Biology subjects

Hardison, R. C.

Publications and source records attributed to Hardison, R. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Dissecting polycomb complexes for enhanced fetal hemoglobin production

Polycomb repressive complexes PRC1 and PRC2 regulate diverse developmental processes, including the fetal-to-adult switch in hemoglobin production, a process whose reversal is a goal for the treatment of sickle cell disease and {beta}-thalassemia. PRC inhibitors show promise for various disorders, but use is limited because of pleiotropic PRC activities. We explored whether fetal hemoglobin (HbF) can be reactivated in adult erythroid cells by selective perturbations of PRC1 or PRC2 components without complete loss of PRC function. A high-density CRISPR-Cas9 mutagenesis screen identified a region in the EZH2 subunit where Cas9 induced exon 14 skipping (EZH2{Delta}14). EZH2{Delta}14, which lacks a portion of the CXC domain, relieves HbF repression while largely maintaining cellular fitness. EZH2{Delta}14 retains H3K27 methylation and repression of a PRC target gene subset. Experiments in cells derived from mice bearing human {beta}-globin genes confirm that pathways mediating EZH2 control of HbF expression can function in a mouse model of HBG switching. These findings demonstrate that partial disruption of PRC can yield selective phenotypes, highlighting the therapeutic potential of targeting non-enzymatic domains within chromatin-modifying complexes. Key PointsO_LICRISPR-Cas9 screen across PRC1 and a saturating mutagenesis screen of PRC2 found the EZH2 CXC domain a desirable target for HbF induction C_LIO_LIthe EZH2-CXC domain leads to exon 14 exclusion, resulting in de-repression of HbF but maintenance of cell fitness. C_LI

molecular biology↗

bioRxiv2025

Divergence between transcriptomes and chromatin accessibility during differentiation from a bipotential progenitor cell population to erythroblasts and megakaryocytes

Changes in gene expression drive differentiation along distinct cell lineages, and these shifts in gene expression are associated with alterations in chromatin accessibility and modifications reflecting activation or repression. We used deep sequencing of polyA+ RNA to map the transcriptomes of the megakaryocyte-erythroid progenitor (MEP) and cells of its two daughter lineages, erythroblasts (ERY) and megakaryocytes (MEG) in mice to reveal insights into differentiation. Transcriptome comparisons revealed that MEPs already expressed much of the MEG program while continuing to express genes associated with parallel myeloid lineages. By contrast, ERY underwent an extensive program of gene induction along with repression of pan-hematopoietic and MEG genes. Maps of transcription factor (TF) occupancy also indicated distinct modes of regulation for the MEG and ERY programs, with MEG genes preferentially occupied by hematopoietic TFs in multipotent progenitors and continued occupancy post-commitment, in contrast to erythroid genes that were primarily occupied in committed ERY. Previous work had indicated a surprising discordance in the clustering of MEP with other hematopoietic cell types by RNA-seq versus chromatin states. We combined the differential expression data with chromatin accessibility across blood cell types to identify trends that contribute to this discordance. Specifically, candidate cis-regulatory elements (cCREs) in some ERY-specific genes were precociously actuated in the bipotential cell populations, and some other genes were expressed in both the MEP population and MEG but their cCREs have less chromatin accessibility in MEP. This discordance in cell type clustering by different modalities of functional genomics may reflect the different contributions of subpopulations in the MEP to the different modalities measured.

genomics↗

bioRxiv2025

Single-stranded DNA binding proteins are essential components of the architectural LDB1 protein complex

Transcriptional enhancers are brought into proximity with promoters via chromatin looping. The architectural transcription cofactor LDB1 facilitates spatial connectivity among enhancers and promoters but whether this occurs through simple dimerization or requires partner molecules is unknown. Here we investigated single-stranded DNA binding proteins (SSBPs), known LDB1 interactors, in regulating LDB1-mediated chromatin looping and transcription. SSBP2, SSBP3, and SSBP4 colocalize with LDB1 genome wide. Among these, only SSBP3 is essential for erythroid cell viability, LDB1 function, and transcription. LDB1, but not single-stranded DNA, is the predominant genome-wide tether of SSBP3 to chromatin. Notably, SSBP3 depletion for under one hour in SSBP2/4 knockout cells globally weakened LDB1-dependent chromatin loops and lowered nascent transcription without impacting LDB1s chromatin binding. Chromatin tethering experiments revealed SSBP3 and LDB1 mutually depend on each other to form looped contacts. SSBP3 stabilizes LDB1 homodimers in solution providing a possible mechanism of action. In sum, SSBPs emerge as key functional components of the architectural LDB1 complex, shedding new light on the regulation of enhancer-promoter interactions and gene expression.

