Biology subjects

Miraldi, E. R.

Publications and source records attributed to Miraldi, E. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Clonal hematopoiesis-associated DNMT3A mutations derepress bivalent Polycomb target genes and enhance macrophage migration

Somatic mutations in the de novo DNA methyltransferase DNMT3A are frequent in clonal hematopoiesis, but how they alter the function of differentiated myeloid cells remains unclear. Here, we used isogenic human embryonic stem cell-derived macrophage models to define the consequences of DNMT3A dysfunction during myeloid differentiation. DNMT3A-mutant macrophages selectively upregulated bivalent Polycomb target genes, accompanied by DNA hypomethylation, reduced H3K27me3 and increased promoter accessibility. Despite broad epigenetic changes across bivalent promoters, transcriptional derepression occurred at a subset of loci characterized by lower baseline DNA methylation and higher H3K27me3, identifying pre-existing chromatin state as a determinant of transcriptional response. This Polycomb-associated program was conserved in murine macrophages and enriched for genes involved in cell migration and wound repair. DNMT3A-mutant macrophages exhibited enhanced migration and preferential early recruitment to injured tissue. These findings link clonal hematopoiesis-associated epigenetic alterations to selective transcriptional reprogramming and altered function of differentiated myeloid cells.

cell biology↗

bioRxiv2026

Gene regulatory networks define human airway epithelial cell types and their distinct responses to type I interferon

The human airway epithelium (HAE) is composed of diverse cell types that coordinate essential functions and host defenses. Among these defenses, interferons (IFNs) are central to antiviral programs. However, the gene regulatory networks (GRNs) governing HAE cellular identities and their IFN responses are incompletely defined. At single-cell resolution, we characterized the transcriptomes and accessible chromatin landscapes of HAE cell types, at steady state and following IFN{beta} stimulation. The resulting scRNA-seq and snATAC-seq data informed genome-scale GRN construction and inference of transcriptional circuits underlying cell identities. In response to IFN, we identified a shared transcriptional program across HAE cell types, and an expanded set of interferon-responsive genes exhibiting cell type-associated expression patterns. Cell type-associated transcription factors and chromatin accessibility contribute to distinct IFN-responsive gene expression programs. Together, these data provide a blueprint for molecular regulation of complex HAE responses and a foundation for therapeutic strategies to enhance host antiviral defense.

systems biology↗

bioRxiv2025

Gene regulatory network determinants of rapid recall in human memory CD4+ T cells

Rapid recall is the hallmark of memory T cells. While naive cells require days to mount effector responses to new threats, antigen-experienced memory cells produce cytokines within hours of repeat encounter. Memory establishment and the control of rapid recall across lifespan is poorly understood. Epigenetic poising is a likely mechanism. Compared to naive, memory cells exhibit enhanced chromatin accessibility proximal to rapid recall genes, but the transcription factors (TFs) that establish, maintain and utilize these putative regulatory elements are unknown. We leverage single-nuclei (sn)multiome-seq (snRNA-seq and snATAC-seq) to characterize the dynamic activation responses of CD4+ T cell subsets and (2) reconstruct the underlying gene regulatory networks. Memory-associated TFs (MAF, PRDM1, RUNX2, SMAD3, KLF6) were predicted to orchestrate rapid recall. KLF6 binding to its predicted target genes was confirmed by ChIP-seq, while the memory-associated activities of all five factors replicated in independent scRNA-seq studies. Integrating GWAS data, we nominate CD4+ T cell populations and gene regulatory mechanisms that might underly genetic risk to immune-mediated diseases.

systems biology↗

bioRxiv2024

Use of Antibody Structural Information in Disease Prediction Models Reveals Antigen Specific B Cell Receptor Sequences in Bulk Repertoire Data

Convergent antibodies are highly similar antibodies elicited in multiple individuals in response to the same antigen. Convergent antibodies provide insight into shared immunological responses and show great promise as diagnostic biomarkers. They have typically been identified using methods that consider the amino acid sequence of the third complementarity-determining region (CDR3) of immunoglobulin heavy chain (IgH). In this study, we extend the definition of convergent antibodies to use structural information about the three IgH CDR regions (CDR1-3). We benchmark the performance of both definitions of convergence by their ability to predict disease status from bulk IgH sequencing data for two different diseases (HIV infection and food sensitization). We show that using predicted structural information outperforms prior approaches for the prediction of food sensitization status and performs on par for HIV infection status. Additionally, the structurally convergent antibody groups driving HIV prediction are from known HIV binders. Thus, the use of structural information allows for the identification of antigen specific antibody groups from bulk IgH sequencing data.

