Cell Type-specific Transcription Research Articles

Identification of the regulatory circuit governing corneal epithelial fate determination and disease.

The transparent corneal epithelium in the eye is maintained through the homeostasis regulated by limbal stem cells (LSCs), while the nontransparent epidermis relies on epidermal keratinocytes for renewal. Despite their cellular similarities, the precise cell fates of these two types of epithelial stem cells, which give rise to functionally distinct epithelia, remain unknown. We performed a multi-omics analysis of human LSCs from the cornea and keratinocytes from the epidermis and characterized their molecular signatures, highlighting their similarities and differences. Through gene regulatory network analyses, we identified shared and cell type-specific transcription factors (TFs) that define specific cell fates and established their regulatory hierarchy. Single-cell RNA-seq (scRNA-seq) analyses of the cornea and the epidermis confirmed these shared and cell type-specific TFs. Notably, the shared and LSC-specific TFs can cooperatively target genes associated with corneal opacity. Importantly, we discovered that FOSL2, a direct PAX6 target gene, is a novel candidate associated with corneal opacity, and it regulates genes implicated in corneal diseases. By characterizing molecular signatures, our study unveils the regulatory circuitry governing the LSC fate and its association with corneal opacity.

Analysis of potential biomarkers for diabetic kidney disease based on single-cell RNA-sequencing integrated with a single-cell sequencing assay for transposase-accessible chromatin.

Diabetic kidney disease (DKD) is a renal microvascular disease caused by hyperglycemia that involves metabolic remodeling, oxidative stress, inflammation, and other factors. The mechanism is complex and not fully unraveled. We performed an integrated single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) and single-cell RNA-sequencing (scRNA-seq) analyses of kidneys from db/db and db/m mice to identify differential open chromatin regions and gene expression, particularly in genes related to proximal tubular reabsorption and secretion. We identified 9,776 differentially expressed genes (DEGs) and 884 cell type-specific transcription factors (TFs) across 15 cell types. Glucose and lipid transporters, and TFs related to the circadian rhythm in the proximal tubules had significantly higher expression in db/db mice than in db/m mice (P<0.01). Crosstalk between podocytes and tubular cells in the proximal tubules was enhanced, and renal inflammation, oxidative stress, and fibrosis pathways were activated in db/db mice. Western blotting and immunohistochemical staining results showed that Wfdc2 expression in the urine and kidneys of DKD patients was higher than that in non-diabetic kidney disease (NDKD) controls. The revealed landscape of chromatin accessibility and transcriptional profiles in db/db mice provide insights into the pathological mechanism of DKD.

Smarca4 deficiency induces Pttg1 oncogene upregulation and hyperproliferation of tubular and interstitial cells during kidney development.

Kidney formation and nephrogenesis are controlled by precise spatiotemporal gene expression programs, which are coordinately regulated by cell-cycle, cell type-specific transcription factors and epigenetic/chromatin regulators. However, the roles of epigenetic/chromatin regulators in kidney development and disease remain poorly understood. In this study, we investigated the impact of deleting the chromatin remodeling factor Smarca4 (Brg1), a human Wilms tumor-associated gene, in Wnt4-expressing cells. Smarca4 deficiency led to severe tubular defects and a shortened medulla. Through unbiased single-cell RNA sequencing analyses, we identified multiple types of Wnt4 Cre-labeled interstitial cells, along with nephron-related cells. Smarca4 deficiency increased interstitial cells but markedly reduced tubular cells, resulting in cells with mixed identity and elevated expression of cell-cycle regulators and genes associated with extracellular matrix and epithelial-to-mesenchymal transition/fibrosis. We found that Smarca4 loss induced a significant upregulation of the oncogene Pttg1 and hyperproliferation of Wnt4 Cre-labeled cells. These changes in the cellular state could hinder the cellular transition into characteristic tubular structures, eventually leading to fibrosis. In conclusion, our findings shed light on novel cell types and genes associated with Wnt4 Cre-labeled cells and highlight the critical role of Smarca4 in regulating tubular cell differentiation and the expression of the cancer-causing gene Pttg1 in the kidney. These findings may provide valuable insights into potential therapeutic strategies for renal cell carcinoma resulting from SMARCA4 deficiency.

