Biology subjects

Gersbach, C. A.

Publications and source records attributed to Gersbach, C. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Interrogation of noncoding schizophrenia risk variants using CRISPR-based functional genomics

Schizophrenia (SCZ) is a highly heritable complex disorder influenced by coding and noncoding genetic variation. Its genetic causes, particularly those involving noncoding variation, are largely unknown. High-throughput CRISPR screens enable dissection of disease-associated loci and identification of noncoding regulatory elements and variants that modulate gene expression. We screened SCZ GWAS loci linked to genes that are also associated in whole-exome sequencing studies to identify regulatory elements and variants impacting expression of disease-relevant genes. We used CRISPRi paired with HCR-FlowFISH to epigenetically silence 333 putative regulatory elements and measure the downstream effects on gene expression of causal SCZ genes, FAM120A, SV2A, and STAG1, in iPSCs and iPSC-derived neurons (iNeurons). We identified 78 regulatory elements that significantly alter expression of a SCZ gene, including noncoding enhancers/silencers as well as promoters of genes and lncRNAs. Pooled prime editing screens interrogated noncoding variant influence on gene expression for SCZ-associated variants and uncharacterized common variants from diverse population studies. We find that a common variant in the promoter of SV2A, rs112851681:A>G (MAF = 3.56%, 1000 Genomes) enhances transcriptional activity in iPSCs and iNeurons. These findings show distinct noncoding mechanisms that map within GWAS signals, and provide a path forward for interrogating noncoding regulatory elements and variants in disease loci.

genomics↗

bioRxiv2026

Quantitative profiling of intrinsic dCas9-DNA recognition reveals key determinants of guide RNA performance

CRISPR technologies based on nuclease-deactivated Cas9 (dCas9) rely on programmable DNA binding rather than DNA cleavage, yet the intrinsic DNA-recognition properties that govern optimal guide RNA (gRNA) performance remain poorly understood. Existing approaches either measure genomic occupancy in cells or infer dCas9 behavior from cleavage-based Cas9 datasets, despite DNA binding being substantially more permissive than DNA cleavage. Here we introduce TANGO (Targeted Array-based Nucleic acid-Guided Occupancy), a high-density DNA-array platform that quantitatively profiles intrinsic dCas9:gRNA binding across tens of thousands of DNA targets in a cell-free system. TANGO captures established features of dCas9 target recognition, while providing substantially greater sensitivity than prior assays. Comparison with ChIP-seq data demonstrates that intrinsic DNA-binding specificity is a major driver of genomic occupancy and reveals that chromatin accessibility modulates the intrinsic binding affinity required for dCas9 recruitment. Across CRISPRi/a guides, TANGO identifies multiple independent biochemical determinants of guide performance--including on-target affinity, mismatch tolerance, and ribonucleoprotein assembly--and flags problematic and highly promiscuous guides overlooked by current specificity metrics. Unexpectedly, some guides retain substantial guide-directed DNA binding even in the absence of a protospacer-adjacent motif (PAM), revealing an additional dimension of dCas9 specificity. Together, these results establish intrinsic DNA recognition as a quantitative and experimentally accessible determinant of dCas9 function, providing a framework for improving guide selection and enhancing the precision of CRISPR technologies.

genomics↗

bioRxiv2026

Region-Level Design and Analysis of CRISPR Perturbation Screens with FRACTEL

We present FRACTEL, a statistical framework for region-level analysis of CRISPR perturbation screens. FRACTEL aggregates gRNA p-values using a bounded minimum across order statistics, preserving scale and enabling adaptive sensitivity to sparse or diffuse effects. Region-level null distributions are estimated via simulation, ensuring precise type I error control. Simulations and real CRISPRi/a datasets demonstrate improved power and replication rate over gRNA-level analyses. FRACTEL also informs experimental design, revealing trade-offs between gRNA redundancy and efficacy and identifying inherent limits in single-cell repression screens of lowly expressed genes. The method integrates with existing pipelines and supports diverse CRISPR screening applications.