immunology↗

bioRxiv2024

Nutrient starvation activates ECM remodeling gene enhancers associated with inflammatory bowel disease risk in fibroblasts

Nutrient deprivation induces a reversible cell cycle arrest state termed quiescence, which often accompanies transcriptional silencing and chromatin compaction. Paradoxically, nutrient deprivation is associated with activated fibroblast states in pathological microenvironments in which fibroblasts drive extracellular matrix (ECM) remodeling to alter tissue environments. The relationship between nutrient deprivation and fibroblast activation remains unclear. Here, we report that serum deprivation extensively activates transcription of ECM remodeling genes in cultured fibroblasts, despite the induction of quiescence. Starvation-induced transcriptional activation accompanied large-scale histone acetylation of putative distal enhancers, but not promoters. The starvation-activated putative enhancers were enriched for non-coding genetic risk variants associated with inflammatory bowel disease (IBD), suggesting that the starvation-activated gene regulatory network may contribute to fibroblast activation in IBD. Indeed, the starvation-activated gene PLAU, encoding uPA serine protease for plasminogen and ECM, was upregulated in inflammatory fibroblasts in the intestines of IBD patients. Furthermore, the starvation-activated putative enhancer at PLAU, which harbors an IBD risk variant, gained chromatin accessibility in IBD patient fibroblasts. This study implicates nutrient deprivation in transcriptional activation of ECM remodeling genes in fibroblasts and suggests nutrient deprivation as a potential mechanism for pathological fibroblast activation in IBD. HIGHLIGHTS- Serum starvation transcriptionally activates ECM remodeling genes in fibroblasts. - Fibroblast starvation activates putative distal enhancers associated with ECM remodeling genes. - Starvation-activated putative enhancers are enriched for inflammatory bowel disease (IBD) risk variants. - PLAU enhancer and expression are activated in IBD intestinal fibroblasts, as in starved fibroblasts.

genomics↗

bioRxiv2024

Accessible chromatin maps of inflammatory bowel disease intestine nominate cell-type mediators of genetic disease risk

Inflammatory Bowel Disease (IBD) is a chronic autoinflammatory disorder with rising incidence in pediatrics. TNFa inhibition (TNFi) is the first-line biologic therapy in children, but many do not achieve mucosal healing. Identifying which patients will benefit from TNFi and the underlying nonresponse mechanisms is critical. We built a novel resource: whole genome sequencing linked to multiome-seq (single-nuclei transcriptome and chromatin accessibility) of intestinal biopsies from a cohort of children with IBD, whose TNFi response was defined by mucosal healing. Our study uncovers links between IBD genetic risk and TNFi response. First, classifiers integrating genetic data with clinical variables identified the IBD polygenic risk score as a top predictor of TNFi response. Second, multiome-seq analysis implicated IBD risk variants in persistent cytokine signaling in monocytes, macrophage and fibroblasts of nonresponders. These data reveal genetic mechanisms of treatment response in pediatric IBD and suggest alternative therapeutic approaches for TNFi nonresponders.

genomics↗

bioRxiv2023

An atlas of gene regulatory networks for T memory cells in youth and old age

Aging profoundly affects immune-system function, promoting susceptibility to pathogens, cancers and chronic inflammation. We previously identified a population of IL-10-producing, T follicular helper-like cells ("Tfh10"), linked to suppressed vaccine responses in aged mice. Here, we integrate single-cell (sc)RNA-seq, scATAC-seq and genome-scale modeling to characterize Tfh10 - and the full CD4+ memory T cell (CD4+TM) compartment - in young and old mice. We identified 13 CD4+TM populations, which we validated through cross-comparison to prior scRNA-seq studies. We built gene regulatory networks (GRNs) that predict transcription-factor control of gene expression in each T-cell population and how these circuits change with age. Through integration with pan-cell aging atlases, we identified intercellular-signaling networks driving age-dependent changes in CD4+TM. Our atlas of finely resolved CD4+TM subsets, GRNs and cell-cell communication networks is a comprehensive resource of predicted regulatory mechanisms operative in memory T cells, presenting new opportunities to improve immune responses in the elderly.

immunology↗

bioRxiv2022

High-resolution promoter interaction analysis in Type 3 Innate Lymphoid Cells implicates Batten Disease gene CLN3 in Crohn's Disease aetiology