genomics↗

bioRxiv2024

JOnTADS: a unified caller for TADs and stripes in Hi-C data

Topologically associating domains (TADs) and stripes are important architectural structures on Hi-C data that are important for gene regulation. We present Joint Optimized nested TADs and Stripes (JOn-TADS), a unified caller for TADs and stripes in Hi-C data. JOnTADS effectively identifies hierarchical TADs and stripes in population Hi-C and micro-C datasets, and hierarchical TADs in single-cell Hi-C data. It provides robust identifications aligned with known biology and effectively captures interaction frequency variations in contact maps across diverse contexts. When multiple samples are available, JOn-TADS leverages shared information across samples in TAD identification, reducing unwanted variation in TAD boundary identification while preserving biological differences. This approach enables robust identifications in single-cell Hi-C data, effectively addressing challenges posed by data sparsity. JOnTADS is computationally efficient and requires minimal user tuning.

bioinformatics↗

bioRxiv2024

LDB1 establishes multi-enhancer networks to regulate gene expression

How specific enhancer-promoter pairing is established is still mostly unclear. Besides the CTCF/cohesin machinery, only a few nuclear factors have been studied for a direct role in physically connecting regulatory elements. Here, we show via acute degradation experiments that LDB1 directly and broadly promotes enhancer-promoter loops. Most LDB1-mediated contacts, even those spanning hundreds of kb, can form in the absence of CTCF, cohesin, or YY1 as determined via the use of multiple degron systems. Moreover, an engineered LDB1-driven chromatin loop is cohesin independent. Cohesin-driven loop extrusion does not stall at LDB1 occupied sites but may aid the formation of a subset of LDB1 anchored loops. Leveraging the dynamic reorganization of nuclear architecture during the transition from mitosis to G1-phase, we establish a relationship between LDB1-dependent interactions in the context of TAD organization and gene activation. Lastly, Tri-C and Region Capture Micro-C reveal that LDB1 organizes multi-enhancer networks to activate transcription. This establishes LDB1 as a direct driver of regulatory network inter-connectivity.

molecular biology↗

bioRxiv2023

RETROFIT: REFERENCE-FREE DECONVOLUTION OF CELL-TYPE MIXTURES IN SPATIAL TRANSCRIPTOMICS

Spatial transcriptomics (ST) enables genome-wide measurement of gene expression in intact tissues, but typically captures mixtures of multiple cell types at each spatial location. Deconvolving these mixtures is essential for resolving cell-type-specific spatial organization and transcriptional programs. Existing approaches often rely on matched single-cell references or curated marker genes, which may be unavailable, incomplete, or difficult to integrate across platforms. We present RETROFIT, a Bayesian framework for reference-free deconvolution of spatial transcriptomics data that operates directly on sequencing measurements and incorporates external information only at a post hoc annotation stage when available. Across extensive simulations and multiple real datasets, RETROFIT demonstrates robust performance, outperforming existing reference-free methods and matching or exceeding reference-based approaches when references are imperfect. Notably, RETROFIT remains effective at near-single-cell resolution, as demonstrated on Visium HD data, recovering fine-grained spatial patterns without requiring single-cell references or marker genes. These results establish RETROFIT as a broadly applicable approach for reference-free spatial transcriptomics analysis across platforms and resolutions. RETROFIT is available at https://bioconductor.org/packages/retrofit/.

