Biology subjects

Danko, C. G.

Publications and source records attributed to Danko, C. G..

At least 19 recordsLinked to original sources

bioRxiv2026

pydreg: a fast Python package for identifying active cis-regulatory elements from nascent transcription

Background: Active promoters and enhancers generate characteristic patterns of RNA transcription that can be measured through nascent RNA sequencing. dREG is a leading method that uses these patterns to identify active cis-regulatory elements across the genome, allowing regulatory activity and gene transcription to be profiled in the same experiment. However, its reference implementation was developed around an R-based workflow and a legacy GPU-accelerated support vector machine library that have become increasingly difficult to maintain and deploy. Findings: To improve future usability of dREG, we developed pydreg, a Python port of dREG. pydreg preserves the original pretrained models and peak calling procedure from dREG while using contemporary numerical libraries for CPU and GPU computation. pydreg achieves 4.5 and 5.4-fold reductions in runtime and peak host memory, respectively, compared to dREG while producing near identical peak calls. Conclusions: pydreg reduces practical barriers to running dREG locally, improves runtime and memory usage, integrates readily with Python-based genomics workflows, and provides a maintainable foundation on modern computing infrastructure. Availability and Implementation: pydreg is implemented in Python 3.11+ and is freely available under the GPL-3 license at https://github.com/adamyhe/pydreg and from PyPI via pip install pydreg[gpu] (for CUDA acceleration) or pip install pydreg[mlx] (for Apple Metal acceleration).

bioinformatics↗

bioRxiv2026

Cross-species analysis links cell-cell communication rewiring to NOTCH2 during serous endometrial carcinogenesis

Cell-cell interactions shape the fate of mutant cells during cancer initiation but how these interactions evolve during progression to pathologically recognizable lesions remain poorly understood. Here, we investigated cell-cell communication during serous endometrial carcinoma (SEC; also known as uterine serous carcinoma) development using a lineage-traceable mouse model and cross-species analyses of the mouse and human neoplastic endometrium. In mice, the early, pre-dysplastic stage was marked by a global decrease in inferred cell-cell interactions, followed by extensive communication network rewiring during neoplastic progression. Pathway-specific analysis revealed a similar pattern for NOTCH signaling, with NOTCH2 emerging as the dominant NOTCH receptor in Trp53/Rb1-mutant immature epithelial cells. Functionally, NOTCH2 promoted the outgrowth of more proliferative mutant organoids. Cross-species transcriptomic analysis identified conserved immature epithelial states in mouse and human neoplastic endometrial epithelium. In human tissues, NOTCH2 was overexpressed in serous endometrial intraepithelial carcinoma, a precursor of SEC, and in overt SEC. Furthermore, elevated NOTCH2 expression was associated with poor patient survival. These findings link cell-cell communication rewiring during experimental SEC development to conserved neoplastic epithelial states and identify NOTCH2 as an early marker and a potential target of disease interception.

cancer biology↗

bioRxiv2026

A comparative analysis of promoter-proximal pausing reveals kinetic and distributional dimensions of variation

Promoter-proximal pausing of RNA polymerase II is a key regulatory checkpoint in metazoan transcription. Despite extensive study of this process, quantitative methods for comparing pausing dynamics across biological contexts have been lacking. Here we introduce a model-based framework for rigorous comparative analysis of both pause-escape kinetics and pause-site distributions. We apply this framework to public datasets together with newly generated PRO-seq and Micro-C data from primate immune cells, enabling a broad comparison of promoter-proximal pausing across conditions, cell types, and species. Analyses of these datasets revealed striking differences across transcriptional perturbations and distinct patterns of variation in pause-escape kinetics and pause-site distributions across cell types and species, with only weak coupling between them. Integration with chromatin and sequence features showed that lower pause-escape rates are associated with stronger promoter-proximal nucleosome occupancy, whereas changes in pause-site dispersion are associated with sequence features such as GC skew. Together, these results reveal kinetic and distributional dimensions of pausing variation across biological contexts.

bioinformatics↗

bioRxiv2025

Meiotic prophase I disruption as a strategy for non-hormonal male contraception using small-molecule inhibitor JQ1

