Biology subjects

Marshall, D.

Publications and source records attributed to Marshall, D..

12 recordsLinked to original sources

bioRxiv2026

Macro evolutionary patterns do not predict micro evolutionary trajectories

As the worlds oceans change in response to climate change, phytoplankton communities will adapt to warmer, more stratified surface waters via plasticity, evolution, and range shifts. Current global ocean models assume that size structured phytoplankton communities have fixed trait relationships, and as a result generally predict that smaller size classes will become more dominant globally. However, this general expectation fails to consider how intra-species trait tradeoffs may operate orthogonally from large-scale inter-species tradeoffs--allowing for alternative evolutionary pathways given the limits and/or possibilities available to ancestral populations. To identify evolutionary pathways phytoplankton populations might take, we develop a novel modeling framework that combines a trait-based phytoplankton quota model with stochastic evolution (ecoTRACE). EcoTRACE explicitly decouples key phytoplankton traits from interspecific allometric relationships, allowing for novel phenotypes to emerge. We validated ecoTRACE against a long-term artificial size selection experiment on Dunaliella tertiolecta. We show that ecoTRACE captures multi-dimensional evolved phenotypes that quota models based on interspecific relationships fail to reproduce. Under fluctuating multi-stressor growth, model populations evolve phenotypic plasticity that deviates from predicted interspecific allometric relationships. EcoTRACE provides a framework for generating hypotheses as to the evolutionary trajectories that phytoplankton will experience in a warmer, more variable ocean.

microbiology↗

bioRxiv2025

Cross-modal quality transfer: enhancing MEG spatial resolution using BOLD-fMRI and Explainable machine learning.

Purpose:1Blood-oxygen-level-dependent functional MRI (BOLD-fMRI) and magnetoencephalog-raphy (MEG) offer complementary insights into brain function, with BOLD-fMRI providing high spatial resolution and MEG offering high temporal sensitivity. This study aimed to enhance MEGs spatial resolution through learning inter-modal relationships via data-driven fusion with BOLD-fMRI using explainable machine learning (xML). MethodsMEG and BOLD-fMRI data were collected for sixteen participants watching the same naturalistic visual stimulus. MEG signals were filtered into standard frequency bands and processed to match the haemodynamic response. Data were then decomposed using Tenso-rial Independent Component Analysis (TICA), yielding 250 MEG (25 per frequency band) and 30 BOLD-fMRI components. A set of Extreme Gradient Boosted tree (XGBoost) models were trained to predict MEG component activity from downsampled BOLD-fMRI components. The models with best-performing configuration of hyperparameters at this resolution were then used to generate voxelwise upsampled MEG maps using the natively higher-resolution BOLD-fMRI data. Performance was compared to trilinear interpolation using R{superscript 2}, mean squared error (MSE), and structural similarity index (SSI). Model inter-pretability was enhanced by generating Shapley values (SHAP), describing relationships between input data and model output. ResultsModels trained on 6mm3 data achieved high predictive performance on previously unseen data (R{superscript 2} = 0.80, MSE = .07). Using higher-resolution 2mm3 BOLD-fMRI data, MEG activ-ity was upsampled to 2mm3, resulting in more detailed image, while maintaining reasonable congruence to naive interpolation (R{superscript 2} = .81, MSE = .06). ConclusionsThis work demonstrates that explainable machine learning enables spatial super-resolution of MEG maps via BOLD-fMRI-informed quality transfer, enabling enhancement of spatial resolution, and offering improved localization, as well as means of generating data-driven insights into neurovascular coupling.

neuroscience↗

bioRxiv2025

The Effects of Intraspecies and Interspecies Competition on Genetic Device Construction and Performance

