Biology subjects

Danko, C. G.

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

At least 37 records · Page 2Linked to original sources

bioRxiv2022

RNA Pol II pausing facilitates phased pluripotency transitions by buffering transcription

Promoter-proximal RNA Pol II pausing is a critical step in transcriptional control. Pol II pausing has been studied predominantly in tissue culture systems. While Pol II pausing has been shown to be required for mammalian development, the phenotypic and mechanistic details of this requirement are unknown. Here, we find that loss of RNA Pol II pausing stalls pluripotent state transitions in the epiblast of the early mouse embryo. Using Nelfb-/- mice and a novel NELFB- degron mouse embryonic stem cells, we show that mouse ES cells (mESCs) representing the naive state of pluripotency successfully initiate a transition program, but fail to balance levels of induced and repressed genes and enhancers in the absence of NELF. Consistently, we find an increase in chromatin-associated NELF during pluripotency transitions. Overall, our work reveals the molecular and phenotypic roles of Pol II pausing in pluripotency and introduces Pol II pausing as a modulator of cell state transitions.

molecular biology↗

bioRxiv2021

Genome edited colorectal cancer organoid models reveal distinct microRNA activity patterns across different mutation profiles

Somatic mutations drive colorectal cancer (CRC) by disrupting gene regulatory mechanisms. Distinct combinations of mutations can result in unique changes to regulatory mechanisms leading to variability in the efficacy of therapeutics. MicroRNAs are important regulators of gene expression, and their activity can be altered by oncogenic mutations. However, it is unknown how distinct combinations of CRC-risk mutations differentially affect microRNAs. Here, using genetically-modified mouse intestinal organoid (enteroid) models, we identify 12 different modules of microRNA expression patterns across distinct combinations of mutations common in CRC. We also show that miR-24-3p is aberrantly upregulated in genetically-modified mouse enteroids irrespective of mutational context. Furthermore, we identify an enrichment of miR-24-3p predicted targets in downregulated gene lists from various mutational contexts compared to WT. In follow-up experiments, we demonstrate that miR-24-3p promotes CRC cell survival in multiple cell contexts. Our novel characterization of genotype-specific patterns of miRNA expression offer insight into the mechanisms that drive inter-tumor heterogeneity and highlight candidate microRNA therapeutic targets for the advancement of precision medicine for CRC.

cancer biology↗

bioRxiv2021

Genetic Dissection of the RNA Polymerase II Transcription Cycle

How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate the strength of base pairing between A-T or G-C dinucleotides as key determinants to the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

genomics↗

bioRxiv2021

Identification and prediction of developmental enhancers in sea urchin embryos

BackgroundThe transcription of developmental regulatory genes is often controlled by multiple cis-regulatory elements. The identification and functional characterization of distal regulatory elements remains challenging, even in tractable model organisms like sea urchins. ResultsWe evaluate the use of chromatin accessibility, transcription and RNA Polymerase II for their ability to predict enhancer activity of genomic regions in sea urchin embryos. ATAC-seq, PRO-seq, and Pol II ChIP-seq from early and late blastula embryos are manually contrasted with experimental cis-regulatory analyses available in sea urchin embryos, with particular attention to common developmental regulatory elements known to have enhancer and silencer functions differentially deployed among embryonic territories. Using the three functional genomic data types, machine learning models are trained and tested to classify and quantitatively predict the enhancer activity of several hundred genomic regions previously validated with reporter constructs in vivo. ConclusionsOverall, chromatin accessibility and transcription have substantial power for predicting enhancer activity. For promoter-overlapping cis-regulatory elements in particular, the distribution of Pol II is the best predictor of enhancer activity in blastula embryos. Furthermore, ATAC- and PRO-seq predictive value is stage dependent for the promoter-overlapping subset. This suggests that the sequence of regulatory mechanisms leading to transcriptional activation have distinct relevance at different levels of the developmental gene regulatory hierarchy deployed during embryogenesis.