bioinformatics↗

bioRxiv2026

Transcription factor collaboration enables precise T cell state engineering

Transcription factors (TFs) collaborate to regulate gene expression programs that define cell fate. In CD8+ T cells, this coordinated regulation underlies exhaustion, a dysfunctional state that constrains immunity in chronic infection and cancer. Here, we screen for cell state-specific TFs by performing pooled overexpression screens of 3,548 TF and TF isoforms in primary T cells across multiple CD8+ T cell states. We identify 82 regulators that collaborate with exhaustion-specific programs and profile their effects using perturb-SHARE-seq, connecting perturbations to changes in chromatin accessibility and gene expression across 702,314 single cells. We identify 38 reproducible regulatory programs and construct a map of 12,616 TF-program connections that shape CD8+ T cell states, nominating KLF2 as predictive of positive response to CAR-T therapy. Using seq2PRINT, a deep learning framework that predicts functional TF interactions, we identify RUNX as a "master collaborator", a TF that broadly collaborates with other factors, and uncover a RUNX2:KLF2 interaction that specifies exhaustion-associated programs. Mutation of the RUNX2:KLF2 protein interface attenuates KLF2-mediated repression of exhaustion, while synthetic tethering of RUNX2 to KLF2 leads to an amplification of the phenotype. More broadly, we identify the collaborative action of RUNX as a driver in CD8+ T cell states, and show that tethering TFs enables the rational engineering of cell state identity for cell and gene therapies.

genomics↗

bioRxiv2026

Enhancer hubs govern chromatin topology and Th17 identity

Between one and two million noncoding regulatory elements have been described across mammalian genomes, but determining their functional role remains a challenge. To address this gap, we measure the regulatory potential of open chromatin regions (OCRs) in five closely related mouse CD4+ T cell subsets with ATAC-STARR-seq, then map endogenous enhancer function and three-dimensional contacts in Th17 cells with pooled CRISPR-based noncoding screens and high-resolution Micro-C. Of all CD4+ T cell OCRs, approximately 25% demonstrate largely subset-shared regulatory activity, though we identify subset-restricted active elements distinguishable by their sequence features. In Th17 cells, we reveal a set of core regulatory OCRs essential for subset polarization at the Batf, Rorc(t) and Il17a/f loci, and confirm their requirement for cell identity in vivo. At these three loci, we resolve nested yet selective enhancer-to-enhancer and enhancer-to-promoter physical interactions that converge into multi-enhancer hubs. Importantly, these hubs contain many of the strongest functional elements. Perturbation of a single enhancer within the Batf locus selectively disrupts hub contacts and Batf expression in Th17 cells, recapitulating the genome-wide transcriptional and chromatin accessibility signatures of a germline knockout. Together, this work assigns regulatory activity to accessible chromatin across CD4+ T cell subsets and couples the function of a set of essential elements to selective three-dimensional contacts in Th17 cells.

genomics↗

bioRxiv2026

Reprogramming of neuronal genome function and phenotype by astrocytes

Heterotypic cell-cell interactions are critical to governing cellular physiology, disease progression, and responses to the environment and pharmacologic interventions. For example, neurons and astrocytes engage in intricate interactions that are essential for brain development and function1-3. However, the transformation of these extracellular signals into epigenomic regulation that governs cell function is poorly understood. Here, we report that weeks of co-culture between human induced pluripotent stem cell (hiPSC)-derived neurons and mouse cortical astrocytes extensively reprograms gene expression and the chromatin accessibility landscape in neurons, affecting thousands of genes and putative gene regulatory elements (REs), including many transcription factors (TFs). These genes are enriched for functions implicated in neuronal differentiation and maturation, and tend to be impacted in schizophrenia, and autosomal dominant Alzheimers disease. Through complementary CRISPR interference and activation screens, we recapitulated hundreds of astrocyte-induced transcriptional and chromatin remodeling events in mono-cultured neurons at both promoters and distal regulatory elements (REs) of TF genes. We discovered functional REs for [~]50 astrocyte-responsive TF genes, providing a map of gene regulatory network control. Astrocyte-responsive TF genes fall into groups that exert independent or counter-balancing transcriptional effects, highlighting the complex coordination of the neuronal response to astrocytes. Functional effects of specific TFs, including POU3F2 and TFAP2E, on neurite morphology and neuronal electrophysiology are consistent with transcriptional effects, demonstrating the capacity of direct epigenetic control to mimic heterotypic cellular signals. This work illuminates the regulation of neurodevelopment-and disease-relevant gene modules by neuron-astrocyte interactions, and provides a blueprint for applying modern functional genomics to uncover the links between cell microenvironment and epigenomic programming. HighlightsO_LINeuronal gene expression and chromatin accessibility landscape are profoundly remodeled by astrocytes over weeks of co-culture C_LIO_LIAstrocyte-responsive neuronal gene modules and neuron-responsive astrocytic gene modules are enriched for genes associated with schizophrenia and familial Alzheimers Disease C_LIO_LISingle-cell CRISPR interference and activation screens of astrocyte-responsive gene regulatory elements identified dozens of functional regulatory elements of TF genes in neurons C_LIO_LISingle-cell CRISPR interference and activation screens of >200 astrocyte-responsive TF genes uncovered discrete functional clusters that promote neuronal maturity or stemness C_LIO_LIAstrocyte-responsive TF genes reprogram neuronal electrophysiology and neurite morphology C_LI