Future genetic devices expressed in microbes need to be tested in complex environments containing multiple organisms to expand their usability. We sought to determine if genetic parts designed for monoculture are predictable when used in co-culture by testing constitutive Anderson promoters driving expression of chromoproteins from a plasmid. In Escherichia coli monoculture a high copy number origin of replication causes stochastic expression regardless of promoter strength, and high Anderson promoter strength leads to selection for inactivating mutations, resulting in inconsistent chromoprotein expression. Medium and low strength Anderson promoters function more predictably in E. coli monoculture but experience an increase in inactivating mutations when grown in co-culture over many generations with Pseudomonas aeruginosa. Expression from native promoters instead of Anderson promoters can lead to stable expression in a complex wastewater culture. Overall, we show intraspecies selection for inactivating mutations due to a competitive growth advantage for E. coli that do not express the genetic device compared to their peers that retain the functional device. We show additional interspecies selection against the functional device when E. coli is co-cultured with another organism. Together, these two selection pressures create a significant barrier to genetic device function in microbial communities that we overcome by utilize a native E. coli promoter. Future strategies for genetic device design in microorganisms that need to function in a complex microbial environment should focus on native promoters and/or strategies that give the microorganism carrying the device a selective or growth advantage. ImportanceFirst generation biotechnology focused on genetic devices designed for use in monoculture conditions. Next generation biotechnology devices will need to function in complex ecosystems with other organisms, so we sought to create conditions where the genetic device retained function when the organism carrying it is in co-culture with other organisms. We discovered that when the genetic device is a significant resource burden on the organism carrying the device mutations will be selected for due to intraspecies and interspecies selection pressures and the device will be rendered non-functional. Therefore, genetic device design for complex ecosystems in next generation biotechnology needs to balance functionality of the genetic device with the need to reduce resource burden on the organism carrying it.

synthetic biology↗

bioRxiv2024

Quantifying Feral Pig Interactions to Inform Disease Transmission Networks

Feral pigs threaten biodiversity in 54 countries worldwide and cause an estimated $120 billion of damage annually in the United States of America (USA). Feral pigs imperil over 600 native species and have directly driven 14 species into extinction. Moreover, feral pig populations pose a significant zoonotic disease threat to humans such as Japanese encephalitis, and act as reservoir for endemic pathogens such as Brucella and leptospirosis. Efforts to understand and control disease spread by feral pigs rely on models of social dynamics, how the animals interact with one another. Yet social dynamics are known to vary enormously from place to place, so knowledge generated for example in USA and Europe might not easily transfer to locations such as Australia. Here, we fill a continental gap in our understanding of feral pig social dynamics by developing a proximity-based social network analysis approach to rapidly assess social interactions using animal tracking data. This method, applied to the continent of Australia, included 146 GPS-monitored feral pigs, and revealed distinct patterns influenced by sex and season, with females demonstrating higher group cohesion (female-female) and males acting as crucial connectors between independent groups. Contact rates are remarkably high within groups, indicating rapid intra-group disease spread that contrasts with much slower potential for inter-group disease spread. Seasonal variations further complicate this dynamic, with contact rates being much higher in summer. The results show that, in Australia, targeting adult males in feral pig control programs could enhance efforts to contain disease outbreaks. Concern over the economic and human health impacts of animal diseases is higher than ever before. We urge a rapid global effort to use models of feral pig social interactions to develop efficient control strategies tailored to local conditions.

ecology↗

bioRxiv2024

A synergistic culture dependent and independent approach reveals a conserved wheat seed mycobiome

The occurrence of pathogenic fungal taxa associated with wheat (Triticum aestivum L.) seeds is well studied, but less is known about non-pathogenic taxa of the wheat seed mycobiome. The goal of our research is to characterize wheat seed fungal endophyte diversity with a synergistic culture dependent and independent experimental approach. Four publicly available winter wheat cultivars developed in the southeastern United States with varying phenotypic and disease resistance traits were examined over a period of two years: Catawba, Hilliard, Shirley, and USG 3640. Our culture dependent methods involving two nutrient media generated 645 fungal isolates representing twelve genera sampled from multiple cultivars. Metabarcoding analysis identified a broader range of fungal taxa and a greater number of unique sequences than culture dependent methods. When examining fungal diversity across cultivars and years, richness decreased in 2021 for both culture dependent and independent approaches. However, wheat seed fungal community structure was stable across cultivars and years. Our results highlight the importance of combining culture independent and dependent methods to capture and establish a diverse endophytic fungal catalog associated with the wheat seed and highlight areas where future culture dependent efforts can focus their efforts.

