Biology subjects

Scott, C. B.

Publications and source records attributed to Scott, C. B..

9 recordsLinked to original sources

bioRxiv2026

Host traits, phylogeny, and symbiont identity explain variation in colony-level symbiont switching across reef-building corals

Flexibility in the coral-algal symbiosis has been proposed as a mechanism by which coral colonies may acclimatize to shifting environmental conditions, yet the rules governing when and why switching occurs remain unresolved. Here, I compile longitudinal data spanning 59 coral species, 26 years, and 95 globally distributed reefs to estimate switching probability at the colony-level across directional environmental change and thermal variability. Switching was neither universal nor random: the identity of the resident symbiont was the strongest predictor of switching, with Cladocopium-dominated and mixed communities showing the greatest flexibility. Transition probabilities were asymmetrical, with shifts toward Durusdinium consistently more probable than shifts away, regardless of starting genus. Among host species- level effects, morphological traits best explained switching propensity along changing environmental conditions, while both traits and phylogenetic history explained sensitivity to thermal variability, suggesting that these two dimensions of abiotic environments impose distinct selective pressures on the symbiosis. Most switching was ultimately transient; colonies had a 78% chance of reverting back to their original symbiont in the following year. Together, these results challenge the assumption that increased environmental variability and rising temperatures universally correlate with higher switching rates, and suggest instead that host traits, phylogeny, and resident symbiont identity may help identify the subset of taxa for which flexibility represents a viable acclimatization strategy under climate stress.

ecology↗

bioRxiv2026

Sex-specific effects of exercise on motor coordination and extended basal ganglia physiology.

Exercise broadly affects the basal ganglia, brain structures involved in motor coordination. Exercise-induced changes in these regions can improve pathological conditions such as Parkinsons disease and substance use disorders. Importantly, biological sex is a significant factor in the effects of exercise and in the presentation of these basal ganglia-related conditions. Here, we find surprising sex differences in exercises influence over motor coordination and neural activity across three extended basal ganglia structures: dorsomedial striatum cholinergic interneurons (CINs), substantia nigra pars compacta (SNc) dopaminergic neurons, and caudal pedunculopontine nucleus (PPN) cholinergic neurons. Using voluntary wheel running, accelerating rotarod, ex vivo electrophysiology, and morphological reconstructions, we found that exercise enhances motor coordination, increases SNc excitability, and strengthens excitatory input onto the PPN selectively in female mice. By contrast, exercise increases spontaneous firing rate and reduces dendritic complexity selectively in male CINs. These data reveal sex-specific exercise effects correlated across behavioral and cellular levels. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/720719v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@d0f755org.highwire.dtl.DTLVardef@11e2335org.highwire.dtl.DTLVardef@199a591org.highwire.dtl.DTLVardef@44e4d9_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIOne week of exercise enhances motor coordination in females but not males C_LIO_LIExercise increases SNc excitability and excitatory input onto the PPN in females C_LIO_LIExercise increases dorsomedial striatal cholinergic neurons activity in males C_LIO_LIBaseline sex differences in morphology of striatal cholinergic and SNc neurons C_LI

neuroscience↗

bioRxiv2026

Environment and host infection history jointly predict disease risk in a multi-pathogen system

Forecasting disease epidemics may require considering both abiotic and biotic conditions. Abiotic conditions can influence pathogen dispersal, survival, and infection, while prior infection by one pathogen species can alter host susceptibility to subsequent pathogens, creating historical contingencies. Yet, the relative importance of environmental conditions, within-host pathogen interactions, and their interplay in predicting seasonal disease dynamics remains underexplored. We analyzed approximately 30,000 plant-level observations of three foliar fungal diseases on the grass species tall fescue in a North Carolina old field, and meteorological data, from 2017-2024. Using such datasets to make ecological predictions that are accurate and interpretable may require multiple modeling approaches. Temporally explicit random forest models predicted future disease with over 80% accuracy for two of the three diseases and revealed environmental thresholds for disease prediction in environmental variables including temperature and humidity. Survival analyses showed that pathogen-pathogen interactions rivaled environmental conditions in predicting risk of crown rust, which was strongly facilitated by prior anthracnose infection. Across all pathogens, Bayesian hierarchical models recovered evidence that facilitative interactions between coinfecting pathogens were modulated by effects of environmental conditions, particularly temperature. Together, these complementary approaches show that a host's current disease state can matter as much as its environment in predicting disease, identify key environmental factors associated with disease risk, and show that modulation of environmental drivers by pathogen coinfections can improve predictions of seasonal disease epidemics. Other disease forecasts may be improved by accounting not just for environmental drivers, but also how those drivers propagate through pathogen species interactions.

