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Reinforcement learning over time: spaced versus massed training establishes stronger value associations

Over the past few decades, neuroscience research has illuminated the neural mechanisms supporting learning from reward feedback, demonstrating a critical role for the striatum and midbrain dopamine system. Learning paradigms are increasingly being extended to understand learning dysfunctions in mood and psychiatric disorders as well as addiction in the area of computational psychiatry. However, one potentially critical characteristic that this research ignores is the effect of time on learning: human feedback learning paradigms are conducted in a single rapidly paced session, while learning experiences in ecologically relevant circumstances and in animal research are almost always separated by longer periods of time. Event spacing is known to have strong positive effects on item memory across species and in reward learning in animals. Remarkably, the effect of spaced training on human reinforcement learning has not been investigated. In our experiments, we examined reward learning distributed across weeks vs. learning completed in a traditionally-paced or \"massed\" single session. Participants learned to make the best response for landscape stimuli that were either associated with a positive or negative value. In our first study, as expected, we found that after equal amounts of extensive training, accuracy was high and equivalent between the spaced and massed conditions. However, in a final online test 3 weeks later, we found that participants exhibited significantly greater memory for the value of spaced-trained stimuli. In our second study, our methods allowed for a direct comparison of maintenance of conditioning. We found that spaced training again had a beneficial effect: more than 87% of conditioning was maintained for spaced-trained stimuli, while only 30% was maintained for massed-trained stimuli. In addition, supporting a role for working memory in massed learning, across both studies we found a significant positive correlation between initial learning and working memory capacity. Our results indicate that single-session learning tasks may not lead to the kind of robust and lasting value associations that are characteristic of \"habitual\" value associations. Overall, these studies begin to address a large gap in our knowledge of fundamental processes of human reinforcement learning, with potentially broad implications for our understanding of learning in mood disorders and addiction.

neuroscience

Small subsets of highly connected taxa predict compositional change in microbial communities

For decades, ecological theory has predicted that the complexity of communities should be related to their stability. However, this prediction has rarely been tested empirically, because of both the difficulty of finding suitable systems where the question is tractable and the trouble of defining \"stability\" in real systems. Microbial communities provide the opportunity to investigate a related question: how does community connectivity relate to the rate of compositional turnover? We used a newly developed metric called community \"cohesion\" to test how microbial community connectivity relates to Bray-Curtis dissimilarity through time. In three long-term datasets, we found that stronger connectivity corresponded to lower rates of compositional turnover. Using two case studies of disturbed and reference communities, we found that the predictive power of community connectivity was diminished by external disturbance. Finally, we tested whether the highly connected taxa were disproportionately important in explaining compositional turnover. We found that subsets of highly connected \"keystone\" taxa, generally comprising 1-5% of community richness, explained community turnover better than using all taxa. Our results suggest that stronger biotic interactions within microbial community dynamics are stabilizing to community composition, and that highly connected taxa are good indicators of pending community shifts.

microbiology

Fixed effect variance and the estimation of the heritability: Issues and solutions

Linear mixed effects models are frequently used for estimating quantitative genetic parameters, including the heritability, of traits of interest. Heritability is an important metric, because it acts as a filter that determines how efficiently phenotypic selection translates into evolutionary change. As a quantity of biological interest, it is important that the denominator, the phenotypic variance, actually reflects the amount of phenotypic variance in the relevant ecological stetting. The current practice of quantifying heritability from mixed effects models frequently deprives the heritability of variance explained by fixed effects (often leading to upward-bias) and it has been suggested to omit fixed effects when estimating heritabilities. We advocate an alternative option of fitting complex models incorporating all relevant effects, while including the variance explained by fixed effects into the estimation of heritabilities. The approach is easily implemented (an example is provided) and allows corrections for the estimation of heritability, such as the exclusion of variance arising from experimental design effects while still including all biologically relevant sources of variation. We explore the complications arising depending on the nature of the covariates included as fixed effects (e.g. biological or experimental origin, characteristics of biological covariates). Furthermore, we discuss fixed effects in non-linear and generalized linear models when fixed effects. In these cases, the variance parameters depend on the location of the intercept and hence on the scaling of the fixed effects. Integration over the biologically relevant range of fixed effects offers a preferred solution in those situations.

