Biology subjects

Dendrou, C. A.

Publications and source records attributed to Dendrou, C. A..

7 recordsLinked to original sources

bioRxiv2026

Reconstructing donor genotypes from scRNA-seq for downstream eQTL and HLA-TCR analysis

Single-cell eQTL studies can reveal heterogeneous genetic effects on gene expression that vary with cell type, but their wider application has been constrained by the frequent absence of matched genotype data. Here, we present single-cell Transcriptome Allelic Prediction and Association Studies (scTAPAS), a bioinformatic framework for reconstructing donor genotypes directly from single-cell RNA-sequencing reads and downstream genetic analysis. Applying scTAPAS to 5' single-cell RNA-sequencing data from the COVID-19 Multi-omic Blood Atlas (COMBAT), we show that reference-based imputation of sparse RNA-derived genetic information generates genotype dosages sufficiently accurate for association testing. Despite testing only 18.0% of the variants available from conventional array-based genotyping and imputation, scTAPAS recovers 68.6% of cell type-eGene pairs identified using conventional array-based genotypes, with strong concordance in effect sizes. We further show that scTAPAS-derived variants can support imputation of classical HLA alleles and enable HLA-aware QTL analyses, including associations between HLA variation and TCR repertoire at single-cell resolution. Using matched single-cell TCR-sequencing data, we identify CD4+ T cell-specific associations between HLA class II alleles and T-cell receptor (TCR) Va; gene segment usage, highlighting the potential of analyses that complement TCR sequencing at single-cell resolution with HLA types. These results show that genetic information recovered from single-cell RNA sequencing data can support both regulatory and immunogenetic association analyses, expanding the discovery potential of single-cell cohorts for which conventional genotyping or HLA typing is unavailable.

bioinformatics↗

bioRxiv2026

Distinct transcriptional states of draining lymph node T cells following influenza vaccination in individuals with underrepresented ancestries

The transcriptional and cell repertoire changes of lymph node (LN) T cells following influenza vaccination have been under-investigated across different ethnicities. Draining (dLN) and non-draining (ndLN) axillary LN cells from 17 participants with genotypically varied African or Asian ancestry (ISRCTN13657999) were collected by fine needle aspiration (FNA) before, 5 days and 42 days after adjuvanted influenza vaccination and analysed by single-cell RNA-sequencing (scRNA-seq). The early dLN transcriptional profile and cellular dynamics were distinct from the ndLN; BACH2 expressing T cells were highly induced, exhibiting stem-like and unique quiescence signatures. Proliferating T follicular helper cells (Tfh) were enriched in dLN and Th1-like Tfh predominated with highly induced transcriptional changes. The BACH2+ T cell state and Th1-like Tfh cells, transcriptionally distinct from germinal centre (GC) T cells, were co-localised with LAMP3+ dendritic cells in the T cell zone of publicly available LN datasets, a region that was also distinct from GC Tfh niches. Together, these findings indicate that the induction of a robust, proliferative, and transcriptionally diverse Tfh response, alongside a discrete subset of BACH2+ T cells, represents a marked feature of the early T cell zone immune response to adjuvanted influenza vaccine in the dLN.

immunology↗

bioRxiv2024

Early regional lymph node activation drives influenza vaccine responses in an ancestrally diverse cohort

Early in vivo dynamics of human immune-cell activation across regionally activated lymphoid tissue sites upon immunisation are poorly characterised in ancestrally diverse individuals. Here, we profiled draining and non-draining axillary lymph nodes (dLNs and ndLNs) by ultrasound-guided fine-needle aspiration (FNA) in 13 Black and Asian ancestry individuals, before and 3-7 days after vaccination with adjuvanted influenza vaccine. Draining but not ndLNs rapidly increased in size post-vaccination, by day 3, with distinct cellular dynamics determined through single cell multiomics. Dissecting LN cellular diversity into 42 lymphoid and non-lymphoid cell states, post-vaccination cell abundance changes were observed across all LNs, but dLNs were specifically characterised by CD4+ T follicular helper (CD4+ Tfh) cell expansion. Gene expression analysis revealed a dLN post-vaccination hub of multicellular activity defined by CD4+ Tfh signalling, cross-compartmental activation, translation, and enhanced antigen-presentation capacity. Thus, robust responses to intramuscular immunisation transcending ancestral inter-individual variation are elicited through temporal, anatomical and cellular lymphatic co-ordination with implications for vaccine design in ancestrally diverse populations. SummaryIn this study of ancestrally diverse young adults, the temporarily co-ordinated response to an adjuvanted influenza vaccine at lymph nodes local to (draining) and distal from (non-draining) the injection site, reveals early regulation of cellular kinetics and anatomical hierarchy of the innate and adaptive immune responses.