Refined read-out: The hUHRF1 Tandem-Tudor domain prefers binding to histone H3 tails containing K4me1 in the context of H3K9me2/3.

UHRF1 is an essential chromatin protein required for DNA methylation maintenance, mammalian development, and gene regulation. We investigated the Tandem-Tudor domain (TTD) of human UHRF1 that is known to bind H3K9me2/3 histones and is a major driver of UHRF1 localization in cells. We verified binding to H3K9me2/3 but unexpectedly discovered stronger binding to H3 peptides and mononucleosomes containing K9me2/3 with additional K4me1. We investigated the combined binding of TTD to H3K4me1-K9me2/3 versus H3K9me2/3 alone, engineered mutants with specific and differential changes of binding, and discovered a novel read-out mechanism for H3K4me1 in an H3K9me2/3 context that is based on the interaction of R207 with the H3K4me1 methyl group and on counting the H-bond capacity of H3K4. Individual TTD mutants showed up to a 10,000-fold preference for the double-modified peptides, suggesting that after a conformational change, WT TTD could exhibit similar effects. The frequent appearance of H3K4me1-K9me2 regions in human chromatin demonstrated in our TTD chromatin pull-down and ChIP-western blot data suggests that it has specific biological roles. Chromatin pull-down of TTD from HepG2 cells and full-length murine UHRF1 ChIP-seq data correlate with H3K4me1 profiles indicating that the H3K4me1-K9me2/3 interaction of TTD influences chromatin binding of full-length UHRF1. We demonstrate the H3K4me1-K9me2/3 specific binding of UHRF1-TTD to enhancers and promoters of cell-type-specific genes at the flanks of cell-type-specific transcription factor binding sites, and provided evidence supporting an H3K4me1-K9me2/3 dependent and TTD mediated downregulation of these genes by UHRF1. All these findings illustrate the important physiological function of UHRF1-TTD binding to H3K4me1-K9me2/3 double marks in a cellular context.

SynCAMs in Normal Vertebrate Neural Development and Neuropsychiatric Disorders: from the Perspective of the OCAs.

Neuronal synaptic junctions connect neurons to enable neuronal signal transmission in the nervous system. The proper establishment of synaptic connections required many adhesion molecules. Malfunctions of these adhesion molecules can result in neural development disorders and neuropsychiatric disorders. How specific synapses are established by various adhesion molecules for proper neural circuitry is a fundamental question of neuroscience. SynCAMs, also named CADMs, Necl, etc., are among the many adhesion proteins found in synapses. Here, we review the current understanding of the physical properties of SynCAMs and their roles in axon pathfinding, myelination, synaptogenesis, and synaptic plasticity. In addition, we discuss the involvement of SynCAMs in neuropsychiatric disorders. Finally, we propose that SynCAM functions can be better viewed and understood from the perspective of orientational cell adhesions (OCAs). In particular, we discuss the possibilities of how SynCAMs can be regulated at the cell-type specific expression, transcription variants, posttranslational modification, and subcellular localization to modulate the diversity of SynCAMs as OCA molecules. Being major components of the synapses, SynCAMs continue to be an important research topic of neuroscience, and many outstanding questions are waiting to be answered.