evolutionary biology

Dynamics of venom composition across a complex life cycle

Little is known about venom in young developmental stages of animals. The appearance of stinging cells in very early life stages of the sea anemone Nematostella vectensis suggests that toxins and venom are synthesized already in eggs, embryos and larvae of this species. Here we harness transcriptomic and biochemical tools as well as transgenesis to study venom production dynamics in Nematostella. We find that the venom composition and arsenal of toxin-producing cells change dramatically between developmental stages of this species. These findings might be explained by the vastly different ecology of the larva and adult polyp as sea anemones develop from a miniature non-feeding mobile planula to a much larger sessile polyp that predates on other animals. Further, the results suggest a much wider and dynamic venom landscape than initially appreciated in animals with a complex life cycle.

evolutionary biology

DddY is a bacterial dimethylsulfoniopropionate lyase representing a new cupin enzyme superfamily with unknown primary function

Dimethylsulfide (DMS) is released at rates of >107 tons annually and plays a key role in the oceanic sulfur cycle and ecology. Marine bacteria, algae, and possibly other organisms, release DMS via cleavage of dimethylsulfoniopropionate (DMSP). Different genes encoding proteins with DMSP lyase activity are known belonging to different superfamilies and exhibiting highly variable levels of DMSP lyase activity. DddY shows the highest activity among all reported bacterial lyases yet is poorly characterized. Here, we describe the characterization of recombinant DddY is from different marine bacteria. We found that DddY activity demands a transition metal ion cofactor. DddY also shares two sequence motifs with other bacterial lyases assigned as cupin-like enzymes, DddQ, DddL, DddK, and DddW. These cupin motif residues are essential for DddY activity, as for the other cupin DMSP lyases, and all these enzymes are characterized by a common metal-chelator inhibitor (TPEN). Analysis of all sequences carrying these cupin motifs defined a superfamily: Cupin-DLL (DMSP lyases and lyase-like). The DMSP lyase families are sporadically distributed suggesting that DMSP lyases evolved within this superfamily independently along multiple lineages. However, the specific activity levels, genomic context analysis, and systematic profiling of substrate selectivity as described in the accompanying paper, indicate that for only some of these families, most distinctly DddY and DddL, DMSP lyase is the primary, native activity. In other families, foremost DddQ, DMSP lyase seems to be merely a promiscuous activity. The native function of DddQ, and of nearly all members of this newly identified Cupin-DLL superfamily, remains unknown.\n\nAbbreviations\n\nFundingFinancial support by the Estate of Mark Scher, and the Sasson & Marjorie Peress Philanthropic Fund, are gratefully acknowledged. D.S.T. is the Nella and Leon Benoziyo Professor of Biochemistry.

biochemistry

Parallel use of a shared genomic island of speciation in clinal and mosaic hybrid zones between cryptic seahorse lineages

Diverging semi-isolated lineages either meet in narrow clinal hybrid zones, or have a mosaic distribution associated with environmental variation. Intrinsic reproductive isolation is often emphasized in the former and local adaptation in the latter, although both can contribute to isolation. Rarely these two patterns of spatial distribution are reported in the same study system. Here we report that the long-snouted seahorse Hippocampus guttulatus is subdivided into discrete panmictic entities by both types of hybrid zones. Along the European Atlantic coasts, a northern and a southern lineage meet in the southwest of France where they coexist in sympatry with little hybridization. In the Mediterranean Sea, two lineages have a mosaic distribution, associated with lagoon-like and marine habitats. A fifth lineage was identified in the Black Sea. Genetic homogeneity over large spatial scales contrasts with isolation maintained in sympatry or close parapatry at a fine scale. A high variation in locus-specific introgression rates provides additional evidence that partial reproductive isolation must be maintaining the divergence. Surprisingly, fixed differences between lagoon and marine populations in the Mediterranean Sea belong to the most differentiated SNPs between the two Atlantic lineages, against the genome-wide pattern of structure. These parallel outlier SNPs cluster on a single chromosome-wide island of differentiation. Since Atlantic lineages do not match the lagoon-sea habitat variation, genetic parallelism at the genomic island suggests a shared genetic barrier contributes to reproductive isolation in contrasting contexts -i.e. spatial vs. ecological. We discuss how a genomic hotspot of parallel differentiation could have evolved and become associated either with space or with a patchy environment in a single study system.

evolutionary biology

Practical unidentifiability of a simple vector-borne disease model: implications for parameter estimation and intervention assessment