Long-acting non-hormonal male contraceptives are urgently needed but developing strategies that are both effective and reversible presents significant challenges. Here, we investigated the potential of meiotic prophase I blockade as a promising and potentially reversible approach to male contraception. To do this, we utilized (+)-JQ1, a small-molecule inhibitor of the testis-specific protein, BRDT. Daily injections of (+)-JQ1 for three weeks resulted in disrupted spermatogenesis resulting in loss of spermatozoa and an inability to sire pups. While spermatogenic cells repopulated the testis within six weeks post drug cessation, full fertility restoration required a longer recovery period. We attribute this delay in full recovery to persistent issues with the pachytene transcriptional program, which is crucial for meiotic progression and spermatid development. These findings underscore the potential of pharmacological approaches to disrupt meiotic prophase I as a targeted, reversible male contraceptive strategy, providing new insights into developing effective non-hormonal contraceptive approaches.

cell biology↗

bioRxiv2025

Transcriptomic and chromatin accessibility profiling unveils new regulators of heat hormesis in Caenorhabditis elegans

Heat hormesis describes the beneficial adaptations resulting from transient exposure to mild heat stress, which enhances stress resilience and promotes healthy aging. While heat hormesis is widely observed, much remains to be learned about its molecular basis. This study bridges a critical knowledge gap through a comprehensive multiomic analysis, providing key insights into the transcriptomic and chromatin accessibility landscapes throughout a heat hormesis regimen in C. elegans. We uncover highly dynamic, dose-dependent molecular responses to heat stress and reveal that while most initial molecular changes induced by mild stress revert to baseline, key differences emerge in response to subsequent heat shock challenge that likely contribute to physiological benefits. We further demonstrate that heat hormesis extends lifespan specifically in wild-type animals, but not in germlineless mutants, likely due to transient disruption of germline activities during mild heat exposure, which appears sufficient to trigger pro-longevity mechanisms. This finding points to tissue-specific responses in mediating the physiological outcomes of heat hormesis. Importantly, we identify several highly conserved regulators of heat hormesis that likely orchestrate gene expression to enhance stress resilience. Among these regulators, some (MARS-1/MARS1, SNPC-4/SNAPc, FOS-1/c-Fos) are broadly required for heat hormesis-induced benefits, whereas others (ELT-2/GATA4, DPY-27/SMC4) are uniquely important in specific genetic backgrounds. This study advances our understanding of stress resilience mechanisms, points to multiple new avenues for future investigations, and provides a molecular framework for promoting healthy aging through strategic mid-life stress management.

genomics↗

bioRxiv2025

Accurate de novo transcription unit annotation from run-on and sequencing data

Functional element annotations are critical tools used to provide insight into the molecular processes governing cell development, differentiation, and disease. Run-on and sequencing assays measure the production of nascent RNAs and can provide an effective data source for discovering functional elements. However, the accurate inference of functional elements from run-on sequencing data remains an open problem because the signal is noisy and challenging to model. Here we investigated computational approaches that convert run-on and sequencing data into annotations representing transcription units, including genes and non-coding RNAs. We developed a convolutional neural network, called convolutional discovery of gene anatomy using PRO-seq (CGAP), trained to identify different anatomical features of a transcription unit, which were then stitched together into transcript annotations using a hidden Markov model (HMM). Comparison with existing methods showed a significant performance improvement using our novel CGAP-HMM approach. We developed a voting system that ensembles the top three annotation strategies, resulting in large and significant improvements in transcription unit annotation accuracy over the best performing individual method. Finally, we also report a conditional generative adversarial network (cGAN) as a generative approach to transcription unit annotation that shows promise for further development. Collectively our work provides novel tools for de novo transcription unit annotation from run-on and sequencing data that are accurate enough to be useful in many applications.

bioinformatics↗

bioRxiv2024

Training deep learning models on personalized genomic sequences improves variant effect prediction

Sequence-to-function models have broad applications in interpreting the molecular impact of genetic variation, yet have been criticized for poor performance in this task. Here we show that training models on functional genomic data with matched personal genomes improves their performance at variant effect prediction. Variant effect representations are retained even when fine tuning models to unseen cellular contexts and experimental readouts. Our results have implications for interpreting trait-associated genetic variation.

bioinformatics↗

bioRxiv2024

Using Functional Genomic Data in Monocytes/Macrophages and Genotyping to Nominate Disease-Driving Single Nucleotide Polymorphisms and Target Genes in Juvenile Idiopathic Arthritis

