Biology subjects

Wright, J.

Publications and source records attributed to Wright, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2020

Fine-scale population structure and demographic history of British Pakistanis

Previous genetic and public health research in the Pakistani population has focused on the role of consanguinity in increasing recessive disease risk, but little is known about its recent population history or the effects of endogamy. Here, we investigate fine-scale population structure, history and consanguinity patterns using genetic and questionnaire data from >4,000 British Pakistani individuals, mostly with roots in Azad Kashmir and Punjab. We reveal strong recent population structure driven by the biraderi social stratification system. We find that all subgroups have had low effective population sizes (Ne) over the last 50 generations, with some showing a decrease in Ne 15-20 generations ago that has resulted in extensive identity-by-descent sharing and increased homozygosity. Using new theory, we show that the footprint of regions of homozygosity in the two largest subgroups is about twice that expected naively based on the self-reported consanguinity rates and the inferred historical Ne trajectory. These results demonstrate the impact of the cultural practices of endogamy and consanguinity on population structure and genomic diversity in British Pakistanis, and have important implications for medical genetic studies.

genomics↗

bioRxiv2020

Variation in the Gut Microbiota of Common Marmosets: Differences with Colony of Origin and Integration

Characterization of the gut microbiome may aid understanding and management of natural and experimental disease states in research animals, thereby promoting reproducibility. In this study, the rectal bacterial communities of three separate common marmoset (Callithrix jacchus) breeding colonies were defined using 16S rRNA sequencing of rectal swab samples. Study animals originated from two German colonies and a United States colony (JHU). The two German cohorts, previously fed the same diet, were imported into the JHU facility; they were then isolated, transitioned onto JHU diet, and then moved into rooms housing JHU animals. To dissect the contributions of diet and integration in shaping the rectal bacterial community, samples were collected from German origin marmosets upon JHU arrival (baseline), following diet transition (100 d), and following cohousing (390 d). Baseline and 390 d samples were collected from stably maintained JHU marmosets. Bacterial community composition was distinct between all three cohorts at baseline, suggesting that factors other than primary diet confer significant differences between captive populations. Beta-diversity of the animals from the two German colonies converged by 100 d but remained distinct from JHU sample beta-diversity throughout the 390-d study, indicating that diet had greater influence on bacterial community composition than did housing animals within the same room. Our results demonstrate substantial differences in gut bacteria between different captive marmoset colonies, with persistence of these differences following husbandry standardization and housing integration. Goals of rigor and reproducibility in research underscore the need to consider microbial differences between marmosets of diverse origin. ImportanceCharacterizing gut microbial populations is expected to promote health and enhance research reproducibility in animal studies. As use of common marmosets as animal models of human diseases expands, evaluating the marmoset gut bacterial community will be critical for interpreting research findings, especially as marmosets are prone to gastrointestinal inflammation. In this study, using 16S rRNA sequencing of rectal swab samples, we compared bacterial community among three captive colonies of marmosets at baseline and following importation of cohorts from two of the colonies into the third colony. Diet history had sustained influence on bacterial community composition, while housing the animals within the same room over a period of eight months did not appear to be a major factor. These persistent differences in marmoset gut bacterial community highlight the need for careful consideration of animal origin as a variable in marmoset research studies.

microbiology↗

bioRxiv2020

Tet1 isoforms differentially regulate gene expression, synaptic transmission and memory in the mammalian brain.

The dynamic regulation of DNA methylation in post-mitotic neurons is necessary for memory formation and other adaptive behaviors. Ten-eleven translocation 1 (TET1) plays a part in these processes by oxidizing 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), thereby initiating active DNA demethylation. However, attempts to pinpoint its exact role in the nervous system have been hindered by contradictory findings, perhaps due in part, to a recent discovery that two isoforms of the Tet1 gene are differentially expressed from early development into adulthood. Here, we demonstrate that both the shorter transcript (Tet1S) encoding an N-terminally truncated TET1 protein and a full-length Tet1 (Tet1FL) transcript encoding canonical TET1 are co-expressed in the adult brain. We show that Tet1S is the predominantly expressed isoform, and is highly enriched in neurons, whereas Tet1FL is generally expressed at lower levels and more abundant in glia, suggesting their roles are at least partially cell-type specific. Using viral-mediated, isoform- and neuron-specific molecular tools, we find that Tet1S repression enhances, while Tet1FL impairs, hippocampal-dependent memory. In addition, the individual disruption of the two isoforms leads to contrasting changes in basal synaptic transmission and the dysregulation of unique gene ensembles in hippocampal neurons. Together, our findings demonstrate that each Tet1 isoform serves a distinct role in the mammalian brain.

