Biology subjects

Hon, G. C.

Publications and source records attributed to Hon, G. C..

16 recordsLinked to original sources

bioRxiv2026

Niche-dependent epistasis within the cancer genome shapes metastatic fitness

Epistasis, the genetic interaction between loci, directs non-additive genotype-to-phenotype outcomes. Within a multicellular organism, how the tissue niche (E) shapes gene-by-gene epistasis (GxG) and its phenotypic consequences remains poorly studied. Using tumor lung metastasis as an experimental model, we mapped GxGxE through combinatorial CRISPR perturbation coupled with depletion of defined host myeloid populations in mice. The metastatic niche first selects disseminated tumor cells on GxG epistatic fitness, then drives transcriptome convergence regardless of genotype. Removing anatomically distinct myeloid populations reshaped the metastatic epistasis landscape despite identical tumor genotypes. Gene-by-gene-by-environment epistasis therefore operates at the organismal level, with interaction magnitude and sign set by niche cells. Beyond metastasis, our data suggest that the tissue niche conditions how genetic interactions translate into divergent phenotypes.

genetics↗

bioRxiv2026

Systematic CRISPRi perturbation of 1,408 autism risk genes maps multilevel transcriptional convergence in human cortical neurons

Genetic heterogeneity in autism spectrum disorder (ASD) complicates the identification of shared molecular pathways amenable to therapeutic intervention. Here, we perform a CRISPRi Perturb-seq screen targeting 1,408 ASD risk genes in human embryonic stem cell-derived immature cortical neurons and profile the resulting transcriptomic effects by single-cell RNA sequencing. We identify 215 ASD risk genes whose repression induces significant global transcriptomic dysregulation. Leveraging this functional atlas, we characterize candidate genes based on transcriptional similarity to established ASD hub genes. We identify gene programs recurrently dysregulated across perturbations, anchored by processes governing microtubule dynamics, neuron differentiation, cell migration, and transmembrane transport. We further identify CHAMP1 as a previously unrecognized regulator of Wnt signaling and define specific ASD risk genes that modulate the rate of cortical neuron differentiation. Analysis of differentially expressed genes reveals both convergent and perturbation-specific downstream transcriptional responses. Together, these findings provide a multilevel map of transcriptomic convergence in ASD and establish a framework for identifying both pathway-level and genotype-specific therapeutic strategies.

neuroscience↗

bioRxiv2026

Perturb-seq resolves physiologic programs and bidirectional regulation of non-canonical NF-κB signaling in epidermal organoids

Regulated keratinocyte differentiation is required for formation of the stratified epidermis and a functional barrier. Understanding genetic drivers of keratinocyte differentiation is crucial for understanding several skin diseases. Perturb-seq is a single-cell CRISPR screen that measures transcriptomic responses to perturbations. To date, Perturb-seq experiments have principally focused on 2-dimensional cell culture models lacking hallmarks of skin development - physiological desmosome formation and barrier function. Here, we leverage Perturb-seq in an epidermal organoid model that recapitulates physiologically relevant differentiation programs. We demonstrate that our perturbations significantly impact diverse differentiation programs and reveal bidirectional function of non-canonical NF-{kappa}B signaling in late keratinocyte differentiation.

genomics↗

bioRxiv2026

Combinatorial transcription factor interactions drive modular gene regulatory networks