genomics↗

bioRxiv2026

Functional Annotation of the Major Histocompatibility Complex Locus

The human major histocompatibility complex (MHC) locus has the greatest density of disease-associations in the human genome, including links to over 100 polygenic disorders. Its complex haplotype structure, rich gene density, and high degree of linkage disequilibrium combine to make deciphering the gene regulatory logic of the MHC locus extremely challenging. Employing complementary high-throughput CRISPR interference (CRISPRi) and activation (CRISPRa) epigenetic screens coupled with single-cell transcriptome profiling across three distinct human cell types, we identified hundreds of new connections between cis-regulatory elements (CREs) and their target genes in this locus. These CRE-gene links are largely cell type-specific and act as enhancers. Additionally, some CREs have complex features, including harboring both active and repressive histone marks, lacking chromatin accessibility, targeting multiple genes, or acting as silencers. Computational methods fail to predict a majority of these CRE-gene connections. These findings emphasize the potential for functional perturbation experiments to dissect complex loci and reveal shared and cell type-specific regulatory mechanisms relevant to genomics of complex diseases. Collectively, this study provides a unique resource for understanding the complex regulatory landscape within the MHC locus and supports the need for creating new models that encompass CRE-gene interactions, cell type-specific gene expression, and disease genetics in the noncoding genome.

genomics↗

bioRxiv2026

Mismatch tolerance of a gRNA for CRISPR-based gene activation confers broad activity critical for cell reprogramming

CRISPR activation and interference systems (CRISPRa/i) are widely used for programmable transcriptional control. Although these technologies are capable of highly specific single-gene activity, some applications of transcriptional network reprogramming require broad, genome-wide effects. Here, we identify a CRISPRa gRNA that robustly reprograms astrocyte transcriptional state. Unexpectedly, this activity arises from extensive off-target binding that induces expression changes in thousands of genes, unlike neighboring gRNAs targeting the same intended on-target site. We leverage this promiscuous gRNA to dissect determinants of gRNA-driven off-target dCas9 binding in the context of transcriptional reprogramming. Using ChIP-seq, high-throughput protein-binding microarrays, and gRNA-variant library screening in cells, we demonstrate that PAM-proximal bases are primary determinants of genomic binding, mismatch tolerance is both gRNA- and base-specific, and targeted mutations within the PAM-proximal region can tune gRNA specificity. We further demonstrate that CRISPRa-driven phenotypes can reflect combined contributions from widespread off-target activity and dose-dependent on-target effects. These findings highlight the potentially widespread impacts of CRISPRa off-target activity, underscore the need to account for cryptic effects when selecting and evaluating gRNAs for programming cell phenotypes, and demonstrate that multi-site binding by CRISPRa systems can be exploited as a feature for network-level perturbations in cell reprogramming. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/703129v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@b697b0org.highwire.dtl.DTLVardef@1a0b390org.highwire.dtl.DTLVardef@16ce710org.highwire.dtl.DTLVardef@b5d87a_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