neuroscience↗

bioRxiv2020

Individual reversible plasticity as a genotype-level bet-hedging strategy

Reversible plasticity in phenotypic traits allows organisms to cope with environmental variation within lifetimes, but costs of plasticity may limit just how well the phenotype matches the environmental optimum. An additional adaptive advantage of plasticity might be to reduce fitness variance, or bet-hedging to maximize geometric (rather than simply arithmetic) mean fitness. Here we model the evolution of reaction norm slopes, with increasing costs as the slope or degree of plasticity increases. We find that greater investment in plasticity (i.e. steeper reaction norm slopes) is favoured in scenarios promoting bet-hedging as a response to multiplicative fitness accumulation (i.e. coarser environmental grains and fewer time steps prior to reproduction), because plasticity lowers fitness variance across environmental conditions. In contrast, in scenarios with finer environmental grain and many time steps prior to reproduction, bet-hedging plays less of a role and individual-level optimization favours evolution of shallower reaction norm slopes. We discuss contrasting predictions from this partitioning of the different adaptive causes of plasticity into short-term individual benefits versus long-term genotypic (bet-hedging) benefits under different costs of plasticity scenarios, thereby enhancing our understanding of the evolution of optimum levels of plasticity in examples from thermal physiology to advances in avian lay dates. Impact summaryPhenotypic plasticity is a key mechanism by which organisms cope with environmental change. Plasticity relies on the existence of some reliable environmental cue that allows organisms to infer current or future conditions, and adjust their traits in response to better match the environment. In contrast, when environmental fluctuations are unpredictable, bet-hedging favours lineages that persist by lowering their fitness variance, either among or within individuals. Plasticity and bet-hedging are therefore often considered to be alternative modes of adaptation to environmental change. However, we here make the point that plasticity also has the capacity to change an organisms variance in fitness across different environmental conditions, and could thus itself be part of - and not an alternative to - a bet-hedging strategy. We show that bet-hedging at the genotype level affects the optimal degree of plasticity that individuals use to track environmental fluctuations, because despite a reduction in expected fitness at the individual level, costly investment in the ability to be plastic also lowers variance in fitness. We also discuss alternative predictions that arise from scenarios with different types of costs of plasticity. Evolutionary bet-hedging and phenotypic plasticity are both topics experiencing a renewed surge of interest as researchers seek to better integrate different adaptations to ongoing rapid environmental change in a range of areas of literature within ecology and evolution, including behavioural ecology, evolutionary physiology and life-history theory. We believe that demonstrating an important novel link between these two mechanisms is of interest to research in many different fields, and opens new avenues for understanding organismal adaptation to environmental change.

evolutionary biology↗

bioRxiv2020

A genome assembly of the barley 'transformation reference' cultivar Golden Promise

BackgroundBarley (Hordeum vulgare) is one of the most important crops worldwide and is also considered a research model for the large-genome small grain temperate cereals. Despite genomic resources improving all the time, they are limited for the cv. Golden Promise, the most efficient genotype for genetic transformation. FindingsWe have developed a barley cv. Golden Promise reference assembly integrating Illumina paired-end reads, long mate-pair reads, Dovetail Chicago in vitro proximity ligation libraries and chromosome conformation capture sequencing (Hi-C) libraries into a contiguous reference assembly. The assembled genome of 7 chromosomes and 4.13Gb in size, has a super-scaffold N50 after Chicago libraries of 4.14Mb and contains only 2.2% gaps. Using BUSCO (benchmarking universal single copy orthologous genes) as evaluation the genome assembly contains 95.2% of complete and single copy genes from the plant database. ConclusionsA high-quality Golden Promise reference assembly will be useful and utilised by the whole barley research community but will prove particularly useful for CRISPR-Cas9 experiments.

