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Imakaev, M.

Publications and source records attributed to Imakaev, M..

17 recordsLinked to original sources

Cohesin bridging as a physical principle of enhancer-promoter communication

Central to genome function, enhancers are non-coding sequences that can control transcription from promoters hundreds of kilobases away. Yet the physical basis of this long-range communication remains unclear. A prevalent view is that enhancers activate promoters when the two elements come into spatial proximity through the 3D folding of chromatin. However, activation by spatial proximity alone has struggled to explain several core features of enhancer function. Here, we propose that the molecular motor cohesin transmits long-range enhancer action by forming bridges between enhancers and promoters during loop extrusion. In this view, rare and transient bridges carry regulatory communication, rather than mere spatial proximity. We develop a quantitative model that predicts transcriptional output from cohesin-bridging dynamics and validate it by engineering cells in which strategically positioned CTCF sites rewire loop extrusion trajectories. The model explains how enhancer action scales with genomic distance, and how it can be either facilitated or insulated by CTCF sites across two orders of magnitude-behaviors incompatible with proximity-based models. Finally, our framework reveals that CTCF sites can block enhancers bidirectionally, by either blocking or releasing cohesin loops, resolving longstanding paradoxes between their effects on transcriptional regulation and genome folding. Together, our results establish cohesin bridging as a mode of enhancer-promoter communication that can be modulated by genomic context to achieve selective and tunable transcriptional control over long genomic distances.

molecular biology↗

Pairtools: from sequencing data to chromosome contacts

The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools - a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. Pairtools provides both crucial core tools as well as auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for multi-way contacts, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.

bioinformatics↗

Cooltools: enabling high-resolution Hi-C analysis in Python

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.

bioinformatics↗

Bioframe: Operations on Genomic Intervals in Pandas Dataframes

MotivationGenomic intervals are one of the most prevalent data structures in computational genome biology, and used to represent features ranging from genes, to DNA binding sites, to disease variants. Operations on genomic intervals provide a language for asking questions about relationships between features. While there are excellent interval arithmetic tools for the command line, they are not smoothly integrated into Python, one of the most popular general-purpose computational and visualization environments. ResultsBioframe is a library to enable flexible and performant operations on genomic interval dataframes in Python. Bioframe extends the Python data science stack to use cases for computational genome biology by building directly on top of two of the most commonly-used Python libraries, numpy and pandas. The bioframe API enables flexible name and column orders, and decouples operations from data formats to avoid unnecessary conversions, a common scourge for bioinformaticians. Bioframe achieves these goals while maintaining high performance and a rich set of features. Availability and implementationBioframe is open-source under MIT license, cross-platform, and can be installed from the Python package index. The source code is maintained by Open2C on Github at https://github.com/open2c/bioframe.

bioinformatics↗

A fractal polymer with loops recapitulates key features of chromosome organization

Chromosomes are exceedingly long topologically-constrained polymers compacted in a cell nucleus. We recently suggested that chromosomes are organized into loops by an active process of loop extrusion. Yet loops remain elusive to direct observations in living cells; detection and characterization of myriads of such loops is a major challenge. The lack of a tractable physical model of a polymer folded into loops limits our ability to interpret experimental data and detect loops. Here, we introduce a new physical model - a polymer folded into a sequence of loops, and solve it analytically. Our model and a simple geometrical argument show how loops affect statistics of contacts in a polymer across different scales, explaining universally observed shapes of the contact probability. Moreover, we reveal that folding into loops reduces the density of topological entanglements, a novel phenomenon we refer as "the dilution of entanglements". Supported by simulations this finding suggests that up to [~] 1 - 2Mb chromosomes with loops are not topologically constrained, yet become crumpled at larger scales. Our theoretical framework allows inference of loop characteristics, draws a new picture of chromosome organization, and shows how folding into loops affects topological properties of crumpled polymers.

biophysics↗

The 4D Nucleome Data Portal: a resource for searching and visualizing curated nucleomics data

The 4D Nucleome (4DN) Network aims to elucidate the complex structure and organization of chromosomes in the nucleus and the impact of their disruption in disease biology. We present the 4DN Data Portal (https://data.4dnucleome.org/), a repository for datasets generated in the 4DN network and relevant external datasets. Datasets were generated with a wide range of experiments, including chromosome conformation capture assays such as Hi-C and other innovative sequencing and microscopy-based assays probing chromosome architecture. All together, the 4DN data portal hosts more than 1800 experiment sets and 34000 files. Results of sequencing-based assays from different laboratories are uniformly processed and quality-controlled. The portal interface allows easy browsing, filtering, and bulk downloads, and the integrated HiGlass genome browser allows interactive visualization and comparison of multiple datasets. The 4DN data portal represents a primary resource for chromosome contact and other nuclear architecture data for the scientific community.