microbiology↗

bioRxiv2022

Copepod life history evolution under high and low food regimes

Copepods play a critical role in the carbon cycle of the planet - they mediate the sequestration of carbon into the deep ocean, and are the trophic link between phytoplankton and marine foodwebs. Global change stressors that decrease copepod productivity create the potential for catastrophic positive feedback loops. Accordingly, a growing list of studies examine the evolutionary capacity of copepods to adapt to the two primary stressors associated with global change: warmer temperatures and lower pH. But the evolutionary capacity of copepods to adapt to changing food regimes, the third major stressor associated with global change, remains unknown. We used experimental evolution to explore how a 10-fold difference in food availability affects life history evolution in the copepod, Tisbe sp. over two years, and spanning 30+ generations. Different food regimes evoked evolutionary responses across the entire copepod life history: we observed evolution in body size, size-fecundity relationships and offspring investment strategies. Our results suggest that changes to food regimes reshape life histories and that cryptic evolution in traits such as body size is likely. We demonstrate that evolution in response to changes in ocean productivity will alter consumer life histories, and may distort trophic links in marine foodchains. Evolution in response to changing phytoplankton productivity may alter the efficacy of the global carbon pump in ways that have not been anticipated until now.1

evolutionary biology↗

bioRxiv2022

Metabolic and demographic evolution in response to interspecific competition

Competition can drive rapid evolution which, in turn, alters the trajectory of ecological communities. The role of eco-evolutionary dynamics in ecological communities is increasingly well-appreciated, but a mechanistic framework for identifying the types of traits that will evolve, and their trajectories, is required. Metabolic theory makes explicit predictions about how competition should shape the evolution of metabolism and size but these predictions have gone largely untested, particularly in eukaryotes. We use experimental evolution of a eukaryotic phototroph to examine how metabolism, size, and demography coevolve under both inter- and intra-specific competition. We find that the focal species evolves a smaller body size in response to competition, reducing density-dependence and maximizing carrying capacity. Metabolic theory successfully predicted most of these adaptations, but we also find important departures from theory. Longer-term evolution (70 generations) led to Pareto improvements in both population growth rate and carrying capacity, suggesting that classic r-K trade-offs observed among species can be evaded within species. The evasion of this trade-off appeared to arise due to the rapid evolution of enhanced metabolic plasticity: lineages exposed to competition evolved more labile metabolisms that tracked resource availability more effectively than lineages that were competition-free. We predict that rapid evolution in both size and metabolism may be a ubiquitous feature of adaptation to changing resource regimes that occur via species invasions and environmental change.

ecology↗

bioRxiv2022

Density dependent environments can select for extremes of body size

Body size variation is an enigma. We do not understand why species achieve the sizes they do, and this means we also do not understand the circumstances under which gigantism or dwarfism is selected. We develop size-structured integral projection models to explore evolution of body size and life history speed. We make few assumptions and keep models simple: all functions remain constant across models except for the one that describes development of body size with age. We set sexual maturity to occur when size attains 80% of the asymptotic size, which is typical of a large mammal, and allow negative density dependence to only affect either reproduction or juvenile survival. Fitness - the quantity that is maximized by adaptive evolution - is carrying capacity in our models, and we are consequently interested in how it changes with size at sexual maturity, and how this association varies with development rate. The simple models generate complex dynamics while providing insight into the circumstances when extremes of body size evolve. The direction of selection leading to either gigantism or dwarfism crucially depends on the proportion of the population that is sexually mature, which in turn depends on how the development function determines the survivorship schedule. The developmental trajectories consequently interact with size-specific survival or reproductive rates to determine the best life history and the optimal body size emerges from that interaction. These dynamics result in trade-offs between different components of the life history, with the form of the trade-off that emerges depending upon where in the life history density dependence operates most strongly. Empirical application of the approach we develop has potential to help explain the enigma of body size variation across the tree of life.