DeltaNMF: A Two-Stage Neural NMF for Differential Gene Program Discovery

Non-negative matrix factorization (NMF) is a foundational dimensionality-reduction method in single-cell transcriptomics, valued for its interpretable gene programs. However, in case-control settings common in perturbation and disease research, standard NMF conflates quantitative shifts in program usage with qualitative emergence of novel programs, obscuring whether observed differences reflect altered activity of shared programs or genuinely new cellular states. Here, we present DeltaNMF, a neural network-based reformulation of NMF that enables flexible biological priors and structured multi-stage fitting. We first demonstrate how our framework incorporates foundation model-derived gene similarities through graph-Laplacian regularization, improving program coherence by 2.4-fold on protein interaction networks. Building on this flexibility, we introduce a two-stage architecture that explicitly separates baseline programs (learned from control cells) from case-specific programs, disambiguating altered usage from novel program emergence. Our GPU-accelerated implementation achieves 20x speedup over consensus NMF while maintaining comparable accuracy. On synthetic data with known ground truth, DeltaNMF correctly identifies which programs are new versus shifted. Applied to coronary artery disease (CAD) Perturb-seq data, DeltaNMF isolates disease programs including the cerebral cavernous malformations pathway identified by Schnitzler et al., while clearly distinguishing them from baseline endothelial programs with altered activity. Our neural network formulation of NMF opens new directions for incorporating diverse biological priors into interpretable single-cell analysis, providing a principled framework for differential program discovery in case-control studies.

bioinformatics↗

bioRxiv2025

SMARCA2 is an essential and potent cofactor for a specific subset of the glucocorticoid response in A549 cells

Glucocorticoids are a widely used, potent class of anti-inflammatory drugs that modulate the expression of hundreds of genes across the genome. Although the glucocorticoid response is primarily carried out by the glucocorticoid receptor (NR3C1, a.k.a. GR), there are many glucocorticoid receptor co-factors that are also essential to the downstream effects. To identify novel factors necessary for the glucocorticoid gene expression response, we used a genome-wide CRISPR screen in A549 lung adenocarcinoma cells. In that screen, we knocked out every gene in the human genome, and measured the effect of expression of the glucocorticoid-induced leucine zipper (GILZ), a classic glucocorticoid-response gene. We identified two chromatin remodeling proteins, SMARCA2 and BPTF, that are essential for GILZ expression. We then evaluated the genome-wide effects of SMARCA2 and BPTF on glucocorticoid-mediated gene expression. BPTF had a highly specific role in the glucocorticoid response, affecting the expression of only a handful of genes, and having virtually no effect on dexamethasone-induced changes in chromatin accessibility. However, SMARCA2 was necessary for 27% of dexamethasone-induced transcriptional changes (152 genes), and [~]7% of dexamethasone-induced changes in chromatin accessibility (586 regions of the genome). Genomic regions with SMARCA2-dependent changes in chromatin accessibility were characterized by high dexamethasone-induced regulatory activity in a massively parallel reporter assay, and dexamethasone-induced increases in transcription factor binding and chromatin states. Taken together, these data suggest that SMARCA2 is critical for chromatin remodeling at a specific set of genomic regions with high regulatory activity, which in turn drive changes in expression for many glucocorticoid-responsive genes.

genomics↗

bioRxiv2025

Circuit-specific gene editing for precision modulation of neuronal activity with CRISPR-rabies virus

CRISPR gene editing has revolutionized our ability to study and manipulate specific genes, enabling novel insights into gene function and potential therapies for brain disorders. Recent advances in cell-type-specific regulatory elements and viral delivery systems have made precise in vivo gene editing possible. However, neurons with similar molecular profiles can belong to different circuits, complicating efforts to manipulate circuit function and behavior. To address this, we developed CRISPR-rabies virus (CRV), which leverages the trans-synaptic spread of rabies virus to enable gene editing within anatomically defined neural circuits. By pairing CRV with cell type-specific Cas9 expression, we achieved targeted gene modifications in specific circuits. We demonstrate that CRV can modulate sodium and potassium channel expression in parvalbumin interneurons, thereby effectively regulating synaptic transmission of pyramidal neurons in the CA3 region of the hippocampus. Its compatibility with 3'-capture single-cell RNA-seq allows simultaneous circuit perturbation and molecular profiling. In summary, CRV allows precise circuit-level gene modulation, providing a platform for studying gene function in neural circuits and developing novel gene therapies for brain disorders.

neuroscience↗

bioRxiv2025

Comprehensive profiling of transcription factors for reprogramming human astrocytes to neuronal cells through endogenous CRISPR-based gene activation

