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Morris, J.

Publications and source records attributed to Morris, J..

At least 19 recordsLinked to original sources

Prefrontal cortex resting-state connectivity is moderated by hunger expectations induced by a placebo intervention in healthy female participants.

Placebo effects, in which a patient's symptoms and subjective well-being improve in response to an inactive treatment, medication, or intervention (a placebo), are well known in clinical research. Basic research in human cognition and neuroscience has shown that these effects are linked to prognostic expectations of effectiveness and to recruitment of prefrontal cortex regions, including the medial (mPFC), ventromedial (vmPFC), and dorsolateral prefrontal cortex (dlPFC). Here, we examined how the intrinsic functional connectivity of these three brain regions at rest, in the absence of any explicit task, was affected by internal beliefs such as placebo-induced hunger expectations. We conducted a seed-based resting-state functional connectivity analysis in 60 healthy female participants who underwent a placebo intervention targeting their hunger. In line with previously published results, the intervention induced hunger expectations and biased hunger sensations. Importantly, these effects were underpinned by attenuated functional connectivity between the mPFC and the angular gyrus within the default mode network the more participants expected the placebo to decrease their hunger. Hunger-increasing expectations attenuated connectivity between the vmPFC and the dm/dlPFC within the frontoparietal network and increased connectivity between the dlPFC and the thalamus. These results suggest that placebo-induced hunger expectations shift the way the prefrontal cortex connects to other brain regions associated with valuation, cognitive control, and interoception. This evidence sheds light on how the brain may translate incoming sensory information into biased sensations under placebo conditions and improves our understanding of the neural and psychological factors that influence a person's response to a placebo.

neuroscience↗

Metabarcode and transcriptome datasets of Pinus sylvestris to assess fungal phyllosphere and disease dynamics.

Understanding how host-microbiome interactions influence tree disease is critical for understanding forest resilience. Here, we present foliar microbiome ITS2 metabarcoding transcriptomic datasets from Pinus sylvestris to investigate susceptibility to Dothistroma needle blight (DNB), a globally important foliar disease caused by Dothistroma septosporum. We hypothesised that host genotype shapes foliar microbial communities and their interactions, thereby influencing disease outcomes. Samples were collected from a progeny-provenance field trial in the south of Scotland representing a broad spectrum of disease susceptibilities. The dataset comprises ITS2 metabarcoding samples from 200 genotypes across three timepoints and RNAseq samples from 48 genotypes across two timepoints. Sampling captured key stages of pathogen exposure and disease progression. Both standardised and bespoke protocols were used for nucleotide extraction, sequencing, and quality control, including multiple negative and positive controls. These datasets, available in the European Nucleotide Archive (project accession PRJEB88228), enable analysis of temporal dynamics in foliar fungal communities, host-microbiome transcriptional responses, and genotype-dependent variation in disease susceptibility.

bioinformatics↗

Genetic architecture of cichlid brain morphology

How evolutionary and developmental processes interact to determine axes of neural variation that produce behavioural diversity has been debated for many decades, with alternative hypotheses giving differential emphasis to functional coupling, which favours co-evolution, and developmental constraint, which enforces it. A critical omission is data on the genetic architecture of brain size and structure, which more closely illuminates the shared developmental dependencies between components of an integrated system. Here, we exploit ecological divergence between Astatotilapia calliptera and Aulonocara stuartgranti, two closely related cichlid species from Lake Malawi, to explore the genetic architecture of brain evolution. Using computer vision and machine learning techniques to extract volumetric data from micro-tomographic images, we first demonstrate significant divergence in brain composition between these species. Genomic and micro-tomographic imaging data from a population of hybrids generated between the two species were used to investigate genetic factors shaping this differentiation. We show that the majority of brain components are integrated phenotypically in hybrids, but genetic correlations between them are generally weaker. We further show that variation in multiple brain components is associated with variation in largely structure-specific quantitative trait loci, rather than determined by genetic factors with broad effects across the entire brain. These results suggest a genetic architecture that can facilitate modular changes in brain structure, and imply that individual components are independently evolvable.