immunology↗

bioRxiv2023

hadge: a comprehensive pipeline for donor deconvolution in single cell

Single cell multiplexing techniques (cell hashing and genetic multiplexing) allow to combine multiple samples, thereby optimizing sample processing and reducing batch effects. Cell hashing conjugates antibody-tags or chemical-oligonucleotides to cell membranes, while genetic multiplexing allows to mix genetically diverse samples and relies on aggregation of RNA reads at known genomic coordinates. We developed hadge (hashing deconvolution combined with genotype information), a Nextflow pipeline that combines 12 methods to perform both hashing- and genotype-based deconvolution. We propose a joint deconvolution strategy combining the best performing methods and we demonstrate how this approach leads to recovery of previously discarded cells in a nuclei hashing of fresh-frozen brain tissue.

bioinformatics↗

bioRxiv2022

Biochemical and metabolic maladaption defines pathological niches in progressive multiple sclerosis

Progressive multiple sclerosis (MS) is driven by demyelination, neuroaxonal loss, and mitochondrial damage occurring behind a closed blood-brain barrier (BBB).1,2 Patients with progressive MS typically fail to respond to available immunomodulatory drugs that reduce relapses in early disease.2 This indicates a dire need to identify non-canonical therapeutic avenues to limit neurodegeneration and promote protection and repair.3 Here, we have employed high-resolution multiomic profiling to characterise the biochemical and metabolic adaptations underpinning MS pathology, as these have been incompletely described but critically, may be amenable to BBB-permeable drug targeting. Using synchrotron radiation (SR)- and focal plane array (FPA)-based Fourier transform infrared microspectroscopy (FTIR), we spatially mapped the biochemical features present in human progressive MS and control post-mortem brain and rare spinal cord tissue. By employing single-nuclear RNA sequencing (snRNA-seq), 10x Genomics Visium spatial transcriptomics and spatial proteomics to resolve their cellular context, we found that these biochemical features provide a uniquely and highly disease-specific barcode for distinct pathological niches within the tissue. Characterisation of the metabolic processes underpinning these niches revealed an associated re-organisation of the astrocytic landscape in the grey and white matter, with implications for the treatment of progressive MS.

neuroscience↗

bioRxiv2022

Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data

With continually improved instrumentation, Fourier transform infrared (FTIR) microspectroscopy can now be used to capture thousands of high-resolution spectra for chemical characterisation of a sample. The spatially resolved nature of this method lends itself well to histological characterisation of complex biological specimens. However, commercial software currently available can make joint analysis of multiple samples challenging and, for large datasets, computationally infeasible. In order to overcome these limitations, we have developed Photizo - an open-source Python library for spectral analysis which includes functions for pre-processing, visualisation and downstream analysis, including principal component analysis, clustering, macromolecular quantification and biochemical mapping. This library can be used for analysis of spectroscopy data without a spatial component, as well as spatially-resolved data, such as data obtained via infrared (IR) microspectroscopy in scanning mode and IR imaging by focal plane array (FPA) detector. Contactcdendrou@well.ox.ac.uk

bioinformatics↗

bioRxiv2019

An integrated platform to systematically identify causal variants and genes for polygenic human traits.

Genome-wide association studies (GWAS) have identified over 150,000 links between common genetic variants and human traits or complex diseases. Over 80% of these associations map to polymorphisms in non-coding DNA. Therefore, the challenge is to identify disease-causing variants, the genes they affect, and the cells in which these effects occur. We have developed a platform using ATAC-seq, DNaseI footprints, NG Capture-C and machine learning to address this challenge. Applying this approach to red blood cell traits identifies a significant proportion of known causative variants and their effector genes, which we show can be validated by direct in vivo modelling.

genetics↗