Biology subjects

Murray, N. J.

Publications and source records attributed to Murray, N. J..

8 recordsLinked to original sources

bioRxiv2025

NKX2-5 congenital heart disease mutations show diverse loss and gain of epigenomic, biochemical and chromatin search functions underpinning pathogenicity

Congenital heart defects (CHD) occur in [~]1% of live births, with inherited and acquired mutations and environmental factors contributing to causation. However, network perturbations in CHD remain poorly understood. We report an integrated functional-epigenomics approach to CHD, focusing on the cardiac homeodomain (HD) transcription factor NKX2-5, mutations which cause diverse heart structural and conduction defects. We selected twelve NKX2-5 CHD variants affecting different residue classes - homeodomain DNA base-contacting, backbone-contacting and helix-stabilizing, and those affecting other conserved protein:protein interaction (PPI) domains. In HL-1 cardiomyocytes, we profiled genome-wide DNA targets of NKX2-5 wild type (WT) and variants, their DNA binding affinity and specificity, PPI with known NKX2-5 cofactors and chromatin search dynamics. Variants showed diverse yet class-specific behaviours. All variants failed to bind many WT targets but retained binding to a subset of core cardiomyocyte-related targets, and bound hundreds of unique "off-targets" via changes to DNA binding site specificity, homodimerization, cofactor interactions and chromatin search functions. Our data suggest that complex residue-by-residue scale epigenomic, biochemical and chromatin search defects involving both loss-and gain-of-function contribute to CHD. These findings may inform precision molecular therapeutic approaches in patients with CHD.

genomics↗

bioRxiv2025

OpenEMMU: a versatile, open-source EdU multiplexing methodology for studying DNA replication and cell cycle dynamics

5-Ethynyl-2-deoxyuridine (EdU) has transformed DNA replication and cell cycle analyses through fast and efficient click chemistry detection. However, commercial EdU kits are expensive, contain proprietary reagents, are suboptimal for antibody multiplexing, and are challenging to use with larger biological specimens, highlighting the need for innovation. Here, we report Open-source EdU Multiplexing Methodology for Understanding DNA replication dynamics (OpenEMMU), an optimized, affordable, and user-friendly click chemistry resource using off-the-shelf reagents. OpenEMMU improves the efficiency, brightness, and multiplexing capabilities of EdU thymidine analog staining with both non-conjugated and conjugated antibodies across various cell types. We validated its effectiveness for fluorescent imaging of nascent DNA in developing embryos and organs, including the embryonic heart and forelimbs, and in 3D hiPSC-derived cardiac organoids. OpenEMMU also enabled 3D imaging of DNA synthesis in zebrafish larvae at fine resolution. This opens new avenues for insights into organismal development and growth, cell proliferation, and DNA replication, with precision and flexibility that surpass traditional methods. TeaserAn open-source and cost-effective resource for DNA replication profiling and cell cycle analysis using click chemistry.

developmental biology↗

bioRxiv2024

Analysing drivers of worldwide tidal wetland change

Tidal wetlands are dynamic coastal ecosystems that can change in extent in response to a broad range of change drivers. We use high spatial resolution satellite imagery to estimate the relative influence of 18 classes of change drivers on observed tidal wetland gains and losses from 1999 to 2019, differentiating direct drivers as those observable at the site of ecosystem change, and indirect drivers as broader processes that influence changes without being directly visible. We developed a random sample of 2823 change detections from a global dataset of tidal wetland change and allocated each change event to driver classes using high-resolution time-series imagery. We identified that indirect drivers were the most widespread type of driver of tidal wetland change (70.9%), with flooding being the predominant driver for losses (47.5%) and unknown natural processes of change for gains (62.7%). Drivers often associated with climate change were evident in interpretations of wetland drivers, with increases in flooded area and reductions in vegetation cover suggesting the effects of relative sea level rise on tidal wetlands are observable in many areas. Our temporal analysis revealed that over 20 years, indirect drivers consistently contributed to larger proportions of gains and losses compared to direct drivers. Asia was the only continent where direct drivers of loss, such as agriculture (22.9%) and aquaculture (17.1%), outweighed indirect drivers, providing further evidence of the widespread transformation of Asias natural coastal ecosystems to anthropogenic shorelines. Globally, coastal land reclamations were mostly observed in mangrove ecosystems, where more than half of the observed losses were of anthropogenic origin. The most observed direct drivers of gains were altered land management and restoration, but none of them contributed to more than 5% of the total gains over 20 years. Our findings suggest a need for efficient conservation measures that allow the dynamic processes that characterise coastal ecosystems to persist, while simultaneously reducing the worldwide impact of direct human activities.

