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Lister, A.

Publications and source records attributed to Lister, A..

15 recordsLinked to original sources

Single-nucleus profiling of social behaviour in a mutualistic reef fish

Complex social decision-making in vertebrates relies on a conserved network within the forebrain. However, the precise neural cell populations and gene regulatory networks that orchestrate these sophisticated social behaviours remain largely unresolved. Here, we present the first single-nucleus transcriptome atlas of the telencephalon in the cleaner wrasse Labroides dimidiatus, a remarkable model for advanced social cognition. Profiling ~67,000 telencephalic nuclei, we mapped the neural architecture of the teleost forebrain and identified highly conserved cell populations including a cholinergic-GABAergic neuron population implicated in social behaviours and cells resembling mammalian striatal medium spiny neurons and hippocampal cell types. By comparing distinct behavioural states, we found that socially interacting fish expanded radial glial subclusters, and associative learning co-expression networks, whereas social observers exhibited gene expression signatures for motivation and behavioural preparedness. Ultimately, the resolved telencephalon atlas reveals the evolutionarily conserved cellular and molecular substrates that may govern complex social behaviour across vertebrates.

animal behavior and cognition↗

EISCA and EISTA: Full-Spectrum Pipelines for Single-Cell and Spatial Transcriptomics Analysis

Single-cell and spatial transcriptomics are transforming our understanding of cellular heterogeneity and tissue organization, yet their analytical complexity remains a major bottleneck. Here, we present EISCA and EISTA, two standardized, end-to-end pipelines for single-cell RNA-seq and imaging-based spatial transcriptomics analysis. Built on the Nextflow nf-core framework, both pipelines implement modular, scalable, and reproducible workflows spanning primary, secondary, and tertiary analyses, from raw data processing to advanced downstream analyses. EISCA supports droplet- and plate-based scRNA-seq technologies, while EISTA is tailored for high-resolution spatial platforms including Vizgen MERFISH and 10x Xenium. Together, they integrate state-of-the-art methods for quality control, normalization, clustering, integration, cell-type annotation, differential expression, and cell-cell communication, with EISTA further enabling spatial statistical analyses. A central design principle is to balance standardization with flexibility: workflows can be executed end-to-end or modularly, enabling iterative, exploratory analyses with minimal overhead. Both pipelines deliver rapid preliminary results alongside an out-of-the-box report, facilitating immediate data assessment and accelerating downstream discovery. Case studies in plant immunity and human sepsis demonstrate that EISTA and EISCA reproducibly can be used to recover biologically meaningful insights. Collectively, these pipelines provide efficient, flexible, and scalable solutions for comprehensive single-cell and spatial transcriptomics analyses.

bioinformatics↗

Evolutionary Rewiring of Root Cell-Type Nitrogen Responses

Nitrate induces widespread transcriptional reprogramming in plants, but how transcription factors coordinate these responses across cell types and evolve across species with divergent root patterning remains unclear. Using single-cell transcriptomics in Arabidopsis thaliana and Solanum lycopersicum (tomato) under varying nitrate conditions, we demonstrate that many transcriptional responses are cell type and developmental stage-specific. Arabidopsis NIN-LIKE PROTEIN 7 (NLP7) directly modulates both broadly expressed and cell-type-specific targets, but is not required to establish the cell type specific nature of these patterns. Comparative analysis reveals evolutionary shifts; key nitrogen programs are localized to different cell types in tomato, with the exodermis as a major regulatory hub. Identification of tomato NLP7a and NLP7b direct targets at cellular resolution supports their role in direct modulation of cell type N-transcriptional programs. This is evidenced by NLP7-controlled exodermal cell wall remodeling in low nitrate, highlighting functional conservation despite divergent cellular topographies.

plant biology↗

A comparison of long-read single-cell transcriptomic approaches

Long-read sequencing enables the incorporation of isoform-level expression into single-cell transcriptomic studies, offering detail beyond those accessible with short-read methods. Although insightful, these approaches have typically been costly and yielded limited data for each individual cell. Recent advances in library preparation approaches and sequencing throughput have brought long-read single-cell studies closer to the mainstream. Here, we present a comparative analysis of commercial approaches for single-cell long-read sequencing. We have performed parallel analyses of the same cDNA material, generated using the 10X genomics platform, on Illumina short-read, and PacBio and Oxford Nanopore long-read platforms. We also demonstrate the impact of CRISPR-based depletion of libraries, to remove highly expressed transcripts, prior to long-read sequencing in these experiments. By analysing single-source cDNA libraries in parallel, we enable a direct comparison of each platform, evaluating standard metrics alongside concordance in clustering and cell type identification. While each approach generates usable gene and isoform expression data, we identify limitations common across platforms, primarily linked to cDNA synthesis inefficiencies and read filtering strategies. Our work demonstrates the increasing utility of single-cell long-read sequencing for isoform-resolved analyses, such as direct immunoglobulin chain reconstruction without additional amplification, and the detection of alternative splicing patterns across immune cell subtypes in CD45, a key gene for immune cell activation and differentiation. Our benchmarking of current platform options provides a foundation for researchers looking to adopt single-cell long-read sequencing into their transcriptomic studies, providing a framework for its integration into diverse biological questions.