IntroductionGWAS have identified multiple regions that confer risk for juvenile idiopathic arthritis (JIA). However, identifying the single nucleotide polymorphisms (SNPs) that drive disease risk is impeded by the SNPs that identify risk loci being in linkage disequilibrium (LD) with hundreds of other SNPs. Since the causal SNPs remain unknown, it is difficult to identify target genes and use genetic information to inform patient care. We used genotyping and functional data in primary human monocytes/macrophages to nominate disease-driving SNPs on JIA risk haplotypes and identify their likely target genes. MethodsWe identified JIA risk haplotypes using Immunochip data from Hinks et al (Nature Gen 2013) and the meta-analysis from McIntosh et al (Arthritis Rheum 2017). We used genotyping data from 3,939 children with JIA and 14,412 healthy controls to identify SNPs that: (1) were situated within open chromatin in multiple immune cell types and (2) were more common in children with JIA than the controls (p< 0.05). We intersected the chosen SNPs (n=846) with regions of bi-directional transcription initiation characteristic of non-coding regulatory regions detected using dREG to analyze GRO-seq data. Finally, we used MicroC data to identify gene promoters interacting with the regulatory regions harboring the candidate causal SNPs. ResultsWe identified 190 SNPs that overlap with dREG peaks in monocytes and126 SNPs that overlap with dREG peaks in macrophages. Of these SNPs, 101 were situated within dREG peaks in both monocytes and macrophages, suggesting that these SNPs exert their effects independent of the cellular activation state. MicroC data in monocytes identified 20 genes/transcripts whose promoters interact with the enhancers harboring the SNPs of interest. ConclusionSNPs in JIA risk regions that are candidate causal variants can be further screened using functional data such as GRO-seq. This process identifies a finite number of candidate causal SNPs, the majority of which are likely to exert their biological effects independent of cellular activation state in monocytes. Three-dimensional chromatin data generated with MicroC identifies genes likely to be influenced by these SNPs. These studies demonstrate the importance of investigations into the role of innate immunity in JIA.

genetics↗

bioRxiv2024

Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation

How the DNA sequence of cis-regulatory elements encode transcription initiation patterns remains poorly understood. Here we introduce CLIPNET, a deep learning model trained on population-scale PRO-cap data that predicts the position and quantity of transcription initiation with single nucleotide resolution from DNA sequence more accurately than existing approaches. Interpretation of CLIPNET revealed a complex regulatory syntax consisting of DNA-protein interactions in five major positions between -200 and +50 bp relative to the transcription start site, as well as more subtle positional preferences among transcriptional activators. Transcriptional activator and core promoter motifs work non-additively to encode distinct aspects of initiation, with the former driving initiation quantity and the latter initiation position. We identified core promoter motifs that explain initiation patterns in the majority of promoters and enhancers, including DPR motifs and AT-rich TBP binding sequences in TATA-less promoters. Our results provide insights into the sequence architecture governing transcription initiation.

genomics↗

bioRxiv2024

Discriminative histone imputation using chromatin accessibility

Histone modifications (HMs) play a pivot role in various biological processes, including transcription, replication and DNA repair, significantly impacting chromatin structure. These modifications underpin the molecular mechanisms of cell-specific gene expression and complex diseases. However, annotating HMs across different cell types solely using experimental approaches is impractical due to cost and time constraints. Herein, we present dHICA (discriminative histone imputation using chromatin accessibility), a novel deep learning framework that integrates DNA sequences and chromatin accessibility data to predict multiple HM tracks. Employing the Transformer architecture alongside dilated convolutions, dHICA boasts an extensive receptive field and captures more cell-type-specific information. dHICA not only outperforms state-of-the-art baselines but also achieves superior performance in cell-specific loci and gene elements, aligning with biological expectations. Furthermore, dHICAs imputations hold significant potential for downstream applications, including chromatin state segmentation and elucidating the functional implications of SNPs. In conclusion, dHICA serves as an invaluable tool for advancing the understanding of chromatin dynamics, offering enhanced predictive capabilities and interpretability.

bioinformatics↗

bioRxiv2023

Multi-omic study of genome-edited human colonoid models of colorectal cancer reveal genotype-specific patterns of microRNA regulation

