Biology subjects

Mitra, R. D.

Publications and source records attributed to Mitra, R. D..

At least 19 recordsLinked to original sources

bioRxiv2026

High-avidity TCR signaling induces a distinct KLR-positive exhaustion state in human tumor-infiltrating CD8 T cells associated with immunotherapy response

T cells adopt diverse states in human disease, with tumor-specific CD8 T cells serving as the quintessential example. These cells are critical for immunotherapy response, yet acquire hypofunctional states of exhaustion that impair treatment efficacy. While significant heterogeneity is observed among exhausted CD8 T cells (TEX), the mechanisms directing their unique phenotypes remain unresolved, limiting our efforts to augment TEX cell function. Here, we profile TEX cells in human head and neck squamous cell carcinoma (HNSCC) tumors and define a major mechanism regulating their cell state. With single-cell RNA and T cell receptor (TCR) sequencing of 106,667 tumor-infiltrating CD8 T cells, we define and validate three fundamental TEX subsets, each harboring dominant clonotypes: a progenitor subset (TPEX) and two intra-tumoral populations marked by intermediate (TEX-int) or high expression of inhibitory receptors, including killer cell lectin-like receptors, such as KLRC1/NKG2A (TEX-KLR). Using an in vitro model, we show that TCR avidity-dependent NFAT signaling governs an axis between the TEX-int and TEX-KLR states across human cancers, with high-avidity signaling driving the TEX-KLR state. Additionally, we uncover that interleukin-12 signaling selectively antagonizes high-avidity TEX-KLR-specific genes, despite broadly potentiating activation and cytotoxicity. Finally, we find that TEX-int and TEX-KLR cells are associated with anti-PD-1 response in HNSCC, with both of these cell types enriched near viable cancer cells following treatment. Together, these findings reveal that TCR avidity orchestrates tumor-infiltrating TEX cell states through NFAT signaling, a tunable axis that may be targeted to improve TEX cell function.

immunology↗

bioRxiv2026

In vivo BMAL1 occupancy mapping using MACS-Calling Cards reveals disease-associated retargeting in Cln3Δex7/8 astrocytes

Astrocytic homeostatic programs, many of which are regulated by the circadian clock, are disrupted early in neurodegenerative disease. The core clock transcription factor (TF) BMAL1 is required for normal astrocyte function, but its role during disease remains unclear. This is partly because methods for identifying cell type-specific TF binding sites are limited. Here, we developed MACS-Calling Cards (MACS-CC), a strategy for mapping astrocyte-specific TF occupancy in vivo. We used MACS-CC to define BMAL1 binding in the Cln3{Delta}ex7/8 mouse model of CLN3 disease, a fatal neurodegenerative disorder marked by early astrocyte dysfunction and circadian disruption. BMAL1 binding was extensively redistributed in Cln3{Delta}ex7/8 astrocytes: wild-type-specific binding sites enriched near glial differentiation genes, whereas Cln3{Delta}ex7/8-specific sites lacked functional enrichment. Consistent with these changes, Cln3{Delta}ex7/8 astrocytes decreased expression of mature astrocyte markers. To define mechanisms underlying BMAL1 retargeting, we tested whether altered chromatin accessibility explained the changes in BMAL1 binding. Although chromatin accessibility was broadly remodeled, differential accessibility did not predict BMAL1 redistribution. Instead, motif analysis suggested that loss of cooperative TF interactions drives BMAL1 retargeting. These findings demonstrate that MACS-CC enables astrocyte-specific TF occupancy mapping and reveals mechanisms behind early rewiring of circadian regulatory programs within a model of a neurodegenerative disease. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/721783v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1ada239org.highwire.dtl.DTLVardef@7564a3org.highwire.dtl.DTLVardef@122222forg.highwire.dtl.DTLVardef@1f2729c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Ubiquitous functional synergy partially explains why most transcription factor binding is non-functional