cell biology↗

Decoding cellular transcriptional regulatory networks governing wheat inflorescence development

Wheat inflorescence architecture, particularly spikelet and floret development, is critical for grain yield. To decode the cellular transcriptional regulatory network (cTRN) underlying wheat inflorescence development, we integrated multiple single-cell omics technologies to construct a spatiotemporal atlas of transcriptional and chromatin accessibility dynamics. This comprehensive analysis identified 20 cell types, 7,211 cell type-specific genes and 152,333 cell type-specific accessible chromatin regions (csACRs) in the wheat inflorescence. Trajectory analysis identified two sub-clusters of proliferating cells as the origins of spikelet and floret formation, deviating from the traditional developmental model. Key transcription factors and hormone-related genes in the cTRN, along with the csACRs, providing new targets for modulating wheat inflorescence architecture. Our findings provide a high-resolution resource for crop inflorescence research and establish a paradigm for applying spatiotemporal single-cell omics analysis to plant biology.

plant biology↗

Spatial Transcriptomics Reveals Expression Gradients in Developing Wheat Inflorescences at Cellular Resolution

The diversity of plant inflorescence architectures is specified by gene expression patterns. In wheat (Triticum aestivum), the lanceolate-shaped inflorescence (spike) is defined by rudimentary spikelets at the base which initiate first but subsequently lag in development compared with central spikelets. While previous studies identified gene expression differences between central and basal inflorescence sections, the spatio-temporal dynamics and gradients along the apical-basal axis remain poorly resolved due to bulk tissue-level techniques. Here, using spatial transcriptomics, we profiled 200 genes across four stages of wheat inflorescence development to cellular resolution. Cell segmentation and unsupervised clustering identified 18 expression domains and their enriched genes, revealing dynamic spatio-temporal organisation along the apical-basal axis of the inflorescence. Along this axis, we uncovered distinct and spatially coordinated gene expression gradients patterning meristems prior to the visible delay in basal spikelet development. This study demonstrates the potential for spatial transcriptomics time-series to advance plant developmental biology.

plant biology↗

Trans-generational adaptation to maternal climate through hormone transport in plants

Whether organisms can inherit parental adaptations to the environment is a major question in evolutionary biology. Plant development is highly plastic and dependent on the seasonal cues which are used to control growth and reproduction. Seed dormancy and germination are key traits which respond strongly to temperature during seed development and here we show that progeny adaptation to seasonal climate is inherited from the mother plant. Loss of maternal LIKE HETEROCHROMATIN PROTEIN 1 (LHP1) causes an inability of progeny seeds to sense temperature and this is linked mechanistically to reduced ABA levels in seeds and activation of the primary nitrate response. At the single cell level, small changes in temperature activate nitrate signalling specifically in the mother, and ABA biosensor imaging reveals temperature-dependent fluxes of ABA into seeds necessary for dormancy induction. Thus, we reveal that progeny seeds inherit the climate adaptation of mother plants via active hormone transport during seed set.

plant biology↗

Single-cell and spatial transcriptomics of the avian embryo tailbud

Vertebrate body axis formation initiates during gastrulation and continues within the tail bud at the posterior end of the embryo. Major structures in the trunk are paired somites, which generate the musculoskeletal system, the spinal cord - forming part of the central nervous system, and the notochord, with important patterning functions. The specification of these different cell lineages by key signalling pathways and transcription factors is essential, however, a global map of cell types and expressed genes in the avian trunk is missing. Here we use single-cell RNA sequencing and RNA tomography to generate a molecular map of the emerging trunk and tailbud in the chick embryo. Single cell RNA-sequencing (scRNA-seq) identifies discrete cell lineages including somites, neural tube, neural crest, lateral plate mesoderm, ectoderm, endothelial and blood progenitors. In addition, high-throughput RNA-seq of sequential tissue sections provides a spatially resolved, genome-wide expression dataset for the avian tailbud and emerging body, comparable to other model systems. Combining the single-cell and spatial datasets, we identify spatially restricted genes, focusing on somites and early myoblasts. Thus, this high-resolution transcriptome map incorporating cell types in the embryonic trunk can expose molecular pathways involved in body axis development.

developmental biology↗

Multi-excitation Raman Spectroscopy Complements Whole Genome Sequencing for Rapid Detection of Bacterial Infection and Resistance in WHO Priority Pathogens