Combinations of oncogenic mutations drive inter-tumor heterogeneity in colorectal cancer (CRC), which promotes distinct phenotypes and affects therapeutic efficacy. We recently demonstrated that combinations of mutations in mouse small intestinal organoids lead to unique changes in microRNA (miRNA) expression profiles. However, it remains unknown how different mutational backgrounds shape miRNA profiles in the human colon. We leveraged human colonic organoid models, termed colonoids, with gene edits targeting genes commonly mutated in CRC to profile genotype-specific changes in miRNA expression. By small RNA-sequencing we characterized genotype-specific miRNA profiles. We identified one group of miRNAs, including mir-34a-5p and mir-10a-5p, that is strongly downregulated in APC/KRAS/TP53 mutant (AKP-mutant) colonoids. Using chromatin run-on sequencing, we showed that most miRNA alterations in AKP-mutant colonoids are concordant with transcriptional changes. Transcription factor (TF) motif enrichment analysis using transcriptional regulatory elements with increased activity in AKP-mutant colonoids revealed an enrichment of binding sites for multiple oncogenic TFs. Several of these harbor predicted binding sites for mir-10a-5p and/or mir-34a-5p, suggesting these miRNAs may play a role in regulating transcriptional programs in AKP-mutant contexts. Ultimately, our study offers a glimpse into regulatory mechanisms that drive inter-tumor heterogeneity, and we highlight candidate therapeutic targets for the advancement of precision medicine.

cancer biology↗

bioRxiv2023

Evolution of promoter-proximal pausing enabled a new layer of transcription control

Promoter-proximal pausing of RNA polymerase II (Pol II) is a key regulatory step during transcription. Despite the central role of pausing in gene regulation, we do not understand the evolutionary processes that led to the emergence of Pol II pausing or its transition to a rate-limiting step actively controlled by transcription factors. Here we analyzed transcription in species across the tree of life. Unicellular eukaryotes display a slow acceleration of Pol II near transcription start sites that transitioned to a longer-lived, focused pause in metazoans. This event coincided with the evolution of new subunits in the NELF and 7SK complexes. Depletion of NELF in mammals shifted the promoter-proximal buildup of Pol II from the pause site into the early gene body and compromised transcriptional activation for a set of heat shock genes. Our work details the evolutionary history of Pol II pausing and sheds light on how new transcriptional regulatory mechanisms evolve.

evolutionary biology↗

bioRxiv2022

The Long Noncoding RNA Playrr Regulates Pitx2 Dosage and Protects Against Cardiac Arrhythmias

RationaleThe most significantly associated atrial fibrillation (AF) risk loci in humans map to a noncoding gene desert upstream of the evolutionarily conserved left-right (LR) transcription factor Pitx2, a master regulator of LR asymmetric organ development. Pitx2 dosage is fundamentally linked to the development of sinus node dysfunction (SND) and AF, the most common cardiac arrhythmia affecting adults, but the mechanistic basis for this remains obscure. We identified a conserved long noncoding RNA (lncRNA), Playrr, which is exclusively transcribed on the embryos right side, opposite to Pitx2 on the left, that participates in mutually antagonistic transcriptional regulation with Pitx2. ObjectiveThe objective of this study was to investigate a role of Playrr in regulating Pitx2 transcription and protecting against the development of cardiac rhythm disturbances. Methods and ResultsPlayrr expression in the developing heart was analyzed with RNA in situ hybridization. Playrr was expressed asymmetrically (on the right) to Pitx2 (on the left) in developing mouse embryos, including in mouse embryonic sinoatrial node cells. We utilized CRISPR/Cas9 genome editing in mice to target Playrr, generating mice lacking Playrr RNA transcript (PlayrrEx1sj allele). Using qRT-PCR we detected upregulation of the cardiac isoform, Pitx2c, during visceral organ morphogenesis in PlayrrEx1sj mutant embryos. Surface ECG (AliveCor(R)) and 24-hour telemetry ECG detected bradycardia and irregular interbeat (R-R) intervals suggestive of SND in PlayrrEx1sj mutant adults. Programmed stimulation of PlayrrEx1sj mutant adults resulted in pacing-induced AF. Within the right atrium of PlayrrEx1sj mutant hearts, Massons trichrome stain revealed increased collagen deposition indicative of fibrosis, and immunofluorescence demonstrated mis-localization of Connexin 43 in atrial cardiomyocytes. These findings suggested an altered atrial substrate in PlayrrEx1sj adult mice. Finally, transcriptomic analysis by chromatin run-on and sequencing (ChRO-seq) in atria of PlayrrEx1sj mutant mice compared to wild type controls revealed differential expression of genes involved in cell-cell adhesion and motility, fibrosis, and dysregulation of the key cardiac genes Tbx5 and Hcn1. ConclusionsAdult mice lacking functional Playrr lncRNA transcript have baseline bradyarrhythmia and increased susceptibility to AF. These cardiac phenotypes are similar to those observed in Pitx2 heterozygous mice. Interactions between Pitx2 and Playrr may provide a genetic mechanism for modulating Pitx2 dosage and susceptibility to SND and AF.