genomics↗

Heterochromatin diversity modulates genome compartmentalization and loop extrusion barriers

Two dominant processes organizing chromosomes are loop extrusion and the compartmental segregation of active and inactive chromatin. The molecular players involved in loop extrusion during interphase, cohesin and CTCF, have been extensively studied and experimentally validated. However, neither the molecular determinants nor the functional roles of compartmentalization are well understood. Here, we distinguish three inactive chromatin states using contact frequency profiling, comprising two types of heterochromatin and a previously uncharacterized inactive state exhibiting a neutral interaction preference. We find that heterochromatin marked by long continuous stretches of H3K9me3, HP1 and HP1{beta} correlates with a conserved signature of strong compartmentalization and is abundant in HCT116 colon cancer cells. We demonstrate that disruption of DNA methyltransferase activity dramatically remodels genome compartmentalization as a consequence of the loss of H3K9me3 and HP1 binding. Interestingly, H3K9me3-HP1/{beta} is replaced by the neutral inactive state and retains late replication timing. Furthermore, we show that H3K9me3-HP1/{beta} heterochromatin is permissive to loop extrusion by cohesin but refractory to CTCF, explaining a paucity of visible loop extrusion-associated patterns in Hi-C. Accordingly, CTCF loop extrusion barriers are reactivated upon loss of H3K9me3-HP1/{beta}, not as a result of canonical demethylation of the CTCF binding motif but due to an intrinsic resistance of H3K9me3-HP1/{beta} heterochromatin to CTCF binding. Together, our work reveals a dynamic structural and organizational diversity of the inactive portion of the genome and establishes new connections between the regulation of chromatin state and chromosome organization, including an interplay between DNA methylation, compartmentalization and loop extrusion. HighlightsO_LIThree inactive chromatin states are distinguishable by long-range contact frequencies in HCT116, respectively associated with H3K9me3, H3K27me3 and a H3K9me2 state with neutral contact preferences. C_LIO_LIH3K9me3-HP1/{beta} heterochromatin has a high degree of homotypic affinity and is permissive to loop extrusion but depleted in extrusion barriers. C_LIO_LIDisrupting DNA methylation causes widespread loss of H3K9me3-HP1/{beta} and dramatic remodeling of genome compartmentalization. C_LIO_LIH3K9me3-HP1/{beta} is replaced by the neutral inactive state, which gains CTCF loop extrusion barriers and associated contact frequency patterns. C_LIO_LIDNA methylation suppresses CTCF binding via two distinct mechanisms. C_LI

genomics↗

Limited evidence of tumour mutational burden as a biomarker of response to immunotherapy

Cancer immunotherapy by checkpoint blockade (ICB) is effective for various cancer types, yet its clinical use is encumbered by a high variability of patient response. Several studies have reported that the number of non-synonymous mutations (Tumor Mutational Burden, TMB), can predict patient response to ICB. This belief has become widespread and led to the FDA approval of immunotherapy patient prioritization based on TMB levels. The notion that TMB is predictive of response to immunotherapy is rooted in the neoantigen theory. It stipulates that cancer-specific mutations can form neoantigens recognized by the immune system; the more mutations a tumor has, the more likely the immune response is triggered. Here we revisit the data underlying the reported association of TMB with response, and the neoantigen theory. First we assembled the largest pan-cancer dataset of immunotherapy patients with sequencing and clinical data. Surprisingly, we find little evidence that TMB is predictive of response to ICB. We demonstrate that associations similar to the ones reported previously can be observed in shuffled data, suggesting that previous studies suffered from a lack of correction for multiple hypotheses testing and confounding disease subtypes. Second, we develop a model that expands the neoantigen theory and can be consistent with both immunogenicity of neoantigens and the lack of association between TMB and response. Our analysis shows that the use of TMB in clinical practice is not supported by available data and can deprive patients of treatment to which they are likely to respond.

genomics↗

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↗

The genome-wide, multi-layered architecture of chromosome pairing in early Drosophila embryos