genomics↗

bioRxiv2021

Deconvolution of Expression for Nascent RNA Sequencing Data (DENR) Highlights Pre-RNA Isoform Diversity in Human Cells

Quantification of mature-RNA isoform abundance from RNA-seq data has been extensively studied, but much less attention has been devoted to quantifying the abundance of distinct precursor RNAs based on nascent RNA sequencing data. Here we address this problem with a new computational method called Deconvolution of Expression for Nascent RNA sequencing data (DENR). DENR models the nascent RNA read counts at each locus as a mixture of user-provided isoforms. The performance of the baseline algorithm is enhanced by the use of machine-learning predictions of transcription start sites (TSSs) and an adjustment for the typical "shape profile" of read counts along a transcription unit. We show using simulated data that DENR clearly outperforms simple read-count-based methods for estimating the abundances of both whole genes and isoforms. By applying DENR to previously published PRO-seq data from K562 and CD4+ T cells, we find that transcription of multiple isoforms per gene is widespread, and the dominant isoform frequently makes use of an internal TSS. We also identify > 200 genes whose dominant isoforms make use of different TSSs in these two cell types. Finally, we apply DENR and StringTie to newly generated PRO-seq and RNA-seq data, respectively, for human CD4+ T cells and CD14+ monocytes, and show that entropy at the pre-RNA level makes a disproportionate contribution to overall isoform diversity, especially across cell types. Altogether, DENR is the first computational tool to enable abundance quantification of pre-RNA isoforms based on nascent RNA sequencing data, and it reveals high levels of pre-RNA isoform diversity in human cells.

genomics↗

bioRxiv2021

The effects of chromosome fusions on genetic diversity and evolutionary turnover of functional loci consistently depends on chromosome size

Major changes in chromosome number and structure are linked to a series of evolutionary phenomena, including intrinsic barriers to gene flow or suppression of recombination due to chromosomal rearrangements. However, chromosome rearrangements can also affect the fundamental dynamics of molecular evolution within populations by changing relationships between linked loci and altering rates of recombination. Here, we build chromosome-level assembly Eueides isabella and, together with the chromosome-level assembly of Dryas iulia, examine the evolutionary consequences of multiple chromosome fusions in Heliconius butterflies. These assemblies pinpoint fusion points on 10 of the 21 autosomal chromosomes and reveal striking differences in the characteristics of fused and unfused chromosomes. The ten smallest autosomes in D. iulia and E. isabella, which have each fused to a longer chromosome in Heliconius, have higher repeat and GC content, and longer introns than predicted by their chromosome length. Following fusion, these characteristics change to become more in line with chromosome length. The fusions also led to reduced diversity, which likely reflects increased background selection and selection against introgression between diverging populations, following a reduction in per-base recombination rate. We further show that chromosome size and fusion impact turnover rates of functional loci at a macroevolutionary scale. Together these results provide further evidence that chromosome fusion in Heliconius likely had dramatic effects on population level processes shaping rates of neutral and adaptive divergence. These effects may have impacted patterns of diversification in Heliconius, a classic example of an adaptive radiation.

evolutionary biology↗

bioRxiv2020

Uncovering Transcriptional Dark Matter via Gene Annotation Independent Single-Cell RNA Sequencing Analysis

Single-cell RNA sequencing (scRNA-seq) enables the study of cell biology with high resolution. scRNA-seq expression analyses rely on the availability of a high quality annotation of genes in the genome. Yet, as we show here with scRNA-seq experiments and analyses spanning human, mouse, chicken, mole rat, lemur and sea urchin, gene annotations often fail to cover the full transcriptome of every cell type at every stage of development, in particular for organisms that are not routinely studied. To overcome this hurdle, we created a scRNA-seq analysis routine that recovers biologically relevant information beyond the scope of the best available gene annotation. This is achieved by performing single-cell expression analysis on any region in the genome for which transcriptional products are detected. Our routine identifies transcriptionally active regions (TARs) using a hidden Markov model, generates a matrix of expression levels for all TARs across all cells in a dataset, performs single-cell TAR expression analysis to identify TARs that are biologically significant, and then annotates biologically significant TARs using gene homology analysis. This procedure leverages single-cell expression analyses as a filter to direct annotation efforts to biologically significant transcripts in complex tissues and thereby uncovers biology to which scRNA-seq would otherwise be in the dark.

