Chun Ye

The paper identifies a rare population of neural crest-derived endocardial cells essential for heart valve development in mice and humans, showing their role in valve morphogenesis through Pthlh signaling.

This study identifies novel SLE autoantigens and links EBV-driven immunity to autoimmunity through longitudinal PhIP-seq and machine learning analysis.

This paper introduces SCITO-Perturb-seq, a CRISPRa platform that maps surface protein regulation in CD4 T cells, finding 16% of activated genes alter surface protein expression.

This paper introduces PerturbSpace, a method combining CRISPR perturbations with spatially hashed single-cell multiomics to study gene function in tissue architecture.

This paper expands structural surfaceomics to identify cancer-specific protein conformations across multiple tumor models, revealing potential immunotherapy targets through crosslinking mass spectrometry and structural modeling.

FastGxC efficiently maps context-specific eQTLs in bulk and single-cell RNA-seq data, improving power and speed while enhancing biological relevance and trait association precision.

The paper introduces ember, an entropy-based framework to assess gene specificity in single-cell RNA sequencing data, revealing unexpected patterns in gene expression across tissues and mouse strains.

ANTIPODE integrates single-cell data across species to identify homologous cell types and reveal gene regulatory divergence in developing mammalian brains.

This study uses base-editing to inactivate a missense mutation in A20ZF7, enhancing CAR-T cell efficacy by reducing exhaustion and improving anti-tumor responses.

The paper uses deep mutational scanning and structural analysis to study the functional effects of missense variants in the P2RY8 receptor and improves variant effect predictions.

This study shows that A20's M1 ubiquitin binding motif suppresses TH17/22 cell activation and IL-22-driven enteritis by regulating RORγt and epigenetic changes in T cells.

This study uses programmable microparticles to enhance CAR-T cell expansion beyond physiological limits by rewiring signaling pathways.

The paper identifies immune signatures in SLE cutaneous subtypes using transcriptomics, revealing subtype-specific pathways and potential therapeutic targets.

This study uses CRISPR screening and single-cell RNA sequencing to analyze host factors and transcriptional changes in RSV-infected and bystander cells, revealing distinct gene expression patterns and host dependencies.

The paper identifies two immunological subtypes of Sjögren's disease using single-cell RNA sequencing, highlighting distinct IFN-I signatures and transitional B cell characteristics.

The paper uses allelic inclusion data to train models that identify antibody sequence constraints, finding stronger correlations with antibody properties than existing methods.

This paper introduces scITD, a method to identify multicellular gene expression patterns that distinguish disease individuals, showing its application in SLE and COVID-19 datasets.

This paper identifies genetic variants in tubule epithelial regulatory elements that explain most heritable differences in human kidney function using GWAS, scATAC-seq, and functional assays.

The paper evaluates deep learning models for predicting chromatin accessibility and finds reduced performance in cell type-specific regions, suggesting strategies to improve accuracy.

The paper introduces MEOTIVE, a statistical framework to identify genetic effects on gene expression variability, revealing new mechanisms of genome regulation and associations with autoimmune disease risk.

Demuxafy improves droplet assignment and doublet removal in scRNA-seq by combining multiple demultiplexing and doublet detection methods.

The paper uses single cell RNA sequencing to assess the effects of protein-altering variants in three genes, showing that single cell expression signatures are more effective than bulk assays and computational models for predicting pathogenicity.

The paper identifies cell-specific transposable element (TE) gene expression associations with SLE phenotypes, finding 731 differentially expressed TEs linked to antiviral pathways and IFN signaling.

This study combines tissue clearing and deep learning to create 3D visualizations of human glioma vasculature, revealing vascular differences between low-grade and high-grade gliomas.

This study uses Perturb-seq to functionally interrogate SARS-CoV-2 host factors in human lung epithelial cells, identifying key factors that influence infection and host response.

The paper introduces clue, a reference-free framework for multiplexed single-cell sequencing to identify genetic modifiers of immune responses using SNP-based clustering and eQTL mapping.

The paper addresses statistical concerns about detecting natural selection during the Black Death using ancient genomic data, reaffirming findings related to immune loci and the ERAP2 variant.

This paper introduces SURGE, a method to discover context-specific eQTLs from single-cell RNA-seq data, showing its relevance in disease through colocalization analysis.

The paper introduces memento, a method for differential expression analysis of scRNA-seq data, and shows it identifies significant differences in mean, variability, and gene correlation across experimental conditions.

The paper identifies cell-type and cell-subtype specific eQTLs in aging human cortex, revealing variant effects on gene expression and disease associations.