developmental biology↗

bioRxiv2022

CRISPRa screen identifies a role for c-KIT signaling in tamoxifen resistance, potentially through upregulation of ABC transporters

Resistance to endocrine therapy is a common problem in patients with estrogen receptor alpha (ER) positive breast cancer. In this study, we took a non-biased genome-wide approach to identify novel mechanisms of endocrine resistance using a clustered regularly interspaced short palindromic repeats (CRISPR) activating (CRISPRa) screen. Results from the screen identified 109 candidate resistance-associated genes, with several of these genes, such as EGFR and SRC, having been previously associated with endocrine resistance. One candidate gene that has not been previously associated with endocrine resistance is the tyrosine kinase receptor, c-KIT. We further tested for associations between c-KIT and endocrine resistance and found that c-KIT overexpressing cells proliferate more rapidly in the presence of tamoxifen compared to control cell lines. To gain deeper insight into the potential role of c-KIT signaling in tamoxifen resistance, we next performed precision nuclear run-on and sequencing (PRO-seq) analysis of c-KIT overexpressing cells to identify downstream factors that may mediate the c-KIT response. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the overexpressed genes found that the only class of factors that was significantly induced by c-KIT was the ATP-binding cassette (ABC) transporters; specifically, ABCA1, ABCA4, and ABCG1. Interestingly, overexpression of two of these ABC transporters, ABCA1 and ABCG1, significantly correlated with worse prognosis in ER+ breast cancer patients following endocrine therapy. We then tested for potential therapeutic effects of c-KIT inhibition on endocrine resistance and found that the c-KIT inhibitor Gleevec appears to synergize with tamoxifen to suppress MCF-7-S cell growth. Together, our findings support the hypothesis that c-KIT signaling promotes endocrine resistance via the induction of ABC transporter activity. Additionally, our studies suggest that inhibition of c-KIT signaling may represent a novel strategy for preventing or overcoming endocrine resistance in ER+ patients.

cancer biology↗

bioRxiv2022

Meiotic gene transcription programs are mediated by A-MYB and BRDT-dependent RNA polymerase II pause release during mammalian prophase I

During meiotic prophase I, germ cells must balance transcriptional activation with meiotic recombination and chromosome synapsis, biological processes requiring extensive changes to chromatin state and structure. Here we explored the interplay between chromatin accessibility and transcription across a detailed time-course of murine male meiosis by measuring genome-wide patterns of chromatin accessibility, nascent transcription, and processed mRNA. To understand the relationship between these parameters of gene regulation and recombination, we integrated these data with maps of double-strand break formation. Maps of nascent transcription show that Pol II is loaded on chromatin and maintained in a paused state early during prophase I. In later stages of prophase I, paused Pol II is released in a coordinated transcriptional burst resulting in [~]3-fold increase in transcription. Release from pause is mediated by the transcription factor A-MYB and the testis-specific bromodomain protein, BRDT. The burst of transcriptional activity is both temporally and spatially segregated from key steps of meiotic recombination: double strand breaks show evidence of chromatin accessibility earlier during prophase I and at distinct loci from those undergoing transcriptional activation, despite shared chromatin marks. Our findings reveal the mechanism underlying chromatin specialization in either transcription or recombination in meiotic cells.