BackgroundMathematical modeling has an extensive history in vector-borne disease epidemiology, and is increasingly used for prediction, intervention design, and understanding mechanisms. Many of these studies rely on parameter estimation to link models and data, and to tailor predictions and counterfactuals to specific settings. However, few studies have formally evaluated whether vector-borne disease models can properly estimate the parameters of interest given the constraints of a particular dataset.\n\nMethodology/Principle FindingsIdentifiability methods allow us to examine whether model parameters can be estimated uniquely--a lack of consideration of such issues can result in misleading or incorrect parameter estimates and model predictions. Here, we evaluate both structural (theoretical) and practical identifiability of a commonly used compartmental model of mosquitoborne disease, using 2010 dengue epidemic in Taiwan as a case study. We show that while the model is structurally identifiable, it is practically unidentifiable under a range of human and mosquito time series measurement scenarios. In particular, the transmission parameters form a practically identifiable combination and thus cannot be estimated separately, which can lead to incorrect predictions of the effects of interventions. However, in spite of unidentifiability of the individual parameters, the basic reproduction number was successfully estimated across the unidentifiable parameter ranges. These identifiability issues can be resolved by directly measuring several additional human and mosquito life-cycle parameters both experimentally and in the field.\n\nConclusionsWhile we only consider the simplest case for the model, without explicit environmental drivers, we show that a commonly used model of vector-borne disease is unidentifiable from human and mosquito incidence data, making it difficult or impossible to estimate parameters or assess intervention strategies. This work illustrates the importance of examining identifiability when linking models with data to make predictions, and particularly highlights the importance of combining experimental, field, and case data if we are to successfully estimate epidemiological and ecological parameters using models.\n\nAuthor SummaryMathematical models have seen increasing use in understanding transmission processes, developing interventions, and predicting disease incidence and prevalence. Vector-borne diseases in particular present both a challenge and an opportunity for modeling, due to the complex interactions between host and vector species. A key step in many of these studies is connecting transmission models with data to infer parameters and make useful predictions, which requires careful consideration of identifiability and uncertainty of the model parameters. Whether due to intrinsic limitations of the model structure, or practical limitations of the data collected, is common that many different parameter values may yield the same or very similar fits to the data, making it impossible to successfully estimate the parameters. This issue of parameter unidentifiability can have broad implications for our ability to draw conclusions from mechanistic models--in some cases making it difficult or impossible to generate specific predictions, forecasts, or parameter estimates from a given model and data. Here, we evaluate these questions for a commonly-used model of vectorborne disease, examining how parameter uncertainty and unidentifiability can affect intervention predictions, estimation of the basic reproduction number, and other public health conclusions drawn from the model.

epidemiology

DNA barcoding British Euphrasia reveals deeply divergent polyploids but lack of species-level resolution

Background and aimsDNA barcoding is emerging as a useful tool not only for species identification but for studying evolutionary and ecological processes. Although plant DNA barcodes do not always provide species-level resolution, the generation of large DNA barcode datasets can provide insights into the mechanisms underlying the generation of species diversity. Here, we use DNA barcoding to study evolutionary processes in taxonomically complex British Euphrasia, a group with multiple ploidy levels, frequent self- fertilization, young species divergence and widespread hybridisation.\n\nMethodsWe sequenced the core plant barcoding loci, supplemented with additional nuclear and plastid loci, in representatives of all 19 British Euphrasia species. We analyse these data in a population genetic and phylogenetic framework. We then date the divergence of haplotypes in a global Euphrasia dataset using a time-calibrated Bayesian approach implemented in BEAST.\n\nKey resultsNo Euphrasia species has a consistent diagnostic haplotype. Instead, haplotypes are either widespread across species, or are population specific. Nuclear genetic variation is strongly partitioned by ploidy levels, with diploid and tetraploid British Euphrasia possessing deeply divergent ITS haplotypes (DXY = 5.1%), with haplotype divergence corresponding to the late Miocene. In contrast, plastid data show no clear division by ploidy, and instead reveal weakly supported geographic patterns.\n\nConclusionsUsing standard DNA barcoding loci for species identification in Euphrasia will be unsuccessful. However, these loci provide key insights into the maintenance of genetic variation, with divergence of diploids and tetraploids suggesting that ploidy differences act as a barrier to gene exchange in British Euphrasia, with rampant hybridisation within ploidy levels. The scarcity of shared diploid-tetraploid ITS haplotypes supports the polyploids being allotetraploid in origin. Overall, these results show that even when lacking species-level resolution, DNA barcoding can reveal insightful evolutionary patterns in taxonomically complex genera.