Innate lymphoid cells (ILCs) are rare, tissue-resident innate lymphocytes that functionally mirror CD4+ T helper cell lineages but lack antigen receptors. Type 3 ILCs (ILC3s) are enriched in the gut, airways, and mucosal lymphoid tissues, where they regulate inflammation and promote barrier integrity. To define the regulatory architecture of primary human ILC3s, we map promoter-anchored chromosomal contacts using high-resolution, low-input Promoter Capture Hi-C (PCHi-C) in these cells alongside CD4+ T cells. By combining statistical detection with a PCHi-C-adapted Activity-by-Contact approach, we link promoters to distal regulatory elements, identifying hundreds of ILC3-specific contacts. We use these maps to connect genome-wide association study (GWAS) risk variants for Crohns disease to target genes using multiCOGS, a Bayesian framework that integrates PCHi-C with summary-statistic imputation and multivariate fine-mapping. This analysis highlights both known and unanticipated candidates, including CLN3, a causal gene for the neurodevelopmental Batten disease. Using a mouse ILC3-like cell line, we show that Cln3 is downregulated upon cytokine stimulation, and Cln3 overexpression alters stimulation-induced transcriptional programmes and cytokine secretion. Extending this approach, we generate a catalogue of ILC3-linked risk genes for five additional autoimmune conditions and show that they are enriched for regulators of the ILC3 inflammatory response identified in a CRISPR interference screen. Together, these findings illuminate long-range gene control in ILC3s and prioritise known and newly implicated autoimmune risk genes with potential roles in this clinically important cell type.

genetics↗

bioRxiv2022

Alveolar epithelial progenitor cells drive lung regeneration via dynamic changes in chromatin topology modulated by lineage-specific Nkx2-1 activity

Lung epithelial regeneration after acute injury requires coordination of extensive cellular and molecular processes controlling proliferation and differentiation of specialized alveolar cells to pattern the morphologically complex alveolar gas exchange surface. During regeneration, specialized Wnt-responsive alveolar epithelial progenitor (AEP) cells, a subset of alveolar type 2 (AT2) cells, proliferate and transition to alveolar type 1 (AT1) cells, though the precise molecular and epigenetic determinants of these processes remain unclear. Here, we report a refined primary murine alveolar organoid assay which recapitulates critical aspects of in vivo regeneration, providing a tractable model to dissect these regenerative processes. Clonal expansion of single AEPs generate complex alveolar organoids with extensive structural maturation and organization. These organoids contain properly patterned AT1 and AT2 cells surrounding numerous alveolar-like cavities with minimal structural contribution from mesenchymal cells, implying extensive cell autonomous regenerative function encoded in adult AEPs. Leveraging a time series of paired scRNAseq and scATACseq, we identified the AEP state at single cell resolution and described two distinct AEP to AT1 intermediate states: a widely reported Krt8+ transitional state defined by cell stress markers and a second state defined by differential activation of signaling pathways mediating AT1 cell differentiation. Transcriptional regulatory network (TRN) analysis demonstrated that these AT1 transition states were driven by distinct regulatory networks controlled in part by differential activity of Nkx2-1. Genetic ablation of Nkx2-1 in AEP-derived organoids was sufficient to cause transition to a proliferative stressed Krt8+ state characterized by disorganized, uncontrolled growth. Finally, AEP-specific deletion of Nkx2-1 in adult mice led to rapid loss of AEP state, clonal expansion, and disorganization of alveolar structure, implying a continuous requirement for Nkx2-1 in maintenance and function of adult lung progenitors. Together, these data provide new insight into cellular hierarchies in lung regeneration and implicate dynamic epigenetic maintenance via lineage transcription factors as central to control of facultative progenitor activity in AEPs.