Most genes in whose promotor a transcription factor (TF) binds do not change in expression when the concentration of the TF is perturbed. No existing model can predict which bound promotors will respond and which will not. We hypothesized that a genes response to perturbation of a TF bound in its promotor can depend on which other TFs are bound there, a phenomenon we call functional synergy. This is distinct from cooperative binding, which is already accounted for in the binding location data. To investigate functional synergy, we created a comprehensive dataset on TF binding locations in yeast using a method that is orthogonal to chromatin immunoprecipitation. We then used mathematical modeling to identify high-confidence instances of functional synergy. We found that such synergies are surprisingly common. Responses to perturbations of 44 different TFs were modified by the presence of other TFs. 48 TFs served as modifiers, but some modified responses to many TFs. We conclude that (1) measuring the binding locations of a single TF will not, in general, reveal which genes the TF regulates, and (2) traditional networks linking TFs to their targets must be made substantially more expressive, allowing some TFs to modify the effects of others.

genomics↗

bioRxiv2025

Inducible Calling Cards: Developing Mouse Reagents for Experimentally Controlled Transposon Insertion in vivo.

The piggyBac transposase enables robust forward genetic screens in mice. Further, fusions of piggyBac with specific transcription factors (TFs) enables recovery of recoverable transposons (Calling Cards) for recording location of DNA binding events in vitro and in vivo. Such applications would be enhanced by engineering inducible transposases, such that timing of recording could be precisely controlled in vivo, as has been previously developed in vitro. Here, we tested two approaches for applying inducible Calling Cards (iCC) in the murine brain. We engineered knock-ins of inducible versions of two TFs: Jun, an immediate early gene that serves as a proxy for neural activity, and Sp1, a promiscuous binder of CpG unmethylated regions that indicates active promoters. We fused hyperPiggyBac transposase and a tamoxifen-inducible domain (ERT2) to these TFs and tested the system for efficacy and temporal control of insertions, both in vitro and in vivo. Jun-iCC mice developed normally with no behavioral abnormalities, showed tamoxifen-dependent recording, and captured neural activity during pharmacologically induced seizures. Jun-iCC yields relatively low numbers of insertions, likely due to the transient expression of Jun. In contrast, Sp1-iCC provided substantially higher insertion numbers, but transgenic animals exhibited developmental abnormalities, including reduced viability, anophthalmia, and reduced body weight, suggesting that ERT2 domains may sequester Sp1 and thus significantly impact development. Nonetheless, these inducible Calling Cards mouse lines enable drug-inducible integration of transposon cargo into specific loci in the living mouse. SIGNIFICANCE STATEMENTTransposases, like the more widely used recombinases (Cre, Flp, etc.), enable the integration of a variety of DNA sequences into the genome, but without dependence on LoxP sites. However, few mouse reagents exist for transposases. Cre has been adapted to be drug-inducible, as well as activity-regulated (e.g., FOS-TRAP). Thus, additional applications would become available if transposases could also be drug-controlled and activity-dependent. Further, there may be benefits to targeting integration to specific genomic region types (e.g., promotors). Here, we report results testing mouse lines for two drug-inducible transposase fusions to transcription factors (TF) - the promoter binding SP1, and activity dependent Jun. Both allowed genomic integration, with viability, efficiency, inducibility and targeting varying by TF-fusion.

neuroscience↗

bioRxiv2025

Scalable transcription factor mapping uncovers the regulatory dynamics of natural and synthetic transcription factors in human T cell states

Heterogeneous T cell states are critical in immune responses and have been explored by CRISPR-based and synthetic domain-swapped transcription factor (TF) screens, yielding novel insights and immunotherapeutics. However, a scalable strategy to map TFs in primary human T cells is lacking, which limits our understanding of the functions of critical TFs. We therefore adapted a transposon-based TF mapping strategy termed Calling Cards for primary human CD8 T cells, applying it to five key TFs with undefined binding sites in this cell type: TOX, TOX2, TCF7, SOX4, and RBPJ. To derive biological insights from these data, we developed an analytical framework to integrate TF binding with multi-omic sequencing data, revealing convergence of TOX and TCF7 binding at dynamic enhancers of memory CD8 T cells. We then identified TF co-bound gene programs related to memory and exhaustion states in addition to putative gene targets of known and unappreciated TF roles, including TOX binding at critical genes of both exhaustion and terminal effector memory differentiation. To further scale our TF analysis platform, we modified Calling Cards to create TFlex: a method uniquely suited for multiplexed mapping of paralogous TFs. We applied TFlex to simultaneously map eight natural and domain-swapped TFs in primary human CD8 T cells, which demonstrated that domain-swapped TFs display emergent behavior in binding site selection and transcriptional effects on target genes that cannot be estimated as the sum of their constituent domains. Collectively, our data highlight the importance of scalable TF mapping in primary human T cells to elucidate TF function and the transcriptional regulation of cell states.