evolutionary biology

Resilience mechanisms of small intestinal lactobacilli to the toxicity of soybean oil fatty acids

Over the past century, soybean oil (SBO) consumption in the United States increased dramatically. The main SBO fatty acid, linoleic acid (18:2), inhibits in vitro the growth of lactobacilli, beneficial members of the small intestinal microbiota. Human-associated lactobacilli have declined in prevalence in Western microbiomes, but how dietary changes may have impacted their ecology is unclear. Here, we compared the in vitro and in vivo effects of 18:2 on Lactobacillus reuteri and L. johnsonii. Directed evolution in vitro in both species led to strong 18:2 resistance with mutations in genes for lipid biosynthesis, acid stress, and the cell membrane or wall. Small-intestinal Lactobacillus populations in mice were unaffected by chronic and acute 18:2 exposure, yet harbored both 18:2- sensitive and resistant strains. This work shows that extant small intestinal lactobacilli are protected from toxic dietary components via the gut environment as well as their own capacity to evolve resistance.

microbiology

A central role for boom-bust cycles in maintaining genetic variation in fluctuating environments

The long-running debate about the role of selection in maintaining genetic variation has been given new impetus by the discovery of hundreds of seasonally oscillating polymorphisms in wild Drosophila, possibly stabilized by an alternating summer-winter selection regime. Historically there has been skepticism about the potential of temporal variation to balance polymorphism, because selection must be strong to have a meaningful stabilizing effect -- unless dominance also varies over time ("reversal of dominance"). Here we develop a simplified model of seasonally variable selection that simultaneously incorporates four different stabilizing mechanisms, including two genetic mechanisms ("cumulative overdominance" and reversal of dominance), as well as ecological "storage" ("protection from selection" and boom-bust demography). We use our model to compare the stabilizing effects of these mechanisms. Although reversal of dominance has by far the greatest stabilizing effect, we argue that the three other mechanisms could also stabilize polymorphism under plausible conditions, particularly when all three are present. With many loci subject to diminishing returns epistasis, reversal of dominance stabilizes many alleles of small effect. This makes the combination of the other three mechanisms, which are incapable of stabilizing small effect alleles, a better candidate for stabilizing the detectable frequency oscillations of large effect alleles.

evolutionary biology

Collaborative environmental DNA sampling from petal surfaces of flowering cherry Cerasus ×- yedoensis 'Somei-yoshino' across the Japanese archipelago

Recent studies have shown that environmental DNA is found almost everywhere. Flower petal surfaces are an attractive tissue to use for investigation of the dispersal of environmental DNA in nature as they are isolated from the external environment until the bud opens and only then can the petal surface accumulate environmental DNA. Here, we performed a crowdsourced experiment, the \"Ohanami Project\", to obtain environmental DNA samples from petal surfaces of Cerasus x yedoensis Somei-yoshino across the Japanese archipelago during spring 2015. C. x yedoensis is the most popular garden cherry species in Japan and clones of this cultivar bloom simultaneously every spring. Data collection spanned almost every prefecture and totaled 577 DNA samples from 149 collaborators. Preliminary amplicon-sequencing analysis showed the rapid attachment of environmental DNA onto the petal surfaces. Notably, we found DNA of other common plant species in samples obtained across a wide distribution; this DNA likely originated from pollen of the Japanese cedar. Our analysis supports our belief that petal surfaces after blossoming are a promising target to reveal the dynamics of environmental DNA in nature. The success of our experiment also shows that crowdsourced environmental DNA analyses have considerable value in ecological studies.

microbiology

Fantastic beasts and how to sequence them: genomic approaches for obscure model organisms.