Transcription factors (TFs) cooperatively drive gene regulatory networks (GRNs) to establish transcriptional states. Forced induction of TFs in combination can reprogram cell state by supplanting existing GRNs. Thus, TFs and GRNs are the building blocks to engineering transcriptional state. However, one key challenge is that the relationship between TF combinations and GRNs remains largely uncharacterized and difficult to accurately predict. Here, we apply single-cell overexpression screens to map the combinatorial activities of [~]100 TFs to gene expression states. Our analysis identifies diverse TF combinations driving cell-type specific regulatory programs. Notably, different TF combinations induce shared gene sets with cell-type specific functions, suggesting a modular regulatory architecture of the transcriptome. Furthermore, we define pairwise TF interactions and show that cooperative interactions improve transcriptional reprogramming. Finally, we developed tools to predict combinatorial TF phenotypes. These findings improve our understanding of cell state and how to manipulate it for biomedical applications. HIGHLIGHTSO_LICombinatorial over-expression screens for [~]100 transcription factors (TFs). C_LIO_LIDiverse TF combinations drive cell-type specific regulatory programs. C_LIO_LITF regulatory networks reveal a modular regulatory architecture of the transcriptome. C_LIO_LITF-TF interactions and predictive models enhance reprogramming cocktails. C_LI

genomics↗

bioRxiv2026

Parallel Activation and Interference CRISPR (PAIR) with Sequencing Uncovers DNA Repair Networks Guiding Precision Cell Engineering

The dynamic balance of cellular homeostasis is often maintained by opposing regulatory pathways, yet most genetic screens interrogate them in one direction and therefore miss the bidirectional gene-gene interactions that shape complex phenotypes such as DNA damage response (DDR). Here, we present PAIR (Parallel Activation and Interference CRISPR), a bidirectional perturbation platform that enables simultaneous activation and suppression of distinct genes within the same cell using CRISPR activation (CRISPRa) and Cas13d RNA knockdown. Applying PAIR to the CRISPR/Cas9 induced DSB repair screen, we mapped gene-gene interactions across competing repair branches and identify synergistic perturbations, including NBN activation combined with suppression of end-joining factors, that shift repair outcomes toward homology-directed repair (HDR) and improve the precision of CRISPR-based gene editing. Using coupled PAIR with single-cell transcriptomic, we further demonstrated that NBN activation induces inflammatory and interferon programs, whereas co-suppression of end-joining factors buffers this response, revealing transcriptional states missed by conventional unidirectional perturbations. To translate these findings into non-viral chimeric antigen receptor (CAR) T cell engineering, we developed an mRNA-based strategy for parallel overexpression and knockdown of NBN-anchored DDR effectors in primary T cells, priming the T cells into a transient HDR-favored state that enhances the efficiency of CAR knock-in on the TRAC locus. Together, the PAIR system provides a general framework for studying opposing regulatory networks, uncovering hidden cell states, and guiding cell-state engineering through bidirectional perturbation.

bioengineering↗

bioRxiv2026

PEPR-GNN: Perturbation-Enhancer-Promoter-RNA Graph Neural Networks for Multiome Perturb-Seq modeling of regulomes

Cellular reprogramming is a complex interplay between perturbations and regulatory elements, culminating in gene expression changes. Current computational approaches do not explicitly model these regulatory interactions. Here, we performed combinatorial reprogramming with cardiac transcription factors, followed by Multiome Perturb-Seq to measure perturbations, open chromatin, and gene expression in individual cells. We then developed PEPR-GNN (Perturbation-Enhancer-Promoter-RNA Graph Neural Network), a theoretical and computational framework to model regulome responses during complex genetic perturbations. By statistically associating gene regulatory relationships, PEPR-GNN organizes genes into regulomes with shared gene regulatory responses to reprogramming, including easy-to-reprogram cardiac genes, difficult-to-reprogram fibroblast genes, and context-specific genes where the impact of a reprogramming factor depends on the presence of others. Finally, we use PEPR-GNN for in silico modeling of how genetic modifications of enhancers can be used to tune gene responses to reprogramming. Overall, through the use of causal perturbation information and an enhancer-aware regulome model of gene regulation, PEPR-GNN can effectively model complex cellular responses to perturbation. HighlightsO_LIMultiome Perturb-Seq of GHMT reprogramming in MEFs with RNA/ATAC-Seq readout. C_LIO_LIPEPR-GNN: a computational framework to model perturbation-induced regulomes. C_LIO_LIPEPR-GNN aids the interpretation of regulomes by diverse reprogramming responses. C_LIO_LIPEPR-GNN enables in silico perturbation to tune gene responses to reprogramming. C_LI

genomics↗

bioRxiv2026

Olfactomedin 4 marks luminal progenitor cells that give rise to a secretory cell lineage in the mouse cervix