immunology↗

bioRxiv2025

SMURF Reconstructs Single-Cells from Visium HD Data to Reveal Zonation of Transcriptional Programs in the Intestine

High-resolution spatial transcriptomics requires new computational methods to accurately assign transcripts to individual cells. We developed SMURF (Segmentation and Manifold UnRolling Framework), a novel, cross-platform, soft-segmentation algorithm that maps mRNAs from barcoded capture spots to nearby nuclei. SMURF also "unrolls" complex tissue architectures by projecting cells onto Cartesian coordinates, enabling analysis of cell-type organization and gene-expression gradients in intact tissues. We benchmarked SMURF and found it assigns mRNAs to single cells more accurately than existing approaches. We evaluated SMURFs ability to unroll complex tissues at cell-type resolution across multiple tissues and platforms. This analysis revealed previously unrecognized zonation of gene-expression programs, identified the transcription factors that regulate these patterns, and provided evidence that regional gene expression at the intestinal tip is reprogrammed by luminal environmental signals. Together, these results establish SMURF as a powerful framework for analyzing gene expression of cells within their native tissue contexts.

genomics↗

bioRxiv2025

EGR1 drives sex-differences in glioblastoma tumorigenicity

Although progress has been made in treating glioblastoma (GBM), with fewer than 5% of patients surviving more than 5 years after diagnosis. For reasons that are not well understood, females are roughly 60% as likely as males to develop GBM, and female patients consistently respond better to treatment than do males. Understanding the molecular etiology of these sex differences in tumor progression and resiliency to treatment could reveal potent new therapeutic targets, ultimately improving survival of both male and female GBM patients. Here we show that the transcription factor Egr1 is a primary mediator of sex differences in multiple GBM tumorigenic phenotypes. In multivariate analysis, high levels of EGR1 expression are correlated with shortened survival for male GBM patients only. To investigate the molecular mechanisms underlying this sex difference, we performed a genomic analysis in our established ex vivo murine model of sex differences, which showed that the transcription factors Egr1 and Klf5 preferentially recruit the transcriptional activator Brd4 to enhancers in male cells relative to female cells, explaining a previously made observation that Brd4 inhibitors reverse sex differences in GBM. Next, using murine and human primary GBM cells, we demonstrated that the small molecule compound SR18662, which downregulates Egr1 and its downstream target Klf5, abrogates GBM growth, migration, invasion, clonogenicity, and response to radiation in a sex-biased fashion. Finally, we knocked down Egr1 and Klf5 via CRISPRi in both untreated and SR18662-treated GBM cells to reveal the sex-biased anti-tumorigenic effects of SR18662 were largely due to Egr1 downregulation, independent of Klf5 downregulation. This result was replicated in vivo. Our results strongly indicate that an Egr1 regulon is a key determinant of sex differences in GBM. As EGR1 is implicated in the cancer biology of many cancers that also display sex differences in incidence and treatment response, our results are likely to be broadly applicable in oncology.

cancer biology↗

bioRxiv2025

Prior epigenetic status predicts future susceptibility to seizures in mice

Wide variation of responses to identical stimuli presented to genetically inbred mice suggests the hypothesis that stochastic epigenetic variation during neurodevelopment can mediate such phenotypic differences. However , this hypothesis is largely untested since capturing pre-existing molecular states requires non-destructive, longitudinal recording. Therefore, we tested the potential of Calling Cards (CC) to record transient neuronal enhancer activity during postnatal development, and thereby associate epigenetic variation with a subsequent phenotypic presentation - degree of seizure response to the pro-convulsant pentylenetetrazol. We show that recorded differences in epigenetics at 243 loci predict a severe vs. mild response, and that these are enriched near genes associated with human epilepsy. We also validated pharmacologically a seizure -modifying role for two novel genes, Htr1f and Let7c. This proof-of-principle supports using CC broadly to discover predisposition loci for other neuropsychiatric traits and behaviors. Finally, as, human disease is also influenced by non-inherited factors, similar epigenetic predispositions are possible in humans.

genomics↗

bioRxiv2025

Single-Cell Resolution of Individual Variation in Hypothalamic Neurons Allows Targeted Manipulation Affecting Social Motivation