developmental biology↗

bioRxiv2022

maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks

Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge highlighted the value of chromatin accessibility data to TFBS prediction, establishing state-of-the- art methods for TFBS prediction from DNase-seq. However, the more recent Assay-for- Transposase-Accessible-Chromatin (ATAC)-seq has surpassed DNase-seq as the most widely- used chromatin accessibility profiling method. Furthermore, ATAC-seq is the only such technique available at single-cell resolution from standard commercial platforms. While ATAC-seq datasets grow exponentially, suboptimal motif scanning is unfortunately the most common method for TFBS prediction from ATAC-seq. To enable community access to state-of-the-art TFBS prediction from ATAC-seq, we (1) curated an extensive benchmark dataset (127 TFs) for ATAC-seq model training and (2) built "maxATAC", a suite of user-friendly, deep neural network models for genome-wide TFBS prediction from ATAC-seq in any cell type. With models available for 127 human TFs, maxATAC is the first collection of high-performance TFBS prediction models for ATAC-seq. maxATAC performance extends to primary cells and single-cell ATAC-seq, enabling improved TFBS prediction in vivo. We demonstrate maxATACs capabilities by identifying TFBS associated with allele-dependent chromatin accessibility at atopic dermatitis genetic risk loci. Author SummaryProteins called transcription factors interpret the genome, reading both DNA sequence and chromatin state, to orchestrate gene expression across the diversity of human cell types. In any given cell type, most chromatin is "inaccessible", and only those parts of the genetic code needed or likely to be needed soon are "accessible" for transcription factor binding to affect gene expression and cellular behavior. Hundreds of transcription factors are expressed in a given cell type and context (e.g., age, disease), and knowledge of their context-specific DNA binding sites is key to uncovering how transcription factors regulate cellular behaviors in health or disease. However, experimentally profiling the >1,600 human transcription factors across all cell types and contexts is infeasible. We built a suite of computational models "maxATAC" to predict transcription factor binding from a measurement of accessible chromatin, ATAC-seq. Importantly, ATAC-seq is feasible even at single-cell resolution. Thus, this data type, in combination with maxATAC, can be used to infer transcription factor binding sites in directly-relevant cell types isolated from physiological and disease settings, enabling insights into disease mechanisms, including how genetic variants and cellular context impact transcription factor binding, gene expression patterns and disease risk.

bioinformatics↗

bioRxiv2021

Inflammatory blockade prevents injury to the developing pulmonary gas exchange surface in preterm primates

Malformations of or injuries to the developing lung are associated with perinatal morbidity and mortality with lifelong consequences for subsequent pulmonary health. One fetal exposure linked with poor health outcomes is chorioamnionitis, which impacts up to 25-40% of preterm births. Severe chorioamnionitis with prematurity is associated with significantly increased risk of pulmonary disease and secondary infections in childhood, suggesting that fetal inflammation may significantly alter developmental ontogeny of the lung. To test this hypothesis, we used intra-amniotic lipopolysaccharide (LPS, endotoxin) to generate experimental chorioamnionitis in prenatal Rhesus macaque (Macaca mulatta), a model which shares critical structural and temporal aspects of human lung development. Inflammatory injury directly disrupts the developing gas exchange surface of the primate lung, with extensive damage to alveolar structure, particularly the close association and coordinated differentiation of alveolar type 1 pneumocytes and specialized alveolar capillary endothelium. Single cell RNA sequencing analysis defined a multicellular alveolar signaling niche driving alveologenesis which was extensively disrupted by perinatal inflammation, leading to loss of gas exchange surface and alveolar simplification similar to that found in chronic lung disease of newborns. Blockade of IL1{beta} and TNF ameliorated endotoxin-induced inflammatory lung injury by blunting stromal response to inflammation and modulating innate immune activation in myeloid cells, restoring structural integrity and key signaling networks in the developing alveolus. These data provide new insight into the pathophysiology of developmental lung injury and suggest that modulating inflammation is a promising therapeutic approach to prevent fetal consequences of chorioamnionitis.

developmental biology↗

bioRxiv2021

Single-cell gene regulatory network inference atscale: The Inferelator 3.0

MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above. ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data. AvailabilityThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/).

systems biology↗

bioRxiv2020

Topoisomerase 1 inhibition therapy protects against SARS-CoV-2-induced inflammation and death in animal models.

The ongoing pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is currently affecting millions of lives worldwide. Large retrospective studies indicate that an elevated level of inflammatory cytokines and pro-inflammatory factors are associated with both increased disease severity and mortality. Here, using multidimensional epigenetic, transcriptional, in vitro and in vivo analyses, we report that Topoisomerase 1 (Top1) inhibition suppresses lethal inflammation induced by SARS-CoV-2. Therapeutic treatment with two doses of Topotecan (TPT), a FDA-approved Top1 inhibitor, suppresses infection-induced inflammation in hamsters. TPT treatment as late as four days post-infection reduces morbidity and rescues mortality in a transgenic mouse model. These results support the potential of Top1 inhibition as an effective host-directed therapy against severe SARS-CoV-2 infection. TPT and its derivatives are inexpensive clinical-grade inhibitors available in most countries. Clinical trials are needed to evaluate the efficacy of repurposing Top1 inhibitors for COVID-19 in humans.

