Search bioRxiv⌕ Search

Biology subjects

Schmidt, P.

Publications and source records attributed to Schmidt, P..

At least 19 recordsLinked to original sources

High-resolution mapping of a rapidly evolving complex trait reveals genotype-phenotype stability and an unpredictable genetic architecture of adaptation

The extent to which adaptation can be predicted is unknown. Here, we leveraged a longitudinal sampling design to test the efficacy of genomic prediction of trait evolution in an ecologically-relevant setting. Specifically, we monitored genome-wide allele frequencies and pigmentation variation in genetically diverse populations of Drosophila melanogaster across seven generations of evolution in both field mesocosms and a controlled, lab-based setting. At two points during trait evolution, we conducted a high-powered quantification of trait architecture that produced a well-resolved genotype-phenotype map. While we were able to use this map to correctly infer the direction of pigmentation evolution in both the field and lab mesocosms, the particular loci responding to selection, and thus the architecture of adaptation itself, was largely unpredictable. Further, we quantified a striking stability of the genotype-phenotype map, even across independent and genetically diverged populations. Our results hold implications for both the promise and limitations of genomic prediction.

evolutionary biology↗

The microbiota elicits compensatory adaptation in a seasonally-adapting animal host

Seasonal adaptation in Drosophila melanogaster is a model for understanding the evolutionary responses of organisms to cyclical environmental changes, including roles played by associated microorganisms ( microbiota). Here we examined how the microbiota influences D. melanogaster seasonal adaptation by rearing flies in outdoor mesocosms, fed diets inoculated with different bacterial strains that have distinct influences on the flies life history. The bacterial treatments influenced fly population dynamics and microbiota composition over a summer-to-fall season. The developmental phenotype of the treated flies initially differed but converged over time in flies reared with a complete microbial community. Conversely, rearing the flies free of their colonizing microorganisms revealed that the bacterial treatments led to evolution of distinct developmental phenotypes. The development time of flies from the different treatments consistently adapted to compensate for the direct influence of the bacteria on host development; e.g., flies evolved faster development times if they were inoculated with microbes that slowed development. This compensatory trend was apparent in flies reared in a second location and season, and is consistent with a previous report of wild-sampled flies whose development phenotype segregated with their microbiota composition. Together, these results reveal that microbiota-dependent selection consistently elicits compensatory adaptation in seasonally-evolving flies, which we conclude is a mechanism whereby horizontally-acquired, low-fidelity microbial partners can shape the evolution of their animal hosts. ImportanceUnderstanding how organisms adapt to seasonal change can model evolutionary responses in a broader changing world. Drosophila melanogaster is a powerful model for studying these dynamics, especially when considering the influence of transient yet impactful colonizing microorganisms. This study reveals that microbial partners can drive consistent, compensatory adaptation in host development across seasons and locations. By demonstrating that flies evolve faster development times in response to microbes that slow a model hosts period of growth and development, this work highlights one way that the microbiota can influence adaptation in their animal hosts. These findings also provide evidence that low-fidelity, horizontally-acquired microbes can exert selective pressures strong enough to shape host life history traits. These insights underscore the microbiotas role as an ecological and evolutionary force.

microbiology↗

Fast segmentation with the NextBrain histological atlas

Structural brain analysis at the subregion level offers critical insights into healthy aging and neurodegenerative diseases. The NextBrain histological atlas was recently introduced to support such fine-grained investigations, but its existing Bayesian segmentation framework remains computationally prohibitive, particularly for large-scale studies. We present a new, open-source tool that dramatically accelerates segmentation using a hybrid approach combining: machine learning, contrast-adaptive segmentation; target-specific image synthesis; and fast diffeomorphic registration (all three with GPU support). Our method enables highly granular segmentation of brain MRI scans of any resolution and contrast (in vivo or ex vivo) at a fraction of the computational cost of the original method (<5 minutes on a GPU). We validate our tool on four different modalities (in vivo MRI, ex vivo MRI, HiP-CT, and photography) across a total of approximately 4,000 brain scans. Our results demonstrate that the accelerated approach achieves comparable accuracy to the original method in terms of Dice scores, while reducing runtime by over an order of magnitude. This work enables high-resolution anatomical analysis at unprecedented scale and flexibility, providing a practical solution for large neuroimaging studies. Our tool is publicly available in FreeSurfer (https://surfer.nmr.mgh.harvard.edu/fswiki/HistoAtlasSegmentation).