evolutionary biology↗

Associations Between Age, Heart Rate Variability, and BOLD fMRI Signal Variability

Numerous studies report that BOLD fMRI signal variance (SDBOLD) decreases with age. However, these associations may partly reflect cardiovascular contributions to the BOLD signal. For example, heart rate variability (HRV) has been positively associated with Resting State Fluctuation Amplitude (RSFA), which captures low frequency components of BOLD fMRI variability. HRV is also negatively associated with age, which could potentially confound age-SDBOLD associations. Yet, limited research has examined HRV-SDBOLD associations or tested within-person HRV-SDBOLD coupling using sliding window analyses of simultaneous HRV and SDBOLD. We analyzed resting-state fMRI data from two independent Midlife in the United States (MIDUS) samples: Core at M3 (n=115) and Refresher at MR1 (n=101). Partial Least Squares (PLS) analyses revealed significant positive HRV-SDBOLD associations (Core: permutation p=0.018; Refresher: permutation p<0.001). Whole brain age-SDBOLD PLS associations were non-significant via permutation tests across several models (Core: permutation p=0.201; Refresher: permutation p=0.121). We found age-related decreases in SDBOLD across [~]70% of voxels in both samples. Concordance analyses showed 67-69% of brain voxels exhibited negative age-SDBOLD but positive HRV-SDBOLD relationships, suggesting that regions showing age-related decreases in SDBOLD also showed HRV-related increases in SDBOLD. Sliding-window analyses demonstrated robust positive within-person associations between person-centered HRV and SDBOLD via different HRV metrics: SDNN (Core: p < 0.001; Refresher: p < 0.001), RMSSD (Core: p = 0.072; Refresher: p = 0.009), and low frequency (Core: p < 0.001; Refresher: p < 0.001), with non-significant effects of high frequency (Core: p = 0.516; Refresher: p = 0.12) HRV. Thus, regardless of baseline levels, windows with higher HRV corresponded to higher SDBOLD, suggesting that cardiovascular factors partially explain age-SDBOLD associations and HRV may mechanistically influence SDBOLD. These results suggest that controlling for HRV, especially low-frequency HRV or SDNN, may be necessary when analyzing SDBOLD to isolate neural effects.

neuroscience↗

Evaluation of combined root exudate and rhizosphere microbiota sampling approaches to elucidate plant-soil-microbe interaction

O_LIDeciphering the root exudate-driven interplay between plants and the rhizosphere microbiota is essential for understanding plant adaptation to the environment and future-proofing crop production. However, sampling root exudates and rhizosphere soil remains challenging due to the low throughput and destructive nature of the process. C_LIO_LIWe used the staple crop barley [Hordeum vulgare] as a model to benchmark different sampling approaches for simultaneous exudation and microbiota profiling of soil-grown plants. C_LIO_LIExudate profiles and total dissolved organic carbon exudation rates were consistent across different sampling approaches, whereas root biomass, root morphology measurements, and organic nitrogen exudation varied. C_LIO_LIHigh-throughput amplicon sequencing and quantitative PCR (qPCR) of phylogenetic markers and nitrogen cycle-selected genes revealed a protocol-specific footprint in the composition and abundance of rhizosphere bacterial and fungal microbiota. Yet, on average, 75% of microbes enriched in, and differentiating between, barley rhizosphere and unplanted soil controls were recovered across all the sampling approaches evaluated. C_LIO_LIOur results demonstrated that, under the tested conditions, different sampling approaches produced comparable microbiota and exudation patterns, enabling the integrated study of root exudation and microbial profiles from the same plant. The observed differences across sampling approaches must be considered according to the experimental scope. C_LI