Despite decades of research, connecting molecular and cellular phenotypes to complex behavioral traits remains an elusive goal1. Social motivation exhibits individual trait variation2, which we hypothesize is mediated by molecular and cellular variability across hypothalamic neurons. To test this, we generated single-nucleus RNA-sequencing profiles3,4 of >120,000 neurons from tuberal hypothalamus and adjacent thalamus in 36 mice, balanced across sex and autism-associated mutation5, with all mice assessed for social motivation2. First, we show that molecular activation patterns predict behavior across individuals: specifically, activation of paraventricular Agtr1a+ (angiotensin receptor 1a) neurons predicted reduced social behavior. Subsequent inhibition of AGTR1A with telmisartan--an FDA-approved antihypertensive6--improved social orienting. Second, we show natural variation in neuronal proportions--likely arising from stochastic developmental events7--is sufficient to shape adult behavior even among genetically-identical individuals: we identified multiple neuronal populations whose relative abundance predicted social reward-seeking behavior. Chemogenetic inhibition of one such population, Nxph4+ neurons of the postero-lateral hypothalamus8, suppressed multiple aspects of social motivation. This work establishes proof-of-principle for an approach where single-cell genomics precisely maps neural substrates governing behavior. This approach revealed that stochastic variations in neuronal architecture deterministically influence social motivation, and enabled identification of therapeutically-actionable targets with immediate translational potential for disorders with social deficits.

genetics↗

bioRxiv2024

Biophysical Simulation Enables Multi-Scale Segmentation and Atlas Mapping for Top-Down Spatial Omics of the Nervous System

Spatial omics (SO) has produced high-definition mapping of subcellular molecules (like transcripts or proteins) within tissue samples. Mapping transcripts to anatomical regions requires segmentation, but even segmenting nuclei remains challenging for tissues like nerve cross sections, let alone for larger regions such as within the spinal cord. Neural networks could address this but need extensive human annotations--a bottleneck. We present SiDoLa-NS (Simulate, Dont Label - Nervous System), an image-driven (top-down) approach to SO analysis in the nervous system. We utilize biophysical properties of tissue architectures to design synthetic images mimicking tissue samples. With these in silico samples, we train supervised instance segmentation convolutional neural networks (CNNs) for nucleus segmentation, achieving precision and F1-scores > 0.95. We take this a step further with generalizable CNNs that can identify macroscopic tissue structures in the mouse brain (mAP50 = 0.869), spinal cord (mAP50 = 0.96), and pig sciatic nerve (mAP50 = 0.995). Short SummaryThe SiDoLa-NS micro-, meso-, and macro-scale models are generalizable, supervised CNNs for neuronal segmentation in cell to tissue-level contexts. SiDoLa-NS is novel in its combination of three core ideas: it is top-down (image first), trained solely on synthetic images, and it is multi-scale. The tool is validated on brain, spinal cord, and sciatic nerve for advanced segmentation tasks.

neuroscience↗

bioRxiv2024

MYT1L deficiency impairs excitatory neuron trajectory during cortical development

Mutations that reduce the function of MYT1L, a neuron-specific transcription factor, are associated with a syndromic neurodevelopmental disorder. Furthermore, MYT1L is routinely used as a proneural factor in fibroblast-to-neuron transdifferentiation. MYT1L has been hypothesized to play a role in the trajectory of neuronal specification and subtype specific maturation, but this hypothesis has not been directly tested, nor is it clear which neuron types are most impacted by MYT1L loss. In this study, we profiled 313,335 nuclei from the forebrains of wild-type and MYT1L-deficient mice at two developmental stages: E14 at the peak of neurogenesis and P21, when neurogenesis is complete, to examine the role of MYT1L levels in the trajectory of neuronal development. We found that MYT1L deficiency significantly disrupted the relative proportion of cortical excitatory neurons at E14 and P21. Significant changes in gene expression were largely concentrated in excitatory neurons, suggesting that transcriptional effects of MYT1L deficiency are largely due to disruption of neuronal maturation programs. Most effects on gene expression were cell autonomous and persistent through development. In addition, while MYT1L can both activate and repress gene expression, the repressive effects were most sensitive to haploinsufficiency, and thus more likely mediate MYT1L syndrome. These findings illuminate the intricate role of MYT1L in orchestrating gene expression dynamics during neuronal development, providing insights into the molecular underpinnings of MYT1L syndrome.