neuroscience↗

Seasonal evolution of Drosophila melanogaster abdominal pigmentation is associated with a multifarious selective landscape

Pigmentation has been widely studied by evolutionary biologists due to both ease of measure and relationship to fitness. Drosophila melanogaster pigmentation has represented a particularly useful avenue of investigation, as extensive genetic tools have enabled the characterization of the traits complex architecture. Drosophila pigmentation also varies predictably across space and time in wild populations, suggesting pigmentation is a component of adaptation to local environmental conditions. Despite this, the impact of D. melanogaster pigmentation on fitness, and the environmental factors that drive the evolution of pigmentation, are not well understood. To address this gap, we experimentally evolved replicated D. melanogaster populations in field mesocosms to determine whether and how pigmentation evolves in response to environmental variation. We found that pigmentation rapidly and predictably adapted to a direct manipulation of temperature, supportive of melanization playing a role in thermoregulation. However, we also determined that pigmentation responded adaptively to direct manipulations of numerous additional factors, including intraspecific competition, diet, and the microbiome. These findings suggest that the selective landscape acting on pigmentation is complex and multifaceted, and that patterns of melanization may be driven, at least in part, by indirect selection due to correlations with other fitness-related traits.

evolutionary biology↗

Conserved programs and specificities of T cells targeting hematological malignancies

T cell-mediated immune surveillance is critical for cancer control, yet its endogenous effectiveness in hematological malignancies remains limited and poorly understood. Here, we integrate single-cell T cell receptor (TCR) profiling, HLA immunopeptidomics and functional antigen mapping to dissect the specificity landscape of bone marrow lymphocytes (BMLs) in multiple myeloma (MM) and acute myeloid leukemia (AML). We identify a rare subset of tumor-reactive T cells that exhibit a stereotyped transcriptional state distinct from bystander and virus-specific populations. Across both malignancies, immunopeptidomic profiling uncovers a partially conserved antigen repertoire enriched for noncanonical peptides, including products of novel or unannotated open reading frames (nuORFs), pseudogenes, and clonotypic immunoglobulin sequences. Several of these epitopes are recurrently presented and associated with convergent TCR responses across individuals. Based on this immune architecture, we develop a TCR-intrinsic fitness model that infers BML tumor specificity from transcriptional cues and stratifies immunotherapy response across three independent patient cohorts. Together, these findings map the latent potential of endogenous anti-tumor immunity in two biologically distinct diseases and provide a framework for decoding and restoring productive immune surveillance of hematological malignancies. HighlightsO_LISingle-cell resolved TCR profiling maps rare tumor-reactive T cells in the bone marrow of multiple myeloma (MM) and acute myeloid leukemia (AML) reveals conserved transcriptional programs C_LIO_LIA shared immunopeptidome across MM and AML includes noncanonical epitopes from nuORFs and idiotype sequences C_LIO_LIConserved tumor antigens elicit convergent T cell responses across patients C_LI O_LIA TCR fitness model predicts tumor specificity in bone marrow lymphocytes and stratifies immunotherapy response in both hematological malignancies C_LI

immunology↗

Multiparent Recombinant Inbred lines crossed to a tester provide novel insights into sources of cis and trans regulation of gene expression

We propose crossing multi-parent recombinant-inbred-lines (RILs) to a common tester and measuring allele specific gene expression in the offspring. Testing whether allelic imbalance between two RIL x Tester crosses is equal, is a test of cis or trans depending on the RIL alleles compared. The study design also enables to separate two sources of trans variation, genetic and environmental, detected via interactions with cis effects. Examining these components of regulatory variation, we demonstrate this approach in a long-read RNA-seq experiment in female abdominal tissue at two time points in Drosophila melanogaster. Among the 40% of all loci that show evidence of genetic variation in cis, trans effects due to the environment are detectable in 31% of loci and trans effects due to genetic background are detectable in 19% of loci with little overlap in sources of trans variation. The loci identified in this study are associated with loci previously reported to exhibit genetic variation in gene expression in a range of tissues and large population samples, suggesting that there is consistent variation for genetic regulation of gene expression. We show that eleven loci in a QTL for thermotolerance, previously shown to differ in expression based on temperature, have evidence for regulation of gene expression regardless of the environment, including Cpr67B, a cuticular protein suggesting a potential functional role for standing variation in gene expression. This study provides a blueprint for efficiently identifying regulatory variation in gene expression, as the tester design maximizes cis variation and enables the efficient assessment of all pairs of RIL alleles relative to the tester, a much smaller study compared to the pairwise direct assessment.