plant biology↗

fgf8a signalling shapes brain divergence between Malawi cichlids

Brain diversification is intimately linked with adaptive radiations, yet the underlying molecular basis remains poorly understood. Here, we examine the mechanisms of neural evolution in two ecologically divergent Lake Malawi cichlid species: a generalist, Astatotilapia calliptera, and a pelagic piscivore, Rhamphochromis sp. chilingali. We demonstrate that forebrain domains diverged independently from other brain regions in these species, consistent with mosaic brain evolution. We identify fibroblast growth factor 8a (fgf8a) as a key factor underlying this neuroanatomical divergence. Species-specific fgf8a expression patterns during critical developmental windows correlate with adult brain differences. Functional knockout experiments confirm fgf8as essential role in cichlid brain patterning, directly linking this conserved developmental gene to interspecific neuroanatomical variation. We identify species-specific transposable element repertoires in the Malawi cichlid fgf8a locus that function as developmental enhancers in brain and sensory systems, providing a potential mechanism for expression divergence between species. Phylogenetic analysis across the radiation reveals elevated transposable element polymorphism at the fgf8a locus in Rhamphochromis, suggesting ongoing regulatory evolution in this clade. Our findings reveal how conserved developmental programmes can accommodate regulatory modification, providing a mechanistic framework for understanding rapid neural diversification during adaptive radiation.

developmental biology↗

Lymph-node transcriptomics define prognostic immune states in mucosal melanoma and reveal IBA1 as a practical biomarker for improved prognosis

Mucosal melanoma (MM) is a rare and aggressive cancer in humans with poor prognosis and limited response to immunotherapy or targeted therapy. Progress has been hindered by the lack of immune-competent, translational models. Dogs develop oral mucosal melanoma (OMM), a biologically equivalent disease, making them a valuable companion animal model that shares the human environment and immune context. In this study, we present the first transcriptomic analysis of regional lymph nodes in dogs with OMM, revealing that lymph nodes stratify into two distinct subgroups, independent of histopathological metastatic status at time of surgery, and which can be succinctly captured with a 35-gene signature. Notably, this stratification correlates with survival outcomes, providing unique early prognostic insights at the time of diagnosis. Furthermore, we explore the immune landscape of these subgroups and identify IBA1+ monocyte/macrophage infiltration as a key distinguishing biomarker. Using immunohistochemistry (IHC) and digital pathology, we demonstrate that higher IBA1 expression is associated with the transcriptomic subgroups associated with improved survival. These findings highlight IBA1 as a potential biomarker for risk stratification, offering a clinically relevant tool for refining prognosis and guiding treatment decisions in canine OMM. HighlightsO_LITranscriptomic profiling of canine OMM lymph nodes identifies two prognostic subgroups, independent of histopathological metastatic status. C_LIO_LILymph node transcriptomic stratification correlates with survival, providing prognostic insights beyond conventional histopathology at the time of diagnosis. C_LIO_LIIBA1+ monocyte/macrophage infiltration is associated with improved survival, and shows strong diagnostic potential via immunohistochemistry, supporting its use as a clinically feasible stratification tool. C_LI

cancer biology↗

How individual differences shape ERP responses to visual statistical learning

Statistical learning (SL) enables the extraction of regularities from sensory input, yet the neural dynamics supporting this process--particularly in the visual modality--remain incompletely understood. Sixty-seven adults were familiarized with a continuous stream of shape sequences containing statistical structure that defined shape triplets. We recorded EEG to familiar sequences (presented in isolation) and unfamiliar foils. Both early (N100) and late (N400) event related potential (ERP) components were significantly more negative for unfamiliar than familiar sequences, reflecting robust neural sensitivity to learned structure. Notably, these familiarity effects were evident in both high- and low-performing participants and were not predicted by overall behavioral sensitivity, suggesting that neural indices of learning can emerge independently of explicit recognition. Follow-up analyses incorporating trial-level accuracy revealed a striking crossover interaction: for sensitive participants, ERP familiarity effects were stronger on correct trials, whereas for insensitive participants, effects were larger on incorrect trials. These findings highlight a dissociation between neural and behavioral measures of statistical learning and underscore the value of ERPs in capturing latent learning processes that may elude conscious awareness.

neuroscience↗

Acinetobacter enrichment shapes composition and function of the bacterial microbiota of field-grown tomato plants