genomics↗

bioRxiv2019

Dataset Decay: the problem of sequential analyses on open datasets

Open data has two principal uses: (i) to reproduce original findings and (ii) to allow researchers to ask new questions with existing data. The latter enables discoveries by allowing a more diverse set of viewpoints and hypotheses to approach the data, which is self-evidently advantageous for the progress of science. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives in the literature. Current practice suggests that the number of tests to be corrected is the number of simultaneous tests performed by a researcher. Here we demonstrate that sequential hypothesis testing on the same dataset by multiple researchers can inflate error rates. This finding is troubling because, as more researchers embrace an open dataset, the likelihood of false positives (i.e. type I errors) will increase. Thus, we should expect a datasets utility for discovering new true relations between variables to decay. We consider several sequential correction procedures. These solutions can reduce the number of false positives but, at the same time, can prompt undesired challenges to open data (e.g. incentivising restricted access).

bioinformatics↗

bioRxiv2019

Formula alters preterm infant gut microbiota and increases its antibiotic resistance load

Infants are at a high risk of acquiring infections caused by antibiotic resistant bacterial strains. Antibiotic resistance gene (ARG) load is typically higher in newborns than in adults, but it is unknown which factors besides antibiotic treatment affect the load. Our study demonstrates that inclusion of any formula in the newborn diet causes shifts in microbial community composition that result in higher ARG loads in formula-fed infants compared to infants not fed formula. The effect of formula was especially strong in premature newborns and newborns treated with antibiotics. Interestingly, antibiotics alone without formula did not have a detectable impact on the ARG load of the newborn gut. We also observed that formula-fed infants had enriched numbers of pathogenic species and were depleted in typical infant gut species such as Bifidobacterium bifidum. The results suggest infant feeding choices should include assessment of risks associated with elevated ARG abundance.

microbiology↗

bioRxiv2019

Time-varying nodal measures with temporal community structure: a cautionary note to avoid misquantification

In network neuroscience, temporal network models have gained popularity. In these models, network properties have been related to cognition and behaviour. Here we demonstrate that calculating nodal properties that are dependent on temporal community structure (such as the participation coefficient) in time-varying contexts can potentially lead to misleading results. Specifically, with regards to the participation coefficient, increases in integration can be inferred when the opposite is occuring. Further, we present a temporal extension to the participation coefficient measure (temporal participation coefficient) that circumnavigates this problem by jointly considering all community partitions assigned to a node through time. The proposed method allows us to track a nodes integration through time while adjusting for the possible changes in the community structure of the overall network.

neuroscience↗

bioRxiv2019

Systematic re-annotation of 191 genes associated with early-onset epilepsy unmasks de novo variants linked to Dravet syndrome in novel SCN1A exons

The early infantile epileptic encephalopathies (EIEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 novel putative transcript models. The extended transcriptional footprint of these genes allowed for 294 intronic or intergenic variants, found in human mutation databases, to be reclassified as exonic, while a further 70 intronic variants were reclassified as splice-site proximal. Using SCN1A as a case study due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome, or a similar phenotype, with a panel of novel exon sequences representing eight established genes and identified two de novo SCN1A variants that now, through improved gene annotation can be ascribed to residing among novel exons. These two (from 122 screened patients, 1.6%) new molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously-classified SCN1A intronic Dravet-associated variant that now lies within a deeply conserved novel exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders. We would expect to find new molecular diagnoses in our 191 genes that were originally suspected by clinicians for patients, with a negative diagnosis.

genomics↗

bioRxiv2019

The identification of temporal communities through trajectory clustering correlates with single-trial behavioural fluctuations in neuroimaging data