Genome organization involves cis and trans chromosomal interactions, both implicated in gene regulation, development, and disease. Here, we focused on trans interactions in Drosophila, where homologous chromosomes are paired in somatic cells from embryogenesis through adulthood. We first addressed the long-standing question of whether pairing extends genome-wide and, to this end, developed a haplotype-resolved Hi-C approach that uses a new strategy to minimize homolog misassignment and thus robustly distinguish trans-homolog from cis contacts. This approach revealed striking genome-wide pairing in Drosophila embryos. Moreover, we discovered pairing to be surprisingly structured, with trans-homolog domains and interaction peaks, many coinciding with the positions of analogous cis features. We also found a significant correlation between pairing and the chromatin accessibility mediated by the pioneer factor Zelda. Our findings reveal a complex, highly structured organization underlying homolog pairing, first discovered more than a century ago.\n\nOne Sentence SummaryA robust approach for haplotype-resolved Hi-C reveals highly-structured homolog pairing in early stage Drosophila embryos.

genetics↗

Non-parametric polygenic risk prediction using partitioned GWAS summary statistics

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the traits heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for Breast Cancer, Type 2 Diabetes, Inflammatory Bowel Disease and Coronary Heart Disease, all of which have available early intervention or prevention treatments.

bioinformatics↗

Higher-Order Organization Principles of Pre-translational mRNPs

Compared to noncoding RNAs (ncRNAs) such as rRNAs and ribozymes, for which high resolution structures abound, little is known about the tertiary structures of mRNAs. In eukaryotic cells, newly made mRNAs are packaged with proteins in highly compacted mRNPs, but the manner of this mRNA compaction is unknown. Here we developed and implemented RIPPLiT (RNA ImmunoPrecipitation and Proximity Ligation in Tandem), a transcriptome-wide method for probing the 3D conformations of RNAs stably-associated with defined proteins, in this case exon junction complex (EJC) core factors. EJCs multimerize with other mRNP components to form megadalton sized complexes that protect large swaths of newly synthesized mRNAs from endonuclease digestion. Unlike ncRNAs, mRNAs behave more like flexible polymers without strong locus-specific interactions. Polymer analysis of proximity ligation data for hundreds of mRNA species demonstrates that pre-translational mammalian mRNPs fold as linear rod-like structures with no strong propensity for 5 and 3 end interaction.

molecular biology↗

Emerging Evidence of Chromosome Folding by Loop Extrusion

Chromosome organization poses a remarkable physical problem with many biological consequences: how can molecular interactions between proteins at the nanometer scale organize micron-long chromatinized DNA molecules, insulating or facilitating interactions between specific genomic elements? The mechanism of active loop extrusion holds great promise for explaining interphase and mitotic chromosome folding, yet remains difficult to assay directly. We discuss predictions from our polymer models of loop extrusion with barrier elements, and review recent experimental studies that provide strong support for loop extrusion, focusing on perturbations to CTCF and cohesin assayed via Hi-C in interphase. Finally, we discuss a likely molecular mechanism of loop extrusion by SMC complexes.

genomics↗

Heterochromatin drives organization of conventional and inverted nuclei

The mammalian cell nucleus displays a remarkable spatial segregation of active euchromatic from inactive heterochromatic genomic regions. In conventional nuclei, euchromatin is localized in the nuclear interior and heterochromatin at the nuclear periphery. In contrast, rod photoreceptors in nocturnal mammals have inverted nuclei, with a dense heterochromatic core and a thin euchromatic outer shell. This inverted architecture likely converts rod nuclei into microlenses to facilitate nocturnal vision, and may relate to the absence of particular proteins that tether heterochromatin to the lamina. However, both the mechanism of inversion and the role of interactions between different types of chromatin and the lamina in nuclear organization remain unknown. To elucidate this mechanism we performed Hi-C and microscopy on cells with inverted nuclei and their conventional counterparts. Strikingly, despite the inversion evident in microscopy, both types of nuclei display similar Hi-C maps. To resolve this paradox we developed a polymer model of chromosomes and found a universal mechanism that reconciles Hi-C and microscopy for both inverted and conventional nuclei. Based solely on attraction between heterochromatic regions, this mechanism is sufficient to drive phase separation of euchromatin and heterochromatin and faithfully reproduces the 3D organization of inverted nuclei. When interactions between heterochromatin and the lamina are added, the same model recreates the conventional nuclear organization. To further test our models, we eliminated lamina interactions in models of conventional nuclei and found that this triggers a spontaneous process of inversion that qualitatively reproduces the pathway of morphological changes during nuclear inversion in vivo. Together, our experiments and modeling suggest that interactions among heterochromatic regions are central to phase separation of the active and inactive genome in inverted and conventional nuclei, while interactions with the lamina are essential for building the conventional architecture from these segregated phases. Ultimately our data suggest that an inverted organization constitutes the default state of nuclear architecture.