Tomato is a staple crop and an excellent model to study host-microbiota interactions in the plant food chain. In this study we describe a lab-in-the-field approach to investigate the microbiota of field-grown tomato plants. High-throughput amplicon sequencing revealed a three-microhabitat partition, phyllosphere, rhizosphere and root interior, differentiating host-associated communities from the environmental microbiota. An individual bacterium, classified as Acinetobacter sp., emerged as a dominant member of the microbiota at the plant-soil continuum. To gain insights into the functional significance of this enrichment, we subjected rhizosphere specimens to shotgun metagenomics. Similar to the amplicon sequencing survey, a microhabitat effect defined by a set of rhizosphere-enriched functions was identified. Mobilisation of mineral nutrients, as well as adaptation to salinity and polymicrobial communities, including antimicrobial resistance genes (ARGs), emerged as a functional requirement sustaining metagenomic diversification. A metagenome-assembled genome (MAG) representative of Acinetobacter calcoaceticus was retrieved and metagenomic reads associated to this species identified a functional specialisation for plant-growth promotion traits (PGPTs), such as phosphate solubilization, siderophores production and reactive oxygen species detoxification, which were similarly represented in across tomato genotype-independent fashion. Our results revealed that the enrichment of a beneficial bacterium capable of alleviating plants abiotic stresses appears decoupled from ARGs facilitating microbiota persistence at the root-soil interface. IMPORTANCETomatoes are at centre-stage in global food security due to their high nutritional value, widespread cultivation, and versatility. Tomatoes provide essential vitamins and minerals, contribute to diverse diets, and support farmer livelihoods, making them a cornerstone of sustainable food systems. Beyond direct dietary benefits, the intricate relationship between tomatoes, their associated microbiota, and ARG is increasingly recognised. Tomato plants host diverse microbial communities in association with their organs, which influence plant health and productivity. Crop management impacts on composition and function of these communities, contributing to the prevalence of ARG in the soil and on the plants themselves. These genes can potentially transfer to human pathogens, posing a food safety and public health risk. Understanding these complex interactions is critical for developing sustainable agricultural practices capable of mitigating the impact of climatic modifications and the global threat of antimicrobial resistance.

plant biology↗

APOE4 drives widespread changes to the hepatic proteome and alters metabolic function

Apolipoprotein E (APOE) is essential for lipid homeostasis and has been extensively studied in the central nervous system, particularly in the context of Alzheimers disease (AD). Individuals carrying an APOE4 allele have an increased risk of AD and exhibit deficits in energy metabolism, including glucose utilization and mitochondrial dysfunction. While the role of APOE in the liver is well characterized, the impact of APOE genetic variation on hepatic health and metabolism remains poorly understood. We sought to investigate this using young female and male APOE3 and APOE4 targeted replacement mice. We also used APOE isogenic induced pluripotent stem cell (iPSC)-derived hepatocyte-like cells (iHLCs) to examine specific effects in a human-relevant cell model. Proteomic and functional assays show that APOE4 causes extensive changes to liver mitochondrial function in a sex-specific manner in mice and alters glucose and lipid metabolism. APOE4 also impairs mitochondrial function in iHLCs and shifts metabolism towards glycolysis while modifying expression of extracellular matrix proteins. Additionally, APOE4 iHLCs display a greater reliance on fatty acids as an energy source and show increased lipid accumulation. Taken together, our findings show that APOE genetic variation causes mitochondrial dysfunction and rewires hepatic metabolism.

physiology↗

Proteomic and metabolic profiling reveals APOE4-dependent shifts in whole brain, neuronal, and astrocytic mitochondrial function and glycolysis