Development of the female reproductive tract in mice occurs in early postnatal life. The current model identifies Trp63 as the master regulator that initiates differentiation of simple columnar Keratin 8+ epithelium in the cervix and vagina into a stratified squamous epithelium. Thereafter Trp63+ basal progenitors maintain cervicovaginal epithelial cell homeostasis and in the adult serve as the progenitor for hormone-regulated shifts in stratified squamous and secretory luminal cells. This model differs from the human in which two progenitors, one columnar and the other basal gives rise to secretory cells in the endocervix and stratified squamous epithelia in the ectocervix and vagina respectively. In the current study, we identify a population of Krt8+, Tp63- epithelial cells that are retained in the cervicovaginal epithelium during the postnatal developmental period and into adulthood. Single cell datasets from the cervices of adult mice, identify Olfactomedin 4 (Olfm4), as a unique marker of the Krt8+Trp63- population. Adult lineage tracing and reassessment of gene markers during postnatal development support a revised model in which two progenitors are delineated in the mouse cervix and vagina by PND15. Olfactomedin 4+ progenitors give rise to specialized secretory goblet cells, while Trp63+ basal progenitors give rise to stratified squamous luminal cells in the cervix and vagina of nonpregnant and pregnant mice. Consistent with the expansion of goblet cells in pregnancy, the Olfm4+ progenitor is highly proliferative in early pregnancy and progesterone regulates increased goblet cell differentiation. These findings reveal a previously unrecognized species similarity between mice and humans in which goblet cell and squamous keratinized cell subtypes are derived from two progenitor populations respectively. HIGHLIGHTSO_LITwo epithelial progenitors (Trp63 and Olfm4) populations are delineated in the cervix and vagina within the first two weeks of postnatal life. C_LIO_LIThe Trp63+ progenitor gives rise to keratinized epithelial cells, whereas the Olfm4+ progenitor cells give rise to secretory goblet cells. C_LIO_LIlfm4 is not required for maintenance of the luminal progenitor or differentiation of goblet cells in the cervix and vagina during adulthood and pregnancy. C_LIO_LIIn adults, progesterone promotes differentiation of Olfm4+ progenitors into goblet cells. C_LI

developmental biology↗

bioRxiv2025

Comprehensive perturbation of transcription factors in human cardiomyocytes reveals the regulatory architecture of congenital heart disease

Transcription factors (TFs), including DNA binding proteins and epigenetic co-regulators, control the timing of gene programs during lineage commitment1. However, systematically defining the dynamic activities of the human genomes nearly 2000 TFs during development remains challenging2,3. Here, we use Perturb-Seq to map the transcriptional impact of nearly all human TFs and a subset of enhancers during cardiomyocyte differentiation. Our results suggest that developmental regulatory networks are distributed across highly connected hub TFs4-6 that are dynamic across lineage and time, rather than organizing into top-down hierarchies directed by "master regulators". We also identify distinct TF ensembles that regulate sequential decision points during cardiac cell-fate specification by coordinating lineage-specific activation with alternate lineage repression. Separately, analysis of TF-TF cooperativity uncovers a dynamic interaction between MEF2 family TFs7 and members of the Polycomb Repressive complex 18-10 to execute alternative fate repression. Building on these regulatory interactions, we construct a deep learning transformer model to accurately predict perturbed TFs driving altered regulatory networks in patient-derived transcriptomes. Together, our results define the regulatory network architecture of human lineage specification and provide a platform for predicting TF function and interpreting disease mechanisms.

