Biology subjects

Talbot, A.

Publications and source records attributed to Talbot, A..

12 recordsLinked to original sources

bioRxiv2026

POISE: Spectral Inference of Parent-of-Origin Effects in Unlabeled Genomic Data

MotivationParent of Origin Effects (POEs), where the effect of an an allele on a phenotype differs based on maternal or paternal inheritance implicated in growth, metabolism, and neurodevelopment. Traditional tests for POEs require family data to determine parental origins of transmitted alleles. Given that such studies are expensive and time consuming compared to genome-wide association studies (GWAS), tests that function absent inheritance information are highly desirable. We develop a method, based on community detection from machine learning, that infers POEs via a spectral decomposition, obtains confidence intervals via a non-parametric bootstrap, and safeguards against confounding by non POE sources of variation. We refer to our method as Parent of Origin Inference via Spectral Estimation (POISE). ResultsWe demonstrate that POISE is well-calibrated under both Gaussian and heavy-tailed noise in simulation studies, with improved robustness to true POEs compared to existing covariance-based tests. POISE provides per-trait effect estimates with bias-corrected bootstrap confidence intervals and incorporates an information-theoretic minimum detectable effect size that filters unreliable estimates, conferring robustness to covariance-deflating variance QTL. We then apply POISE to GWAS data from the UK Biobank using BMI, LDL cholesterol, and HDL cholesterol. POISE recovers established POE loci and identifies 134 additional variants at genes implicated in lipid metabolism, immune regulation, and growth. Availability and implementationThe code for this method in Python is available at https://github.com/bystrogenomics/POISE.

genetics↗

bioRxiv2026

Development of a Fully Non-Viral 1XX-enhanced BCMA CAR-T Cell Therapy for Multiple Myeloma

Multiple myeloma (MM) is a clonal plasma cell malignancy characterized by bone marrow infiltration, monoclonal immunoglobulin production, and microenvironmental dysregulation that leads to systemic organ damage. The advent of B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T-cell therapy has induced unprecedented responses and durability for patients with relapsed/refractory MM. These outcomes are rarely observed with prior salvage strategies, although relapse remains the predominant long-term challenge for most patients. The two currently approved BCMA CAR-T cell products use viral vectors to semi-randomly insert the CAR gene, which results in heterogeneous genomic composition and variability in efficacy, safety, and product consistency. To address these challenges, we integrated targeted CRISPR genome engineering with precise CAR transgene insertion at the T-cell receptor alpha constant (TRAC) locus, 1XX CAR signaling architecture to enhance potency and durability, and non-viral manufacturing with a single-stranded DNA repair template to improve efficiency and yield. This approach confers physiological CAR expression, reduces insertional mutagenesis, and improves persistence by mitigating tonic signaling and exhaustion. Our GMP manufacturing process consistently achieved high CAR integration (37.7-72.7%) and yields across all full-scale runs and met predefined release criteria for identity, purity, safety, and quality. In NSG mouse models of MM, the UCCT-BCMA-1 product exhibited exceptionally potent tumor control, CAR-T cell expansion 100-1000-fold greater than that of lentiviral constructs, and durable clearance of myeloma cells after multiple rechallenges. These findings establish a CRISPR-edited, fully non-viral manufacturing platform for next-generation 1XX-BCMA CAR-T therapies with enhanced persistence, safety, and efficacy. One Sentence SummaryCRISPR-engineered, TRAC-targeted 1XX-BCMA CAR-T therapy with improved safety, potency, and persistence in relapsed and refractory multiple myeloma.

cancer biology↗

bioRxiv2025

Site-specific genome engineering of primary human natural killer cells for programmable anti-tumor function

