Biology subjects

Heffer, J.

Publications and source records attributed to Heffer, J..

5 recordsLinked to original sources

bioRxiv2026

4D spatial transcriptomics reveals nodule identity emerges through stacked parallel developmental programs

Legume root nodules enable symbiotic nitrogen fixation through the development of specialized cells that accommodate nitrogen-fixing bacteria intracellularly and support bacterial nitrogenase activity. Here, we present a 4D (3D space and time) spatial transcriptomic atlas of Medicago truncatula nodules and lateral roots, revealing specialized symbiotic cell types that develop alongside a conserved lateral-root-derived program that underpins vascularization. Spatial profiling of both plant and bacterial transcripts resolves distinct transcriptional states and previously unrecognized cell states. Spatial analysis of developmental regulator mutants uncovers a cascading series of cell-type-specific programs during nodule maturation. LSH1/LSH2 are central regulators of these programs, and lsh1/lsh2 mutants exhibit collapse of hormonal gradients and nodule identity. Strikingly, loss of nodule identity collapses to a primary-root identity rather than lateral-root fate. This work reveals how tissue complexity emerges through stacked developmental programs sustained in distinct cellular compartments, allowing the emergence of cell types specialized for harboring nitrogen-fixing bacteria. HIGHLIGHTSO_LI>136,000 cells define a 4D spatial atlas of nodules and lateral roots C_LIO_LI3D spatial and dual-species analysis resolves dynamic host and rhizobial cell states C_LIO_LIA shared meristem generates 3 spatially coordinated symbiotic, non-symbiotic, and vascular cell programs C_LIO_LILSH1/LSH2 are critical for regulatory programs underlying nodule development and identity C_LIO_LINodule identity loss collapses toward a primary root-associated state, not a lateral root fate C_LI

plant biology↗

bioRxiv2025

A scalable approach for tissue microarray profiling using spatial single cell transcriptomics

Spatially resolved transcriptomics was named Method of the Year 20201 and has continued to evolve rapidly since then, providing novel insights in development, physiology, and disease processes. Many approaches now offer excellent performance in formalin-fixed paraffin embedded tissue, opening up a wealth of archived clinical samples to these high-throughput spatial biology modalities. In this Chapter, we introduce a methodology to apply 10x Xenium In Situ to FFPE tissue microarrays. Using this method we have achieved a cost-effective approach to profile hundreds of genes with subcellular resolution in over a hundred human liver samples. Our method can easily be adapted to other tumour types, diseases, or model systems.

pathology↗

bioRxiv2025

Plant-Compatible Xenium In Situ Sequencing: Optimised Protocol for Spatial Transcriptomics in Medicago truncatula Roots and Nodules

Elucidating the spatial and temporal regulation of gene expression during plant organogenesis is crucial for enabling precise crop improvement strategies that incorporate beneficial traits into crops while avoiding adverse effects. Root nodules, specialised organs formed in symbiosis with nitrogen-fixing bacteria, provide a valuable system to study cell-type-specific gene networks in a symbiosis-induced developmental context. However, capturing these dynamics at cellular resolution in intact plant tissues remains technically challenging. Spatial transcriptomics technologies developed for animal systems are often not directly transferable to plant tissues due to fundamental differences in tissue composition between plants and animals, including rigid and heterogeneous plant cell walls, high cell wall autofluorescence, and large vacuoles in plant cells that complicate probe access and signal detection. To address these challenges, we present an optimised protocol for applying the Xenium in situ sequencing platform to formalin-fixed paraffin-embedded (FFPE) sections of plant tissues, including Medicago truncatula roots and nodules. Key technical adaptations include customised tissue preparation, optimised section thickness, hybridisation conditions, post-Xenium staining, imaging, and downstream image analysis, all tailored specifically for plant samples. To mitigate autofluorescence and enhance detection sensitivity, we employed a strategic approach to codeword selection during probe design. Furthermore, we developed a modular probe design approach combining a custom 380-gene standalone panel with a 100-gene add-on panel. This design allows flexibility for addressing diverse research questions and includes orthologous gene sequences from two Medicago ecotypes, ensuring compatibility for downstream functional validation using mutant lines available in both genetic backgrounds. We validated the protocol across nodules at multiple developmental stages using both the 50-gene panel targeting mature nodule cell identity and the extended 480-gene panel, which includes markers across different cell types and developmental stages, as well as genes of interest identified from prior single-cell and bulk RNA-seq analyses. This optimised workflow provides a reproducible and scalable method for high-resolution spatial transcriptomics in plant tissues, establishing a robust foundation for adaptation to other plant species and developmental systems.

plant biology↗

bioRxiv2021

Altered Sub-Genomic RNA Expression in SARS-CoV-2 B.1.1.7 Infections

SARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median expression. We hypothesise that this is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT>CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3 of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern. One Sentence SummaryThe recently emerged and more transmissible SARS-CoV-2 lineage B.1.1.7 shows greater subgenomic RNA expression in clinical infections and enhanced expression of a noncanonical subgenomic RNA near ORF9b.

genomics↗

bioRxiv2020

periscope: sub-genomic RNA identification in SARS-CoV-2 ARTIC Network Nanopore Sequencing Data

We have developed periscope, a tool for the detection and quantification of sub-genomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed "sub-genomic RNAs". sgRNAs are produced through discontinuous transcription which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L which is located in the 5 UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5 end of all sgRNA. We applied periscope to 1,155 SARS-CoV-2 genomes from Sheffield, UK and validated our findings using orthogonal datasets and in vitro cell systems. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sgRNA. We were able to detect all canonical sgRNAs at expected abundances, with the exception of ORF10. A number of recurrent non-canonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/- cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing datasets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.

bioinformatics↗