bioinformatics↗

bioRxiv2020

Multiple stages of evolutionary change in anthrax toxin receptor expression in humans

The advent of animal husbandry and hunting increased human exposure to zoonotic pathogens. To understand how a zoonotic disease influenced human evolution, we studied changes in human expression of anthrax toxin receptor 2 (ANTXR2), which encodes a cell surface protein necessary for Bacillus anthracis virulence toxins to cause anthrax disease. In immune cells, ANTXR2 was 8-fold down-regulated in all available human samples compared to non-human primates, indicating regulatory changes early in the evolution of modern humans. We also observed multiple genetic signatures consistent with recent positive selection driving a European-specific decrease in ANTXR2 expression in several non-immune tissues affected by anthrax toxins. Our observations fit a model in which humans adapted to anthrax disease following early ecological changes associated with hunting and scavenging, as well as a second period of adaptation after the rise of modern agriculture.

genetics↗

bioRxiv2020

A rapid, sensitive, scalable method for Precision Run-On sequencing (PRO-seq)

Tracking active transcription with the nuclear run-on (NRO) assays has been instrumental in uncovering mechanisms of gene regulation. The coupling of NROs with high-throughput sequencing has facilitated the discovery of previously unannotated or undetectable RNA classes genome-wide. Precision run-on sequencing (PRO-seq) is a run-on variant that maps polymerase active sites with nucleotide or near-nucleotide resolution. One main drawback to this and many other nascent RNA detection methods is the somewhat intimidating multi-day workflow associated with creating the libraries suitable for high-throughput sequencing. Here, we present an improved PRO-seq protocol where many of the enzymatic steps are carried out while the biotinylated NRO RNA remains bound to streptavidin-coated magnetic beads. These adaptations reduce time, sample loss and RNA degradation, and we demonstrate that the resulting libraries are of the same quality as libraries generated using the original published protocol. The assay is also more sensitive which permits reproducible, high-quality libraries from 104-105 cells instead of 106-107. Altogether, the improved protocol is more tractable allows for nascent RNA profiling from small samples, such as rare samples or FACS sorted cell populations.

genomics↗

bioRxiv2020

Accurate imputation of histone modifications using transcription

The role of histone modifications in transcription remains incompletely understood. Here we used experimental perturbations combined with sensitive machine learning tools that infer the distribution of histone marks using maps of nascent transcription. Transcription predicted the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. Blocking transcription rapidly removed two punctate marks, H3K4me3 and H3K27ac, from chromatin indicating that transcription is required for active histone modifications. Transcription was also required for maintenance of H3K27me3 consistent with a role for RNA in recruiting PRC2. A subset of DNase-I hypersensitive sites were refractory to prediction, precluding models where transcription initiates pervasively at any open chromatin. Our results, in combination with past literature, support a model in which active histone modifications serve a supportive, rather than a regulatory, role in transcription.

genomics↗

bioRxiv2020

Hotspots of aberrant enhancer activity in fibrolamellar carcinoma reveal molecular mechanisms of oncogenesis and intrinsic drug resistance

Fibrolamellar carcinoma (FLC) is a rare, therapeutically intractable liver cancer that disproportionately affects youth. Although FLC tumors exhibit a distinct gene expression profile, the causative transcriptional mechanisms remain unclear. Here we used chromatin run-on sequencing to discover approximately 7,000 enhancers and 141 enhancer hotspots activated in FLC relative to non-malignant liver. Detailed bioinformatic analyses revealed aberrant ERK/MEK signaling and candidate master transcriptional regulators. We also defined the genes most strongly associated with aberrant FLC enhancer activity, including CA12 and SLC16A14. Treatment of FLC cell models with inhibitors of CA12 or SLC16A14 independently reduced cell viability and/or significantly enhanced the effect of MEK inhibitor cobimetinib. These findings highlight new molecular targets for drug development as well as novel drug combination approaches.

