donation game and only donate to other individuals that are sufficiently similar to themselves in a multidimensional phenotype space. We find the generic maintenance of robust altruism when phenotypes are multidimensional. Selection for altruism is driven by the coevolution of individual strategy and phenotype; altruism levels shape the distribution of individuals in phenotype space. Low donation rates induce a phenotype distribution that renders the population vulnerable to the invasion of altruists, whereas high donation rates prime a population for cheater invasion, resulting in cyclic dynamics that maintain substantial levels of altruism. Altruism is therefore robust to invasion by cheaters in the long term in this model. Furthermore, the shape of the phenotype distribution in high phenotypic dimension allows altruists to better resist the invasion by cheaters, and as a result the amount of donation increases with increasing phenotype dimension. We also generalize previous results in the regime of weak selection to two competing strategies in continuous phenotype space, and show that success under weak selection is crucial to success under strong selection in our model. Our results support the viability of a simple similarity-based mechanism for altruism in a well-mixed population.

Inferring Transmission Bottleneck Size from Viral Sequence Data Using a Novel Haplotype Reconstruction Method.

The transmission bottleneck is defined as the number of viral particles that transmit from one host to establish an infection in another. Genome sequence data have been used to evaluate the size of the transmission bottleneck between humans infected with the influenza virus; however, the methods used to make these estimates have some limitations. Specifically, viral allele frequencies, which form the basis of many calculations, may not fully capture a process which involves the transmission of entire viral genomes. Here, we set out a novel approach for inferring viral transmission bottlenecks; our method combines an algorithm for haplotype reconstruction with maximum likelihood methods for bottleneck inference. This approach allows for rapid calculation and performs well when applied to data from simulated transmission events; errors in the haplotype reconstruction step did not adversely affect inferences of the population bottleneck. Applied to data from a previous household transmission study of influenza A infection, we confirm the result that the majority of transmission events involve a small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a tight population bottleneck, the bottleneck is not so tight as to universally prevent the transmission of within-host viral diversity.IMPORTANCE Viral populations undergo a repeated cycle of within-host growth followed by transmission. Viral evolution is affected by each stage of this cycle. The number of viral particles transmitted from one host to another, known as the transmission bottleneck, is an important factor in determining how the evolutionary dynamics of the population play out, restricting the extent to which the evolved diversity of the population can be passed from one host to another. Previous study of viral sequence data has suggested that the transmission bottleneck size for influenza A transmission between human hosts is small. Reevaluating these data using a novel and improved method, we largely confirm this result, albeit that we infer a slightly higher bottleneck size in some cases, of between 1 and 13 virions. While a tight bottleneck operates in human influenza transmission, it is not extreme in nature; some diversity can be meaningfully retained between hosts.

Fitness dependence preserves selection for recombination across diverse mixed mating strategies.

Meiotic recombination and the factors affecting its rate and fate in nature have inspired many studies in theoretical evolutionary biology. Classical theoretical models have inferred that recombination can be favored under a rather restricted parameter range. Thus, the ubiquity of recombination in nature remains an open question. However, these models assumed constant recombination with an equal rate across all individuals within the population, whereas empirical evidence suggests that recombination may display certain sensitivity to ecological stressors and/or genotype fitness. Models assuming condition-dependent recombination show that such a strategy can often be favored over constant recombination. Moreover, in our recent model with panmictic populations subjected to purifying selection, fitness-dependent recombination was quite often favored even when any constant recombination was rejected. By using numerical modeling, we test whether such a 'recombination-rescuing potential' of fitness dependence holds also beyond panmixia, given the recognized effect of mating strategy on the evolution of recombination. We show that deviations from panmixia generally increase the recombination-rescuing potential of fitness dependence, with the strongest effect under intermediate selfing or high clonality. We find that under partial clonality, the evolutionary advantage of fitness-dependent recombination is determined mostly by selection against heterozygotes and additive-by-additive epistasis, while under partial selfing, additive-by-dominance epistasis is also a driver.

Network segregation varies with neural distinctiveness in sensorimotor cortex.