Current methods for diagnosing acute and complex infections mostly rely on culture-based methods and, for biofilms, fluorescence in-situ hybridization. These techniques are labor-intensive and can take 2-4 days to return a test result, especially considering an extra culturing step required for the antibiotic susceptibility testing (AST). This places a significant burden on healthcare providers, delaying treatment and leading to adverse patient outcomes. Here, we report the complementary use of our newly developed multi-excitation Raman spectroscopy (ME-RS) method with whole-genome sequencing (WGS). Four WHO priority pathogens are AST phenotyped and their antimicrobial resistance (AMR) profile determined by WGS. On application of ME-RS method we find high correlation with the WGS characterization. Highly accurate classification based on the species (98.93%), wild-type/non-wild type (99.45%), and presence or absence of thick peptidoglycan layers in cell walls (100%), as well as at the individual strain level (99.29%). These results clearly demonstrate the potential of ME-RS as a rapid and first-stage tool for species, resistance and strain-level classification which can be followed up by WGS for confirmation. Such a workflow can facilitate efficient antimicrobial stewardship to handle and prevent the spread of AMR.

microbiology↗

High expression of VRT2 during wheat spikelet initiation increases the number of rudimentary basal spikelets

Spikelets are the fundamental building blocks of Poaceae inflorescences and their development and branching patterns determine the various inflorescence architectures and grain yield of grasses. In wheat, the central spikelets produce the most and largest grains, while spikelet size gradually decreases acro- and basipetally, giving rise to the characteristic lanceolate shape of wheat spikes. The acropetal gradient correlates with the developmental age of spikelets, however the basal spikelets are developed first and the cause of their small size and rudimentary development is unclear. Here, we adapted G&T-seq, a low-input transcriptomics approach, to characterise gene expression profiles within spatial sections of individual spikes before and after the establishment of the lanceolate shape. We observed larger differences in gene expression profiles between the apical, central and basal sections of a single spike than between any section belonging to consecutive developmental timepoints. We found that SVP MADS-box transcription factors, including VRT-A2, are expressed highest in the basal section of the wheat spike and display the opposite expression gradient to flowering E-class SEP1 genes. Based on multi-year field trials and transgenic lines, we show that higher expression of VRT-A2 in the basal sections of the spike is associated with increased numbers of rudimentary basal spikelets. Our results, supported by computational modelling, suggest that the delayed transition of basal spikelets from vegetative to floral developmental programmes results in the lanceolate shape of wheat spikes. This study highlights the value of spatially resolved transcriptomics to gain new insights into developmental genetics pathways of grass inflorescences. One sentence summaryLarge transcriptional gradients exist within a wheat spike and are associated with rudimentary basal spikelet development, resulting in the characteristic lanceolate shape of wheat spikes.

plant biology↗

Sequencing smart: De novo sequencing and assembly approaches for non-model mammals.

BackgroundWhilst much sequencing effort has focused on key mammalian model organisms such as mouse and human, little is known about the correlation between genome sequencing techniques for non-model mammals and genome assembly quality. This is especially relevant to non-model mammals, where the samples to be sequenced are often degraded and low quality. A key aspect when planning a genome project is the choice of sequencing data to generate. This decision is driven by several factors, including the biological questions being asked, the quality of DNA available, and the availability of funds. Cutting-edge sequencing technologies now make it possible to achieve highly contiguous, chromosome-level genome assemblies, but relies on good quality high-molecular-weight DNA. The funds to generate and combining these data are often only available within large consortiums and sequencing initiatives, and are often not affordable for many independent research groups. For many researchers, value-for-money is a key factor when considering the generation of genomic sequencing data. Here we use a range of different genomic technologies generated from a roadkill European Polecat (Mustela putorius) to assess various assembly techniques on this low-quality sample. We evaluated different approaches for de novo assemblies and discuss their value in relation to biological analyses.\n\nResultsGenerally, assemblies containing more data types achieved better scores in our ranking system. However, when accounting for misassemblies, this was not always the case for Bionano and low-coverage 10x Genomics (for scaffolding only). We also find that the extra cost associated with combining multiple data types is not necessarily associated with better genome assemblies.\n\nConclusionsThe high degree of variability between each de novo assembly method (assessed from the seven key metrics) highlights the importance of carefully devising the sequencing strategy to be able to carry out the desired analysis. Adding more data to genome assemblies not always results in better assemblies so it is important to understand the nuances of genomic data integration explained here, in order to obtain cost-effective value-for-money when sequencing genomes.