microbiology↗

bioRxiv2020

Genome-wide discovery of lupus genetic risk variant allelic regulatory activity

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3,073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we constructed a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 revealed 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second, larger class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

genomics↗

bioRxiv2019

Discovery Of UFO Proteins: Human-Virus Chimeric Proteins Generated During Influenza Virus Infection

Influenza A virus (IAV) is a threat to mankind because it generates yearly epidemics and poorly predictable sporadic pandemics with catastrophic potential. IAV has a small RNA genome composed of 8 mini-chromosomes (segments) that constitute a 5UTR followed by a coding region and a 3UTR. Transcription of IAV RNA into mRNA depends on host mRNA, as the viral polymerase cleaves 5m7G-capped nascent transcripts to use as primers to initiate viral mRNA synthesis. We hypothesized that captured host transcripts bearing AUG could drive the expression of upstream ORFs in the viral segments, a phenomenon that would depend on the translatability of the viral 5UTRs. Here we report the existence of this mechanism, which generates host-virus chimeric proteins. We label these proteins as Upstream Flu ORFs (UFO). Depending on the frame, two types of host-virus UFO proteins are made: canonical viral proteins with human-derived N term extensions or novel uncharacterized proteins. Here we show that both types are made during IAV infection. Sequences that enable chimeric protein synthesis are conserved across IAV strains, indicating that selection allowed the expansion of the proteome diversity of IAV in infected cells to include multiple human-virus proteins.

microbiology↗

bioRxiv2018

Transcriptional regulatory networks that promote and restrict identities and functions of intestinal innate lymphoid cells

Innate lymphoid cells (ILCs) can be subdivided into several distinct cytokine-secreting lineages that promote tissue homeostasis and immune defense but also contribute to inflammatory diseases. Accumulating evidence suggests that ILCs, similarly to other immune populations, are capable of phenotypic and functional plasticity in response to infectious or environmental stimuli. Yet the transcriptional circuits that control ILC identity and function are largely unknown. Here we integrate gene expression and chromatin accessibility data to infer transcriptional regulatory networks within intestinal type 1, 2, and 3 ILCs. We predict the \"core\" sets of transcription-factor (TF) regulators driving each ILC subset identity, among which only a few TFs were previously known. To assist in the interpretation of these networks, TFs were organized into cooperative clusters, or modules that control gene programs with distinct functions. The ILC network reveals extensive alternative-lineage-gene repression, whose regulation may explain reported plasticity between ILC subsets. We validate new roles for c-MAF and BCL6 as regulators affecting the type 1 and type 3 ILC lineages. Manipulation of TF pathways identified here might provide a novel means to selectively regulate ILC effector functions to alleviate inflammatory disease or enhance host tolerance to pathogenic microbes or noxious stimuli. Our results will enable further exploration of ILC biology, while our network approach will be broadly applicable to identifying key cell state regulators in other in vivo cell populations.

immunology↗

bioRxiv2018

Sequence-Dependent DNA Shape Features Regulate IL-4 Induced Chromatin Accessibility in Alternatively Activated Macrophages

Interleukin-4 (IL-4) activates macrophages to adopt a distinct phenotype associated with clearance of helminth infections and tissue repair. Here, we describe changes in the accessible chromatin landscape following IL-4 stimulation of terminally differentiated mouse peritoneal macrophages. This chromatin remodeling process occurs in both tissue resident and monocyte-derived macrophages, but the regions gaining accessibility post-stimulation are macrophage-specific. PU.1 motif is similarly associated with tissue resident and monocyte-derived IL-4 induced regions, but has macrophage-specific DNA shape and predicted co-factors. In addition, IL-4 stimulation leads to short-term dampening of macrophage secondary response. However, the degree of dampening differs between macrophages derived from different genetic backgrounds. Together, these results lead us to propose that DNA sequence variations can alter parts of the accessible chromatin landscape and differences in secondary responses due to host genetics can contribute to phenotypic variations in immune responses.

immunology↗

bioRxiv2018

Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells

Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The Assay for Transposase Accessible Chromatin (ATAC)-seq, coupled with transcription-factor motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to influence gene expression modeling. We rigorously test our methods in the context of T Helper Cell Type 17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources (plentiful gene expression data, TF knock-outs and ChIP-seq experiments). In this resource-rich mammalian setting, our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF KO, ChIP-seq). We highlight new roles for individual TFs and groups of TFs (\"TF-TF modules\") in Th17 gene regulation. Given the popularity of ATAC-seq, which provides high-resolution with low sample input requirements, we anticipate that application of our methods will improve TRN inference in new mammalian systems, especially in vivo, for cells directly from humans and animal models.

systems biology↗