bioinformatics↗

bioRxiv2023

Cross-species regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

genomics↗

bioRxiv2021

CTCF blocks anti-sense transcription initiation at divergent gene promoters

Transcription at most promoters is divergent, initiating at closely spaced oppositely oriented core promoters to produce sense transcripts along with often unstable upstream antisense (uasTrx). How antisense transcription is regulated and to what extent it is coordinated with sense transcription is largely unknown. Here by combining acute degradation of the multi-functional transcription factor CTCF and nascent transcription measurements, we find that CTCF specifically suppresses antisense but not sense transcription at hundreds of divergent promoters, the great majority of which bear proximal CTCF binding sites. Genome editing, chromatin conformation studies, and high-resolution transcript mapping revealed that precisely positioned CTCF directly suppresses the initiation of uasTrx, in a manner independent of its chromatin architectural function. Primary transcript RNA FISH revealed co-bursting of sense and anti-sense transcripts is disfavored, suggesting CTCF-regulated competition for transcription initiation. In sum, CTCF shapes the transcriptional landscape in part by suppressing upstream antisense transcription.

molecular biology↗

bioRxiv2021

CTCF and transcription influence chromatin structure re-configuration after mitosis

During mitosis, transcription is globally attenuated and chromatin architecture is dramatically reconfigured. Here we exploited the M- to G1-phase progression to interrogate the contributions of the architectural factor CTCF and the process of transcription to re-sculpting the genome in newborn nuclei. Depletion of CTCF specifically during the M- to G1-phase transition altered the re-establishment of local short-range compartmentalization after mitosis. Chromatin domain boundary reformation was impaired upon CTCF loss, but a subset ([~]27%) of boundaries, characterized by transitions in chromatin states, was established normally. Without CTCF, structural loops failed to form, leading to illegitimate contacts between cis-regulatory elements (CREs). Transient CRE contacts that are normally resolved after telophase persisted deeply into G1-phase in CTCF depleted cells. CTCF loss-associated gains in transcription were often linked to increased, normally illegitimate enhancer-promoter contacts. In contrast, at genes whose expression declined upon CTCF loss, CTCF seems to function as a conventional transcription activator, independent of its architectural role. CTCF-anchored structural loops facilitated formation CRE loops nested within them, especially those involving weak CREs. Transcription inhibition did not elicit global architectural changes and left transcription start site-associated boundaries intact. However, ongoing transcription contributed considerably to the formation of gene domains, regions of enriched contacts spanning the length of gene bodies. Notably, gene domains formed rapidly in ana/telophase prior to the completion of the first round of transcription, suggesting that epigenetic features in gene bodies contribute to genome reconfiguration prior to transcription. The focus on the de novo formation of nuclear architecture during G1 entry yielded novel insights into how CTCF and transcription contribute to the dynamic re-configuration of chromatin architecture during the mitosis to G1 phase progression.

genomics↗

bioRxiv2020

High-dimensional association detection in large scale genomic data

Joint analyses of genomic datasets obtained in multiple different conditions are essential for understanding the biological mechanism that drives tissue-specificity and cell differentiation, but they still remain computationally challenging. To address this we introduce CLIMB (Composite LIkelihood eMpirical Bayes), a statistical methodology that learns patterns of condition-specificity present in genomic data. CLIMB provides a generic framework facilitating a host of analyses, such as clustering genomic features sharing similar condition-specific patterns and identifying which of these features are involved in cell fate commitment. We apply CLIMB to three sets of hematopoietic data, which examine CTCF ChIP-seq measured in 17 different cell populations, RNA-seq measured across constituent cell populations in three committed lineages, and DNase-seq in 38 cell populations. Our results show that CLIMB improves upon existing alternatives in statistical precision, while capturing interpretable and biologically relevant clusters in the data.

bioinformatics↗

bioRxiv2020

Effects of sheared chromatin length on ChIP-seq quality and sensitivity

Chromatin immunoprecipitation followed by massively parallel, high throughput sequencing (ChIP-seq) is the method of choice for identifying, on a genome-wide scale, the segments of DNA bound by specific transcription factors (TFs) or in chromatin with particular histone modifications. However, the quality of ChIP-seq datasets vary over a wide range, with a substantial fraction being of intermediate to poor quality. Such experimental variability can lead to many false positives or false negatives, impairing the ability to interpret the data. Thus, it is important to discern and control the factors that contribute to variation in ChIP-seq. In this study, we focus on the sonication step to produce sheared chromatin, a variable controllable by the user and applicable to all ChIP-seq protocols. We systematically varied the amount of shearing of fixed chromatin from a mouse erythroid cell line, carefully measured the distribution of resultant fragment lengths using the Agilent Bioanalzyer 2100, and then immunoprecipitated these batches of chromatin using highly specific antibodies against either TAL1 or CTCF. We found that the level of sonication, which was affected by both the number of sonication cycles, as well as the starting cell number, had a pronounced impact on the quality of resulting ChIP-seq signals. Specifically, over-sonication led to degradation of quality (e.g. increased background and reduction in signal), while the impact of under-sonication of chromatin differed between the two transcription factors, leading to the loss of sites occupied by TAL1 but not those bound by CTCF. We leveraged these findings to produce a set of CTCF ChIP-seq datasets in primary hematopoietic progenitor cells, including several rare cell types. Together, these results suggest that the amount of sonication is a key variable in success of ChIP-seq experiments, and that carefully monitoring the level of chromatin sonication is one way to improve ChIP-seq quality and reproducibility, which in turn facilitates low input ChIP-seq in rare cell types.

