Biology subjects

Norman, T. M.

Publications and source records attributed to Norman, T. M..

12 recordsLinked to original sources

bioRxiv2026

Engineered regulatory states resolve context-dependent genetics in macular degeneration

The effects of many genes and disease-associated variants remain hidden in standard cellular models, limiting functional interpretation. Here we engineer regulatory states via CRISPR activation of transcription factors (TFs) in human RPE-1 cells, a model for age-related macular degeneration (AMD). Multiome Perturb-seq profiling of single-TF perturbations identified regulators that selectively opened chromatin at AMD GWAS variants inaccessible in resting RPE-1. Priming of partner motifs in chromatin made accessible by single-TF perturbations predicted TF pairs generating emergent transcriptional states in combinatorial Perturb-seq, providing a design principle for selecting informative interactions. Distinct TF pairs also showed variable convergence between polygenic AMD signals and Mendelian retinal disease genes, supporting an omnigenic model shaped by regulatory states. Finally, Mosaic, a chromatin-informed model of TF interaction phenotypes, nominated out-of-sample regulators, including a higher-order combination with experimentally validated emergent effects on AMD-associated programs. Engineered regulatory states thus bring hidden disease biology within experimental reach.

systems biology↗

bioRxiv2026

Scaling perturbations: beyond genome-scale CRISPR screens

CRISPR screens have become essential tools for systematically probing gene function from basic biology to drug discovery, yet important frontiers remain beyond genome scale. Probing regulatory elements, interpreting genetic variants, and mapping genetic interactions all challenge the sensitivity and scalability of existing approaches. Here we introduce two synergistic technologies to address these limitations. PORTAL (Perturbation Output via Reporter Transcriptional Activity in Lineages) shifts pooled genetics toward quantitative RNA phenotypes, encoding perturbation effects in expressed transcripts to enable single-molecule measurements with lineage or single-cell resolution. CAP cloning (Covalently closed Assembly Products) bypasses bacterial transformation to enable construction of ultrahigh-complexity lentiviral libraries. Combining these advances, we construct a genetic interaction map spanning 665,856 pairwise perturbations across 46 million clonal lineages--the largest exhaustive map in human cells and the first at this scale using a non-fitness phenotype. More broadly, this work charts a path toward comprehensive genetic interaction mapping in human cells.

systems biology↗

bioRxiv2025

C/EBPβ-mediated PARP1 Suppression Drives Tumor Progression of Aneuploid Cells

Aneuploidy--defined as gains and losses of chromosomes--is frequently observed in cancer and has been implicated in promoting tumor progression and metastasis. However, the molecular mechanisms underlying this phenomenon remain poorly understood. By generating new models of aneuploidy, we found that aneuploidy confers remarkable resistance to reactive oxygen species (ROS)-mediated cell death. This resistance is a general consequence of aneuploidy, independent of the specific chromosomes gained or lost. Mechanistically, Poly(ADP-Ribose) Polymerase 1 (PARP1) is suppressed in aneuploid cells, which inhibits PARP1-mediated cell death after ROS (parthanatos). We validated aneuploidy-associated PARP1 suppression across 15 cell models and human tumors, with pronounced effects in metastatic tumors. Importantly, decreased PARP1 levels promote tumor metastasis while increased PARP1 suppresses it. Through a genome-wide CRISPR screen and functional validation, we identified the transcription factor CCAAT/enhancer-binding protein beta (CEBPB) as a critical mediator of PARP1 downregulation and ROS resistance in aneuploid cells. Furthermore, we found that lysosomal dysfunction serves as the upstream mediator of CEBPB activation in aneuploid cells. We propose that aneuploidy-driven CEBPB activation promotes PARP1 suppression, fostering ROS resistance and cancer progression. HighlightsO_LIAneuploidy confers resistance to oxidative stress independent of p53 status, karyotype and cell lineage through inhibition of PARP1 expression and activity C_LIO_LISuppressed PARP1 enhances metastatic potential, while PARP1 restoration suppresses metastatic spread, revealing a novel mechanism linking aneuploidy to cancer progression. C_LIO_LIPARP1 suppression compromises DNA damage repair and cell death to multiple genotoxic stressors, including reactive oxygen species, alkylating agents, and UV radiation. C_LIO_LIA genome-wide CRISPR screen and a CRISPRa screen identifies CEBPB as a critical transcription factor mediating PARP1 regulation and ROS resistance. C_LIO_LINuclear CEBPB increases significantly after aneuploidization in experimental systems and in primary human cancers. C_LI O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/670212v2_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1bf4edforg.highwire.dtl.DTLVardef@d3311eorg.highwire.dtl.DTLVardef@13daf25org.highwire.dtl.DTLVardef@b5e65f_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2024

Comprehensive transcription factor perturbations recapitulate fibroblast transcriptional states