METB-03. THE DISTINCT GENOMICS OF HIGH-GRADE INFANT GLIOMAS AMONG PEDIATRIC GLIOMAS HARBORING RECEPTOR TYROSINE KINASE FUSIONS

Abstract Gliomas account for about 60% of pediatric brain tumors, about half of which are classified as high-grade. Recent studies have shown that infants with high-grade gliomas (HGG) harboring receptor tyrosine kinase (RTK) fusions have a more favorable prognosis than pediatric HGG patients. The molecular mechanisms for this favorable, but from the histology divergent clinical outcome, are yet unknown. We analyzed n=18 brain tumor samples (n=7 infant, n=11 pediatric) of patients with low-grade glioma (LGGs) or HGG presenting with RTK fusions using single-cell RNA sequencing. Considering the different fusion genes (ALK n=6, NTRK n=8, and MET n=4), age groups, and glioma grades, we evaluated the metaprograms of tumor cells and their proportions using non-negative matrix factorization. Preliminary results show similar metaprograms comparing infant and pediatric LGG. Cells detected as MES-like did not occur in LGG but were found in several HGG samples. However, in HGG, the MES-like cells show different expression patterns for infant and pediatric samples. In addition, compared with pediatric HGG, infant HGG has a higher proportion of programs that are predominantly present in LGG, such as AC-like and NPC-like. These initial findings serve as a starting point for cell type-specific transcription factor regulatory networks and are an important step toward understanding the underlying biology of this distinct pediatric brain tumor entity.

Establishment of the fetal-maternal interface: developmental events in human implantation and placentation.

Early pregnancy is a complex and well-orchestrated differentiation process that involves all the cellular elements of the fetal-maternal interface. Aberrant trophoblast-decidual interactions can lead to miscarriage and disorders that occur later in pregnancy, including preeclampsia, intrauterine fetal growth restriction, and preterm labor. A great deal of research on the regulation of implantation and placentation has been performed in a wide range of species. However, there is significant species variation regarding trophoblast differentiation as well as decidual-specific gene expression and regulation. Most of the relevant information has been obtained from studies using mouse models. A comprehensive understanding of the physiology and pathology of human implantation and placentation has only recently been obtained because of emerging advanced technologies. With the derivation of human trophoblast stem cells, 3D-organoid cultures, and single-cell analyses of differentiated cells, cell type-specific transcript profiles and functions were generated, and each exhibited a unique signature. Additionally, through integrative transcriptomic information, researchers can uncover the cellular dysfunction of embryonic and placental cells in peri-implantation embryos and the early pathological placenta. In fact, the clinical utility of fetal-maternal cellular trafficking has been applied for the noninvasive prenatal diagnosis of aneuploidies and the prediction of pregnancy complications. Furthermore, recent studies have proposed a viable path toward the development of therapeutic strategies targeting placenta-enriched molecules for placental dysfunction and diseases.

Single-Cell RNA Sequencing of Sox17-Expressing Lineages Reveals Distinct Gene Regulatory Networks and Dynamic Developmental Trajectories.

During early embryogenesis, the transcription factor SOX17 contributes to hepato-pancreato-biliary system formation and vascular-hematopoietic emergence. To better understand Sox17 function in the developing endoderm and endothelium, we developed a dual-color temporal lineage-tracing strategy in mice combined with single-cell RNA sequencing to analyze 6934 cells from Sox17-expressing lineages at embryonic days 9.0-9.5. Our analyses showed 19 distinct cellular clusters combined from all 3 germ layers. Differential gene expression, trajectory and RNA-velocity analyses of endothelial cells revealed a heterogenous population of uncommitted and specialized endothelial subtypes, including 2 hemogenic populations that arise from different origins. Similarly, analyses of posterior foregut endoderm revealed subsets of hepatic, pancreatic, and biliary progenitors with overlapping developmental potency. Calculated gene-regulatory networks predict gene regulons that are dominated by cell type-specific transcription factors unique to each lineage. Vastly different Sox17 regulons found in endoderm versus endothelial cells support the differential interactions of SOX17 with other regulatory factors thereby enabling lineage-specific regulatory actions.

Super-enhancer-associated transcription factors collaboratively regulate trophoblast-active gene expression programs in human trophoblast stem cells.