cancer biology↗

bioRxiv2020

Bayesian Inference of Cell Composition and Gene Expression Reveals Tumor-Microenvironment Interactions

Understanding the interactions between cells in their environment is a major challenge in genomics. Here we developed BayesPrism, a Bayesian method to jointly predict cellular composition and gene expression in each cell type, including heterogeneous malignant cells, from bulk RNA-seq using scRNA-seq as prior information. We conducted an integrative analysis of 1,412 bulk RNA-seq samples in primary glioblastoma, head and neck squamous cell carcinoma, and melanoma using single-cell datasets of 85 patients. We identified cell types correlated with clinical outcomes and explored spatial heterogeneity in malignant cell states and non-malignant cell type composition. We refined subtypes using gene expression in malignant cells, after excluding confounding non-malignant cell types. Finally, we identified genes whose expression in malignant cells correlated with infiltration of macrophages, T cells, fibroblasts, and endothelial cells across multiple tumor types. Our work introduces a new lens that uses scRNA-seq to accurately infer cellular composition and expression in large cohorts of bulk data.

genomics↗

bioRxiv2019

Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data

The rate at which RNA molecules decay is a key determinant of cellular RNA concentrations, yet current approaches for measuring RNA half-lives are generally labor-intensive, limited in sensitivity, and/or disruptive to normal cellular processes. Here we introduce a simple method for estimating relative RNA half-lives that is based on two standard and widely available high-throughput assays: Precision Run-On and sequencing (PRO-seq) and RNA sequencing (RNA-seq). Our method treats PRO-seq as a measure of transcription rate and RNA-seq as a measure of RNA concentration, and estimates the rate of RNA decay required for a steady-state equilibrium. We show that this approach can be used to assay relative RNA half-lives genome-wide, with good accuracy and sensitivity for both coding and noncoding transcription units. Using a structural equation model (SEM), we test several features of transcription units, nearby DNA sequences, and nearby epigenomic marks for associations with RNA stability after controlling for their effects on transcription. We find that RNA splicing-related features are positively correlated with RNA stability, whereas features related to miRNA binding, DNA methylation, and G+C-richness are negatively correlated with RNA stability. Furthermore, we find that a measure based on U1-binding and polyadenylation sites distinguishes between unstable noncoding and stable coding transcripts but is not predictive of relative stability within the mRNA or lincRNA classes. We also identify several histone modifications that are associated with RNA stability. Together, our estimation method and systematic analysis shed light on the pervasive impacts of RNA stability on cellular RNA concentrations.

genomics↗

bioRxiv2019

Chromatin conformation remains stable upon extensive transcriptional changes driven by heat shock

Heat shock (HS) initiates rapid, extensive, and evolutionarily conserved changes in transcription that are accompanied by chromatin decondensation and nucleosome loss at heat shock loci. Here we have employed in situ Hi-C to determine how heat stress affects long-range chromatin conformation in human and Drosophila cells. We found that compartments, topologically-associated domains (TADs), and looping interactions all remain unchanged by an acute HS. Knockdown of Heat Shock Factor 1 (HSF1), the master transcriptional regulator of the HS response, identified HSF1-dependent genes and revealed that up-regulation is often mediated by distal HSF1 bound enhancers. HSF1-dependent genes were usually found in the same TAD as the nearest HSF1 binding site. However, the HSF1 binding sites and the target promoters did not exhibit a focal increase in contact frequencies compared with surrounding regions, nor did we find evidence of increased contact frequency following HS. Integrating information about HSF1 binding strength, RNA polymerase abundance at the enhancer, and contact frequency with a target promoter in the non-heat shock (NHS) condition accurately predicted which up-regulated genes were direct targets of HSF1 during HS. Our results suggest that the chromatin conformation necessary for a robust HS response is pre-established in normal (uninduced) cells of diverse metazoan species.

molecular biology↗

bioRxiv2018

AlleleHMM: a data-driven method to identify allele-specific differences in distributed functional genomic marks