ecology↗

bioRxiv2024

Soil carbon in the world's tidal marshes

Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training data from 3,710 unique locations, landscape-level environmental drivers and a newly developed global tidal marsh extent map to produce the first global, spatially-explicit map of SOC storage in tidal marshes at 30 m resolution. We estimate the total global SOC stock to 1 m to be 1.44 Pg C, with a third of this value stored in the United States of America. On average, SOC in tidal marshes 0-30 and 30-100 cm soil layers are estimated at 83.1 Mg C ha-1 (average predicted error 44.8 Mg C ha-1) and 185.3 Mg C ha-1 (average predicted error 105.7 Mg C ha-1), respectively. Our spatially-explicit model is able to capture 59% of the variability in SOC density, with elevation being the strongest driver aside from soil depth. Our study reveals regions with high prediction uncertainty and therefore highlights the need for more targeted sampling to fully capture SOC spatial variability.

ecology↗

bioRxiv2023

The distribution of global tidal marshes from earth observation data

AimTidal marsh ecosystems are heavily impacted by human activities, highlighting a pressing need to address gaps in our knowledge of their distribution. To better understand the global distribution and changes in tidal marsh extent, and identify opportunities for their conservation and restoration, it is critical to develop a spatial knowledge base of their global occurrence. Here, we develop a globally consistent tidal marsh distribution map for the year 2020 at 10-m resolution. LocationGlobal Time period2020 Major taxa studiedTidal marshes MethodsTo map the location of the worlds tidal marshes we applied a random forest classification model to earth observation data from the year 2020. We trained the classification model with a reference dataset developed to support distribution mapping of coastal ecosystems, and predicted the spatial distribution of tidal marshes between 60{degrees}N to 60{degrees}S. We validated the tidal marsh map using standard accuracy assessment methods, with our final map having an overall accuracy score of 0.852. ResultsWe estimate the global extent of tidal marshes in 2020 to be 52,880 km2 (95% CI: 32,030 to 59,780 km2) distributed across 120 countries and territories. Tidal marsh distribution is centred in temperate and Arctic regions, with nearly half of the global extent of tidal marshes occurring in the temperate Northern Atlantic (45%) region. At the national scale, over a third of the global extent (18,510 km2; CI: 11,200 - 20,900) occurs within the USA. Main conclusionsOur analysis provides the most detailed spatial data on global tidal marsh distribution to date and shows that tidal marshes occur in more countries and across a greater proportion of the worlds coastline than previous mapping studies. Our map fills a major knowledge gap regarding the distribution of the worlds coastal ecosystems and provides the baseline needed for measuring changes in tidal marsh extent and estimating their value in terms of ecosystem services