Apolipoprotein E (APOE) genetic variation is the strongest genetic risk factor for late onset Alzheimers disease (LOAD). Studies on APOE genotype dependent changes have largely focused on amyloid beta (A{beta}) aggregation, disease pathology, and lipid metabolism. Recently, there has been increased interest in the relationship between metabolic function and APOE genetic variation. In this study, we examined how APOE genotype can alter metabolism in the brains of young male and female APOE3 and APOE4 targeted replacement (TR) mice. In combination with this, we also examined cell type-specific differences using induced pluripotent stem cell (iPSC) derived astrocytes and neurons. We found sex and genotype dependent changes to metabolism in the brains of young APOE TR mice. Specifically, APOE4 mice show signs of metabolic stress and compensatory mechanisms in the brain. Using proteomics and stable isotope tracing metabolomics, we found that APOE4 iAstrocytes and iNeurons exhibit signs of inflammation, mitochondrial dysfunction, altered TCA cycle and malate-aspartate shuttle activity, and a metabolic shift toward glycolysis. Taken together, this data indicates APOE4 causes early changes to metabolism within the central nervous system. While this study establishes a relationship between APOE genotype and alterations in bioenergetics, additional studies are needed to investigate underlying mechanisms.

neuroscience↗

Retinol Binding Protein 4 reactivates latent HIV-1 via the JAK/STAT5 and JNK pathways

Reactivation of the latent viral reservoirs is crucial for a cure of HIV/AIDS. However, current latency reversing agents are inefficient and the endogenous factors that have the potential to reactivate HIV in vivo remain poorly understood. To identify natural activators of latent HIV-1, we screened a comprehensive peptide/protein library derived from human hemofiltrate, representing the entire blood peptidome, using J-Lat cell lines harboring transcriptionally silent HIV-1 GFP reporter viruses. Fractions potently reactivating HIV-1 from latency contained human Retinol Binding Protein 4 (RBP4), the carrier of retinol (vitamin A). We found that retinol-bound holo-RBP4 but not retinol-free apo-RBP4 strongly reactivates HIV-1 in a variety of latently infected T cell lines. Functional analysis revealed that this reactivation depends on the JAK/STAT5 and JNK pathways but does not require retinoic acid production. High levels of RBP4 were detected in plasma from both healthy individuals and people living with HIV-1. Physiological concentrations of RBP4 induced significant viral reactivation in latently infected cells from individuals on long-term antiretroviral therapy with undetectable viral loads. As a potent natural HIV-1 latency-reversing agent, RBP4 offers a novel approach to activating the latent reservoirs and bringing us closer to a cure.

immunology↗

Combinations of RAS pathway inhibitors with targeted agents are active in spheroids of patient-derived cells with oncogenic KRAS variants from multiple cancer types

The KRAS gene is among the most frequently altered genes in cancer and the KRAS protein was long deemed undruggable. Recent strategies to target oncogenic KRAS have included both direct inhibition of the KRAS protein and indirect inhibition of its activity by targeting upstream and downstream signaling pathway mediators. A high-throughput screen of multi-cell type tumor spheroids was designed to identify active combinations of targeted small molecules and KRAS pathway inhibitors. Inhibitors of the non-receptor protein tyrosine phosphatase SHP2 and the guanine nucleotide exchange factor SOS1 were tested to evaluate indirect upstream pathway inhibition, while sotorasib directly inhibited the KRAS G12C variant. As single agents, sotorasib and the SHP2 inhibitor batoprotafib (TNO155) exhibited selectivity towards spheroids with KRAS G12C, whereas the SOS1 inhibitor BI-3406 showed varying activity across KRAS variants. Vertical inhibition of the RAS/MEK/ERK pathway by targeting SHP2 or SOS1 and the downstream kinases MEK (trametinib) or ERK (temuterkib) was highly effective. Inhibition of upstream tyrosine receptor kinases with nintedanib in combination with batoprotafib or BI-3406 was also effective, and in combination with sotorasib, demonstrated synergy in spheroids harboring KRAS G12C. Dual inhibition of the RAS/MEK/ERK and PI3K/AKT/mTOR pathways with batoprotafib or sotorasib with either the mTORC1/2 inhibitor sapanisertib or the AKT inhibitor ipatasertib demonstrated combination activity, primarily in spheroids harboring KRAS G12C. Combination of the BCL-2 inhibitor venetoclax with sotorasib, batoprotafib or BI-3406 resulted in additive and synergistic cytotoxicity. Lastly, concurrent inhibition of the KRAS pathway with sotorasib and batoprotafib demonstrated combination activity in spheroids containing KRAS G12C. SIGNIFICANCEKRAS variants are oncogenic drivers for a range of human cancers. Multiple combinations of small molecule agents that target RAS signaling were screened and reduced the viability of multi-cell type spheroid models for a variety of human solid tumors. Combinations warranting further testing were identified.