The placenta is an essential organ that supports the growth and development of the fetus during pregnancy. However, cell type-specific enhancers and transcription factors (TFs), and the mechanisms underlying the maintenance and differentiation of trophoblast stem cell (TSC) populations in the human placenta remain elusive. Here, using human TSCs as a model system, we identify 31,362 enhancers that are enriched with the motifs of previously reported TSC-pivotal TFs, including TEAD4, GATA2/3 and TFAP2C. Subsequently, we identify 580 super-enhancers (SEs) and 549 SE-associated genes. These genes are robustly expressed in the human placenta and include numerous TFs, implying that SE-associated TFs (SE-TFs) may play crucial roles in placental development. Additionally, we identify the global binding sites of five TSC-pivotal SE-TFs (FOS, GATA2, MAFK, TEAD4 and TFAP2C), revealing that they preferentially co-occupy enhancers, regulate each otherand form a trophoblast-active gene regulatory network. Loss-of-function studies unveil that the five TFs promote self-renewal of TSCs by activating proliferation-associated genes while repressing developmental genes. We further reveal that the five TFs exert conserved and unique functions on placental development between humans and mice. Our study provides important insights into the roles of human TSC-pivotal TFs in regulating placenta-specific gene expression programs.

How Deepbics Quantifies Intensities of Transcription Factor-DNA Binding and Facilitates Prediction of Single Nucleotide Variant Pathogenicity With a Deep Learning Model Trained On ChIP-Seq Data Sets.

The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants occurring in these binding regions play crucial roles in human disease by disrupting the cis-regulation of gene expression. We first implemented a sequence-based deep learning model called deepBICS to quantify the intensity of transcription factors-DNA binding. The experimental results not only showed the superiority of deepBICS on ChIP-seq data sets but also suggested deepBICS as a language model could help the classification of disease-related and neutral variants. We then built a language model-based method called deepBICS4SNV to predict the pathogenicity of single nucleotide variants. The good performance of deepBICS4SNV on 2 tests related to Mendelian disorders and viral diseases shows the sequence contextual information derived from language models can improve prediction accuracy and generalization capability.

The role of B-type lamins in genome architecture, chromatin dynamics, and gene regulation.

Chromatin is hierarchically organized in a dynamic manner in the mammalian cell nucleus, but the causal relationship between physical 3D genome organization and transcriptional activity and genome activity remains to be fully understood. Genome-wide studies have suggested that the interplay of several principles leads to the emergence of the major organizational features of the genome, including polymer-polymer interactions, chromatin loop extrusion, phase separation, the physical interaction of chromatin with stable architectural elements of the nucleus (i.e., nuclear envelope), and chromatin dynamics. The nuclear lamina is the ultimate determinant of nuclear space that posits a structural limit on the 3D genome organization. Lamins are structural components of the nuclear lamina that provide mechanical support to the nucleus and regulate genome organization and transcription. However, identifying the direct roles of lamins on dynamic genome organization has been challenging as depletion of lamin proteins severely impacts cell viability. To overcome this challenge, we engineered colon carcinoma cells to rapidly and completely degrade endogenous B-type lamins using Auxin-induced degron (AID) technology. We utilized a suite of novel technologies such as live-cell Dual Partial Wave Spectroscopic (Dual-PWS) microscopy, in situ Hi-C, and CRISPR-Sirius to demonstrate that acute lamin depletion increases chromatin dynamics at the nuclear periphery and weakens chromatin compartmentalization, as well as physically repositions gene-specific loci with respect to the nuclear periphery. Further, using the reversible AID system, we show that significantly altered genes after acute lamin depletion are enriched near LADs, and replenishment of lamins re-establishes their basal expression. Our findings provide a deeper understanding of the role B-type lamins in cell type-specific 3D genome organization and transcription.