Natural killer (NK) cells are emerging as a promising platform for engineered adoptive cell therapies. However, gene editing in NK cells remains challenging, and more effective strategies are needed. Here, we established a robust, feeder-free, and modular workflow for genome engineering in primary human NK cells, combining CRISPR/Cas9 with AAV6-mediated transgene delivery. Efficient site-specific transgene integration was achieved at various loci and can be coupled with concurrent disruption of the target locus in a single editing step. Furthermore, transgene expression was tunable according to the integration site and promoter. We applied this strategy to target a chimeric antigen receptor (CAR) transgene to a panel of inhibitory NK receptor loci, establishing a synergistic approach to enhance anti-tumor activity and facilitate the reliable comparison of CAR variants without expression bias. We identified TIGIT as an ideal locus that supports strong CAR expression and anti-tumor function. This genome engineering framework, which leverages multiple, complementary and precisely controlled genetic edits, can support the rational design of future NK-cell therapies tailored to overcome cell-intrinsic limitations and tumor-specific barriers.

immunology↗

bioRxiv2025

Scalp EEG predicts intracranial brain activity in humans

Inferring deep brain activity from noninvasive scalp recordings remains a fundamental challenge in neuroscience. Here, we analyzed concurrent scalp and intracranial recordings from 1918 electrode contacts across 20 patients affected by drug-resistant epilepsy undergoing intracranial depth electrode monitoring for pre-surgical evaluation to establish predictive relationships between surface and deep brain signals. Using regularized and cross-validated linear regression within subjects, we demonstrate that scalp recordings can predict spontaneous intracranial activity, with accuracy varying by region, depth, and frequency. Low-frequency signals (<12 Hz) were most predictable, with our models explaining approximately 10% of intracranial signal variance across contacts. Prediction accuracy decreased with contact depth, particularly for high-frequency signals. Using Bayesian modeling with leave-one-patient-out cross-validation, we observed generalizable prediction of activity in mesial temporal, prefrontal, and orbitofrontal cortices, explaining 10-12% of low-frequency signal variance. This scalp-to-intracranial mapping derived from spontaneous activity was further validated by its correlation with scalp responses evoked by direct electrical stimulation. These findings support the development of improved inverse models of brain activity and potentially more accurate scalp-based markers of disease and treatment response.

neuroscience↗

bioRxiv2023

Identification of Lactuca sativa transcription factors impacting resistance to Botrytis cinerea through predictive network inference

Lettuce is susceptible to a wide range of plant pathogens including the fungal pathogens Botrytis cinerea and Sclerotinia sclerotiorum, causal agents of grey mould and lettuce drop, respectively. Chemical control is routinely used but there is an urgent need to develop varieties with enhanced resistance given the economic and environmental costs of preventative pesticide sprays, the prevalence of fungicide-resistant isolates of both pathogens in the field, and the increasing withdrawal of approved fungicides through legislation. Resistance against Botrytis cinerea and Sclerotinia sclerotiorum is quantitative, governed by multiple small-medium impact loci, with plant responses involving large-scale transcriptional reprogramming. The elucidation of the gene regulatory networks (GRNs) mediating these responses will not only identify key transcriptional regulators but also interactions between regulators and show how the defence response is fine-tuned to a particular pathogen. We generated high-resolution (14 time points) time series expression data from lettuce leaves following mock-inoculation or inoculation with B. cinerea, capturing the dynamics of the transcriptional response to infection. Integrating this data with a time series dataset from S. sclerotiorum infection of lettuce identified a core set of 4362 genes similarly differentially expressed in response to both pathogens. Using the expression data for these core genes (with additional single time point data from 21 different lettuce accessions) we inferred a GRN underlying the lettuce defence response to these pathogens. Using the GRN, we have predicted and validated key regulators of lettuce immunity, identifying both positive (LsBOS1) and negative (LsNAC53) regulators of defence against B. cinerea, as well as downstream target genes. These data provide a high level of detail on defence-induced transcriptional change in a crop species and a GRN with the ability to predict transcription factors mediating disease resistance both in lettuce and other species.