genetics↗

Pervasive fitness trade-offs revealed by rapid adaption in large experimental populations of Drosophila melanogaster

Trade-offs are an inherent feature of organismal biology that are expected play a fundamental role in the evolution of natural populations. Efforts to quantify trade-offs are largely confined to phenotypic measurements and the identification of negative genetic-correlations among fitness-relevant traits. Here, we use time-series genomic data collected during experimental evolution in large, genetically diverse populations of Drosophila melanogaster to directly measure the manifestation of trade-offs in response to fluctuating selection on ecological timescales. Specifically, we first conducted a lab-based selection experiment to quantify a genome-wide signal of antagonistic pleiotropy elicited in response to shifting population densities and associated with reproduction and stress tolerance selection. In doing so, we identified a putative role of two cosmopolitan inversions in these trade-offs. We then conducted an independent experiment to show that a simple manipulation of increasing population density under controlled lab-based conditions identified loci that are relevant to selection during population expansion and collapse in a complex, semi-natural setting. In concert, our results reveal how adaptation in complex, natural environments can be coarse-grained in such a manner to drive repeatable and predictable patterns of genomic variation, and further add credence to models positing a role of generic fitness trade-offs in the maintenance of variation in natural populations.

evolutionary biology↗

Dominance reversal protects large-effect resistance polymorphisms in temporally varying environments

Large-effect functional genetic variation is commonly found in natural populations, even though natural selection should erode such variants. Theory suggests that under fluctuating selective pressures, beneficial reversal of dominance - where alleles are dominant when beneficial and recessive when deleterious - can protect these loci from selection, allowing them to persist. However, empirical evidence for this mechanism remains elusive because testing requires direct measurements of selection and dominance in natural conditions. Here, we show that insecticide-resistant alleles at the Ace locus in Drosophila melanogaster persist worldwide at intermediate frequencies and exhibit beneficial reversal of dominance. By combining laboratory and large-scale field mesocosm experiments with insecticide manipulation, and mathematical modeling, we show that the benefits of the resistant Ace alleles are dominant while their fitness costs recessive. We further show that fluctuating insecticide selection generates chromosome-scale genomic perturbations at sites linked to the resistant Ace alleles, revealing broader genomic consequences of this mechanism. Overall, our results suggest that beneficial reversal of dominance contributes to the maintenance of functional genetic variation and impacts patterns of genomic diversity via linked fluctuating selection.

evolutionary biology↗

Environment and diet shape the geography-specific Drosophila melanogaster microbiota composition

Geographic and environmental variation in the animal microbiota can be directly linked to the evolution and wild fitness of their hosts but often appears to be disordered. Here, we sought to better understand patterns that underlie wild variation in the microbiota composition of Drosophila melanogaster. First, environmental temperature predicted geographic variation in fly microbial communities better than latitude did. The microbiota also differed between wild flies and their diets, supporting previous conclusions that the fly microbiota is not merely a reflection of diet. Flies feeding on different diets varied significantly in their microbiota composition, and flies sampled from individual apples were exceptionally depauperate for the Lactic Acid Bacteria (LAB), a major bacterial group in wild and laboratory flies. However, flies bore significantly more LAB when sampled from other fruits or compost piles. Follow-up analyses revealed that LAB abundance in the flies uniquely responds to fruit decomposition, whereas other microbiota members better indicate temporal seasonal progression. Finally, we show that diet-dependent variation in the fly microbiota is associated with phenotypic differentiation of fly lines collected in a single orchard. These last findings link covariation between the flies dietary history, microbiota composition, and genetic variation across relatively small (single-orchard) landscapes, reinforcing the critical role that environment-dependent variation in microbiota composition can play in local adaptation and genomic differentiation of a model animal host. SIGNIFICANCE STATEMENTThe microbial communities of animals influence their hosts evolution and wild fitness, but it is hard to predict and explain how the microbiota varies in wild animals. Here, we describe that the microbiota composition of wild Drosophila melanogaster can be ordered by temperature, humidity, geographic distance, diet decomposition, and diet type. We show how these determinants of microbiota variation can help explain lactic acid bacteria (LAB) abundance in the flies, including the rarity of LAB in some previous studies. Finally, we show that wild fly phenotypes segregate with the flies diet and microbiota composition, illuminating links between the microbiota and host evolution. Together, these findings help explain how variation in microbiota compositions can shape an animals life history.

microbiology↗

Drosophila melanogaster pigmentation demonstrates adaptive phenotypic parallelism but genomic unpredictability over multiple timescales