neuroscience↗

bioRxiv2023

Pathogenic Morphological Signatures of Perturbations in Mitochondrial-Related Genes Revealed by Pooled Imaging Assay

Mutations in mitochondrial-related genes underlie numerous neurodegenerative diseases, yet the significance of most variants remains uncertain concerning disease phenotypes. Several thousand genes have been shown to regulate mitochondria in eukaryotic cells, but which of these genes are necessary for proper mitochondrial dynamics? We investigated the degree of morphological disruptions in mitochondrial gene-silenced cells to understand the magnitude of genetic contribution to properly functioning mitochondria and to identify pathogenic variants. We analyzed 5,835 gRNAs in a high dimensional phenotypic dataset produced by the image-based pooled analysis platform Raft-Seq. Using the MFN2-mutant cell phenotype, we identified several genes, including TMEM11, TIMM8A, and three NADH Ubiquinone proteins, as crucial for normal mitochondrial morphology in human U2OS cells. Additionally, we found several missense and UTR variants within the genes SLC25A19 and ATAD3A as drivers of mitochondrial aggregation. By examining multiple features instead of a single readout, this analysis was powered to detect genes which had morphological signatures aligned with MFN2-mutant phenotypes. Reanalysis with anomaly detection revealed other critical genes, including APOOL, MCEE, NIT, PHB, and SLC16A7, which perturb mitochondrial network morphology in a manner divergent from MFN2. These studies offer insights into the molecular basis for mitochondrial dysfunction, setting the stage for new genomic diagnostics and therapeutic discovery.

genetics↗

bioRxiv2023

Calling Cards: a customizable platform to longitudinally record protein-DNA interactions over time in cells and tissues

Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next generation sequencing. Compared to other genomic assays, whose readout provides a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon (SRT) "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile specific transcription factor binding with custom transcription factor (TF)-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Card reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 1-2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. Basic Protocol 1: Preparation and delivery of Calling Cards reagents Basic Protocol 2: Sample preparation Basic Protocol 3: Sequencing library preparation Basic Protocol 4: Library pooling and sequencing Basic Protocol 5: Data analysis

genomics↗

bioRxiv2021

Measuring Transcription Factor Binding and Gene Expression using Barcoded Self-Reporting Transposon Calling Cards and Transcriptomes

Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover in vitro binding sites for four basic helix-loop-helix transcription factors with important roles in cell fate specification: ASCL1, MYOD1, NEUROD2, and NGN1. Further, simultaneous calling cards and transcriptional profiling during transcription factor overexpression identified both binding sites and gene expression changes for two of these factors. Lastly, we demonstrated barcoded calling cards can record binding in vivo in the mouse brain. In sum, RNA-based identification of transcription factor binding sites and gene expression through barcoded self-reporting transposon calling cards and transcriptomes is an efficient and powerful method to infer gene regulatory networks in a population of cells.

genomics↗

bioRxiv2021

Mitochondrial Phenotypes Distinguish Pathogenic MFN2 Mutations by Pooled Functional Genomics Screen

Most human genetic variation is classified as VUS - variants of uncertain significance. While advances in genome editing have allowed innovation in pooled screening platforms, many screens deal with relatively simple readouts (viability, fluorescence) and cannot identify the complex cellular phenotypes that underlie most human diseases. In this paper, we present a generalizable functional genomics platform that combines high-content imaging, machine learning, and microraft isolation in a new method termed "Raft-Seq". We highlight the efficacy of our platform by showing its ability to distinguish pathogenic point mutations of the mitochondrial regulator MFN2, even when the cellular phenotype is subtle. We also show that our platform achieves its efficacy using multiple cellular features, which can be configured on-the-fly. Raft-Seq enables a new way to perform pooled screening on sets of mutations in biologically relevant cells, with the ability to physically capture any cell with a perturbed phenotype and expand it clonally, directly from the primary screen. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/434746v2_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@c774b4org.highwire.dtl.DTLVardef@bee63corg.highwire.dtl.DTLVardef@fd7099org.highwire.dtl.DTLVardef@eb7d87_HPS_FORMAT_FIGEXP M_FIG C_FIG Here, we address the need to evaluate the impact of numerous genetic variants. This manuscript depicts the methods of using machine learning on a biologically relevant phenotype to predict specific point mutations, followed by physically capturing those mutated cells.

