Gary C. Hon

The paper maps gene-by-gene-by-environment epistasis in cancer metastasis using CRISPR perturbations in mice, showing niche-dependent fitness and transcriptome convergence.

This study uses CRISPRi Perturb-seq to analyze 1,408 autism risk genes in human cortical neurons, identifying 215 genes that cause global transcriptomic dysregulation and uncovering shared transcriptional pathways.

The paper uses Perturb-seq in epidermal organoids to study non-canonical NF-κB signaling's role in keratinocyte differentiation.

The paper identifies dynamic regulatory network hubs in human lineage specification using Perturb-Seq and constructs a deep learning model to predict perturbed TFs in patient transcriptomes.

The paper uses single-cell overexpression screens to study how combinations of transcription factors drive gene regulatory networks and cell-type specific gene expression programs.

PAIR combines CRISPR activation and RNA knockdown to study bidirectional gene interactions in DNA repair, revealing strategies to enhance CRISPR-based gene editing precision.

The paper introduces PEPR-GNN, a graph neural network framework to model regulome responses during genetic perturbations using Multiome Perturb-Seq data.

The paper identifies Olfm4 as a marker for luminal progenitor cells in the mouse cervix that give rise to secretory goblet cells, revealing a species similarity with humans.

This study benchmarks and optimizes Perturb-seq in human pluripotent stem cells, identifying shared regulatory networks during cardiomyocyte differentiation.

The paper uses single-cell CRISPRi screens to show variant-associated enhancers regulate cancer genes in breast cancer, revealing network motifs and subtype-specific functions.

This study identifies Caveolin-1 as a context-dependent regulator of survival signaling in Ewing Sarcoma, revealing a reversible CD99High state with enhanced survival.

This paper develops an optimized protocol for large-scale production of human blastoids and identifies signaling pathways and endometrial stromal effects in blastocyst development.

The paper identifies enhancers linked to congenital heart defects that, when repressed, impair human cardiomyocyte differentiation.

The paper characterizes the heterogeneity of the interstitium during kidney development and identifies distinct cell states and roles for beta-catenin in medullary interstitial cells.

SCINA is a semi-supervised model for analyzing scRNA-Seq and flow cytometry data, improving accuracy and efficiency over unsupervised methods by leveraging gene signatures.

The paper develops Reprogram-Seq to screen TF cocktails for reprogramming cell states, identifying a 3-TF combination that reprograms MEFs to epicardial-like cells.

The paper identifies SUOX as a vitiligo-associated gene by integrating GWAS data with tissue-specific gene expression prediction and experimental validation of an enhancer.

The paper identifies frequent recombination between sgRNA and barcode in single-cell CRISPR assays, reducing signal-to-noise ratio and suggesting improved methods.