Biology subjects

Hartemink, A. J.

Publications and source records attributed to Hartemink, A. J..

11 recordsLinked to original sources

bioRxiv2026

Deconvolving the spatiotemporal chromatin landscape through the cell cycle

Profiling genomic processes during the cell cycle is challenging because synchronized populations gradually lose synchrony as individual cells progress through the cycle at different rates and divide asymmetrically. Researchers have addressed this challenge by modeling the loss of synchrony and applying sophisticated branching process deconvolution methods to mitigate the effects of imperfect synchrony. Such methods have been used to deconvolve cell cycle transcription, but despite the central role of the chromatin landscape in orchestrating eukaryotic transcription and replication, comparable approaches to deconvolving cell cycle chromatin occupancy have not been developed, because the data are orders of magnitude larger and because DNA replication introduces non-uniform copy number effects across the genome during S phase. We present CyCLOPS, a computational framework that overcomes these technical challenges, enabling deconvolution of the genome-wide chromatin landscape throughout the cell cycle at high spatiotemporal resolution. We apply CyCLOPS to MNase-seq data collected from synchronized yeast populations at 10-minute intervals to produce the first dynamic atlas of genome-wide chromatin occupancy through the cell cycle, profiled at sub-minute resolution. We identify functional groups of cell cycle genes through chromatin-based clustering and uncover chromatin regulatory dynamics, including at non-genic loci. Our atlas reveals that chromatin occupancy and transcription fluctuate largely independently.

bioinformatics↗

bioRxiv2024

Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation

Epigenetic mechanisms contribute to gene regulation by altering chromatin accessibility through changes in transcription factor (TF) and nucleosome occupancy throughout the genome. Despite numerous studies focusing on changes in gene expression, the intricate chromatin-mediated regulatory code remains largely unexplored on a comprehensive scale. We address this by employing a factor-agnostic, reverse-genetics approach that uses MNase-seq to capture genome-wide TF and nucleosome occupancies in response to the individual deletion of 201 transcriptional regulators in Saccharomyces cerevisiae, thereby assaying nearly one million mutant-gene interactions. We develop a principled approach to identify and quantify chromatin changes genome-wide, observing differences in TF and nucleosome occupancy that recapitulate well-established pathways identified by gene expression data. We also discover distinct chromatin signatures associated with the up- and downregulation of genes, and use these signatures to reveal regulatory mechanisms previously unexplored in expression-based studies. Finally, we demonstrate that chromatin features are predictive of transcriptional activity and leverage these features to reconstruct chromatin-based transcriptional regulatory networks. Overall, these results illustrate the power of an approach combining genetic perturbation with high-resolution epigenomic profiling; the latter enables a close examination of the interplay between TFs and nucleosomes genome-wide, providing a deeper, more mechanistic understanding of the complex relationship between chromatin organization and transcription.

genomics↗

bioRxiv2023

Single-cell multiome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

We present a novel gene-level regulatory model called SCARlink that predicts single-cell gene expression from single-cell chromatin accessibility within and flanking (+/-250kb) the genic loci by training on multiome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on a peak atlas. SCARlink significantly outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across across high-coverage multiome data sets while giving comparable to improved performance on low-coverage data sets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 8x-35x enriched in fine-mapped eQTLs and 22x-35x enriched in fine-mapped GWAS variants across 83 UK Biobank traits. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

bioinformatics↗

bioRxiv2023

Spatiotemporal kinetics of CAF-1-dependent chromatin maturation ensures transcription fidelity during S-phase

Proper maintenance of epigenetic information after replication is dependent on the rapid assembly and maturation of chromatin. Chromatin Assembly Complex 1 (CAF-1) is a conserved histone chaperone that deposits (H3-H4)2 tetramers as part of the replication-dependent chromatin assembly process. Loss of CAF-1 leads to a delay in chromatin maturation, albeit with minimal impact on steady-state chromatin structure. However, the mechanisms by which CAF-1 mediates the deposition of (H3-H4)2 tetramers and the phenotypic consequences of CAF-1-associated assembly defects are not well understood. We used nascent chromatin occupancy profiling to track the spatiotemporal kinetics of chromatin maturation in both wild-type (WT) and CAF-1 mutant yeast cells. Our results show that loss of CAF-1 leads to a heterogeneous rate of nucleosome assembly, with some nucleosomes maturing at near WT kinetics and others exhibiting significantly slower maturation kinetics. The slow-to-mature nucleosomes are enriched in intergenic and poorly transcribed regions, suggesting that transcription-dependent assembly mechanisms can reset the slow-to-mature nucleosomes following replication. Nucleosomes with slow maturation kinetics are also associated with poly(dA:dT) sequences, which implies that CAF-1 deposits histones in a manner that counteracts resistance from the inflexible DNA sequence, promoting the formation of histone octamers as well as ordered nucleosome arrays. In addition, we demonstrate that the delay in chromatin maturation is accompanied by a transient and S-phase specific loss of gene silencing and transcriptional regulation, revealing that the DNA replication program can directly shape the chromatin landscape and modulate gene expression through the process of chromatin maturation.

