Biology subjects

Browne, L.

Publications and source records attributed to Browne, L..

4 recordsLinked to original sources

bioRxiv2026

Is epigenetics Lamarck's revenge? The evolutionary and ecological impacts of DNA methylation in a California oak

DNA methylation, an epigenetic mechanism, has been proposed as a basis for Lamarckian inheritance of acquired characteristics. This hypothesis raises questions about environmental induction of DNA methylation, its persistence across generations, and associations with gene expression. We investigated these processes in the California oak, Quercus lobata. Based on 40 range-wide adult trees and their progeny grown in two common gardens, we tested four predictions: (i) DNA methylation is environmentally induced; (ii) methylation shows parent-offspring correspondence; (iii) environmentally induced patterns remain stable after transmission; and (iv) DNA methylation is associated with gene expression, varying by sequence context and TE proximity. Using methylomes and transcriptomes, we found support for all predictions except the third: CHH methylation was environmentally induced, but rarely showed parent/offspring correspondence, whereas CG methylation showed the opposite pattern. DNA methylation was associated with gene expression, depending on the sequence context and proximity to TEs. We identified one stress-associated gene with environmentally responsive CHH methylation that showed parent offspring correspondence in two common gardens in both gardens. Still, overall evidence for Lamarckian like evolution is not compelling. Nevertheless, DNA methylation was environmentally responsive, showed parent offspring correspondence, and was associated with gene expression, highlighting its potential importance for the ecological and evolutionary responses of long-lived trees to environmental change.

evolutionary biology↗

bioRxiv2025

Stromal subsets modulate T-cell infiltration in early breast cancer

Recent studies of the tumour microenvironment have elucidated the heterogeneity of stromal cells, with increasing evidence suggesting that stromal subsets play an important role in regulating anti-tumour immunity in breast cancer. However, the functional diversity of these cells within the tumour immune microenvironment and how they interact with immune cells in a spatial and clinical context remain poorly understood. We performed multiplex immunofluorescence on tumour microarrays from two cohorts consisting of 591 breast cancer patients to assess the abundance and spatial co-localisation of stromal and immune subsets and their correlation with clinicopathological features and patient outcomes. We found that stromal cells were spatially distinct. A perivascular-like subset that was disseminated throughout the stroma rather than restricted to vessel-adjacent regions was enriched in an immune cold environment and associated with T-cell exclusion. An inflammatory-like cancer-associated fibroblast subset was associated with segregation of T cells from cancer cells. Our findings highlight the differential impact of stromal subsets on immune infiltration and activation within the breast cancer tumour microenvironment with potential implications for patient outcomes. SignificanceThis study characterised spatially-defined interactions between stromal and immune subsets in large clinical cohorts of early breast cancer. Findings from this study will contribute to gaps in current knowledge in how diverse stromal cell subsets, particularly novel subsets, interact with immune cells in a clinically-relevant context.

cancer biology↗

bioRxiv2021

Data science competition for cross-site delineation and classification of individual trees from airborne remote sensing data

Delineating and classifying individual trees in remote sensing data is challenging. Many tree crown delineation methods have difficulty in closed-canopy forests and do not leverage multiple datasets. Methods to classify individual species are often accurate for common species, but perform poorly for less common species and when applied to new sites. We ran a data science competition to help identify effective methods for delineation of individual crowns and classification to determine species identity. This competition included data from multiple sites to assess the methods ability to generalize learning across multiple sites simultaneously, and transfer learning to novel sites where the methods were not trained. Six teams, representing 4 countries and 9 individual participants, submitted predictions. Methods from a previous competition were also applied and used as the baseline to understand whether the methods are changing and improving over time. The best delineation method was based on an instance segmentation pipeline, closely followed by a Faster R-CNN pipeline, both of which outperformed the baseline method. However, the baseline (based on a growing region algorithm) still performed well as did the Faster R-CNN. All delineation methods generalized well and transferred to novel forests effectively. The best species classification method was based on a two-stage fully connected neural network, which significantly outperformed the baseline (a random forest and Gradient boosting ensemble). The classification methods generalized well, with all teams training their models using multiple sites simultaneously, but the predictions from these trained models generally failed to transfer effectively to a novel site. Classification performance was strongly influenced by the number of field-based species IDs available for training the models, with most methods predicting common species well at the training sites. Classification errors (i.e., species misidentification) were most common between similar species in the same genus and different species that occur in the same habitat. The best methods handled class imbalance well and learned unique spectral features even with limited data. Most methods performed better than baseline in detecting new (untrained) species, especially in the site with no training data. Our experience further shows that data science competitions are useful for comparing different methods through the use of a standardized dataset and set of evaluation criteria, which highlights promising approaches and common challenges, and therefore advances the ecological and remote sensing field as a whole.

ecology↗

bioRxiv2020

Brief sensory deprivation triggers cell type-specific structural and functional plasticity in olfactory bulb neurons

Can alterations in experience trigger different plastic modifications in neuronal structure and function, and if so, how do they integrate at the cellular level? To address this question, we interrogated circuitry in the mouse olfactory bulb responsible for the earliest steps in odour processing. We induced experience-dependent plasticity in mice by blocking one nostril for a day, a minimally-invasive manipulation which leaves the sensory organ undamaged and is akin to the natural transient blockage suffered during common mild rhinal infections. We found that such brief sensory deprivation produced structural and functional plasticity in one highly specialised bulbar cell type: axon-bearing dopaminergic neurons in the glomerular layer. After 24h naris occlusion, the axon initial segment (AIS) in bulbar dopaminergic neurons became significantly shorter, a structural modification that was also associated with a decrease in intrinsic excitability. These effects were specific to the AIS-positive dopaminergic subpopulation, because no experience-dependent alterations in intrinsic excitability were observed in AIS-negative dopaminergic cells. Moreover, 24h naris occlusion produced no structural changes at the AIS of bulbar excitatory neurons - mitral/tufted and external tufted cells - nor did it alter their intrinsic excitability. By targeting excitability in one specialised dopaminergic subpopulation, experience-dependent plasticity in early olfactory networks might act to fine-tune sensory processing in the face of continually fluctuating inputs.

neuroscience↗