genomics↗

bioRxiv2020

S3V2-IDEAS: a package for normalizing, denoising and integrating epigenomic datasets across different cell types

SummaryEpigenetic modifications reflect key aspects of transcriptional regulation, and many epigenomic data sets have been generated under many biological contexts to provide insights into regulatory processes. However, the technical noise in epigenomic data sets and the many dimensions (features) examined make it challenging to effectively extract biologically meaningful inferences from these data sets. We developed a package that reduces noise while normalizing the epigenomic data by a novel normalization method, followed by integrative dimensional reduction by learning and assigning epigenetic states. This package, called S3V2-IDEAS, can be used to identify epigenetic states for multiple features, or identify signal intensity states and a master peak list across different cell types for a single feature. We illustrate the outputs and performance of S3V2-IDEAS using 137 epigenomics data sets from the VISION project that provides ValIdated Systematic IntegratiON of epigenomic data in hematopoiesis. Availability and implementationS3V2-IDEAS pipeline is freely available as open source software released under an MIT license at: https://github.com/guanjue/S3V2_IDEAS_ESMP Contactrch8@psu.edu, gzx103@psu.edu Supplementary informationS3V2-IDEAS-bioinfo-supplementary-materials.pdf

bioinformatics↗

bioRxiv2020

Detecting local changes in chromatin architecture with false discovery control

Hi-C experiments are a powerful means to describe the organization of chromatin interactions genome-wide. By using Hi-C data to identify differentially organized genomic regions, relationships between this organization, gene expression, and cell identity may be established. However, Hi-C data exhibit a unique and challenging spatial structure, as genomic loci can show strong correlations when they are nearby in 3D space within the nucleus or 1D space along the chromosome. Consequently, the development of methods that can accurately detect differences between Hi-C samples while controlling false discoveries has remained difficult. To meet this need, we introduce a spatial modeling approach based on sliding window statistics. Using polymer simulations, we illustrate the improved power and precision of our method to identify differentially interacting genomic regions. We further demonstrate our methods ability to reveal biologically meaningful changes in chromatin architecture through two data analyses concerning the loss of architectural and chromatin remodeling proteins.

genomics↗

bioRxiv2020

ZNF410 uniquely activates the NuRD component CHD4 to silence fetal hemoglobin expression

Metazoan transcription factors typically regulate large numbers of genes. Here we identify via a CRISPR-Cas9 genetic screen ZNF410, a pentadactyl DNA binding protein that in human erythroid cells directly and measurably activates only one gene, the NuRD component CHD4. Specificity is conveyed by two highly evolutionarily conserved clusters of ZNF410 binding sites near the CHD4 gene with no counterparts elsewhere in the genome. Loss of ZNF410 in adult-type human erythroid cell culture systems and xenotransplant settings diminishes CHD4 levels and derepresses the fetal hemoglobin genes. While previously known to be silenced by CHD4, the fetal globin genes are exposed here as among the most sensitive to reduced CHD4 levels. In vitro DNA binding assays and crystallographic studies reveal the ZNF410-DNA binding mode. ZNF410 is a remarkably selective transcriptional activator in erythroid cells whose perturbation might offer new therapeutic opportunities in the treatment of hemoglobinopathies. HighlightsO_LIA CRISPR screen implicates ZNF410 in fetal globin gene repression C_LIO_LIThe CHD4 gene is the singular direct ZNF410 target in erythroid cells C_LIO_LIThe fetal globin genes are exquisitely sensitive to CHD4 levels C_LIO_LIFive C2H2 zinc fingers of ZNF410 recognize the major groove of a 14 base pair sequence C_LI

molecular biology↗

bioRxiv2020

The changing mouse embryo transcriptome at whole tissue and single-cell resolution