Neuronal loss is a hallmark of neurodegeneration and brain injury. Direct reprogramming of astrocytes into neurons has emerged as a promising approach to restore lost neurons. Comprehensive mapping and characterization of candidate astrocyte-to-neuron reprogramming factors is an essential step to realizing the potential of this strategy. Here, we established a CRISPR activation (CRISPRa)-based approach for neuronal reprogramming of primary human astrocytes. We conducted high-throughput CRISPRa screens of all human genes encoding transcription factors (TFs) to identify novel and efficient reprogramming factors. scRNA-seq characterization of top hits revealed that single TFs reprogram primary human astrocytes into multiple neuronal subtypes with distinct cell type-specific gene signatures. We demonstrate that INSM1 reprograms astrocytes to a glutamatergic neuron-like state and has broad neurogenic activity across different cell types and across human and mouse contexts. Finally, we conduct paired CRISPRa screens to identify cofactors that cooperate with INSM1 to enhance neuronal reprogramming and subtype specification, and elucidate genomic mechanisms of interaction and downstream regulators.

cell biology↗

bioRxiv2025

RELB Reprograms Exhausted Tumor-Infiltrating Lymphocytes for Improved Adoptive Cell Therapy

Tumor-infiltrating lymphocytes (TILs) are a promising autologous cell therapy to treat solid tumors. TILs are manufactured by expanding and reinfusing tumor-reactive T cells from tumor biopsies. Efficacy of TIL therapies has been limited by the heterogeneity of expanded TIL products and the high prevalence of dysfunctional exhausted CD8+ T cells (TEX). While a subset of CD8+ TILs co-expressing CD103 and CD39 are enriched for tumor-reactive TILs across multiple cancer types, these cells are often in the TEX state with low proliferative potential. To identify regulators of human TIL proliferation, we screened an open reading frame library encoding for all human transcription factors (TFs). RELB emerged as the dominant driver of human TIL expansion with a skew towards CD8+ cells. TCR diversity was maintained after multiple days of in vitro expansion driven by RELB. Transcriptome profiling of multiple RELB-expressing TIL subtypes revealed a shift towards a memory/costimulatory-like phenotype. Using a HER2-targeting CAR and tumor co-culture model, RELB conferred improved persistence after multiple tumor challenges in vitro and improved solid tumor control in mouse xenografts in vivo. Finally, co-culture of RELB-overexpressing TILs with patient-matched tumor organoids showed an increase in TIL product polyfunctionality, tumor reactivity, and tumor killing. Collectively these results support promoting RELB expression as a strategy for broadly enabling TIL therapy for treating solid tumors.

bioengineering↗

bioRxiv2025

A gene regulatory element modulates myosin expression and controls cardiomyocyte response to stress

A hallmark of heart disease is gene dysregulation and reactivation of fetal gene programs. Reactivation of these fetal programs has compensatory effects during heart failure, depending on the type and stage of the underlying cardiomyopathy. Thousands of putative cardiac gene regulatory elements have been identified that may control these programs, but their functions are largely unknown. We profile genome-wide changes to gene expression and chromatin structure in cardiomyocytes derived from human pluripotent stem cells. We identify and characterize a gene regulatory element essential for the regulation of MYH6, which encodes human fetal myosin. Using chromatin conformation assays in combination with epigenome editing, we find that gene regulation is mediated by direct interaction between MYH6 and the enhancer. We also find that enhancer activation alters cardiomyocyte response to the hypertrophy-inducing peptide endothelin-1. Enhancer activation prevents polyploidization and changes in calcium dynamics following stress with endothelin-1. Collectively, these results identify regulatory mechanisms of cardiac gene expression programs that modulate cardiomyocyte maturation, cellular stress response, and could serve as potential therapeutic targets.

genomics↗

bioRxiv2024

Characterization and bioinformatic filtering of ambient gRNAs in single-cell CRISPR screens using CLEANSER