How DNA sequence variation influences gene expression remains poorly understood. Diploid organisms have two homologous copies of their DNA sequence in the same nucleus, providing a rich source of information about how genetic variation affects a wealth of biochemical processes. However, few computational methods have been developed to discover allele-specific differences in functional genomic data. Existing methods either treat each SNP independently, limiting statistical power, or combine SNPs across gene annotations, preventing the discovery of allele specific differences in unexpected genomic regions. Here we introduce AlleleHMM, a new computational method to identify blocks of neighboring SNPs that share similar allele-specific differences in mark abundance. AlleleHMM uses a hidden Markov model to divide the genome among three hidden states based on allele frequencies in genomic data: a symmetric state (state S) which shows no difference between alleles, and regions with a higher signal on the maternal (state M) or paternal (state P) allele. AlleleHMM substantially outperformed naive methods using both simulated and real genomic data, particularly when input data had realistic levels of overdispersion. Using PRO-seq data, AlleleHMM identified thousands of allele specific blocks of transcription in both coding and non-coding genomic regions. AlleleHMM is a powerful tool for discovering allele-specific regions in functional genomic datasets.

bioinformatics↗

bioRxiv2018

Simultaneous multiplexed amplicon sequencing and transcriptome profiling in single cells

We describe Droplet Assisted RNA Targeting by single cell sequencing (DART-seq), a versatile technology that enables multiplexed amplicon sequencing and transcriptome profiling in single cells. We applied DART-seq to simultaneously characterize the non-A-tailed transcripts of a segmented dsRNA virus and the transcriptome of the infected cell. In addition, we used DART-seq to simultaneously determine the natively paired, variable region heavy and light chain amplicons and the transcriptome of B lymphocytes.

genomics↗

bioRxiv2018

Identification of regulatory elements from nascent transcription using dREG

Our genomes encode a wealth of transcription initiation regions (TIRs) that can be identified by their distinctive patterns of actively elongating RNA polymerase. We previously introduced dREG to identify TIRs using PRO-seq data. Here we introduce an efficient new implementation of dREG that uses PRO-seq data to identify both uni- and bidirectionally transcribed TIRs with 70% improvements in accuracy, 3-4-fold higher resolution, and >100-fold increases in computational efficiency. Using a novel strategy to identify TIRs based on their statistical confidence reveals extensive overlap with orthogonal assays, yet also reveals thousands of additional weakly-transcribed TIRs that were not identified by H3K27ac ChIP-seq or DNase-I-hypersensitivity. Novel TIRs discovered by dREG were often associated with RNA polymerase III initiation, bound by pioneer transcription factors, or located in broad domains marked by repressive chromatin modifications. We provide a web interface to dREG that can be used by the scientific community (http://dREG.DNASequence.org).

bioinformatics↗

bioRxiv2017

A common pattern of DNase-I footprinting throughout the human mtDNA unveils clues for a chromatin-like organization

Human mitochondrial DNA (mtDNA) is believed to lack chromatin and histones. Instead, it is coated solely by the transcription factor TFAM, which binds the mtDNA without sequence specificity and packs it into a bacterial-like nucleoid in a dose-dependent fashion. We asked whether mtDNA packaging is more regulated than once thought. As a first step to address this question, we analyzed mtDNA DNase-I-seq experiments in 324 different human cell types and found, for the first time, a pattern of 29 Genomic footprinting (DGF) sites throughout the mtDNA shared by [~]90% of the tested samples. Low SNP density at the DGF sites, and their conservation in mouse DNase-seq experiments, reflect strong selective constraints. Co-localization of the DGFs with known mtDNA regulatory elements and with recently-discovered transcription pausing sites, suggest a role for such DGFs in mtDNA transcription. Altered mtDNA DGF pattern in IL-3 treated CD+34 cells offer first clue to their physiological importance. Taken together, human mtDNA has a conserved and regulated protein-DNA organization, which is likely involved in regulation of mtDNA gene expression.

genomics↗