Normal aging is associated with declines in sensorimotor function. Previous studies have linked age-related behavioral declines to decreases in neural differentiation (i.e., dedifferentiation), including decreases in the distinctiveness of neural activation patterns and in the segregation of large-scale neural networks at rest. However, no studies to date have explored the relationship between these two neural measures and whether they explain the same aspects of behavior. To investigate these issues, we collected a battery of sensorimotor behavioral measures in older and younger adults and estimated (a) the distinctiveness of neural representations in sensorimotor cortex and (b) sensorimotor network segregation in the same participants. Consistent with prior findings, sensorimotor representations were less distinct and sensorimotor resting state networks were less segregated in older compared to younger adults. We also found that participants with the most distinct sensorimotor representations exhibited the most segregated sensorimotor networks. However, only sensorimotor network segregation was associated with individual differences in sensorimotor performance, particularly in older adults. These novel findings link network segregation to neural distinctiveness, but also suggest that network segregation may play a larger role in maintaining sensorimotor performance with age.

Why Are CD8 T Cell Epitopes of Human Influenza A Virus Conserved?

The high degree of conservation of CD8 T cell epitopes of influenza A virus (IAV) may allow for the development of T cell-inducing vaccines that provide protection across different strains and subtypes. This conservation is not fully explained by functional constraint, since an additional mutation(s) can compensate for the replicative fitness loss of IAV escape variants. Here, we propose three additional mechanisms that contribute to the conservation of CD8 T cell epitopes of IAV. First, influenza-specific CD8 T cells may protect predominantly against severe pathology rather than infection and may have only a modest effect on transmission. Second, polymorphism of the human major histocompatibility complex class I (MHC-I) gene restricts the advantage of an escape variant to only a small fraction of the human population who carry the relevant MHC-I alleles. Finally, infection with CD8 T cell escape variants may result in a compensatory increase in the responses to other epitopes of IAV. We use a combination of population genetics and epidemiological models to examine how the interplay between these mechanisms affects the rate of invasion of IAV escape variants. We conclude that for a wide range of biologically reasonable parameters, the invasion of an escape variant virus will be slow, with a timescale of a decade or more. The results suggest T cell-inducing vaccines do not engender the rapid evolution of IAV. Finally, we identify key parameters whose measurement will allow for more accurate quantification of the long-term effectiveness and impact of universal T cell-inducing influenza vaccines.IMPORTANCE Universal influenza vaccines against the conserved epitopes of influenza A virus have been proposed to minimize the burden of seasonal outbreaks and prepare for the pandemics. However, it is not clear how rapidly T cell-inducing vaccines will select for viruses that escape these T cell responses. Our mathematical models explore the factors that contribute to the conservation of CD8 T cell epitopes and how rapidly the virus will evolve in response to T cell-inducing vaccines. We identify the key biological parameters to be measured and questions that need to be addressed in future studies.

Neural distinctiveness declines with age in auditory cortex and is associated with auditory GABA levels.

Neural activation patterns in the ventral visual cortex in response to different categories of visual stimuli (e.g., faces vs. houses) are less selective, or distinctive, in older adults than in younger adults, a phenomenon known as age-related neural dedifferentiation. In this study, we investigated whether neural dedifferentiation extends to the auditory cortex. Inspired by previous animal work, we also investigated whether individual differences in GABA are associated with individual differences in neural distinctiveness in humans. 20 healthy young adults (ages 18-29) and 23 healthy older adults (over 65) completed a functional magnetic resonance imaging (fMRI) scan, during which neural activity was estimated while they listened to music and foreign speech. GABA levels in the auditory, ventrovisual and sensorimotor cortex were estimated in the same individuals in a separate magnetic resonance spectroscopy (MRS) scan. Relative to the younger adults, the older adults exhibited both (1) less distinct activation patterns for music vs. speech stimuli and (2) lower GABA levels in the auditory cortex. Also, individual differences in auditory GABA levels (but not ventrovisual or sensorimotor GABA levels) were associated with individual differences in neural distinctiveness in the auditory cortex in the older adults. These results demonstrate that age-related neural dedifferentiation extends to the auditory cortex and suggest that declining GABA levels may play a role in neural dedifferentiation in older adults.

Sensorimotor network segregation declines with age and is linked to GABA and to sensorimotor performance.

