Biology subjects

Davis, O.

Publications and source records attributed to Davis, O..

7 recordsLinked to original sources

bioRxiv2026

scRepresenter: a workflow for computing, integrating and benchmarking cellular representations in single-cell transcriptomics

MotivationSingle-cell RNA sequencing (scRNA-seq) has become an attractive tool for studying complex diseases, in which transient cell states affecting diverse cell populations characterise disease development and progression. However, due to data sparsity and disease heterogeneity analysis is often challenging. With recent advances in machine learning, two widely used approaches have emerged for learning cellular representations: large-scale foundation models and biological knowledge-guided methods. Despite their complementary strengths, there is currently no unified workflow for systematically comparing and integrating these approaches. ResultsHere, we present scRepresenter, an open-source workflow for computing, integrating, and validating cellular embeddings derived from foundation models and biological knowledge-guided methods in the context of complex diseases. It consists of two components: a command-line workflow that computes cellular embeddings and performs downstream analyses, and an interactive Shiny application for visualizing and comparing the computed embeddings. scRepresenter supports four categories of cellular representations: (1) expression-based, (2) knowledge-guided, (3) foundation model-derived, and (4) hybrid embeddings that combine foundation model-derived representations with knowledge-guided representations. This approach takes a cell-by-gene count matrix as input and outputs an integrated object containing the computed embeddings. Then, this object can be uploaded into our interactive Shiny application to compare different embeddings. AvailabilityThe workflow is available at https://github.com/GuilhermePocas/scRepresenter ContactAL291@cam.ac.uk; MA2129@cam.ac.uk

bioinformatics↗

bioRxiv2025

A non-catalytic role for MLL2 in controlling chromatin organisation and mobility during the priming of pluripotent cells for differentiation

How the chromatin regulator MLL2 (KMT2B) influences cell differentiation remains poorly understood. MLL2 is the main histone 3 lysine 4 (H3K4) trimethyltransferase acting at bivalent promoters in embryonic stem cells (ESCs) and is required for ESCs to differentiate into neuroectoderm. We show here that this requirement occurs during exit from naive pluripotency, days before neuroectoderm differentiation is impaired. Although MLL2 knockout has only a subtle effect on transcription during exit, reducing the expression of a few important neuroectodermal transcription factors, it substantially remodels chromatin architecture, disrupting 3D chromatin loops associated with bivalent promoters. The enzymatic activity of MLL2 is not needed for stabilising these loops or for neuroectoderm differentiation. This non-catalytic function of MLL2 in stabilising 3D chromatin loops has implications for lineage specification. Because MLL2 shares features with all four MLLs, chromatin tethering, rather than H3K4 methylation, may represent the primary function of MLL proteins during lineage commitment.

cell biology↗

bioRxiv2025

Telomerase mRNA Reduces Radiation-induced DNA Damage of human skin

Over four million people undergo radiation therapy annually in the United States. Among these, more than 90% experience varying degrees of radiation-induced skin injury. Despite the enormity of the problem, there is currently no FDA-approved agent to prevent or treat skin damage caused by ionizing radiation. In the current study, ionizing radiation induced dose-dependent genomic and mitochondrial DNA damage, leading to apoptosis in primary cutaneous cells. Prior treatment with mRNA encoding telomerase reverse transcriptase (TERT) substantially reduced radiation-induced DNA damage in human primary skin cells and tissues. Mechanistically, TERT mRNA pretreatment enhances DNA repair, reduces mitochondrial ROS, and decreases apoptosis without extending telomere length during the experimental period, suggesting a non-canonical function of TERT to accelerate the cellular recovery from radiation. These findings highlight a potential therapeutic approach for preventing radiation-induced skin injury. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/636031v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@5bcee4org.highwire.dtl.DTLVardef@16c0c28org.highwire.dtl.DTLVardef@922c5dorg.highwire.dtl.DTLVardef@9eafd0_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2019

Shared Genetic Risk between Eating Disorder- and Substance-Use-Related Phenotypes: Evidence from Genome-Wide Association Studies

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; q<0.0001), and cannabis initiation and AN with binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to -0.23; qs<0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for MDD loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships between these behaviors.

genetics↗

bioRxiv2019

Calretinin positive neurons form an excitatory amplifier network in the spinal cord dorsal horn

The passage of nociceptive information is relayed through the spinal cord dorsal horn, a critical area in sensory processing. The neuronal circuits in this region that underpin sensory perception must be clarified to better understand how dysfunction can lead to pathological pain. This study used an optogenetic approach to selectively activate neurons that contain the calcium-binding protein calretinin (CR). We show that CR+ interneurons form an interconnected network that can initiate and sustain enhanced excitatory signaling, and directly relays signals to lamina I projection neurons. In vivo photoactivation of CR+ interneurons resulted in a significant nocifensive behavior that was morphine sensitive and cause a conditioned place aversion. Furthermore, halorhodopsin-mediated inhibition of CR+ interneurons elevated sensory thresholds. These results suggest that neuronal circuits in the superficial dorsal horn that involve excitatory CR+ neurons are important for the generation and amplification of pain, and identify these interneurons as a future analgesic target.

neuroscience↗

bioRxiv2017

Automating Mendelian randomization through machine learning to construct a putative causal map of the human phenome

A major application for genome-wide association studies (GWAS) has been the emerging field of causal inference using Mendelian randomization (MR), where the causal effect between a pair of traits can be estimated using only summary level data. MR depends on SNPs exhibiting vertical pleiotropy, where the SNP influences an outcome phenotype only through an exposure phenotype. Issues arise when this assumption is violated due to SNPs exhibiting horizontal pleiotropy. We demonstrate that across a range of pleiotropy models, instrument selection will be increasingly liable to selecting invalid instruments as GWAS sample sizes continue to grow. Methods have been developed in an attempt to protect MR from different patterns of horizontal pleiotropy, and here we have designed a mixture-of-experts machine learning framework (MR-MoE 1.0) that predicts the most appropriate model to use for any specific causal analysis, improving on both power and false discovery rates. Using the approach, we systematically estimated the causal effects amongst 2407 phenotypes. Almost 90% of causal estimates indicated some level of horizontal pleiotropy. The causal estimates are organised into a publicly available graph database (http://eve.mrbase.org), and we use it here to highlight the numerous challenges that remain in automated causal inference.

epidemiology↗

bioRxiv2016

Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations

Anorexia nervosa (AN) is a serious eating disorder characterized by restriction of energy intake relative to requirements, resulting in abnormally low body weight. It has a lifetime prevalence of approximately 1%, disproportionately affects females1,2, and has no well replicated evidence of effective pharmacological or psychological treatments despite high morbidity and mortality2. Twin studies support a genetic basis for the observed aggregation of AN in families3, with heritability estimates of 48%-74%4. Although initial genome-wide association studies (GWASs) were underpowered5,6, evidence suggested that signals for AN would be detected with increased power5. We present a GWAS of 3,495 AN cases and 10,982 controls with one genome-wide significant locus (index variant rs4622308, p=4.3x10-9) in a region (chr12:56,372,585-56,482,185) which includes six genes. The SNP-chip heritability [Formula] of AN from these data is 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability stems from common genetic variation. Using these GWAS results, we also find significant positive genetic correlations with schizophrenia, neuroticism, educational attainment, and HDL cholesterol, and significant negative genetic correlations with body mass, insulin, glucose, and lipid phenotypes. Our results support the reconceptualization of AN as a disorder with both psychiatric and metabolic components.

genomics↗