biophysics↗

Chromatin Organization by an Interplay of Loop Extrusion and Compartmental Segregation

Mammalian chromatin is organized on length scales ranging from individual nucleosomes to chromosomal territories. At intermediate scales two dominant features emerge in interphase: (i) alternating regions (<5Mb) of active and inactive chromatin that spatially segregate into different compartments, and (ii) domains (<1Mb), i.e. regions that preferentially interact internally, which are also termed topologically associating domains (TADs) and are central to gene regulation. There is growing evidence that TADs are formed by active extrusion of chromatin loops by cohesin, whereas compartments are established by a phase separation process according to local chromatin states. Here we use polymer simulations to examine how the two processes, loop extrusion and compartmental segregation, work collectively and potentially interfere in shaping global chromosome organization. Our integrated model faithfully reproduces Hi-C data from previously puzzling experimental observations, where targeting of the TAD-forming machinery led to changes in compartmentalization. Specifically, depletion of chromatin-associated cohesin reduced TADs and revealed hidden, finer compartments, while increased processivity of cohesin led to stronger TADs and reduced compartmentalization, and depletion of the TAD boundary protein, CTCF, weakened TADs while leaving compartments unaffected. We reveal that these experimental perturbations are special cases of a general polymer phenomenon of active mixing by loop extrusion. This also predicts that interference with chromatin epigenetic states or nuclear volume would affect compartments but not TADs. Our results suggest that chromatin organization on the megabase scale emerges from competition of non-equilibrium active loop extrusion and epigenetically defined compartment structure.

biophysics↗

A Mechanism of Cohesin-Dependent Loop Extrusion Organizes Zygotic Genome Architecture

Fertilization triggers assembly of higher-order chromatin structure from a naive genome to generate a totipotent embryo. Chromatin loops and domains are detected in mouse zygotes by single-nucleus Hi-C (snHi-C) but not bulk Hi-C. We resolve this discrepancy by investigating whether a mechanism of cohesin-dependent loop extrusion generates zygotic chromatin conformations. Using snHi-C of mouse knockout embryos, we demonstrate that the zygotic genome folds into loops and domains that depend on Scc1-cohesin and are regulated in size by Wapl. Remarkably, we discovered distinct effects on maternal and paternal chromatin loop sizes, likely reflecting loop extrusion dynamics and epigenetic reprogramming. Polymer simulations based on snHi-C are consistent with a model where cohesin locally compacts chromatin and thus restricts inter-chromosomal interactions by active loop extrusion, whose processivity is controlled by Wapl. Our simulations and experimental data provide evidence that cohesin-dependent loop extrusion organizes mammalian genomes over multiple scales from the one-cell embryo onwards.\n\nHighlightsO_LIZygotic genomes are organized into cohesin-dependent chromatin loops and TADs\nC_LIO_LILoop extrusion leads to different loop strengths in maternal and paternal genomes\nC_LIO_LICohesin restricts inter-chromosomal interactions by altering chromosome surface area\nC_LIO_LILoop extrusion organizes chromatin at multiple genomic scales\nC_LI

genomics↗

FISH-ing for captured contacts: towards reconciling FISH and 3C

Deciphering how the one-dimensional information encoded in a genomic sequence is read out in three-dimensions is a pressing contemporary challenge. Chromosome conformation capture (3C) and fluorescence in-situ hybridization (FISH) are two popular technologies that provide important links between genomic sequence and 3D chromosome organization. However, how to integrate views from 3C, or genome-wide Hi-C, and FISH is far from solved. We first discuss what each of these methods measure by reconsidering available matched experimental data for Hi-C and FISH. Using polymer simulations, we then demonstrate that contact frequency is distinct from average spatial distance. We show this distinction can create a seemingly-paradoxical relationship between 3C and FISH. Finally, we consider how the measurement of specific interactions between chromosomal loci might be differentially affected by the two technologies. Together, our results have implications for future attempts to cross-validate and integrate 3C and FISH, as well as for developing models of chromosomes.

genomics↗