Aging is typically associated with declines in sensorimotor performance. Previous studies have linked some age-related behavioral declines to reductions in network segregation. For example, compared to young adults, older adults typically exhibit weaker functional connectivity within the same functional network but stronger functional connectivity between different networks. Based on previous animal studies, we hypothesized that such reductions of network segregation are linked to age-related reductions in the brain's major inhibitory transmitter, gamma aminobutyric acid (GABA). To investigate this hypothesis, we conducted graph theoretical analyses of resting state functional MRI data to measure sensorimotor network segregation in both young and old adults. We also used magnetic resonance spectroscopy to measure GABA levels in the sensorimotor cortex and collected a battery of sensorimotor behavioral measures. We report four main findings. First, relative to young adults, old adults exhibit both less segregated sensorimotor brain networks and reduced sensorimotor GABA levels. Second, less segregated networks are associated with lower GABA levels. Third, less segregated networks and lower GABA levels are associated with worse sensorimotor performance. Fourth, network segregation mediates the relationship between GABA and performance. These findings link age-related differences in network segregation to age-related differences in GABA levels and sensorimotor performance. More broadly, they suggest a neurochemical substrate of age-related dedifferentiation at the level of large-scale brain networks.

The expected time to cross extended fitness plateaus.

For a population to acquire a complex adaptation requiring multiple individually neutral mutations, it must cross a plateau in the fitness landscape. We consider plateaus involving three mutations, and show that large populations can cross them rapidly via lineages that acquire multiple mutations while remaining at low frequency, much faster than the ∝µ3 rate for simultaneous triple mutations. Plateau-crossing is fastest for very large populations. At intermediate population sizes, recombination can greatly accelerate adaptation by combining independent mutant lineages to form triple-mutants. For more frequent recombination, such that the population is kept near linkage equilibrium, we extend our analysis to find simple expressions for the expected time to cross plateaus of arbitrary width.

Michigan Neural Distinctiveness (MiND) study protocol: investigating the scope, causes, and consequences of age-related neural dedifferentiation.

BACKGROUND: Aging is often associated with behavioral impairments, but some people age more gracefully than others. Why? One factor that may play a role is individual differences in the distinctiveness of neural representations. Previous research has found that neural activation patterns in visual cortex in response to different visual stimuli are often more similar (i.e., less distinctive) in older vs. young participants, a phenomenon referred to as age-related neural dedifferentiation. Furthermore, older people whose neural representations are less distinctive tend to perform worse on a wide range of behavioral tasks. The Michigan Neural Distinctiveness (MiND) project aims to investigate the scope of neural dedifferentiation (e.g., does it also occur in auditory, motor, and somatosensory cortex?), one potential cause (age-related reductions in the inhibitory neurotransmitter gamma-aminobutyric acid (GABA)), and the behavioral consequences of neural dedifferentiation. This protocol paper describes the study rationale and methods being used in complete detail, but not the results (data collection is currently underway). METHODS: The MiND project consists of two studies: the main study and a drug study. In the main study, we are recruiting 60 young and 100 older adults to perform behavioral tasks that measure sensory and cognitive function. They also participate in functional MRI (fMRI), MR spectroscopy, and diffusion weighted imaging sessions, providing data on neural distinctiveness and GABA concentrations. In the drug study, we are recruiting 25 young and 25 older adults to compare neural distinctiveness, measured with fMRI, after participants take a placebo or a benzodiazepine (lorazepam) that should increase GABA activity. DISCUSSION: By collecting multimodal imaging measures along with extensive behavioral measures from the same subjects, we are linking individual differences in neurochemistry, neural representation, and behavioral performance, rather than focusing solely on group differences between young and old participants. Our findings have the potential to inform new interventions for age-related declines. TRIAL REGISTRATION: This study was retrospectively registered with the ISRCTN registry on March 4, 2019. The registration number is ISRCTN17266136 .

Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus.