Interacting sets of nodes and fluctuations in their interaction are important properties of a dynamic network system. In some cases the edges reflecting these interactions are directly quantifiable from the data collected. However, in many cases (such as functional magnetic resonance imaging (fMRI) data), the edges must be inferred from statistical relations between the nodes. Here we present a new method, Temporal Communities through Trajectory Clustering (TCTC), that derives time-varying communities directly from time-series data collected from the nodes in a network. First, we verify TCTC on resting and task fMRI data by showing that time-averaged results correspond with expected static connectivity results. We then show that the time-varying communities correlate and predict single-trial behaviour. This new perspective on temporal community detection of node-collected data identifies robust communities revealing ongoing spatiotemporal community configurations during task performance.

neuroscience↗

bioRxiv2019

Bet-hedging across generations can affect the evolution of variance-sensitive strategies within generations

In order to understand how organisms cope with ongoing changes in environmental variability it is important to consider all types of adaptations to environmental uncertainty on different time-scales. Conservative bet-hedging represents a long-term genotype-level strategy that maximizes lineage geometric mean fitness in stochastic environments by decreasing individual fitness variance, despite also lowering arithmetic mean fitness. Meanwhile, variance-prone (aka risk-prone) strategies produce greater variance in short-term payoffs because this increases expected arithmetic mean fitness if the relationship between payoffs and fitness is accelerating. Using two evolutionary simulation models, we investigate whether selection for such variance-prone strategies are counteracted by selection for bet-hedging that works to adaptively reduce fitness variance. We predict that variance-prone strategies will be favored in scenarios with more decision events per lifetime and when fitness accumulates additively rather than multiplicatively. In our model variance-proneness evolved in fine-grained environments (with lower correlations among individuals in energetic state and/or in payoffs when choosing the variable decision), and with larger numbers of independent decision events over which resources accumulate prior to selection. In contrast, geometric fitness accumulation caused by coarser environmental grain and fewer decision events prior to selection favors conservative bet-hedging via greater variance-aversion. We discuss examples of variance-sensitive strategies in optimal foraging, migration, life histories and cooperative breeding in light of these results concerning bet-hedging. By linking disparate fields of research studying adaptations to variable environments we should be more able to understand the effects in nature of human-induced rapid environmental change. Data depositionR code is available upon request.

evolutionary biology↗

bioRxiv2019

Generalists versus specialists in fluctuating environments: a bet-hedging perspective

Bet-hedging evolves in fluctuating environments because long-term genotype success is determined by geometric mean fitness across generations. However, specialist versus generalist strategies are usually considered in terms of arithmetic mean fitness benefits to individuals, as in habitat or foraging preferences. We model how environmental variability affects phenotypic variation within and among individuals to maximize either long-term arithmetic versus geometric mean fitness. For traits with additive fitness effects within lifetimes (e.g. foraging-related traits), genotypes of similar generalists or diversified specialists perform equally well. However, if fitness effects are multiplicative within lifetimes (e.g. sequential survival probabilities), generalist individuals are always favored, since geometric mean fitness favors greater within-individual phenotypic variation than arithmetic mean fitness does. Interestingly, this conservative bet-hedging effect outcompetes diversifying bet-hedging. These results link behavioral and ecological specialization and earlier models of bet-hedging, and thus apply to a range of natural phenomena from habitat choice to host specificity in parasites.\n\nImpact summaryWhich factors determine whether it is better to be a specialist or a generalist? Environmental fluctuations are becoming larger and more unpredictable across the globe as a result of human-induced rapid environmental change. A key challenge of evolutionary biology is therefore to understand how organisms adapt to such variation within and among generations, and currently represents a knowledge gap in evolutionary theory. Here we focus on how traits evolve when the (changing) environment determines the optimal value of a trait, so that the optimal trait value changes unpredictably over time. Our mathematical model investigates how much variation is optimal in a trait. We expect specialists (low within-individual trait variation) to be favored in stable environments, with generalists (high trait variation) favored in more variable environments. We show that the answer depends on whether we look from the point of view of the individual or all individuals of the same genotype. If an individual does well in the short term, but its offspring all experience a different environment and therefore do badly, the genotype as a whole is in trouble, and will not be favored in the long term. One solution to this problem could be to produce offspring with different trait values, to ensure that at least some of the offspring do well no matter the environmental conditions they grow up in. This \"dont put all your eggs in one basket\" diversification strategy is well-known in some organisms, but how helpful is it if there is also some within-individual (i.e. generalist) trait variation? By answering these questions under various environmental scenarios, we link together many different concepts in evolutionary ecology and animal behavior, increasing our understanding about how organisms may cope with the current changes in environmental conditions around the world.