In mammalian embryogenesis differential gene expression gradually builds the identity and complexity of each tissue and organ system. We systematically quantified mouse polyA-RNA from embryo day E10.5 to birth, sampling 17 whole tissues, enhanced with single-cell measurements for the developing limb. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets, characterized by their promoters transcription factor (TF) motif codes. We decomposed the tissue-level transcriptome using scRNA-seq and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for 1/3 of differential gene expression and over 40% of identified cell types. Integrating promoter sequence motifs with companion ENCODE epigenomic profiles identified a promoter de-repression mechanism unique to neuronal expression clusters and attributable to known and novel repressors. Focusing on the developing limb, scRNA-seq identified 25 known and candidate novel cell types, including progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell type TF networks and complementary sets of candidate enhancer elements by de-convolving whole-tissue IDEAS epigenome chromatin state models. These ENCODE reference data, computed network components and IDEAS chromatin segmentations, are companion resources to the matching epigenomic developmental matrix, available for researchers to further mine and integrate.

developmental biology↗

bioRxiv2019

Systematic integration of GATA transcription factors and epigenomes via IDEAS paints the regulatory landscape of mouse hematopoietic cells

Members of the GATA family of transcription factors play key roles in the differentiation of specific cell lineages by regulating the expression of target genes. Three GATA factors play distinct roles in hematopoietic differentiation. In order to better understand how these GATA factors function to regulate genes throughout the genome, we are studying the epigenomic and transcriptional landscapes of hematopoietic cells in a model-driven, integrative fashion. We have formed the collaborative multi-lab VISION project to conduct ValIdated Systematic IntegratiON of epigenomic data in mouse and human hematopoiesis. The epigenomic data included nuclease accessibility in chromatin, CTCF occupancy, and histone H3 modifications for twenty cell types covering hematopoietic stem cells, multilineage progenitor cells, and mature cells across the blood cell lineages of mouse. The analysis used the Integrative and Discriminative Epigenome Annotation System (IDEAS), which learns all common combinations of features (epigenetic states) simultaneously in two dimensions - along chromosomes and across cell types. The result is a segmentation that effectively paints the regulatory landscape in readily interpretable views, revealing constitutively active or silent loci as well as the loci specifically induced or repressed in each stage and lineage. Nuclease accessible DNA segments in active chromatin states were designated candidate cis-regulatory elements in each cell type, providing one of the most comprehensive registries of candidate hematopoietic regulatory elements to date. Applications of VISION resources are illustrated for regulation of genes encoding GATA1, GATA2, GATA3, and Ikaros. VISION resources are freely available from our website http://usevision.org.

genomics↗

bioRxiv2019

An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis

Thousands of epigenomic datasets have been generated in the past decade, but it is difficult for researchers to effectively utilize all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for ValIdated Systematic IntegratiON of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By employing IDEAS as our Integrative and Discriminative Epigenome Annotation System, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of over 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website (usevision.org) to aid research in genomics and hematopoiesis.

genomics↗

bioRxiv2018

Transcriptional burst initiation and polymerase pause release are key control points of transcriptional regulation

Transcriptional regulation occurs via changes to the rates of various biochemical processes. Sequencing-based approaches that average together many cells have suggested that polymerase binding and polymerase release from promoter-proximal pausing are two key regulated steps in the transcriptional process. However, single cell studies have revealed that transcription occurs in short, discontinuous bursts, suggesting that transcriptional burst initiation and termination might also be regulated steps. Here, we develop and apply a quantitative framework to connect changes in both Pol II ChIP-seq and single cell transcriptional measurements to changes in the rates of specific steps of transcription. Using a number of global and targeted transcriptional regulatory perturbations, we show that burst initiation rate is indeed a key regulated step, demonstrating that transcriptional activity can be frequency modulated. Polymerase pause release is a second key regulated step, but the rate of polymerase binding is not changed by any of the biological perturbations we examined. Our results establish an important role for transcriptional burst regulation in the control of gene expression.

systems biology↗