The bottleneck governing infectious disease transmission describes the size of the pathogen population transferred from the donor to the recipient host. Accurate quantification of the bottleneck size is particularly important for rapidly evolving pathogens such as influenza virus, as narrow bottlenecks reduce the amount of transferred viral genetic diversity and, thus, may decrease the rate of viral adaptation. Previous studies have estimated bottleneck sizes governing viral transmission by using statistical analyses of variants identified in pathogen sequencing data. These analyses, however, did not account for variant calling thresholds and stochastic viral replication dynamics within recipient hosts. Because these factors can skew bottleneck size estimates, we introduce a new method for inferring bottleneck sizes that accounts for these factors. Through the use of a simulated data set, we first show that our method, based on beta-binomial sampling, accurately recovers transmission bottleneck sizes, whereas other methods fail to do so. We then apply our method to a data set of influenza A virus (IAV) infections for which viral deep-sequencing data from transmission pairs are available. We find that the IAV transmission bottleneck size estimates in this study are highly variable across transmission pairs, while the mean bottleneck size of 196 virions is consistent with a previous estimate for this data set. Furthermore, regression analysis shows a positive association between estimated bottleneck size and donor infection severity, as measured by temperature. These results support findings from experimental transmission studies showing that bottleneck sizes across transmission events can be variable and influenced in part by epidemiological factors.IMPORTANCE The transmission bottleneck size describes the size of the pathogen population transferred from the donor to the recipient host and may affect the rate of pathogen adaptation within host populations. Recent advances in sequencing technology have enabled bottleneck size estimation from pathogen genetic data, although there is not yet a consistency in the statistical methods used. Here, we introduce a new approach to infer the bottleneck size that accounts for variant identification protocols and noise during pathogen replication. We show that failing to account for these factors leads to an underestimation of bottleneck sizes. We apply this method to an existing data set of human influenza virus infections, showing that transmission is governed by a loose, but highly variable, transmission bottleneck whose size is positively associated with the severity of infection of the donor. Beyond advancing our understanding of influenza virus transmission, we hope that this work will provide a standardized statistical approach for bottleneck size estimation for viral pathogens.

Behavioral and neural correlates of disrupted orienting attention in posttraumatic stress disorder.

Prior work has revealed that posttraumatic stress disorder (PTSD) is associated with altered (a) attentional performance and (b) resting-state functional connectivity (rsFC) in brain networks linked to attention. Here, we sought to characterize and link these behavioral and brain-based alterations in the context of Posner and Peterson's tripartite model of attention. Male military veterans with PTSD (N = 49; all deployed to Iraq or Afghanistan) and healthy age-and-gender-matched community controls (N = 26) completed the Attention Network Task. A subset of these individuals (36 PTSD and 21 controls) also underwent functional magnetic resonance imaging (fMRI) to assess rsFC. The behavioral measures revealed that the PTSD group was impaired at disengaging spatial attention, relative to the control group. FMRI measures further revealed that, relative to the control group, the PTSD group exhibited greater rsFC between the salience network and (a) the default mode network, (b) the dorsal attention network, and (c) the ventral attention network. Moreover, problems with disengaging spatial attention increased the rsFC between the networks above in the control group, but not in the PTSD group. The present findings link PTSD to both altered orienting of spatial attention and altered relationships between spatial orienting and functional connectivity involving the salience network. Interventions that target orienting and disengaging spatial attention may be a new avenue for PTSD research.

Congruency sequence effects and previous response times: conflict adaptation or temporal learning?

In the present study, we followed up on a recent report of two experiments in which the congruency sequence effect-the reduction of the congruency effect after incongruent relative to congruent trials in Stroop-like tasks-was observed without feature repetition or contingency learning confounds. Specifically, we further scrutinized these data to determine the plausibility of a temporal learning account as an alternative to the popular conflict adaptation account. To this end, we employed a linear mixed effects model to investigate the role of previous response time in producing the congruency sequence effect, because previous response time is thought to influence temporal learning. Interestingly, slower previous response times were associated with a reduced current-trial congruency effect, but only when the previous trial was congruent. An adapted version of the parallel episodic processing (PEP) model was able to fit these data if it was additionally assumed that attention "wanders" during different parts of the experiment (e.g., due to fatigue or other factors). Consistent with this assumption, the magnitude of the congruency effect was correlated across small blocks of trials. These findings demonstrate that a temporal learning mechanism provides a plausible account of the congruency sequence effect.

Limits to the rate of adaptive substitution in sexual populations.