plant biology↗

bioRxiv2022

Brain-wide oscillatory network selectively encodes aggression

Aggression is a psychological state characterized by intent to harm oneself or others, and often manifests as hostile, harmful, or violent action. Social aggression can aid an organism in securing access to resources1,2, or it can impair group function and survival in behavioral pathology3-5. Since many brain regions contribute to multiple social behaviors6-8, expanded knowledge of how the brain distinguishes between social states would enable the development of interventions that suppress violent action, while leaving other social behaviors intact. Here we showed that a murine aggressive internal state is encoded by a widespread network. This network is organized by prominent and synchronized theta (4-11 Hz) and beta (14-30 Hz) oscillations that relay through the medial prefrontal cortex, and couples to widespread cellular firing. Strikingly, network activity during social isolation was found to encode the trait aggressiveness of mice, and causal cellular manipulations known to impact aggression were found to modulate the networks activity. We next established that this network mediates aggression using closed-loop stimulation of medial prefrontal cortex and causal mediation analysis. Finally, we deployed Long-term integration of Circuits using connexins (LinCx) to selectively edit a key circuit within the network from the medial prefrontal cortex to nucleus accumbens. Editing this circuit chronically suppressed violent action while leaving non-aggressive social behavior intact.

neuroscience↗

bioRxiv2022

Identification of genetic loci in lettuce mediating quantitative resistance to fungal pathogens

Lactuca sativa L. (lettuce) is an important leafy vegetable crop grown and consumed globally. Chemicals are routinely used to control major pathogens, including the causal agents of grey mould (Botrytis cinerea) and lettuce drop (Sclerotinia sclerotiorum). With increasing prevalence of pathogen resistance to fungicides and environmental concerns, there is an urgent need to identify sources of genetic resistance to B. cinerea and S. sclerotiorum in lettuce. We demonstrated genetic variation for quantitative resistance to B. cinerea and S. sclerotiorum in a set of 97 diverse lettuce and wild relative accessions, and between the parents of lettuce mapping populations. Transcriptome profiling across multiple lettuce accessions enabled us to identify genes with expression correlated with resistance, predicting the importance of post-transcriptional gene regulation in the lettuce defence response. We identified five genetic loci influencing quantitative resistance in a F10 mapping population derived from a Lactuca serriola (wild relative) x lettuce cross, which each explained 5-10% of the variation. Differential gene expression analysis between the parent lines, and integration of data on correlation of gene expression and resistance in the diversity set, highlighted potential causal genes underlying the quantitative trait loci. Key MessageWe demonstrate genetic variation for quantitative resistance against important fungal pathogens in lettuce and its wild relatives, map loci conferring resistance and predict key molecular mechanisms using transcriptome profiling.

plant biology↗

bioRxiv2021

Epigenetic clock and methylation studies in gray short-tailed opossums

The opossum (Monodelphis domestica), with its sequenced genome, ease of laboratory care and experimental manipulation, and unique biology, is the most used laboratory marsupial. Using the mammalian methylation array, we generated DNA methylation data from n=100 opossum tissues including blood, liver, and tail. We contrast age-related changes in the opossum methylome to those of C57BL/6J mice. We present several epigenetic clocks for opossums that are distinguished by their compatibility with tissue type (pan-tissue and blood clock) and species (opossum and human). Two dual-species human-opossum pan-tissue clocks accurately measure chronological age and relative age, respectively. These human-opossum epigenetic clocks are expected to provide a significant boost to the attractiveness of opossum as a biological model.

evolutionary biology↗

bioRxiv2021

Hybrid ssDNA repair templates enable high yield genome engineering in primary cells for disease modeling and cell therapy manufacturing