Integrative single-cell RNA-seq and ATAC-seq analysis of myogenic differentiation in pig

BackgroundSkeletal muscle development is a multistep process whose understanding is central in a broad range of fields and applications, from the potential medical value to human society, to its economic value associated with improvement of agricultural animals. Skeletal muscle initiates in the somites, with muscle precursor cells generated in the dermomyotome and dermomyotome-derived myotome before muscle differentiation ensues, a developmentally regulated process that is well characterized in model organisms. However, the regulation of skeletal muscle ontogeny during embryonic development remains poorly defined in farm animals, for instance in pig. Here, we profiled gene expression and chromatin accessibility in developing pig somites and myotomes at single-cell resolution.ResultsWe identified myogenic cells and other cell types and constructed a differentiation trajectory of pig skeletal muscle ontogeny. Along this trajectory, the dynamic changes in gene expression and chromatin accessibility coincided with the activities of distinct cell type-specific transcription factors. Some novel genes upregulated along the differentiation trajectory showed higher expression levels in muscular dystrophy mice than that in healthy mice, suggesting their involvement in myogenesis. Integrative analysis of chromatin accessibility, gene expression data, and in vitro experiments identified EGR1 and RHOB as critical regulators of pig embryonic myogenesis.ConclusionsCollectively, our results enhance our understanding of the molecular and cellular dynamics in pig embryonic myogenesis and offer a high-quality resource for the further study of pig skeletal muscle development and human muscle disease.

A chromosome-scale epigenetic map of the Hydra genome reveals conserved regulators of cell state.

The epithelial and interstitial stem cells of the freshwater polyp Hydra are the best-characterized stem cell systems in any cnidarian, providing valuable insight into cell type evolution and the origin of stemness in animals. However, little is known about the transcriptional regulatory mechanisms that determine how these stem cells are maintained and how they give rise to their diverse differentiated progeny. To address such questions, a thorough understanding of transcriptional regulation in Hydra is needed. To this end, we generated extensive new resources for characterizing transcriptional regulation in Hydra, including new genome assemblies for Hydra oligactis and the AEP strain of Hydra vulgaris, an updated whole-animal single-cell RNA-seq atlas, and genome-wide maps of chromatin interactions, chromatin accessibility, sequence conservation, and histone modifications. These data revealed the existence of large kilobase-scale chromatin interaction domains in the Hydra genome that contain transcriptionally coregulated genes. We also uncovered the transcriptomic profiles of two previously molecularly uncharacterized cell types: isorhiza-type nematocytes and somatic gonad ectoderm. Finally, we identified novel candidate regulators of cell type-specific transcription, several of which have likely been conserved at least since the divergence of Hydra and the jellyfish Clytia hemisphaerica more than 400 million years ago.

Profiling Chromatin Accessibility on Replicated DNA with repli-ATAC-Seq.

Open or accessible chromatin typifies euchromatic regions and helps define cell type-specific transcription programs. DNA replication massively disorders chromatin composition and structure, and how accessible regions are affected by and recover from this disruption has been unclear. Here, we present repli-ATAC-seq, a protocol to profile accessible chromatin genome-wide on replicated DNA starting from 100,000 cells. In this method, replicated DNA is labeled with a short 5-ethynyl-2'-deoxyuridine (EdU) pulse in cultured cells and isolated from a population of tagmented fragments for amplification and next-generation sequencing. Repli-ATAC-seq provides high-resolution information on chromatin dynamics after DNA replication and reveals new insights into the interplay between DNA replication, transcription, and the chromatin landscape.

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes.

Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.

Deep learning approaches for noncoding variant prioritization in neurodegenerative diseases.