evolutionary biology↗

bioRxiv2019

Rare Microbial Taxa Emerge When Communities Collide: Freshwater and Marine Microbiome Responses to Experimental Seawater Intrusion

Whole microbial communities regularly merge with one another, often in tandem with their environments, in a process called community coalescence. Such events allow us to address a central question in ecology - what processes shape community assembly. We used a reciprocal transplant and mixing experiment to directly and independently unravel the effects of environmental filtering and biotic interactions on microbiome success when freshwater and marine communities coalesce. The brackish treatment and community mixing resulted in strong convergence of microbiome structure and function toward the marine. Brackish exposure imposed a 96% taxa loss from freshwater and 66% loss from marine microbiomes, which was somewhat counterbalanced by the emergence of tolerant rare taxa. Community mixing further resulted in 29% and 49% loss from biotic interactions between freshwater and marine microbiomes, offset somewhat by mutualistically-assisted rare microbial taxa. Our study emphasizes the importance of the rare biosphere as a critical component of community resilience.

ecology↗

bioRxiv2019

Analysis of the recombination landscape of hexaploid bread wheat reveals genes controlling recombination and gene conversion frequency

Sequence exchange between homologous chromosomes through crossing over and gene conversion is highly conserved among eukaryotes, contributing to genome stability and genetic diversity. Lack of recombination limits breeding efforts in crops, therefore increasing recombination rates can reduce linkage-drag and generate new genetic combinations. We use computational analysis of 13 recombinant inbred mapping populations to assess crossover and gene conversion frequency in the hexaploid genome of wheat (Triticum aestivum). We observe that high frequency crossover sites are shared between populations and that closely related parental founders lead to populations with more similar crossover patterns. We demonstrate that gene conversion is more prevalent and covers more of the genome in wheat than in other plants, making it a critical process in the generation of new haplotypes, particularly in centromeric regions where crossovers are rare. We have identified QTL for altered gene conversion and crossover frequency and confirm functionality for a novel RecQ helicase gene that belongs to an ancient clade that is missing in some plant lineages including Arabidopsis. This is the first gene to be demonstrated to be involved in gene conversion in wheat. Harnessing the RecQ helicase has the potential to break linkage-drag utilizing widespread gene conversions.

genetics↗

bioRxiv2019

Deep phenotyping of a healthy human HAO1 knockout informs therapeutic development for primary hyperoxaluria type 1.

Primary Hyperoxaluria Type 1 (PH1) is a rare autosomal recessive metabolic disorder of oxalate metabolism leading to kidney failure as well as multi-organ damage. Overproduction of oxalate occurs in the liver due to an inherited genetic defect in the enzyme alanine-glyoxylate aminotransferase (AGXT), causing pathology due to the insolubility of calcium oxalate crystals in body fluids. The main current therapy is dual liver-kidney transplant, which incurs high morbidity and has poor availability in some health systems where PH1 is more prevalent. One approach currently in active clinical investigation targets HAO1 (hydroxyacid oxidase 1), encoding glycolate oxidase, to reduce substrate levels for oxalate production. To inform drug development, we sought individuals with reduced HAO1 function due to naturally occurring genetic variation.\n\nAnalysis of loss of function variants in 141,456 sequenced individuals suggested individuals with complete HAO1 knockout would only be observed in 1 in 30 million outbred people. However in a large sequencing and health records program (Genes & Health), in populations with substantial autozygosity, we identified a healthy adult individual predicted to have complete knockout of HAO1 due to an ultra rare homozygous frameshift variant (rs1186715161, ENSP00000368066.3:p.Leu333SerfsTer4). Primary care and hospital health records confirmed no apparently related clinical phenotype. At recall, urine and plasma oxalate levels were normal, however plasma glycolate levels (171 nmol/mL) were 12 times the upper limit of normal in healthy, reference individuals (mean+2sd=14 nmol/mL, n=67) while her urinary glycolate levels were 6 times the upper limit of normal. Comparison with preclinical and phase 1 clinical trial data of an RNAi therapeutic targeting HAO1 (lumasiran) suggests the individual likely retains <2% residual glycolate oxidase activity.\n\nThese results provide important data to support the safety of HAO1 inhibition as a potential chronic therapy for a devastating metabolic disease (PH1). We also suggest that the effect of glycolate oxidase suppression in any potential other roles in humans beyond glycolate oxidation do not lead to clinical phenotypes, at least in this specific individual. This demonstrates the value of studying the lifelong complete knockdown of a target protein in a living human to aid development of a potential therapeutic, both in de-risking the approach and providing potential hypotheses to optimize its development. Furthermore, therapy for PH1 is likely to be required lifelong, in contrast to data from chronicity studies in non-human species or relatively short-term therapeutic studies in people. Our approach demonstrates the potential for improved drug discovery through unlocking relevant evidence hiding in the diversity of human genetic variation.