cancer biology↗

microbetag: simplifying microbial network interpretation through annotation, enrichment tests and metabolic complementarity analysis

Microbial co-occurrence network inference is often hindered by low accuracy and tool dependency. We introduce microbetag, a comprehensive software ecosystem designed to enhance network annotation. Nodes (taxa) are enriched with phenotypic traits, while edges represent metabolic complementarities, highlighting potential cross-feeding relationships. microbetags online version relies on microbetagDB, a database of 34,608 high-quality genomes with detailed annotations. A stand-alone tool allows users to apply microbetag to custom reference genomes/bins/MAGs. Additionally, MGG, a CytoscapeApp, offers a streamlined, user-friendly interface for network retrieval and visualization. microbetag effectively identified known metabolic interactions and serves as a robust hypothesis-generating tool.

systems biology↗

GERMIN3 plays a role in plasmodesmatal gating to regulate meristem activation related to tuberisation, tuber dormancy release and stem branching in potato

O_LIGERMIN3 has previously been identified as a target of the tuberigen activation complex suggesting a function in potato tuberisation but its role is presently unknown. C_LIO_LITo understand the role of GERMIN3 we analysed morphological, agronomic and molecular phenotypes in transgenic lines. C_LIO_LIGERMIN3 over-expressing lines of Solanum tuberosum ssp. andigena exhibited increased tuber yields under permissive conditions and enhanced tuber numbers. Post-harvest tuber sprouting exhibited reduced apical dominance with increased numbers of sprouts. Apical dominance was reduced in aerial tissues of mature plants where stem growth from axillary buds was activated. Similar results were observed in the commercial cultivar Desiree. Over-expression of GERMIN3 had no impact on the expression of SP6A, a positive regulator of tuberisation or TFL1B, a negative regulator. The GERMIN3 protein localised to the endoplasmic reticulum and transient expression in N. benthamiana leaves resulted in plasmodesmatal gating allowing intercellular transport of GFP-tagged sporamin independent of GERMIN3 oxalate oxidase activity. C_LIO_LIGERMIN3 affects tuberisation and other developmental processes by facilitating meristem activation. This identifies GERMIN3 as a novel protein associated with control of plasmodesmatal transport and supports the importance of plasmodesmatal gating in the regulation of key potato developmental processes. C_LI

plant biology↗

Ex vivo and in vivo HIV-1 latency reversal by Mukungulu, a protein kinase C-activating African medicinal plant extract

Current HIV latency reversing agents (LRAs) have had limited success in clinic, indicating the need for new strategies that can reactivate and/or eliminate HIV reservoirs. "Mukungulu," prepared from the bark of Croton megalobotrys Mull. Arg., is traditionally used for HIV/AIDS management in Northern Botswana despite containing an abundance of protein kinase C (PKC)-activating phorbol esters ("namushens"). Here we show that Mukungulu is tolerated in mice at up to 12.5 mg/kg while potently reversing latency in antiretroviral therapy (ART)-suppressed HIV-infected humanized mice at 5 mg/kg. In peripheral blood mononuclear cells (PBMC) and isolated CD4+ T-cells from ART-suppressed people living with HIV-1, 1 {micro}g/mL Mukungulu reverses latency on par with or superior to anti-CD3/CD28 positive control, as measured by HIV gag-p24 protein expression, where the magnitude of HIV reactivation in PBMC corresponds to intact proviral burden levels in CD4+ T-cells. Bioassay-guided fractionation identifies 5 namushen phorbol ester compounds that reactivate HIV expression, yet namushens alone do not match Mukungulus activity, suggesting additional enhancing factors. Together, these results identify Mukungulu as a robust natural LRA which may warrant inclusion in future LRA-based HIV cure and ART-free remission efforts.

microbiology↗

Silencing of a raspberry homologue of VRN1 is associated with disruption of dormancy induction and misregulation of subsets of dormancy-associated genes.