molecular biology↗

bioRxiv2021

Cell cycle-dependent chromatin dynamics at replication origins

Origins of DNA replication are specified by the ordered recruitment of replication factors in a cell cycle dependent manner. The assembly of the pre-replicative complex in G1 and the pre-initiation complex prior to activation in S-phase are well characterized; however, the interplay between the assembly of these complexes and the local chromatin environment is less well understood. To investigate the dynamic changes in chromatin organization at and surrounding replication origins, we used micrococcal nuclease (MNase) to generate genome-wide chromatin occupancy profiles of nucleosomes, transcription factors and replication proteins through consecutive cell cycles in Saccharomyces cerevisiae. During each G1 phase of two consecutive cell cycles, we observed the downstream repositioning of the origin-proximal +1 nucleosome and an increase in protected DNA fragments spanning the ARS consensus sequence (ACS) indicative of pre-RC assembly. We also found that the strongest correlation between the chromatin occupancy at the ACS and origin efficiency occurred in early S-phase consistent with the rate limiting formation of the Cdc45-Mcm2-7-GINS (CMG) complex being a determinant of origin activity. Finally, we observed nucleosome disruption and disorganization emanating from replication origins and traveling with the elongating replication forks across the genome in S-phase, likely reflecting the disassembly and assembly of chromatin ahead of and behind the replication fork, respectively. These results provide insights into cell cycle-regulated chromatin dynamics and how they relate to the regulation of origin activity.

genomics↗

bioRxiv2020

Quantitative occupancy of myriad transcription factors from one DNase experiment enables efficient comparisons across conditions

Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TOP, a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single DNase-seq experiment. TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of nearly 1500 human TF motifs, and examined how their occupancies changed genome-wide in multiple contexts: across 178 cell types, over 12 hours of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.

bioinformatics↗

bioRxiv2020

Integrating MNase-seq and RNA-seq time series data to study chromatin and transcription dynamics under cadmium stress

Though the sequence of the genome within each eukaryotic cell is essentially fixed, it exists within a complex and changing chromatin state. This state is determined, in part, by the dynamic binding of proteins to the DNA. These proteins--including histones, transcription factors (TFs), and polymerases--interact with one another, the genome, and other molecules to allow the chromatin to adopt one of exceedingly many possible configurations. Understanding how changing chromatin configurations associate with transcription remains a fundamental research problem. We sought to characterize at high spatiotemporal resolution the dynamic interplay between transcription and chromatin in response to cadmium stress. While gene regulatory responses to environmental stress in yeast have been studied, how the chromatin state changes and how those changes connect to gene regulation remain unexplored. By combining MNase-seq and RNA-seq data, we found chromatin signatures of transcriptional activation and repression involving both nucleosomal and TF-sized DNA-binding factors. Using these signatures, we identified associations between chromatin dynamics and transcriptional regulation, not only for known cadmium response genes, but across the entire genome, including antisense transcripts. Those associations allowed us to develop generalizable models that can predict dynamic transcriptional responses on the basis of dynamic chromatin signatures.

genomics↗

bioRxiv2020

RoboCOP: Jointly computing chromatin occupancy profiles for numerous factors from chromatin accessibility data

Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of occupancy of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. On the other hand, epigenomic accessibility data like ATAC-seq, DNase-seq, and MNase-seq provide insight into the chromatin landscape of all factors bound along the genome, but with minimal insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin information from epigenomic accessibility data with nucleotide sequence to compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors at once. We apply RoboCOP to MNase-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome. Using available protein-binding datasets from the literature, we show that our model predicts the binding of these factors genome-wide more accurately than existing methods.

bioinformatics↗

bioRxiv2019

Local nucleosome dynamics and eviction following a double-strand break are reversible by NHEJ-mediated repair in the absence of DNA replication