CRISPR-Cas9 offers unprecedented opportunities to modify genome sequences in primary human cells to study disease variants and reprogram cell functions for next-generation cellular therapies. CRISPR has several potential advantages over widely used retroviral vectors including: 1) site-specific transgene insertion via homology directed repair (HDR), and 2) reductions in the cost and complexity of genome modification. Despite rapid progress with ex vivo CRISPR genome engineering, many novel research and clinical applications would be enabled by methods to further improve knock-in efficiency and the absolute yield of live knock-in cells, especially with large HDR templates (HDRT). We recently reported that Cas9 target sequences (CTS) could be introduced into double-stranded DNA (dsDNA) HDRTs to improve knock-in, but yields and efficiencies were limited by toxicity at high HDRT concentrations. Here we developed a novel system that takes advantage of lower toxicity with single-stranded DNA (ssDNA). We designed hybrid ssDNA HDRTs that incorporate CTS sites and were able to boost knock-in percentages by >5-fold and live cell yields by >7-fold relative to dsDNA HDRTs with CTS. Knock-in efficiency and yield with ssCTS HDRTs were increased further with small molecule inhibitor combinations to improve HDR. We demonstrate application of these methods across a variety of target loci, knock-in constructs, and primary human cell types to reach ultra-high HDR efficiencies (>80-90%) which we use for pathogenic gene variant modeling and universal gene replacement strategies for IL2RA and CTLA4 mutations associated with mendelian immune disorders. Finally, we develop a GMP-compatible method for fully non-viral CAR-T cell manufacturing, demonstrating knock-in efficiencies of 46-62% and generating yields of >1.5 x 109 CAR+ T cells, well above current doses for adoptive cellular therapies. Taken together, we present a comprehensive non-viral approach to model disease associated mutations and re-write targeted genome sequences to program immune cell therapies at a scale compatible with future clinical application.

synthetic biology↗

bioRxiv2020

Prenatal Environmental Stressors Impair Postnatal Microglia Function and Adult Behavior in Males

Gestational exposure to environmental toxins and socioeconomic stressors are epidemiologically linked to neurodevelopmental disorders with strong male-bias, such as autism. We modeled these prenatal risk factors in mice, by co-exposing pregnant dams to an environmental pollutant and limited-resource stress, which robustly activated the maternal immune system. Only male offspring displayed long-lasting behavioral abnormalities and alterations in the activity of brain networks encoding social interactions. Cellularly, prenatal stressors diminished microglial function within the anterior cingulate cortex, a central node of the social coding network, in males during early postnatal development. Genetic ablation of microglia during the same critical period mimicked the impact of prenatal stressors on a male-specific behavior, indicating that environmental stressors alter neural circuit formation in males via impairing microglia function during development.

neuroscience↗

bioRxiv2020

Brain-wide electrical dynamics encode an appetitive socioemotional state

Many cortical and subcortical regions contribute to complex social behavior; nevertheless, the network level architecture whereby the brain integrates this information to encode appetitive socioemotional behavior remains unknown. Here we measure electrical activity from eight brain regions as mice engage in a social preference assay. We then use machine learning to discover an explainable brain network that encodes the extent to which mice chose to engage another mouse. This socioemotional network is organized by theta oscillations leading from prelimbic cortex and amygdala that converge on ventral tegmental area, and network activity is synchronized with brain-wide cellular firing. The network generalizes, on a mouse-by-mouse basis, to encode socioemotional behaviors in healthy animals, but fails to encode an appetitive socioemotional state in a high confidence genetic mouse model of autism. Thus, our findings reveal the architecture whereby the brain integrates spatially distributed activity across timescales to encode an appetitive socioemotional brain state in health and disease.

neuroscience↗

bioRxiv2016

Architecture and dynamics of the jasmonic acid gene regulatory network

The phytohormone jasmonic acid (JA) is a critical regulator of plant growth and defense. To significantly advance our understanding of the architecture and dynamics of the JA gene regulatory network, we performed high-resolution RNA-Seq time series analyses of methyl JA-treated Arabidopsis thaliana. Computational analysis unraveled in detail the chronology of events that occur during the early and later phases of the JA response. Several transcription factors, including ERF16 and bHLH27, were uncovered as early components of the JA gene regulatory network with a role in pathogen and insect resistance. Moreover, analysis of subnetworks surrounding the JA-induced transcription factors ORA47, RAP2.6L, and ANAC055 provided novel insights into their regulatory role of defined JA network modules. Collectively, our work illuminates the complexity of the JA gene regulatory network, pinpoints to novel regulators, and provides a valuable resource for future studies on the function of JA signaling components in plant defense and development.

plant biology↗