Linking the dynamics of chromatin occupancy and transcription with predictive models

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.

Bipartite networks represent causality better than simple networks: evidence, algorithms, and applications

A network, whose nodes are genes and whose directed edges represent positive or negative influences of a regulatory gene and its targets, is often used as a representation of causality. To infer a network, researchers often develop a machine learning model and then evaluate the model based on its match with experimentally verified "gold standard" edges. The desired result of such a model is a network that may extend the gold standard edges. Since networks are a form of visual representation, one can compare their utility with architectural or machine blueprints. Blueprints are clearly useful because they provide precise guidance to builders in construction. If the primary role of gene regulatory networks is to characterize causality, then such networks should be good tools of prediction because prediction is the actionable benefit of knowing causality. But are they? In this paper, we compare prediction quality based on "gold standard" regulatory edges from previous experimental work with non-linear models inferred from time series data across four different species. We show that the same non-linear machine learning models have better predictive performance, with improvements from 5.3% to 25.3% in terms of the reduction in the root mean square error (RMSE) compared with the same models based on the gold standard edges. Having established that networks fail to characterize causality properly, we suggest that causality research should focus on four goals: (i) predictive accuracy; (ii) a parsimonious enumeration of predictive regulatory genes for each target gene g; (iii) the identification of disjoint sets of predictive regulatory genes for each target g of roughly equal accuracy; and (iv) the construction of a bipartite network (whose node types are genes and models) representation of causality. We provide algorithms for all goals.

Nucleosome-Omics: A Perspective on the Epigenetic Code and 3D Genome Landscape

Genetic information is loaded on chromatin, which involves DNA sequence arrangement and the epigenetic landscape. The epigenetic information including DNA methylation, nucleosome positioning, histone modification, 3D chromatin conformation, and so on, has a crucial impact on gene transcriptional regulation. Out of them, nucleosomes, as basal chromatin structural units, play an important central role in epigenetic code. With the discovery of nucleosomes, various nucleosome-level technologies have been developed and applied, pushing epigenetics to a new climax. As the underlying methodology, next-generation sequencing technology has emerged and allowed scientists to understand the epigenetic landscape at a genome-wide level. Combining with NGS, nucleosome-omics (or nucleosomics) provides a fresh perspective on the epigenetic code and 3D genome landscape. Here, we summarized and discussed research progress in technology development and application of nucleosome-omics. We foresee the future directions of epigenetic development at the nucleosome level.

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 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.

Disruption of origin chromatin structure by helicase activation in the absence of DNA replication

Prior to initiation of DNA replication, the eukaryotic helicase, Mcm2-7, must be activated to unwind DNA at replication start sites in early S phase. To study helicase activation within origin chromatin, we constructed a conditional mutant of the polymerase α subunit Cdc17 (or Pol1) to prevent priming and block replication. Recovery of these cells at permissive conditions resulted in the generation of unreplicated gaps at origins, likely due to helicase activation prior to replication initiation. We used micrococcal nuclease (MNase)-based chromatin occupancy profiling under restrictive conditions to study chromatin dynamics associated with helicase activation. Helicase activation in the absence of DNA replication resulted in the disruption and disorganization of chromatin, which extends up to 1 kb from early, efficient replication origins. The CMG holohelicase complex also moves the same distance out from the origin, producing single-stranded DNA that activates the intra-S-phase checkpoint. Loss of the checkpoint did not regulate the progression and stalling of the CMG complex but rather resulted in the disruption of chromatin at both early and late origins. Finally, we found that the local sequence context regulates helicase progression in the absence of DNA replication, suggesting that the helicase is intrinsically less processive when uncoupled from replication.

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

Chromatin is a 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 occupancy levels 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. In contrast, epigenomic accessibility data like MNase-seq, DNase-seq, and ATAC-seq provide insight into the chromatin landscape of all factors bound along the genome, but with little insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin accessibility data with nucleotide sequence to jointly compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors. We apply RoboCOP to MNase-seq and ATAC-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome, and show that our model makes better predictions than existing methods. We also compute a chromatin occupancy profile of the yeast genome under cadmium stress, revealing chromatin dynamics associated with transcriptional regulation.

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

We interrogated at nucleotide resolution the spatiotemporal order of chromatin changes that occur immediately following a site-specific double-strand break (DSB) upstream of the PHO5 locus and its subsequent repair by nonhomologous end joining (NHEJ). We observed the immediate eviction of a nucleosome flanking the break and the repositioning of adjacent nucleosomes away from the break. These early chromatin events were independent of the end-processing Mre11-Rad50-Xrs2 (MRX) complex and preceded the MRX-dependent broad eviction of histones and DNA end-resectioning that extends up to ∼8 kb away from the break. We also examined the temporal dynamics of NHEJ-mediated repair in a G1-arrested population. Concomitant with DSB repair by NHEJ, we observed the redeposition and precise repositioning of nucleosomes at their originally occupied positions. This re-establishment of the prelesion chromatin landscape suggests that a DNA replication-independent mechanism exists to preserve epigenome organization following DSB repair.