genetics↗

bioRxiv2018

Cohort Profile: East London Genes & Health (ELGH), a community based population genomics and health study in people of British-Bangladeshi and -Pakistani heritage.

Cohort profile in a nutshellO_LIEast London Genes & Health (ELGH) is a large scale, community genomics and health study (to date >34,000 volunteers; target 100,000 volunteers). C_LIO_LIELGH was set up in 2015 to gain deeper understanding of health and disease, and underlying genetic influences, in British-Bangladeshi and British-Pakistani people living in east London. C_LIO_LIELGH prioritises studies in areas important to, and identified by, the community it represents. Current priorities include cardiometabolic diseases and mental illness, these being of notably high prevalence and severity. However studies in any scientific area are possible, subject to community advisory group and ethical approval. C_LIO_LIELGH combines health data science (using linked UK National Health Service (NHS) electronic health record data) with exome sequencing and SNP array genotyping to elucidate the genetic influence on health and disease, including the contribution from high rates of parental relatedness on rare genetic variation and homozygosity (autozygosity), in two understudied ethnic groups. Linkage to longitudinal health record data enables both retrospective and prospective analyses. C_LIO_LIThrough Stage 2 studies, ELGH offers researchers the opportunity to undertake recall-by-genotype and/or recall-by-phenotype studies on volunteers. Sub-cohort, trial-within-cohort, and other study designs are possible. C_LIO_LIELGH is a fully collaborative, open access resource, open to academic and life sciences industry scientific research partners. C_LI

genomics↗

bioRxiv2018

An Artificial Intelligence Workflow for Defining Host-Pathogen Interactions

For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capability to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella typhimurium we demonstrate HRMAns capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses.

microbiology↗

bioRxiv2018

Short-term insurance versus long-term bet-hedging strategies as adaptations to variable environments

Understanding how organisms adapt to environmental variation is a key challenge of biology. Central to this are bet-hedging strategies that maximize geometric mean fitness across generations, either by being conservative or diversifying phenotypes. Theoretical models of bet-hedging and the multiplicative fitness effects of environmental variation across generations have traditionally assumed that environmental conditions are constant within lifetimes. However, behavioral ecology has revealed adaptive responses to additive fitness effects of environmental variation within lifetimes, either through insurance or risk-sensitive strategies. Here we explore whether the effects of adaptive insurance interact with the evolution of bet-hedging by varying the position and skew of fitness functions within and between lifetimes. When insurance causes the optimal phenotype to shift from the peak to down the less steeply decreasing side of the fitness function, then conservative bet-hedging does not generally evolve on top of this, even if diversifying bet-hedging can. Canalization to reduce phenotypic variation within a lifetime is almost always favored, except when the tails of the fitness function are steeply convex and produce a novel risk-sensitive increase in phenotypic variance akin to diversifying bet-hedging. Importantly, using skewed fitness functions, we provide the first example of how conservative and diversifying bet-hedging strategies might coexist.

evolutionary biology↗