Application of genomic approaches to \"obscure model organisms\" (OMOs), meaning species with little or no genomic resources, enables increasingly sophisticated studies of genomic basis of evolution, acclimatization and adaptation in real ecological contexts. Here, I highlight sequencing solutions and data handling techniques most suited for genomic analysis of OMOs.\n\nGlossary- Allele Frequency Spectrum, AFS (same as Site Frequency Spectrum, SFS): histogram of the number of segregating variants depending on their frequency in one or more populations.\n- Restriction site-Associated DNA (RAD) sequencing: family of diverse genotyping methods that sequence short fragments of the genome adjacent to recognition site(s) for specific restriction endonuclease(s).\n- Linkage Disequilibrium (LD): in this review, correlation of genotypes at a pair of markers across individuals.\n- LD block: typical distance between markers in the genome across which their genotypes remain correlated.\n- Genome scan: profiling of genotypes along the genome looking for unusual patterns. Often used to look for signatures of natural selection or introgression.\n- \"Denser-than-LD\" genotyping: genotyping of several polymorphic markers per LD block.\n- Highly contiguous reference: genome or transcriptome reference sequence containing the least amount of fragmentation.\n- Phased data: data showing which SNP alleles belong to the same homologous chromosome copy.\n- Cross-tissue gene expression analysis: looking for individual-specific shifts in gene expression detectable across multiple tissues. Such shifts are predominantly genetic in nature.

genomics

Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results

Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed seven recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Though gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior.

neuroscience

Developmental transcriptomics of the brittle star Amphiura filiformis reveals gene regulatory network rewiring in echinoderm larval skeleton evolution

Amongst the echinoderms the class Ophiuroidea is of particular interest for its phylogenetic position, ecological importance, developmental and regenerative biology. However, compared to other echinoderms, notably echinoids (sea urchins), relatively little is known about developmental changes in gene expression in ophiuroids. To address this issue we have generated and assembled a large RNAseq data set of four key stages of development in the brittle star Amphiura filiformis and a de novo reference transcriptome of comparable quality to that of a model echinoderm - the sea urchin Strongyloncentrotus purpuratus. Furthermore, we provide access to the new data via a web interface: http://www.echinonet.eu/shiny/Amphiura_filiformis/. With a focus on skeleton development, we have identified highly conserved genes associated with the development of a biomineralized skeleton. We also identify important class-specific characters, including the independent duplication of the msp130 class of genes in different echinoderm classes and the unique occurrence of spicule matrix (sm) genes in echinoids. Using a new quantification pipeline for our de novo transcriptome, validated with other methodologies, we find major differences between brittle stars and sea urchins in the temporal expression of many transcription factor genes. This divergence in developmental regulatory states is more evident in early stages of development when cell specification begins, than when cells initiate differentiation. Our findings indicate that there has been a high degree of gene regulatory network rewiring in the evolution of echinoderm larval development.\n\nData DepositionsAll sequence reads are available at Genbank SRR4436669 - SRR4436674. Any sequence alignments used are available by the corresponding author upon request.

evolutionary biology

The human auditory brainstem response to running speech reveals a subcortical mechanism for selective attention

Humans excel at selectively listening to a target speaker in background noise such as competing voices. While the encoding of speech in the auditory cortex is modulated by selective attention, it remains debated whether such modulation occurs already in subcortical auditory structures. Investigating the contribution of the human brainstem to attention has, in particular, been hindered by the tiny amplitude of the brainstem response. Its measurement normally requires a large number of repetitions of the same short sound stimuli, which may lead to a loss of attention and to neural adaptation. Here we develop a mathematical method to measure the auditory brainstem response to running speech, an acoustic stimulus that does not repeat and that has a high ecological validity. We employ this method to assess the brainstems activity when a subject listens to one of two competing speakers, and show that the brainstem response is consistently modulated by attention.

neuroscience

An updated infrageneric classification of the oaks: review of previous taxonomic schemes and synthesis of evolutionary patterns