evolutionary biology↗

bioRxiv2021

Long-term experimental evolution decouples size and production costs in Escherichia coli

Body size covaries with population dynamics across lifes domains. Theory holds that metabolism imposes fundamental constraints on the coevolution of size and demography. However, studies of interspecific patterns are confounded by other factors that covary with size and demography, and experimental tests of the causal links remain elusive. Here we leverage a 60,000-generation experiment in which Escherichia coli populations evolved larger cells to examine intraspecific metabolic scaling and correlations with demographic parameters. Metabolic theory successfully predicted the relations among size, metabolism, and maximum population density, with strong support for Damuths law of energy equivalence in this experiment. In contrast, populations of larger cells grew faster than those of smaller cells, contradicting the fundamental assumption that costs of production should increase proportionately with size. The finding that the costs of production are substantially decoupled from size requires re-examining the evolutionary drivers and ecological consequences of biological size more generally.

evolutionary biology↗

bioRxiv2020

Genetic variation for plant growth traits in a common wheat population is dominated by known variants and novel QTL

Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL. We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models. In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.

genetics↗

bioRxiv2020

The structure-fitness landscape of pairwise relations in generative sequence models

If disentangled properly, patterns distilled from evolutionarily related sequences of a given protein family can inform their traits - such as their structure and function. Recent years have seen an increase in the complexity of generative models towards capturing these patterns; from sitewise to pairwise to deep and variational. In this study we evaluate the degree of structure and fitness patterns learned by a suite of progressively complex models. We introduce pairwise saliency, a novel method for evaluating the degree of captured structural information. We also quantify the fitness information learned by these models by using them to predict the fitness of mutant sequences and then correlate these predictions against their measured fitness values. We observe that models that inform structure do not necessarily inform fitness and vice versa, contrasting recent claims in this field. Our work highlights a dearth of consistency across fitness assays as well as divergently provides a general approach for understanding the pairwise decomposable relations learned by a given generative sequence model.

bioinformatics↗

bioRxiv2019

Sequence based mapping identifies AWNS1, a candidate transcription repressor underlying awn suppression at the B1 locus in wheat

Awns are stiff, hair-like structures that grow from the spikelets of wheat (Triticum aestivum L.) and other grasses. In wild wheat relatives, awns play a role in seed dispersal. Awn suppression in domesticated wheat, where awns are shortened or even eliminated entirely, is variably adaptive with both awned and awnless types under widespread cultivation. Although the B1 locus on the long arm of chromosome 5A is a major determinant of awn suppression, no underlying gene or mechanism of action has been identified. Using association mapping, we identified a SNP marker located on the distal end of 5AL (5A28417) predictive of awn status in a panel of 640 U.S. winter wheat breeding lines, indicating that B1 was the determinant of awn suppression in this germplasm. Analysis of historical data available for the panel determined 5A28417 was also significantly associated with grain test weight. Evaluation of spike morphology and kernel traits was undertaken in a 341 RIL population developed from a cross between awned soft winter wheat cultivar LA95135 and awnless cultivar SS-MPV57. Awn suppression in the population co-segregated with 5A28417 and was co-located with QTL for number of spikelets per spike, kernel weight and kernel length. Fine-mapping located B1 to a region containing only two predicted genes, including a C2H2 zinc finger transcription factor 219 bp from 5A28417 that we named AWNS-A1. Deletions encompassing both genes were present in awned mutants of the awnless cultivar Brundage. Polymorphisms in the AWNS-A1 coding region were not observed in diverse wheat germplasm. However, sequencing of wheat lines representing different marker haplotypes in the surrounding region identified a deletion 3 kb downstream of AWNS-A1. A marker for this deletion was highly predictive of awn suppression in a collection of diverse wheat accessions, and indicates that AWNS-A1 is likely the major determinant of awn suppression in global wheat germplasm. AWNS-A1 is more highly expressed in developing spikes of awnless individuals, suggesting a mechanism for awn suppression.

genetics↗