In large populations, many beneficial mutations may be simultaneously available and may compete with one another, slowing adaptation. By finding the probability of fixation of a favorable allele in a simple model of a haploid sexual population, we find limits to the rate of adaptive substitution, Λ, that depend on simple parameter combinations. When variance in fitness is low and linkage is loose, the baseline rate of substitution is Λ0 = 2NU , where N is the population size, U is the rate of beneficial mutations per genome, and is their mean selective advantage. Heritable variance v in log fitness due to unlinked loci reduces Λ by e⁻4(v) under polygamy and e⁻8 (v) under monogamy. With a linear genetic map of length R Morgans, interference is yet stronger. We use a scaling argument to show that the density of adaptive substitutions depends on s, N, U, and R only through the baseline density: Λ/R = F (Λ0/R). Under the approximation that the interference due to different sweeps adds up, we show that Λ/R ~(Λ0/R) / (1 +2Λ9/R) , implying that interference prevents the rate of adaptive substitution from exceeding one per centimorgan per 200 generations. Simulations and numerical calculations confirm the scaling argument and confirm the additive approximation for Λ0/R ~ 1; for higher Λ0/R , the rate of adaptation grows above R/2, but only very slowly. We also consider the effect of sweeps on neutral diversity and show that, while even occasional sweeps can greatly reduce neutral diversity, this effect saturates as sweeps become more common-diversity can be maintained even in populations experiencing very strong interference. Our results indicate that for some organisms the rate of adaptive substitution may be primarily recombination-limited, depending only weakly on the mutation supply and the strength of selection.

Both congruent and incongruent trials drive the congruency sequence effect: Novel support for an episodic retrieval view of adaptive control in the prime-probe task.

The congruency effect in Stroop-like tasks-a popular measure of distraction-is smaller after incongruent relative to congruent trials. However, it is unclear whether this congruency sequence effect (CSE)-a popular index of coping with distraction-reflects adjustments of control after congruent trials, incongruent trials, or both. The episodic retrieval account of the CSE posits adjustments of control after both congruent and incongruent trials. In this account, retrieving a memory of the previous trial's congruency (i.e., congruent or incongruent) biases control processes to prepare for an upcoming trial with the same congruency (i.e., congruent or incongruent). In contrast, the default setting account posits adjustments of control after a single trial type. For example, control processes might increase inhibition of the response cued by the distractor after incongruent trials but make no adjustments after congruent trials. To distinguish between these accounts for the first time while (a) using long distractor-target intervals and (b) excluding prevalent feature integration and contingency learning confounds, we employed a confound-minimized prime-probe task with neutral trials. We usually observed adjustments of control after both trial types. Furthermore, whether the reduction of the congruency effect after incongruent trials indexed (a) inhibition of the distractor-congruent response or (b) activation of the distractor-incongruent response depended on whether the distractor and target were same-sized or different-sized, respectively. These findings favor the episodic retrieval account of the CSE over the default setting account. They also indicate that "low-level" stimulus properties may influence the nature of "high-level" control adjustments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Average Nucleotide Identity based Staphylococcus aureus strain grouping allows identification of strain-specific genes in the pangenome.

Staphylococcus aureus causes both hospital and community acquired infections in humans worldwide. Due to the high incidence of infection S. aureus is also one of the most sampled and sequenced pathogens today, providing an outstanding resource to understand variation at the bacterial subspecies level. We processed and downsampled 83,383 public S. aureus Illumina whole genome shotgun sequences and 1,263 complete genomes to produce 7,954 representative substrains. Pairwise comparison of core gene Average Nucleotide Identity (ANI) revealed a natural boundary of 99.5% that could be used to define 145 distinct strains within the species. We found that intermediate frequency genes in the pangenome (present in 10-95% of genomes) could be divided into those closely linked to strain background ("strain-concentrated") and those highly variable within strains ("strain-diffuse"). Non-core genes had different patterns of chromosome location; notably, strain-diffuse associated with prophages, strain-concentrated with the vSaß genome island and rare genes (<10% frequency) concentrated near the origin of replication. Antibiotic genes were enriched in the strain-diffuse class, while virulence genes were distributed between strain-diffuse, strain-concentrated, core and rare classes. This study shows how different patterns of gene movement help create strains as distinct subspecies entities and provide insight into the diverse histories of important S. aureus functions.