Cell atlas projects have nominated recurrent transcriptional states as drivers of biological processes and disease, but their origins, regulation, and properties remain unclear. To enable complementary functional studies, we developed a scalable approach for recapitulating cell states in vitro using CRISPR activation (CRISPRa) Perturb-seq. Aided by a novel multiplexing method, we activated 1,836 transcription factors in two cell types. Measuring 21,958 perturbations showed that CRISPRa activated targets within physiological ranges, that epigenetic features predicted activatable genes, and that the protospacer seed region drove an off-target effect. Perturbations recapitulated in vivo fibroblast states, including universal and inflammatory states, and identified KLF4 and KLF5 as key regulators of the universal state. Inducing the universal state suppressed disease-associated states, highlighting its therapeutic potential. Our findings cement CRISPRa as a tool for perturbing differentiated cells and indicate that in vivo states can be elicited via perturbation, enabling studies of clinically relevant states ex vivo.

systems biology↗

bioRxiv2024

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.

systems biology↗

bioRxiv2022

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we rigorously compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides the best balance between strong on-target knockdown and minimal nonspecific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

genomics↗

bioRxiv2022

Heterogeneity of Inflammation-associated Synovial Fibroblasts in Rheumatoid Arthritis and Its Drivers

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand the spectrum of states observed in cells that are constitutively resident. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored heterogeneity of synovial fibroblasts (FLS) in inflamed joints of rheumatoid arthritis (RA) patients using paired single cell RNA and ATAC sequencing (scRNA/ATAC-seq), multiplexed imaging, and spatial transcriptomics along with in vitro modeling of cell extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell derived cytokines, TNF, IFN{gamma}, IL-1{beta}, or lack thereof, drive six distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium.

immunology↗

bioRxiv2021

Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (pooled CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells and present a framework to power biological discovery with the resulting genotype-phenotype map. We use transcriptional phenotypes to predict the function of poorly-characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena - from RNA processing to differentiation. We leverage this ability to systematically identify the genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene function and cellular behavior.

genomics↗

bioRxiv2019

Titrating gene expression with series of systematically compromised CRISPR guide RNAs

Biological phenotypes arise from the degrees to which genes are expressed, but the lack of tools to precisely control gene expression limits our ability to evaluate the underlying expression-phenotype relationships. Here, we describe a readily implementable approach to titrate expression of human genes using series of systematically compromised sgRNAs and CRISPR interference. We empirically characterize the activities of compromised sgRNAs using large-scale measurements across multiple cell models and derive the rules governing sgRNA activity using deep learning, enabling construction of a compact sgRNA library to titrate expression of [~]2,400 genes involved in central cell biology and a genome-wide in silico library. Staging cells along a continuum of gene expression levels combined with rich single-cell RNA-seq readout reveals gene-specific expression-phenotype relationships with expression level-specific responses. Our work provides a general tool to control gene expression, with applications ranging from tuning biochemical pathways to identifying suppressors for diseases of dysregulated gene expression.

genomics↗

bioRxiv2019

Exploring genetic interaction manifolds constructed from rich phenotypes

Synergistic interactions between gene functions drive cellular complexity. However, the combinatorial explosion of possible genetic interactions (GIs) has necessitated the use of scalar interaction readouts (e.g. growth) that conflate diverse outcomes. Here we present an analytical framework for interpreting manifolds constructed from high-dimensional interaction phenotypes. We applied this framework to rich phenotypes obtained by Perturb-seq (single-cell RNA-seq pooled CRISPR screens) profiling of strong GIs mined from a growth-based, gain-of-function GI map. Exploration of this manifold enabled ordering of regulatory pathways, principled classification of GIs (e.g. identifying true suppressors), and mechanistic elucidation of synthetic lethal interactions, including an unexpected synergy between CBL and CNN1 driving erythroid differentiation. Finally, we apply recommender system machine learning to predict interactions, facilitating exploration of vastly larger GI manifolds.\n\nOne Sentence SummaryPrinciples and mechanisms of genetic interactions are revealed by rich phenotyping using single-cell RNA sequencing.

genomics↗

bioRxiv2018

Direct capture of CRISPR guides enables scalable, multiplexed, and multi-omic Perturb-seq

Pairing CRISPR-based genetic screens with single-cell transcriptional phenotypes (Perturb-seq) has advanced efforts to explore the function of mammalian genes and genetic networks. We present strategies for Perturb-seq that enable direct capture of CRISPR sgRNAs within 3 or 5 single-cell RNA-sequencing libraries using the 10x Genomics platform. This technology greatly expands the accessibility, scalability, and flexibility of Perturb-seq, specifically enabling use with programmed combinatorial perturbations and multiplexing with multi-omic measurements.

genomics↗

bioRxiv2018

Approaches to maximize sgRNA-barcode coupling in Perturb-seq screens

Perturb-seq is a platform for single-cell gene expression profiling of pooled CRISPR screens. Like many functional genomics platforms, Perturb-seq relies on lentiviral transduction to introduce perturbation libraries to cells. On this platform, these are barcoded sgRNA libraries. A critical consideration for performing Perturb-seq experiments is uncoupling of barcodes from linked sgRNA expression cassettes, which can occur during lentiviral transduction of co-packaged libraries due to reverse transcriptase-mediated template switching. This problem is common to lentiviral libraries designed with linked variable regions. Here, we demonstrate that recombination between Perturb-seq vectors scrambles linked variable regions separated by 2 kb. This predicts information loss in Perturb-seq screens performed with co-packaged libraries. We also demonstrate ways to address this problem and discuss best practices for single-cell screens with transcriptional readouts.

genomics↗