Winter dormancy is a key process in the phenology of temperate perennials. The changing climate is severely impacting its course leading to economic losses in agriculture. A better understanding of the underlying mechanisms, as well as the genetic basis of the different responses, are necessary for the development of climate-resilient cultivars. This study aims to provide an insight into winter dormancy in red raspberry (Rubus idaeus L). We report the transcriptomic profiles during dormancy in two raspberry cultivars with contrasting responses. The cultivar Glen Ample showed a typical perennial phenology, whereas Glen Dee registered consistent dormancy dysregulation, exhibiting active growth and flowering out of season. RNA-seq combined with weighted gene co-expression network analysis (WGCNA) highlighted gene clusters in both genotypes that exhibited time-dependent expression profiles, Functional analysis of Glen Ample gene clusters highlighted the significance of the cell and structural development prior to dormancy entry as well the role of genetic and epigenetic processes such as RNAi and DNA methylation in regulating gene expression. On the contrary, dormancy release in Glen Ample was associated with upregulation of transcripts associated with the resumption of metabolism, nucleic acid biogenesis and processing signal response pathways. Many of the processes occurring in Glen Ample were dysregulated in Glen Dee and twenty-eight transcripts exhibiting time-dependent expression in Ample that also had an Arabidopsis homologue were not found in all samples from Glen Dee. These included a gene with homology to Arabidopsis VRN1 (RiVRN1.1) that exhibited a sharp decline in expression following dormancy induction in Glen Ample. Characterisation of the gene region in the Glen Dee genome revealed two large insertions upstream of the ATG start codon. We propose that non-expression of a specific VRN1 homologue in Glen Dee causes dormancy misregulation as a result of inappropriate expression of a subset of genes that are directly or indirectly regulated by RiVRN1.1. HIGHLIGHTThe raspberry cultivar Glen Dee exhibits aberrant winter dormancy status associated with insertions in the upstream promoter region of a VRN1 (RiVRN1.1) homologue that silence expression, allowing the identification of dormancy-associated genetic modules that are regulated by RiVRN1.1.

plant biology↗

Marine phytoplankton and heterotrophic bacteria rapidly adapt to future pCO2 conditions in experimental co-cultures

The CO2 content of Earths atmosphere is rapidly increasing due to human consumption of fossil fuels. Models based on short-term culture experiments predict that major changes will occur in marine phytoplankton communities in the future ocean, but these models rarely consider how the evolutionary potential of phytoplankton or interactions within marine microbial communities may influence these changes. Here we experimentally evolved representatives of four phytoplankton functional types (silicifiers, calcifiers, coastal cyanobacteria, and oligotrophic cyanobacteria) in co-culture with a heterotrophic bacterium, Alteromonas, under either present-day or predicted future pCO2 conditions. Growth rates of cyanobacteria generally increased under both conditions, and the growth defects observed in ancestral Prochlorococcus cultures at elevated pCO2 and in axenic culture were diminished after evolution, possibly due to regulatory mutations in antioxidant genes. Except for Prochlorococcus, mutational profiles suggested phytoplankton experienced primarily purifying selection, but most Alteromonas lineages showed evidence of directional selection, especially when co-cultured with eukaryotic phytoplankton, where evolution appeared to favor a broad metabolic switch from growth on small organic acids to catabolism of more complex carbon substrates. Evolved Alteromonas were also poorer "helpers" for Prochlorococcus, supporting the assertion that the interaction between Prochlorococcus and heterotrophic bacteria is not a true mutualism but rather a competitive interaction stabilized by Black Queen processes. This work provides new insights on how phytoplankton will respond to anthropogenic change and on the evolutionary mechanisms governing the structure and function of marine microbial communities.

evolutionary biology↗