genomics↗

bioRxiv2025

Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells

Perturb-seq is a powerful approach to systematically assess how genes and enhancers impact the molecular and cellular pathways of development and disease. However, technical challenges have limited its application in stem cell-based systems. Here, we benchmarked Perturb-seq across multiple CRISPRi modalities, on diverse genomic targets, in multiple human pluripotent stem cells, during directed differentiation to multiple lineages, and across multiple sgRNA delivery systems. To ensure cost-effective production of large-scale Perturb-seq datasets as part of the Impact of Genomic Variants on Function (IGVF) consortium, our optimized protocol dynamically assesses experiment quality across the weeks-long procedure. Our analysis of 1,996,260 sequenced cells across benchmarking datasets reveals shared regulatory networks linking disease-associated enhancers and genes with downstream targets during cardiomyocyte differentiation. This study establishes open tools and resources for interrogating genome function during stem cell differentiation.

genomics↗

bioRxiv2024

Caveolin-1 regulates context-dependent signaling and survival in Ewing Sarcoma.

Plasticity is a hallmark function of cancer cells, yet the mechanisms that enable dynamic switching between survival states remain incompletely understood. Here, we identify Caveolin-1, a membrane-domain scaffolding protein, as a context-dependent regulator of survival signaling in Ewing sarcoma (EwS). Single-cell analyses reveal a distinct subpopulation of EwS cells marked by high CD99 and elevated Caveolin-1 expression. These CD99High cells exhibit unique morphology, transcriptional programs, and markedly enhanced survival both under chemotherapeutic challenge and in vivo. Importantly, CD99High and CD99Low states are reversible, providing EwS cells with a flexible route to survival-oriented plasticity. Mechanistically, we show that Caveolin-1 in CD99High cells orchestrates PI3K/AKT survival signaling by modulating the spatial organization of PI3K activity on the plasma membrane. We propose that the CD99High state establishes a Caveolin-1-driven signaling architecture that supports survival through mechanisms distinct from those used by CD99Low cells. These findings uncover a dynamic state transition in EwS cells and position Caveolin-1 as a key driver of context-specific survival signaling.

cancer biology↗

bioRxiv2023

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

genomics↗

bioRxiv2022

Large scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal crosstalk

Recent advances in human blastoids generated from naive pluripotent stem cells have opened a new avenue for modelling early human development and implantation. Despite the success, however, existing protocols have several limitations, e.g., the use of custom-built microwell arrays impedes wide adoption by the research community, and mass production of human blastoids is hampered by low-output or low-efficiency methods. To address these issues, here we developed an optimized protocol based on commercially available microwell plates, which enabled efficient generation of high-fidelity human blastoids at a large scale. Leveraging on the improved protocol, we identified MAPK. PI3K/AKT and mTOR signaling pathways were activated in both blastoids and blastocyst, and discovered endometrial stromal effects in promoting trophoblast cell survival, proliferation and syncytialization during extended co-culture with blastoids. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, tractable, and ethical model for human blastocysts.

developmental biology↗

bioRxiv2022

CHD-associated enhancers shape human cardiomyocyte lineage commitment

Enhancers orchestrate gene expression programs that drive multicellular development and lineage commitment. Thus, genetic variants at enhancers are thought to contribute to developmental diseases by altering cell fate commitment. However, while many variant-containing enhancers have been identified, studies to endogenously test the impact of these enhancers on lineage commitment have been lacking. We perform a single-cell CRISPRi screen to assess the endogenous roles of 25 enhancers and putative cardiac target genes implicated in genetic studies of congenital heart defects (CHD). We identify 16 enhancers whose repression leads to deficient differentiation of human cardiomyocytes (CMs). A focused CRISPRi validation screen shows that repression of TBX5 enhancers delays the transcriptional switch from mid- to late-stage CM states. Endogenous genetic deletions of two TBX5 enhancers phenocopy epigenetic perturbations. Together, these results identify critical enhancers of cardiac development and suggest that misregulation of these enhancers could contribute to cardiac defects in human patients. HIGHLIGHTSO_LISingle-cell enhancer perturbation screens during human cardiomyocyte differentiation. C_LIO_LIPerturbation of CHD-linked enhancers/genes causes deficient CM differentiation. C_LIO_LIRepression or knockout of TBX5 enhancers delays transition from mid to late CM states. C_LIO_LIDeficient differentiation coincides with reduced expression of known cardiac genes. C_LI