Populations are capable of responding to environmental change over ecological timescales via adaptive tracking. However, the translation from patterns of allele frequency change to rapid adaptation of complex traits remains unresolved. We used abdominal pigmentation in Drosophila melanogaster as a model phenotype to address the nature, genetic architecture, and repeatability of rapid adaptation in the field. We show that D. melanogaster pigmentation evolves as a highly parallel and deterministic response to shared environmental gradients across latitude and season in natural North American populations. We then experimentally evolved replicate, genetically diverse fly populations in field mesocosms to remove any confounding effects of demography and/or cryptic structure that may drive patterns in wild populations; we show that pigmentation rapidly responds, in parallel, in fewer than fifteen generations. Thus, pigmentation evolves concordantly in response to spatial and temporal climatic gradients. We next examined whether phenotypic differentiation was associated with allele frequency change at loci with established links to genetic variance in pigmentation in natural populations. We found that across all spatial and temporal scales, phenotypic patterns were associated with variation at pigmentation-related loci, and the sets of genes we identified in each context were largely nonoverlapping. Therefore, our findings suggest that parallel phenotypic evolution is associated with distinct components of the polygenic architecture shifting across each environmental gradient to produce redundant adaptive patterns.

evolutionary biology↗

Humidity determines penetrance of a latitudinal gradient in genetic selection on the microbiota by Drosophila melanogaster

The fruit fly Drosophila melanogaster is a model for understanding how hosts and their microbial partners interact as the host adapts to wild environments. These interactions are readily interrogated because of the low taxonomic and numeric complexity of the flies bacterial communities. Previous work has established that host genotype, the environment, diet, and interspecies microbial interactions can all influence host fitness and microbiota composition, but the specific processes and characters mediating these processes are incompletely understood. Here, we compared the variation in microbiota composition between wild-derived fly populations when flies could choose between the microorganisms in their diets and when flies were reared under environmental perturbation (different humidities). We also compared the colonization of the resident and transient microorganisms. We show that the ability to choose between microorganisms in the diet and the environmental condition of the flies can influence the relative abundance of the microbiota. There were also key differences in the abundances of the resident and transient microbiota. However, the microbiota only differed between populations when the flies were reared at humidities at or above 50% relative humidity. We also show that elevated humidity determined the penetrance of a gradient in host genetic selection on the microbiota that is associated with the latitude the flies were collected from. Finally, we show that the treatment-dependent variation in microbiota composition is associated with variation in host stress survival. Together, these findings emphasize that host genetic selection on the microbiota composition of a model animal host can be patterned with the source geography, and that such variation has the potential to influence their survival in the wild. ImportanceThe fruit fly Drosophila melanogaster is a model for understanding how hosts and their microbial partners interact as hosts adapt in wild environments. Our understanding of what causes geographic variation in the fruit fly microbiota remains incomplete. Previous work has shown that the D. melanogaster microbiota has relatively low numerical and taxonomic complexity. Variation in the fly microbiota composition can be attributed to environmental characters and host genetic variation, and variation in microbiota composition can be patterned with the source location of the flies. In this work we explored three possible causes of patterned variation in microbiota composition. We show that host feeding choices, the host niche colonized by the bacteria, and a single environmental character can all contribute to variation in microbiota composition. We also show that penetrance of latitudinally-patterned host genetic selection is only observed at elevated humidities. Together, these results identify several factors that influence microbiota composition in wild fly genotypes and emphasize the interplay between environmental and host genetic factors in determining the microbiota composition of these model hosts.

microbiology↗

A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next - generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct [~]10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimers disease and healthy brain ageing based on [~]4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 m isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease.

neuroscience↗

Continuously fluctuating selection reveals extreme granularity and parallelism of adaptive tracking

Temporally fluctuating environmental conditions are a ubiquitous feature of natural habitats. Yet, how finely natural populations adaptively track fluctuating selection pressures via shifts in standing genetic variation is unknown. We generated high-frequency, genome-wide allele frequency data from a genetically diverse population of Drosophila melanogaster in extensively replicated field mesocosms from late June to mid-December, a period of [~]12 generations. Adaptation throughout the fundamental ecological phases of population expansion, peak density, and collapse was underpinned by extremely rapid, parallel changes in genomic variation across replicates. Yet, the dominant direction of selection fluctuated repeatedly, even within each of these ecological phases. Comparing patterns of allele frequency change to an independent dataset procured from the same experimental system demonstrated that the targets of selection are predictable across years. In concert, our results reveal fitness-relevance of standing variation that is likely to be masked by inference approaches based on static population sampling, or insufficiently resolved time-series data. We propose such fine-scaled temporally fluctuating selection may be an important force maintaining functional genetic variation in natural populations and an important stochastic force affecting levels of standing genetic variation genome-wide.

