Biology subjects

England, J.

Publications and source records attributed to England, J..

4 recordsLinked to original sources

bioRxiv2026

scRBP infers cell-specific RNA-binding protein regulons from single-cell transcriptomes at gene and isoform resolution

Single-cell regulatory network inference remains dominated by transcription factors, despite RNA-binding proteins (RBPs) orchestrating major aspects of transcriptional regulation. We present scRBP, a framework that infers motif-supported RBP regulons from short- and long-read single-cell transcriptomes at gene and isoform resolution, resolves targets by transcript region (5'UTR, CDS, intron, 3'UTR), scores regulon activity in individual cells, and tests common- and rare-variant association against matched empirical nulls. From 20,746 motifs for 616 RBPs, scRBP recovered experimentally defined targets across 223 ENCODE eCLIP datasets at gene and isoform level. Across 30 tissues, transcript-region preferences separated 3'UTR-associated stability factors from intron-dominant splicing regulators. In published genome-scale CRISPRi Perturb-seq data, scRBP-inferred targets were over-represented among genes responding to RBP knockdown (1.4-2.5-fold across 161 RBPs; FDR<2x10-4). Across 6.2 million cells and 50 traits, scRBP prioritized cell-specific post-transcriptional programs linking human genetic risk to development and disease.

genetics↗

bioRxiv2023

Learning Perturbation-specific Cell Representations for Prediction of Transcriptional Response across Cellular Contexts

High-throughput screens (HTS) are widely utilized to profile transcriptional states across multiple cell types and perturbations, and are often the first step on the bridge to the patient. However, their representative capacity to encompass all the cellular contexts encountered in a patient is limited. Thus, we present PerturbX, a novel deep learning model that leverages the rich information obtained from HTS to predict transcriptional responses to chemical or genetic perturbations in unobserved cellular contexts, and demonstrate its effectiveness in an experimental setting. Further-more, we show that the model is able to uncover interpretable genetic signatures associated with the predicted response, which can ultimately be translated into the clinical setting.

systems biology↗

bioRxiv2022

Neutrophil-Mediated Stromal-Tumor IL-6/STAT-3 Signaling Underlies the Association between Neutrophil-to-Lymphocyte Ratio Dynamics and Chemotherapy Response in Localized Pancreatic Cancer: A Hybrid Clinical-Preclinical Study

BackgroundPartial/complete pathologic response following neoadjuvant chemotherapy (NAC) in pancreatic cancer (PDAC) patients undergoing pancreatectomy is associated with improved survival. We sought to determine whether neutrophil-to-lymphocyte ratio (NLR) dynamics predict pathologic response following chemotherapy in PDAC, and if manipulating NLR impacts chemosensitivity in preclinical models and uncovers potential mechanistic underpinnings underlying these effects. MethodsPathologic response in PDAC patients (n=94) undergoing NAC and pancreatectomy (7/2015-12/2019) was dichotomized as partial/complete or poor/absent (case-cohort design). Bootstrap-validated multivariable models assessed associations between pre-chemotherapy NLR (%neutrophils/%lymphocytes) or NLR dynamics during chemotherapy ({Delta}NLR=pre-surgery--pre-chemotherapy NLR) and pathologic response, disease-free survival (DFS), and overall survival (OS). To preclinically model effects of NLR attenuation on chemosensitivity, C57BL/6 mice (n=8-10/arm) were orthotopically injected with KrasG12D/+;Trp53fl/+;PdxCre(KPC)cells and randomized to vehicle, NLR-attenuating anti-Ly6G, gemcitabine/paclitaxel, or gemcitabine/paclitaxel+anti-Ly6G treatments. ResultsIn 94 PDAC patients undergoing NAC (median:4 months), pre-chemotherapy NLR (P<0.001) and {Delta}NLR attenuation during NAC (P=0.002) were independently associated with partial/complete pathologic response. An NLR score=pre-chemotherapy NLR+{Delta}NLR correlated with DFS (P=0.006) and OS (P=0.002). Upon preclinical modeling, combining NLR-attenuating anti-Ly6G treatment with gemcitabine/paclitaxel--compared with gemcitabine/paclitaxel or anti-Ly6G alone--not only significantly reduced tumor burden and metastatic outgrowth, but also augmented tumor-infiltrating CD107a+-degranulating CD8+ T-cells (P<0.01) while dampening inflammatory cancer-associated fibroblast (CAF) polarization (P=0.006) and chemoresistant IL-6/STAT-3 signaling in vivo. Neutrophil-derived IL-1{beta} emerged as a novel mediator of stromal inflammation, inducing inflammatory CAF polarization and CAF-tumor cell IL-6/STAT-3 signaling in ex vivo co-cultures. ConclusionsTherapeutic strategies to mitigate neutrophil-CAF-tumor cell IL-1{beta}/IL-6/STAT-3 signaling during NAC may improve pathologic responses and/or survival in PDAC.

immunology↗

bioRxiv2020

Estimating the effect-size of gene dosage on cognitive ability across the coding genome

Genomic Copy Number Variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect-size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect-sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs >50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect-size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of IQ when duplicated or deleted, respectively. Effect-sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect-sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect-size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect-sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways.

genetics↗