Although the molecular events required for the repair of double-strand breaks (DSB) have been well characterized, the role of epigenetic processes in the recognition and repair of DSBs has only been investigated at low resolution. We rapidly and synchronously induced a site-specific DSB in Saccharomyces cerevisiae upstream of the PHO5 locus, which has well-positioned nucleosomes. Utilizing MNase-seq epigenome mapping we interrogated the order of chromatin changes that occur immediately following a DSB by generating a base-pair resolution map of the chromatin landscape. In wild type cells, the first nucleosome left of the break was rapidly evicted. The eviction of this flanking nucleosome was dynamic and proceeded through an early intermediate chromatin structure where the nucleosome was repositioned in the adjacent linker DNA. Other nucleosomes bordering both sides of the break were also shifted away from the break; however, their loss was more gradual. These local changes preceded a broader loss of chromatin organization and nucleosome eviction that was marked by increased MNase sensitivity in the regions [~]8 kb on each side of the break. While the broad loss of chromatin organization was dependent on the end-processing complex, Mre11-Rad50-Xrs2 (MRX), the early remodeling and repositioning of the nucleosome adjacent to the break was independent of the MRX and YKU70/80 complexes. We also examined the temporal dynamics of NHEJ-mediated repair in a G1-arrested population, where 5 to 3 end-resection of DSB ends is blocked. Concomitant with DSB repair, we observed the re-deposition and precise re-positioning of nucleosomes at the originally-occupied positions. This re-establishment of the pre-lesion chromatin landscape suggests that a DNA replication-independent mechanism exists in G1 cells to preserve epigenome organization following DSB repair.

genomics↗

bioRxiv2017

Manifold Alignment Reveals Correspondence Between Single Cell Transcriptome and Epigenome Dynamics

Single cell genomic techniques promise to yield key insights into the dynamic interplay between gene expression and epigenetic modification. However, the experimental difficulty of performing multiple measurements on the same cell currently limits efforts to combine multiple genomic data sets into a united picture of single cell variation. We show that it is possible to construct cell trajectories, reflecting the changes that occur in a sequential biological process, from single cell ATAC-seq, bisulfite sequencing, and ChIP-seq data. In addition, we present an approach called MATCHER that computationally circumvents the experimental difficulties inherent in performing multiple genomic measurements on a single cell by inferring correspondence between single cell transcriptomic and epigenetic measurements performed on different cells of the same type. MATCHER works by first learning a separate manifold for the trajectory of each kind of genomic data, then aligning the manifolds to infer a shared trajectory in which cells measured using different techniques are directly comparable. Using scM&T-seq data, we confirm that MATCHER accurately predicts true single cell correlations between DNA methylation and gene expression without using known cell correspondence information. We also used MATCHER to infer correlations among gene expression, chromatin accessibility, and histone modifications in single mouse embryonic stem cells. These results reveal the dynamic interplay between epigenetic changes and gene expression underlying the transition from pluripotency to differentiation priming. Our work is a first step toward a united picture of heterogeneous transcriptomic and epigenetic states in single cells.

bioinformatics↗

bioRxiv2016

Characterization of Dependencies Between Growth and Division in Budding Yeast

Cell growth and division are processes vital to the proliferation and development of life. Coordination between these two processes has been recognized for decades in a variety of organisms. In the budding yeast Saccharomyces cerevisiae, this coordination or size control appears as an inverse correlation between cell size and the rate of cell-cycle progression, routinely observed in G1 prior to cell division commitment. Beyond this point, cells are presumed to complete S/G2/M at similar rates and in a size-independent manner. As such, studies of dependence between growth and division have focused on G1. Moreover, coordination between growth and division has commonly been analyzed within the cycle of a single cell without accounting for correlations in growth and division characteristics between cycles of related cells. In a comprehensive analysis of three published time-lapse microscopy datasets, we analyze both intra-and inter-cycle dependencies between growth and division, revisiting assumptions about the coordination between these two processes. Interestingly, we find evidence (1) that S/G2/M durations are systematically longer in daughters than in mothers, (2) of dependencies between S/G2/M and size at budding that echo the classical G1 dependencies, and, (3) in contrast with recent bacterial studies, of negative dependencies between size at birth and size accumulated during the cell cycle. In addition, we develop a novel hierarchical model to uncover inter-cycle dependencies, and we find evidence for such dependencies in cells growing in sugar-poor environments. Our analysis highlights the need for experimentalists and modelers to account for new sources of cell-to-cell variation in growth and division, and our model provides a formal statistical framework for the continued study of dependencies between biological processes.

bioinformatics↗