ecology↗

bioRxiv2025

The Acropora millepora microbiome is predicted by algal symbionts, host genetics, and environment

The coral microbiome is a critical component of coral health and resilience, yet it is unclear what factors drive coral microbiome composition, especially within the context of coral bleaching. Here, we use whole genome sequencing data combined with a machine learning approach (RDAforest) to assess predictors of the microbiome in 208 colonies of Acropora millepora from 12 reef sites in the Central Great Barrier Reef during a 2016 bleaching event. We characterized microbiome variation using k-mers. While some environmental variables, such as chlorophyll seasonal range and maximum degree heating weeks, were associated with microbiome composition, we find that host genetics and dominant photosymbionts were more powerful predictors. In contrast, bleaching score had negligible predictive power. The corals microbiome therefore correlates with dominant photosymbiont identity even during a bleaching event. The association of the microbiome with the environment suggests that the coral microbiome can serve as a proxy for environmental variation when environment cannot be measured directly, which may be especially useful in ancient DNA studies.

evolutionary biology↗

bioRxiv2025

The microbial fingerprint: fine-scale environmental, genetic, and temporal factors drive the reef metagenome during coral spawning

Understanding the stability of microbial community assembly on coral reefs is crucial for determining their response to changing environments. Here, we evaluate how the marine sediment, water column, and mountainous star coral (Orbicella faveolata) metagenomic communities shift over temporal, spatial, and genetic gradients, centered on the annual coral spawning event on St. Croix, USVI. Using low-coverage shotgun sequencing and a reference-free approach, we characterized metagenomic communities and additionally report 15 metagenome-assembled genomes from environmental samples. We show that diel time can be as important as kilometer-scale distance in structuring the coral-associated and marine sediment community structure, albeit with other highly local factors (genotype, within-reef location) driving most variation. Through multivariate machine learning methods, we find several taxa and metabolic pathways enriched over time, where broad metagenomic community shifts may be linked with concurrent temperature increase or the annual coral spawning event. As understanding the coral microbiome in the context of its environment becomes increasingly important, our research underscores the importance of small-scale variation, both spatially and temporally, in structuring coral reef metagenomic communities.

ecology↗

bioRxiv2024

Inhibitory basal ganglia nuclei differentially innervate pedunculopontine nucleus subpopulations and evoke opposite motor and valence behaviors.

The canonical basal ganglia model predicts that the substantia nigra pars reticulata (SNr) and the globus pallidus externa (GPe) will have specific effects on locomotion: the SNr inhibiting locomotion and the GPe enhancing it. In this study, we use in vivo optogenetics to show that the GPe exerts non-canonical effects on locomotion while the SNr has no gross motor impact through inhibition of the PPN. We also show that these structures mediate opposing effects on reward. To understand how these structures differentially modulate the PPN, we use ex vivo whole-cell recording with optogenetics to comprehensively dissect the SNr and GPe synaptic connections to regionally- and molecularly-defined populations of PPN neurons. The SNr inhibits all PPN subtypes, but most strongly inhibits caudal glutamatergic neurons. The GPe selectively inhibits caudal glutamatergic and GABAergic neurons, avoiding both cholinergic and rostral cells. This circuit characterization reveals non-canonical basal ganglia pathways for locomotion and valence. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/606694v2_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@11e6a13org.highwire.dtl.DTLVardef@1c63735org.highwire.dtl.DTLVardef@5282b7org.highwire.dtl.DTLVardef@103da4a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