evolutionary biology↗

Head and neck cancer cells terminally differentiate reflecting their tissue of origin: a rationale for differentiation therapies

BackgroundHuman papillomavirus-negative head and neck squamous cell carcinoma (HNSCC) is a highly malignant disease with high death rates that have remained substantially unaltered for decades. Therefore, new treatment approaches are urgently needed. Human papillomavirus-negative tumors harbor areas of terminally differentiated tissue that are characterized by cornification. Dissecting this intrinsic ability of HNSCC cells to irreversibly differentiate into non-malignant cells may have striking tumor-targeting potential. MethodsWe modeled the cornification of HNSCC cells in a primary spheroid model and analyzed the mechanisms underlying differentiation by RNA-seq and ATAC-seq. Results were verified by immunofluorescence using human HNSCC tissue of distinct anatomical locations. ResultsHNSCC cell differentiation was accompanied by cell adhesion, proliferation stop, diminished tumor-initiating potential in immunodeficient mice, and activation of a wound healing-associated signaling program. Small promoter accessibility increased despite overall chromatin closure. Differentiating cells upregulated KRT17 and cornification markers. Although KRT17 represents a basal stem-cell marker in normal mucosa, we confirm KRT17 to represent an early differentiation marker in HNSCC tissue and dysplastic mucosa. Cornification was observed to frequently surround necrotic and immune-infiltrated areas in human tumors, indicating an involvement of pro-inflammatory stimuli. Indeed, inflammatory mediators were found to activate the HNSCC cell differentiation program. ConclusionsDistinct cell differentiation states create a common tissue architecture in normal mucosa and HNSCCs. Our data demonstrate a loss of cell malignancy upon HNSCC cell differentiation, indicating that targeted differentiation approaches may be therapeutically valuable. Moreover, we describe KRT17 to be a candidate biomarker for HNSCC cell differentiation and early tumor detection.

cancer biology↗

An Ancestral Balanced Inversion Polymorphism Confers Global Adaptation

Since the pioneering work of Dobzhansky in the 1930s and 1940s, many chromosomal inversions have been identified but how they contribute to adaptation remains poorly understood. In Drosophila melanogaster, the widespread inversion polymorphism In(3R)Payne underpins latitudinal clines in fitness traits on multiple continents. Here, we use single-individual whole-genome sequencing, transcriptomics and published sequencing data to study the population genomics of this inversion on four continents: in its ancestral African range and in derived populations in Europe, North America, and Australia. Our results confirm that this inversion originated in sub-Saharan Africa and subsequently became cosmopolitan; we observe marked monophyletic divergence of inverted and non-inverted karyotypes, with some substructure among inverted chromosomes between continents. Despite divergent evolution of this inversion since its out-of-Africa migration, derived non-African populations exhibit similar patterns of long-range linkage disequilibrium between the inversion breakpoints and major peaks of divergence in its center, consistent with balancing selection and suggesting that the inversion harbors alleles that are maintained by selection on several continents. Using RNA-seq we identify overlap between inversion-linked SNPs and loci that are differentially expressed between inverted and non-inverted chromosomes. Expression levels are higher for inverted chromosomes at low temperature, suggesting loss of buffering or compensatory plasticity and consistent with higher inversion frequency in warm climates. Our results suggest that this ancestrally tropical balanced polymorphism spread around the world and became latitudinally assorted along similar but independent climatic gradients, always being frequent in subtropical/tropical areas but rare or absent in temperate climates.

evolutionary biology↗

How predictable is rapid evolution?