genomics↗

bioRxiv2019

SCINA: Semi-Supervised Analysis of Single Cells in silico

Advances in single-cell RNA sequencing (scRNA-Seq) have allowed for comprehensive analyses of single cell data. However, current analyses of scRNA-Seq data usually start from unsupervised clustering or visualization. These methods ignore the prior knowledge of transcriptomes and of the probable structures of the data. Moreover, cell identification heavily relies on subjective and inaccurate human inspection afterwards. We reversed this paradigm and developed SCINA, a semi-supervised model, for analyses of scRNA-Seq and flow cytometry/CyTOF data, and other data of similar format, by automatically exploiting previously established gene signatures using an expectation-maximization (EM) algorithm. We applied SCINA on a wide range of datasets, and showed its accuracy, stableness and efficiency exceeded most popular unsupervised approaches. Notably, SCINA discovered an intermediate stage of oligodendrocyte from mouse brain scRNA-Seq data. SCINA also detected immune cell population shifting in Stk4 knock-out mouse cytometry data. Finally, SCINA identified a new kidney tumor clade with similarity to FH-deficient tumors from bulk tumor data. Overall, SCINA provides both methodological advances and biological insights from perspectives different from traditional analytical methods.

bioinformatics↗

bioRxiv2018

A cellular anatomy of the normal adult human prostate and prostatic urethra

A cellular anatomy of normal human organs is essential for solving the cellular origins of disease. We report the first comprehensive cellular atlas of the young adult human prostate and prostatic urethra using an iterative process of single cell RNA sequencing and flow cytometry on ~98,000 cells taken from different anatomical regions. Two previously unrecognized epithelial cell types were identified by KRT13 and SCGB1A1 expression and found to be highly similar to hillock and club cells of the proximal lung. It was demonstrated by immunohistochemistry that prostate club and hillock cells are similarly concentrated in the proximal prostate. We also optimized a new flow cytometry antibody panel to improve cell type-specific purification based on newly established cellular markers. The molecular classification, anatomical distribution, and purification methods for each cell type in the human prostate create a powerful new resource for experimental design in human prostate disease.

cell biology↗

bioRxiv2018

Tissue-specific Gene Expression Prediction Associates Vitiligo with SUOX through an Active Enhancer

Vitiligo is an autoimmune disease featuring destruction of melanocytes, which results in patchy depigemtation of skin and hair; two vitiligo GWAS studies identified multiple significant associations, including SNPs in 12q13.2 region. But one study ascribed the association to IKZF4 because it encodes a regulator of T cell activation and is associated with two autoimmune diseases; while the other study ascribed the association to PMEL because it encodes melanocyte protein and has the strongest differential expression between vitiligo lesions and perilesional normal skins. Here we show that vitiligo associated gene in 12q13.2 region is SUOX. Reanalyzing one GWAS dataset, we predicted tissue-specific gene-expression by leveraging Genotype-Tissue Expression (GTEx) datasets, and performed association mapping between the predicted gene-expressions and vitiligo status. SUOX expression is significantly associated with vitiligo in both Nerve (tibia) and Skin (sun exposed) tissues. Epigenetic marks encompass the most significant eQTL of SUOX in both nerve and skin tissues suggest a putative enhancer 3Kb downstream of SUOX. We silenced the putative enhancer using the CRISPR interference system and observed 50% decrease in SUOX expression in K562 cells, a cell line that has similar DNase hypersensitive sites and gene expression pattern to the skin tissue at SUOX locus. Our work provided an example to make sense GWAS hits through examining factors that affect gene expression both computationally and experimentally.

genetics↗