genomics↗

bioRxiv2020

The qBED track: a novel genome browser visualization for point processes

SummaryTransposon calling cards is a genomic assay for identifying transcription factor binding sites in both bulk and single cell experiments. Here we describe the qBED format, an open, text-based standard for encoding and analyzing calling card data. In parallel, we introduce the qBED track on the WashU Epigenome Browser, a novel visualization that enables researchers to inspect calling card data in their genomic context. Finally, through examples, we demonstrate that qBED files can be used to visualize non-calling card datasets, such as CADD scores and GWAS/eQTL hits, and may have broad utility to the genomics community. Availability and ImplementationThe qBED track is available on the WashU Epigenome Browser (http://epigenomegateway.wustl.edu/browser), beginning with version 46. Source code for the WashU Epigenome Browser with qBED support is available on GitHub (http://github.com/arnavm/eg-react and http://github.com/lidaof/eg-react). We have also released a tutorial on how to upload qBED data to the browser (dx.doi.org/10.17504/protocols.io.bca8ishw).

bioinformatics↗

bioRxiv2019

Multiplexed single-cell autism modeling reveals convergent mechanisms altering neuronal differentiation

The overwhelming success of exome- and genome-wide association studies in discovering thousands of disease-associated genes necessitates novel high-throughput functional genomics approaches to elucidate the mechanisms of these genes. Here, we have coupled multiplexed repression of neurodevelopmental disease-associated genes to single-cell transcriptional profiling in differentiating human neurons to rapidly assay the functions of multiple genes in a disease-relevant context, assess potentially convergent mechanisms, and prioritize genes for specific functional assays. For a set of 13 autism spectrum disorder (ASD) associated genes, we demonstrate that this approach generated important mechanistic insights, revealing two functionally convergent modules of ASD genes: one that delays neuron differentiation and one that accelerates it. Five genes that delay neuron differentiation (ADNP, ARID1B, ASH1L, CHD2, and DYRK1A) mechanistically converge, as they all dysregulate genes involved in cell-cycle control and progenitor cell proliferation. Live-cell imaging after individual ASD gene repression validated this functional module, confirming that these genes reduce neural progenitor cell proliferation and neurite growth. Finally, these functionally convergent ASD gene modules predicted shared clinical phenotypes among individuals with mutations in these genes. Altogether these results demonstrate the utility of a novel and simple approach for the rapid functional elucidation of neurodevelopmental disease-associated genes.

genomics↗

bioRxiv2019

Transposon-mediated, cell type-specific transcription factor recording in the mouse brain

Transcription factors (TFs) play a central role in the regulation of gene expression, controlling everything from cell fate decisions to activity dependent gene expression. However, widely-used methods for TF profiling in vivo (e.g. ChIP-seq) yield only an aggregated picture of TF binding across all cell types present within the harvested tissue; thus, it is challenging or impossible to determine how the same TF might bind different portions of the genome in different cell types, or even to identify its binding events at all in rare cell types in a complex tissue such as the brain. Here we present a versatile methodology, FLEX Calling Cards, for the mapping of TF occupancy in specific cell types from heterogenous tissues. In this method, the TF of interest is fused to a hyperactive piggyBac transposase (hypPB), and this bipartite gene is delivered, along with donor transposons, to mouse tissue via a Cre-dependent adeno-associated virus (AAV). The fusion protein is expressed in Cre-expressing cells where it inserts transposon "Calling Cards" near to TF binding sites. These transposons permanently mark TF binding events and can be mapped using high-throughput sequencing. Alternatively, unfused hypPB interacts with and records the binding of the super enhancer (SE)-associated bromodomain protein, Brd4. To demonstrate the FLEX Calling Card method, we first show that donor transposon and transposase constructs can be efficiently delivered to the postnatal day 1 (P1) mouse brain with AAV and that insertion profiles report TF occupancy. Then, using a Cre-dependent hypPB virus, we show utility of this tool in defining cell type-specific TF profiles in multiple cell types of the brain. This approach will enable important cell type-specific studies of TF-mediated gene regulation in the brain and will provide valuable insights into brain development, homeostasis, and disease.

neuroscience↗