Although evolution is historically considered a slow, gradual process, it is now clear that evolution can occur rapidly over generational timescales. It remains unclear both how predictable rapid evolution is and what timescales are ecologically relevant due to a paucity of longitudinal studies. We use a common garden approach to measure genetic-based change in complex, fitness-associated traits that are important for climatic adaptation in wild Drosophila over multiple timescales: an estimated 1-16 generations within each year and 48-89 generations over five consecutive years. Evolution is fast and pervasive with parallel patterns of rapid evolution in three distinct locations that span 4{o} latitude. Developmental time evolves consistently across seasons with flies collected in spring developing faster than those collected in autumn. The evolutionary trajectory of stress traits (heat knockdown and starvation) depends on the severity of the preceding winter: harsh winters result in a predictable evolutionary trajectory with high stress tolerance in spring flies that declines in the subsequent generations across the summer. Flies collected after mild winters do not evolve in a predictable pattern but may utilize an alternative strategy as plasticity for chill coma recovery and starvation evolves across seasons. Overall, winter severity determines the predictability of rapid seasonal evolution, but there are also long-term shifts in the phenotypic correlations and allele frequencies that indicate long-term population changes that have broader implications for how organisms respond to the changing climate. Significance StatementAdaptive tracking may result in rapid evolution over short timescales, but the repeatability and predictability of rapid adaptation is less well resolved without long-term, multi-year analyses. Here, we collect wild flies at regular intervals across five years to determine what traits evolve consistently over seasons and which environmental variables predict this rapid evolution. Traditional temperate seasonal patterns of harsh winters are crucial for normal selection patterns, although independently changing phenotypic and genetic correlations help the populations respond to long-term shifts over years, particularly in response to heat stress. This has the implication that populations may be flexible within certain genetic constraints to adapt to changing climatic temperatures.

evolutionary biology↗

Histone methylation regulates reproductive diapause in Drosophila melanogaster

Fluctuating environments threaten fertility and viability. To better match the immediate, local environment, many organisms adopt alternative phenotypic states, a phenomenon called "phenotypic plasticity". Local adaptation shapes phenotypic plasticity: natural populations that predictably encounter fluctuating environments tend to be more plastic than conspecific populations that encounter a constant environment. Despite pervasive evidence of such "adaptive phenotypic plasticity," the evolution of the gene regulatory mechanisms underlying plasticity remains poorly understood. Here we test the hypothesis that environment-dependent phenotypic plasticity is mediated by epigenetic factors and that these epigenetic factors vary across naturally occurring genotypes. To test these hypotheses, we exploit the adaptive reproductive arrest of Drosophila melanogaster females, called diapause. Using an inbred line from a natural population with high diapause plasticity, we demonstrate that diapause is determined epigenetically: only a subset of genetically identical individuals enter diapause and this diapause plasticity is epigenetically transmitted for at least three generations. Upon screening a suite of epigenetic marks, we discovered that the active histone marks H3K4me3 and H3K36me1 are depleted in diapausing ovaries. Using ovary-specific knockdown of histone mark writers and erasers, we demonstrate that H3K4me3 and H3K36me1 depletion promotes diapause. Given that diapause is highly polygenic - distinct suites of alleles mediate diapause plasticity across distinct genotypes - we investigated the potential for genetic variation in diapause-determining epigenetic marks. Specifically, we asked if these histone marks were similarly depleted in diapause of a geographically distinct, comparatively less plastic genotype. We found evidence of genotypic divergence in both the gene expression program and histone mark abundance. This study reveals chromatin determinants of adaptive plasticity and suggests that these determinants are genotype-dependent, offering new insight into how organisms may exploit and evolve epigenetic mechanisms to persist in fluctuating environments.

genetics↗

Elemental stoichiometry and insect chill tolerance: Evolved and plastic changes in organismal Na+ and K+ content in Drosophila

Acclimation and evolutionary adaptation can produce phenotypic change that allows organisms to cope with challenges like those associated with climate change. Determining the relative contributions of acclimation and adaptation is of central importance to understanding animal responses to change. Rates of evolution have traditionally been considered slow relative to ecological processes that shape biodiversity. Many organisms nonetheless show patterns of spatial genetic variation suggestive of adaptation and some evidence is emerging that adaptation can act sufficiently fast to allow phenotypic tracking in response to environmental change ( adaptive tracking). In Drosophila, both plastic and evolved differences in chill tolerance are associated with ionoregulation. Here we combine acclimation, latitudinal field collections, and a replicated field experiment to assess the effects of acclimation and adaptation on chill coma recovery and elemental (Na and K) stoichiometry in both sexes of Drosophila melanogaster. Acclimation and spatial adaptation both shape chill coma recovery, with acclimation producing the greatest magnitude response. Leveraging knowledge on the physiological mechanisms that underlie variation in chill tolerance traits, we find that the relationship between K content and chill tolerance differs among flies acclimated vs. adapted to cold. Taken together, these data reinforce the importance of acclimation in responses to abiotic challenges and illustrate that the mechanisms of phenotypic change can differ between acclimation and basal tolerance adaptation.

evolutionary biology↗