genomics↗

Spatially resolved transcriptomics reveals plant host responses to pathogens

BackgroundThorough understanding of complex model systems requires the characterisation of processes in different cell types of an organism. This can be achieved with high-throughput spatial transcriptomics at a large scale. However, for plant model systems this is still challenging as suitable transcriptomics methods are sparsely available. Here we present Grid-seq, an easy to adopt, micro-scale spatial-transcriptomics workflow that allows to study expression profiles across small areas of plant tissue at a fraction of the cost of existing sequencing-based methods.\n\nResultsWe compare the Grid-seq method with widely used library preparation methods (Illumina TruSeq). In spatial experiments we show that the Grid-seq method is sensitive enough to identify expression differences across a plant organ. We further assess the spatial transcriptome response of Arabidopsis thaliana leaves exposed to the bacterial molecule flagellin-22.\n\nConclusionWe show that our method can be used to identify known, rapidly flagellin-22 elicited genes, plant immune response pathways to bacterial attack and spatial expression patterns of genes associated with these pathways.

genomics↗

FAIRsharing: working with and for the community to describe and link data standards, repositories and policies

In this modern, data-driven age, governments, funders and publishers expect greater transparency and reuse of research data, as well as greater access to and preservation of the data that supports research findings. Community-developed standards, such as those for the identification1 and reporting2 of data, underpin reproducible and reusable research, aid scholarly publishing, and drive both the discovery and evolution of scientific practice. The number of these standardization efforts, driven by large organizations or at the grass root level, has been on the rise since the early 2000s. Thousands of community-developed standards are available (across all disciplines), many of which have been created and/or implemented by several thousand data repositories. Nevertheless, their uptake by the research community, however, has been slow and uneven. This is mainly because investigators lack incentives to follow and adopt standards. The situation is exacerbated if standards are not promptly implemented by databases, repositories and other research tools, or endorsed by infrastructures. Furthermore, the fragmentation of community efforts results in the development of arbitrarily different, incompatible standards. In turn, this leads to standards becoming rapidly obsolete in fast-evolving research areas.\n\nAs with any other digital object, standards, databases and repositories are dynamic in nature, with a life cycle that encompasses formulation, development and maintenance; their status in this cycle may vary depending on the level of activity of the developing group or community. There is an urgent need for a service that enhances the information available on the evolving constellation of heterogeneous standards, databases and repositories, guides users in the selection of these resources, and that works with developers and maintainers of these resources to foster collaboration and promote harmonization. Such an informative and educational service is vital to reduce the knowledge gap among those involved in producing, managing, serving, curating, preserving, publishing or regulating data. A diverse set of stakeholders-representing academia, industry, funding agencies, standards organizations, infrastructure providers and scholarly publishers-- both national and domain-specific as well global and general organizations-- have come together as a community, representing the core adopters, advisory board members, and/or key collaborators of the FAIRsharing resource. Here, we introduce its mission and community network. We present an evaluation of the standards landscape, focusing on those for reporting data and metadata - the most diverse and numerous of the standards - and their implementation by databases and repositories. We report on the ongoing challenge to recommend resources, and we discuss the importance of making standards invisible to the end users. We report on the ongoing challenge to recommend resources, and we discuss the importance of making standards invisible to the end users. We present guidelines that highlight the role each stakeholder group must play to maximize the visibility and adoption of standards, databases and repositories.

scientific communication and education↗

A critical comparison of technologies for a plant genome sequencing project

A high quality genome sequence of your model organism is an essential starting point for many studies. Old clone based methods are slow and expensive, whereas faster, cheaper short read only assemblies can be incomplete and highly fragmented, which minimises their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, human. However, plant genomes can be much more repetitive and larger than human, and plant biology makes obtaining high quality DNA free from contaminants difficult. Reflecting their challenging nature we observe that plant genome assembly statistics are typically poorer than for vertebrates. Here we compare Illumina short read, PacBio long read, 10x Genomics linked reads, Dovetail Hi-C and BioNano Genomics optical maps, singly and combined, in producing high quality long range genome assemblies of the potato species S. verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA, compute requirements and sequencing costs. We expect our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.

genomics↗

BioSharing: Harnessing Metadata Standards For The Data Commons

The use of community-driven metadata standards, such as minimal information guidelines, terminologies, formats/models, is essential to ensure that data and other digital research outputs are Findable, Accessible, Interoperable, and Reusable, according to the FAIR principles. As with other types of digital assets, metadata standards also need be FAIR. Their discoverability and accessibility is ensured by BioSharing, the most comprehensive resource of metadata standards, interlinked to data repositories and policies, available in the life, environmental and biomedical sciences. With its growing content, endorsements, and collaborative network, BioSharing is part of a larger ecosystem of interoperable resources. Here we describe some of the activities under the USA National Institutes of Health (NIH)s Big Data to Knowledge (BD2K) Initiative, illustrating how we track the evolution and use of metadata standards and work to connect them to indexes and annotation tools.

scientific communication and education↗