genomics↗

bioRxiv2022

RNA polymerase II and PARP1 shape enhancer-promoter contacts

How enhancers control target gene expression over long genomic distances remains an important unsolved problem. Here we studied enhancer-promoter contact architecture and communication by integrating data from nucleosome-resolution genomic contact maps, nascent transcription, and perturbations to transcription-associated proteins and thousands of candidate enhancers. Contact frequency between functionally validated enhancer-promoter pairs was most enriched near the +1 and +2 nucleosomes at enhancers and target promoters, indicating that functional enhancer-promoter pairs spend time in close physical proximity. Blocking RNA polymerase II (Pol II) caused major disruptions to enhancer-promoter contacts. Paused Pol II occupancy and the enzymatic activity of poly (ADP-ribose) polymerase 1 (PARP1) stabilized enhancer-promoter contacts. Based on our findings, we propose an updated model that couples transcriptional dynamics and enhancer-promoter communication.

genomics↗

bioRxiv2022

GDNF-RET signaling and EGR1 form a positive feedback loop that promotes tamoxifen resistance via cyclin D1

BackgroundRearranged during transfection (RET) tyrosine kinase signaling has been previously implicated in endocrine resistant breast cancer, however the mechanism by which this signaling cascade promotes resistance is currently not well described. We recently reported that glial-cell derived neurotrophic factor (GDNF)-RET signaling appears to promote a positive feedback loop with the transcription factor early growth response 1 (EGR1). Here we investigate the mechanism behind this feedback loop and test the hypothesis that GDNF-RET signaling forms a regulatory loop with EGR1 to upregulate cyclin D1 (CCND1) transcription, leading to cell cycle progression and tamoxifen resistance. MethodsTo gain a better understanding of the GDNF-RET-EGR1 resistance mechanism, we studied the GDNF-EGR1 positive feedback loop and the role of GDNF and EGR1 in endocrine resistance by modulating their transcription levels using CRISPR-dCAS9 in tamoxifen sensitive (TamS) and tamoxifen resistant (TamR) MCF-7 cells. Additionally, we performed kinetic studies using recombinant GDNF (rGDNF) treatment of TamS cells. Statistical significance for qPCR and chromatin immunoprecipitation (ChIP)-qPCR was determined using a students t-test. ResultsGDNF-RET signaling formed a positive feedback loop with EGR1 and also downregulated estrogen receptor 1 (ESR1) transcription. Upregulation of GDNF and EGR1 promoted tamoxifen resistance in TamS cells and downregulation of GDNF promoted tamoxifen sensitivity in TamR cells. Additionally, we show that rGDNF treatment activated GDNF-RET signaling in TamS cells, leading to recruitment of p-ELK-1 to the EGR1 promoter, upregulation of EGR1 mRNA and protein, binding of EGR1 to the GDNF and CCND1 promoters, increased GDNF protein expression, and subsequent upregulation of CCND1 mRNA levels. ConclusionOutcomes from these studies support the hypotheses that GDNF-RET signaling forms a positive feedback loop with the transcription factor EGR1, and that GDNF-RET-EGR1 signaling promotes endocrine resistance via signaling to cyclin D1. Inhibition of components of this signaling pathway could lead to therapeutic insights into the treatment of endocrine resistant breast cancer.

molecular biology↗

bioRxiv2022

Run-on sequencing reveals nascent transcriptomics of the human microbiome

Precise regulation of transcription initiation and elongation enables bacteria to control cellular responses to environmental stimuli. RNAseq is the most common tool for measuring the transcriptional output of bacteria, comprising predominantly mature transcripts. To gain further insight into transcriptional dynamics, it is necessary to discriminate actively transcribed loci from those represented in the total RNA pool. One solution is to capture RNA polymerase (RNAP) in the act of transcription, but current methods are restricted to culturable and genetically tractable organisms. Here, we apply precision run-on sequencing (PRO-seq) to profile nascent transcription, a method amenable to diverse species. We find that PRO-seq is well-suited to profile small, structured, or post-transcriptionally modified RNAs, which are often excluded from RNAseq libraries. When PRO-seq is applied to the human microbiome, we identify taxon-specific RNAP pause motifs. We also uncover concurrent transcription and cleavage of guide RNAs and tRNA fragments at active CRISPR and tRNA loci. We demonstrate the specific utility of PRO-seq as a tool for exploring transcriptional dynamics in diverse microbial communities.

microbiology↗