ecology↗

bioRxiv2020

Myanmar's terrestrial ecosystems: status, threats and conservation opportunities

Myanmar is highly biodiverse, with more than 16,000 plant, 314 mammal, 1131 bird, 293 reptile, and 139 amphibian species. Supporting this biodiversity is a variety of natural ecosystems--mostly undescribed--including tropical and subtropical forests, savannas, seasonally inundated wetlands, extensive shoreline and tidal systems, and alpine ecosystems. Although Myanmar contains some of the largest intact natural ecosystems in Southeast Asia, remaining ecosystems are under threat from accelerating land use intensification and over-exploitation. In this period of rapid change, a systematic risk assessment is urgently needed to estimate the extent and magnitude of human impacts and identify ecosystems most at risk to help guide strategic conservation action. Here we provide the first comprehensive conservation assessment of Myanmars natural terrestrial ecosystems using the IUCN Red List of Ecosystems categories and criteria. We identified 64 ecosystem types for the assessment, and used models of ecosystem distributions and syntheses of existing data to estimate declines in distribution, range size, and functioning of each ecosystem. We found that more than a third (36.9%) of Myanmars area has been converted to anthropogenic ecosystems over the last 2-3 centuries, leaving nearly half of Myanmars ecosystems threatened (29 of 64 ecosystems). A quarter of Myanmars ecosystems were identified as Data Deficient, reflecting a paucity of studies and an urgency for future research. Our results show that, with nearly two-thirds of Myanmar still covered in natural ecosystems, there is a crucial opportunity to develop a comprehensive protected area network that sufficiently represents Myanmars terrestrial ecosystem diversity.

ecology↗

bioRxiv2020

Forest condition in the Congo Basin for the assessment of ecosystem conservation status

Measuring forest degradation is important for understanding and designing measures to protect biodiversity and the capacity of forests to deliver ecosystem services. Conservation planning, particularly the prioritization of management interventions for forests, is often lacking spatial data on ecological condition, and it is often overlooked within decision-making processes. Existing methods for assessing forest degradation via proxies or binary measures (i.e. intact or not) cannot adequately consider the important variations of ecological condition. Direct methods to measure degradation (e.g. through remote sensing) require extensive training data, calibration and validation, and may be too sensitive to small-scale or short-term changes which may not be related to degradation. We developed a metric termed Forest Condition (FC) which aims to measure the degree of forest degradation, incorporating temporal history of forest change over a large spatial extent. We parameterized this metric based on estimated changes in above ground biomass in the context of forest fragmentation over time to estimate a continuous measure of forest degradation for Congo Basin countries. We estimate that just less than 70% of Congo Basin forests remain fully intact. FC was validated by direct remote sensing measurements from Landsat imagery for DRC. Results showed that FC was significantly positively correlated with forest canopy cover, gap area per hectare, and magnitude of temporal change in Normalized Burn Ratio. We tested the ability of FC to distinguish primary and secondary degradation and deforestation and found significant differences in gap area and spectral anomalies to validate our theoretical model. We used the IUCN Red List of Ecosystems criteria to demonstrate the value of applying forest degradation to assess the risk of ecosystem collapse. Based on this assessment, we found that without including FC in the assessment of biotic disruption, 12 ecosystems could not have a threat status assigned, and a further 9 ecosystems would have a lower threat status. Our overall assessment of ecosystems found approximately half of forest of Congo Basin ecosystem types which cover over 20% of all forest area are threatened including 4 ecosystems (<1% of total area) which are critically engendered. FC is a transferrable and scalable assessment to support forest monitoring, planning, and management.

ecology↗

bioRxiv2017

REMAP: An online remote sensing application for land cover classification and monitoring

O_LIRecent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to make ecosystem maps from remote sensing data.\nC_LIO_LIWe have developed a free and open-access online remote sensing and environmental modelling application, REMAP (the remote ecosystem monitoring and assessment pipeline; https://remap-app.org) that enables volunteers, managers, and scientists with little or no experience in remote sensing to develop high-resolution classified maps of land cover and land use change over time.\nC_LIO_LIREMAP utilizes the geospatial data storage and analysis capacity of the Google Earth Engine, and requires only spatially resolved training data that define map classes of interest (e.g., ecosystem types). The training data, which can be uploaded or annotated interactively within REMAP, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in REMAP represent topographic (e.g. slope, elevation), spectral (Landsat Archive image composites) and climatic variables (precipitation, temperature) that can inform on the distribution of ecosystems and land cover classes.\nC_LIO_LIThe ability of REMAP to develop and export high-quality classified maps in a very short (<10 minute) time frame represents a considerable advance towards globally accessible and free application of remote sensing technology. By enabling access to data and simplifying remote sensing classifications, REMAP can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of biodiversity, identifying hotspots of ecosystem diversity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales, and supporting environmental education initiatives.\nC_LI

ecology↗