The battle of the sexes in humans is highly polygenic

Sex-differential selection (SDS), which occurs when the fitness effects of alleles differ between males and females, can have profound impacts on the maintenance of genetic variation, disease risk, and other key aspects of natural populations. Because the sexes mix their autosomal genomes each generation, quantifying SDS is not possible using conventional population genetic approaches. Here, we introduce a novel method that exploits subtle sex differences in haplotype frequencies resulting from SDS acting in the current generation. Using data from 300K individuals in the UK Biobank, we estimate the strength of SDS throughout the genome. While only a handful of loci under SDS are individually significant, we uncover polygenic signals of genome-wide SDS for both viability and fecundity. An interesting life-history tradeoff emerges: alleles that increase viability more in one sex increase fecundity more in the other sex. Lastly, we find evidence of SDS on fecundity acting on alleles affecting arm fat-free mass. Taken together, our findings connect the long-standing evidence of SDS acting on human phenotypes with its impact on the genome. Significance statementSelection often acts differently on females and males, as evidenced by the striking sexual dimorphism found in many taxa. As a result, alleles can have different fitness effects in each sex. Consequences can include higher levels of genetic variation and higher disease burdens in populations. This study introduces a novel method to quantify this sex-differential selection (SDS) and reveals that it acts throughout the human genome. We discovered a life history tradeoff between survival and fecundity in females and males and that SDS on fecundity acts on alleles affecting arm fat-free mass.

evolutionary biology↗

bioRxiv2024

From juveniles to giants: Drivers of holobiont assembly in massive Porites

The fate of coral reefs in response to climate change depends on their ability to adapt to new environments. The coral animal is buffered from environmental stress by its algal endosymbionts and microbial partners (together, the "holobiont"). However, the flexibility of holobiont community assembly is not well understood, making it difficult to estimate its contribution to coral adaptation. To clarify these processes, we genetically profiled holobiont components (coral, algal symbiont, and microbiome) of massive Porites sampled across two size classes (>2m and <30cm) and ecologically distinct reef sites near Orpheus and Pelorus Islands, Australia. We recovered five major genetic clusters in the coral host, with additional splits within them potentially defining up to ten distinct subclusters. We estimated the relative contributions of the host genetic structure, site, and size class to holobiont community composition. Host genetic structure was the primary driver of both Symbiodiniaceae and microbial communities, indicating strong holobiont specificity in cryptic lineages. In addition, the microbial community was associated with reef site and size class, unlike Symbiodiniaceae that were not significantly affected by either factor. As environmentally segregated, cryptic genetic lineages emerge as a common feature of scleractinian corals, these results emphasize that failure to assess cryptic genetic structure of the coral host may lead to dramatic overestimation of holobiont flexibility.

ecology↗

bioRxiv2022

Consensus Label Propagation with Graph Convolutional Networks for Single-Cell RNA Sequencing Cell Type Annotation

MotivationSingle-cell RNA sequencing (scRNA-seq) data, annotated by cell type, is useful in a variety of downstream biological applications, such as profiling gene expression at the single-cell level. However, manually assigning these annotations with known marker genes is both time-consuming and subjective. ResultsWe present a Graph Convolutional Network (GCN) based approach to automate the annotation process. Our process builds upon existing labeling approaches, using state-of-the-art tools to find cells with highly confident label assignments through consensus and spreading these confident labels with a semi-supervised GCN. Using simulated data and two scRNA-seq data sets from different tissues, we show that our method improves accuracy over a simple consensus algorithm and the average of the underlying tools. We also compare our method to a non-parametric neighbor majority approach, showing comparable results. We then demonstrate that our GCN method allows for feature interpretation, identifying important genes for cell type classification. We present our completed pipeline, written in PyTorch, as an end-to-end tool for automating and interpreting the classification of scRNA-seq data. AvailabilityOur code for conducting the experiments in this paper and using our model is available at https://github.com/lewinsohndp/scSHARP Contactd_lewinsohn@coloradocollege.edu Supplementary informationSupplementary data are available at Journal Name online.

bioinformatics↗