Determining how noncoding genetic variants contribute to neurodegenerative dementias is fundamental to understanding disease pathogenesis, improving patient prognostication, and developing new clinical treatments. Next generation sequencing technologies have produced vast amounts of genomic data on cell type-specific transcription factor binding, gene expression, and three-dimensional chromatin interactions, with the promise of providing key insights into the biological mechanisms underlying disease. However, this data is highly complex, making it challenging for researchers to interpret, assimilate, and dissect. To this end, deep learning has emerged as a powerful tool for genome analysis that can capture the intricate patterns and dependencies within these large datasets. In this review, we organize and discuss the many unique model architectures, development philosophies, and interpretation methods that have emerged in the last few years with a focus on using deep learning to predict the impact of genetic variants on disease pathogenesis. We highlight both broadly-applicable genomic deep learning methods that can be fine-tuned to disease-specific contexts as well as existing neurodegenerative disease research, with an emphasis on Alzheimer's-specific literature. We conclude with an overview of the future of the field at the intersection of neurodegeneration, genomics, and deep learning.

Deciphering multi-way interactions in the human genome

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types.

SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions

MotivationAberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factor’s motif.ResultsSEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions for CTCF. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease.Availability and ImplementationSEMplMe is available from https://github.com/Boyle-Lab/SEMplMe.

REALGAR: a web app of integrated respiratory omics data.

In the post genome-wide association study (GWAS) era, omics techniques have characterized information beyond genomic variants to include cell and tissue type-specific gene transcription, transcription factor binding sites, expression quantitative trait loci (eQTL) and many other biological layers. Analysis of omics data and its integration has in turn improved the functional interpretation of disease-associated genetic variants. Over 170000 transcriptomic and epigenomic datasets corresponding to studies of various cell and tissue types under specific disease, treatment and exposure conditions are available in the Gene Expression Omnibus resource. Although these datasets are valuable to guide the design of experimental validation studies to understand the function of disease-associated genetic loci, in their raw form, they are not helpful to experimental researchers who lack adequate computational resources or experience analyzing omics data. We sought to create an integrated re-source of tissue-specific results from omics studies that is guided by disease-specific knowledge to facilitate the design of experiments that can provide biologically meaningful insights into genetic associations. We designed the Reducing Associations by Linking Genes and omics Results web app to provide multi-layered omics information based on results from GWAS, transcriptomic, epigenomic and eQTL studies for gene-centric analysis and visualization. With a focus on asthma datasets, the integrated omics results it contains facilitate the formulation of hypotheses related to airways disease-associated genes and can be addressed with experimental validation studies. The REALGAR web app is available at: http://realgar.org/. The source code is available at: https://github.com/HimesGroup/realgar. Supplementary data are available at Bioinformatics online.

SpyChIP identifies cell type-specific transcription factor occupancy from complex tissues

Chromatin immunoprecipitation (ChIP) is an important technique for characterizing protein-DNA binding invivo. One drawback of ChIP-based techniques is the lack of cell type-specificity when profiling complex tissues. To overcome this limitation, we developed SpyChIP to identify cell type-specific transcription factor (TF) binding sites in native physiological contexts without tissue dissociation or nuclei sorting. SpyChIP takes advantage of a specific covalent isopeptide bond that rapidly forms between the 15-amino acid SpyTag and the 17-kDa protein SpyCatcher. In SpyChIP, the target TF is fused with SpyTag by genome engineering, and an epitope tagged SpyCatcher is expressed in cell populations of interest, where it covalently binds to SpyTag-TF. Cell type-specific ChIP is obtained by immunoprecipitating chromatin prepared from whole tissues using antibodies directed against the epitope-tagged SpyCatcher. Using SpyChIP, we identified the genome-wide binding profiles of the Hox protein Ultrabithorax (Ubx) in two distinct cell types of the Drosophila haltere imaginal disc. Our results revealed extensive region-specific Ubx-DNA binding events, highlighting the significance of cell type-specific ChIP and the limitations of whole-tissue ChIP approaches. Analysis of Ubx::SpyChIP results provided insights into the relationship between chromatin accessibility and Ubx-DNA binding, as well as different mechanisms Ubx employs to regulate its downstream cis-regulatory modules. In addition to SpyChIP, we suggest that SpyTag-SpyCatcher technology, as well as other protein pairs that form covalent isopeptide bonds, will facilitate many additional invivo applications that were previously impractical.