In this paper, we review major classification schemes proposed for oaks by John Claudius Loudon, Anders Sandoe Orsted, William Trelease, Otto Karl Anton Schwarz, Aimee Antoinette Camus, Yuri Leonardovich Menitsky, and Kevin C. Nixon. Classifications of oaks (Fig. 1) have thus far been based entirely on morphological characters. They differed profoundly from each other because each taxonomist gave a different weight to distinguishing characters; often characters that are homoplastic in oaks. With the advent of molecular phylogenetics our view has considerably changed. One of the most profound changes has been the realisation that the traditional split between the East Asian subtropical to tropical subgenus Cyclobalanopsis and the subgenus Quercus that includes all other oaks is artificial. The traditional concept has been replaced by that of two major clades, each comprising three infrageneric groups: a Palearctic-Indomalayan clade including Group Ilex (Ilex oaks), Group Cerris (Cerris oaks) and Group Cyclobalanopsis (cycle-cup oaks), and a predominantly Nearctic clade including Group Protobalanus (intermediate or golden cup oaks), Group Lobatae (red oaks) and Group Quercus (white oaks, with most species in America and some 30 species in Eurasia). The main morphological feature characterising these phylogenetic lineages is pollen morphology, a character overlooked in traditional classifications. This realisation, along with the now available (molecular-)phylogenetic framework, opens new avenues for biogeographic, ecological and evolutionary studies and a re-appraisal of the fossil record. We provide an overview about recent advances in these fields and outline how the results of these studies contribute to the establishment of a unifying systematic scheme of oaks. Ultimately, we propose an updated classification of Quercus recognising two subgenera with eight sections. This classification considers morphological traits, molecular-phylogenetic relationships, and the evolutionary history of one of the most important temperate woody plant genera.\n\nO_FIG O_LINKSMALLFIG WIDTH=156 HEIGHT=200 SRC=\"FIGDIR/small/168146_fig1.gif\" ALT=\"Figure 1\">\nView larger version (49K):\norg.highwire.dtl.DTLVardef@d5a05org.highwire.dtl.DTLVardef@91295forg.highwire.dtl.DTLVardef@3338fcorg.highwire.dtl.DTLVardef@e24a58_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO Classification schemes for Quercus from Loudon to Nixon (see Appendix). Colour coding denotes the actual systematic affiliation of species included in each taxon: of the Old World or mid-latitude clade section Cyclobalanopsis (cycle-cup oaks, yellow), section Cerris (Cerris oaks; orange), and section Ilex (Ilex oaks; green); and of the New World or high-latitude clade section Quercus (white oaks s.str.; blue), sections Virentes (cyan) and Ponticae (dark blue), section Protobalanus (intermediate oaks; purple), and section Lobatae (red oaks; red). Colour gradients are proportional, i.e. reflect the proportion of species with different systematic affiliation included in each taxon. Note: Menitsky (1984) and Trelease (1924) only treated the Eurasian and American oaks, respectively, and provided classifications in (nearly) full agreement with current phylogenies.\n\nC_FIG

plant biology

A GAL80 collection to nullify transgenes in Drosophila olfactory sensory neurons

Fruit flies recognize hundreds of ecologically relevant odors and respond appropriately to them. The complexity, redundancy and interconnectedness of the olfactory machinery complicate efforts to pinpoint the functional contributions of any component neuron or receptor to behavior. Some contributions can only be elucidated in flies that carry multiple mutations and transgenes, but the production of such flies is currently labor-intensive and time-consuming. Here, we describe a set of transgenic flies that express the Saccharomyces cerevisiae GAL80 in specific olfactory sensory neurons (OrX-GAL80s). The GAL80s effectively and specifically subtract the activities of GAL4-driven transgenes that impart anatomical and physiological phenotypes. OrX-GAL80s can allow researchers to efficiently activate only one or a few types of functional neurons in an otherwise nonfunctional olfactory background. Such experiments will improve our understanding of the mechanistic connections between odorant inputs and behavioral outputs at the resolution of only a few functional neurons.

neuroscience

Effects of population- and seed bank noise on neutral evolution and efficacy of natural selection

Population genetics models typically consider a fixed population size and a unique selection coefficient. However, population dynamics inherently generate noise in numbers of individuals and selection acts on various components of the individuals fitness. In plant species with seed banks, the size of both the above- and below-ground compartments present noise depending on seed production and the state of the seed bank. We investigate if this noise has consequences on 1) the rate of genetic drift, and 2) the efficacy of selection. We consider four variants of two-allele Moran-type models defined by combinations of presence and absence of noise in above-ground and seed bank compartments. Time scale analysis and dimension reduction methods allow us to reduce the corresponding Fokker-Planck equation to a one-dimensional diffusive Moran model. We first show that if the above-ground noise classically affects the rate of genetic drift, below-ground noise reduces the diversity storage effect of the seed bank. Second, we consider that selection can act on four different components of the plant fitness: plant or seed death rate, seed production or seed germination. Our striking result is that the efficacy of selection for seed death rate or germination rate is reduced by seed bank noise, whereas selection occurring on plant death rate or seed production is not affected. We derive the expected site-frequency spectrum reflecting this heterogeneity in selection efficacy between genes underpinning different plant fitness components. Our results highlight the importance to consider the effect of ecological noise to predict the impact of seed banks on neutral and selective evolution.

evolutionary biology