Recent technological developments in single-cell RNA-seq CRISPR screens enable high-throughput investigation of the genome. Through transduction of a gRNA library to a cell population followed by transcriptomic profiling by scRNA-seq, it is possible to characterize the effects of thousands of genomic perturbations on global gene expression. A major source of noise in scRNA-seq CRISPR screens are ambient gRNAs, which are contaminating gRNAs that likely originate from other cells. If not properly filtered, ambient gRNAs can result in an excess of false positive gRNA assignments. Here, we utilize CRISPR barnyard assays to characterize ambient gRNA noise in single-cell CRISPR screens. We use these datasets to develop and train CLEANSER, a mixture model that identifies and filters ambient gRNA noise. This model takes advantage of the bimodal distribution between native and ambient gRNAs and includes both gRNA and cell-specific normalization parameters, correcting for confounding technical factors that affect individual gRNAs and cells. The output of CLEANSER is the probability that a gRNA-cell assignment is in the native distribution over the ambient distribution. We find that ambient gRNA filtering methods impact differential gene expression analysis outcomes and that CLEANSER outperforms alternate approaches by increasing gRNA-cell assignment accuracy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/611293v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@165c63dorg.highwire.dtl.DTLVardef@ba0e15org.highwire.dtl.DTLVardef@f2b12eorg.highwire.dtl.DTLVardef@14e6c86_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Machine learning methods for predicting guide RNA effects in CRISPR epigenome editing experiments

CRISPR epigenomic editing technologies enable functional interrogation of non-coding elements. However, current computational methods for guide RNA (gRNA) design do not effectively predict the power potential, molecular and cellular impact to optimize for efficient gRNAs, which are crucial for successful applications of these technologies. We present "launch-dCas9" (machine LeArning based UNified CompreHensive framework for CRISPR-dCas9) to predict gRNA impact from multiple perspectives, including cell fitness, wild-type abundance (gauging power potential), and gene expression in single cells. Our launch-dCas9, built and evaluated using experiments involving >1 million gRNAs targeted across the human genome, demonstrates relatively high prediction accuracy (AUC up to 0.81) and generalizes across cell lines. Method-prioritized top gRNA(s) are 4.6-fold more likely to exert effects, compared to other gRNAs in the same cis-regulatory region. Furthermore, launch-dCas9 identifies the most critical sequence-related features and functional annotations from >40 features considered. Our results establish launch-dCas9 as a promising approach to design gRNAs for CRISPR epigenomic experiments.

bioinformatics↗

bioRxiv2024

Activation of the imprinted Prader-Willi Syndrome locus by CRISPR-based epigenome editing

SummaryEpigenome editing with DNA-targeting technologies such as CRISPR-dCas9 can be used to dissect gene regulatory mechanisms and potentially treat associated disorders. For example, Prader-Willi Syndrome (PWS) is caused by loss of paternally expressed imprinted genes on chromosome 15q11.2-q13.3, although the maternal allele is intact but epigenetically silenced. Using CRISPR repression and activation screens in human induced pluripotent stem cells (iPSCs), we identified genomic elements that control expression of the PWS gene SNRPN from the paternal and maternal chromosomes. We showed that either targeted transcriptional activation or DNA demethylation can activate the silenced maternal SNRPN and downstream PWS transcripts. However, these two approaches function at unique regions, preferentially activating different transcript variants and involving distinct epigenetic reprogramming mechanisms. Remarkably, transient expression of the targeted demethylase leads to stable, long-term maternal SNRPN expression in PWS iPSCs. This work uncovers targeted epigenetic manipulations to reprogram a disease-associated imprinted locus and suggests possible therapeutic interventions.

genomics↗

bioRxiv2024

Mechanosensitive genomic enhancers potentiate the cellular response to matrix stiffness

Epigenetic control of cellular transcription and phenotype is influenced by changes in the cellular microenvironment, yet how mechanical cues from these microenvironments precisely influence epigenetic state to regulate transcription remains largely unmapped. Here, we combine genome-wide epigenome profiling, epigenome editing, and phenotypic and single-cell RNA-seq CRISPR screening to identify a new class of genomic enhancers that responds to the mechanical microenvironment. These mechanoenhancers could be active on either soft or stiff extracellular matrix contexts, and regulated transcription to influence critical cell functions including apoptosis, mechanotransduction, proliferation, and migration. Epigenetic editing of mechanoenhancers on rigid materials tuned gene expression to levels observed on softer materials, thereby reprogramming the cellular response to the mechanical microenvironment. These editing approaches may enable the precise alteration of mechanically-driven disease states.

genomics↗