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Flyamer, I. M.

Publications and source records attributed to Flyamer, I. M..

12 recordsLinked to original sources

Genome-wide absolute quantification of chromatin looping

3D genomics methods such as Hi-C and Micro-C have uncovered chromatin loops across the genome and linked these loops to gene regulation. However, these methods only measure 3D interaction probabilities on a relative scale. Here, we overcome this limitation by using live imaging data to calibrate Micro-C in mouse embryonic stem cells, thus obtaining absolute looping probabilities for 36,804 chromatin loops across the genome. We find that the looped state is generally rare, with a mean probability of 2.3% and a maximum of 26% across the quantified loops. On average, CTCF-CTCF loops are stronger than loops between cis-regulatory elements (3.2% vs. 1.1%). Our findings can be extended to human stem cells and differentiated cells under certain assumptions. Overall, we establish an approach for genome-wide absolute loop quantification and report that loops generally occur with low probabilities, generalizing recent live imaging results to the whole genome.

biophysics↗

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↗

Ultra-long-range interactions between active regulatory elements

Contacts between enhancers and promoters are thought to relate to their ability to activate transcription. Investigating mechanisms that drive such chromatin interactions is therefore important for understanding gene regulation. Here, we have determined contact frequencies between millions of pairs of cis-regulatory elements from chromosome conformation capture datasets and analysed a collection of hundreds of DNA-binding factors for binding at regions of enriched contacts. This analysis revealed enriched contacts at sites bound by many factors associated with active transcription. We show that active regulatory elements, independent of cohesin and polycomb, interact with each other across distances of 10s of megabases in vertebrate and invertebrate genomes and that interactions correlate and change with activity. However, these ultra-long-range interactions are not dependent on RNA polymerase II transcription or several transcription cofactors. We propose that long-range interactions between cis-regulatory elements are driven by three distinct mechanisms - cohesin-mediated loop extrusion, polycomb contacts, and association between active regions.

genomics↗

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↗

Cohesin is required for long-range enhancer action

The mammalian genome is organised into topologically associating domains (TADs) that are formed through the process of cohesin-driven loop extrusion1-3 and whose extent is constrained at TAD boundaries by orientation-dependent CTCF binding4-7. The large regulatory landscapes of developmental genes frequently correspond to TADs, leading to the hypothesis that TADs and/or loop extrusion are important for enhancers to act on their cognate gene8,9. However, it has proven hard to interpret the consequences of experimental disruption of TADs or loop-extrusion on gene regulation3,6,10, in part because of the difficulty in distinguishing direct from indirect effects on enhancer-driven gene expression. By coupling acute protein degradation with synthetic activation by targeted transcription factor recruitment in mouse embryonic stem cells, here we show that cohesin, but not CTCF, is required for activation of a target gene by distant distal regulatory elements. Cohesin is not required for activation directly at the promoter or activation from an enhancer located closer to the gene. Our findings support the hypothesis that chromatin compaction mediated by cohesin-mediated loop extrusion allows for genes to be activated by regulatory elements that are located many hundreds of kilobases away in the linear genome but suggests that cohesin is dispensable for more genomically close enhancers.

genetics↗

MCM complexes are barriers that restrict cohesin-mediated loop extrusion

Eukaryotic genomes are compacted into loops and topologically associating domains (TADs), which contribute to transcription, recombination and genomic stability. Cohesin extrudes DNA into loops that are thought to lengthen until CTCF boundaries are encountered. Little is known about whether loop extrusion is impeded by DNA-bound macromolecular machines. We demonstrate that the replicative helicase MCM is a barrier that restricts loop extrusion in G1 phase. Single-nucleus Hi-C of one-cell embryos revealed that MCM loading reduces CTCF-anchored loops and decreases TAD boundary insulation, suggesting loop extrusion is impeded before reaching CTCF. Single-molecule imaging shows that MCMs are physical barriers that frequently constrain cohesin translocation in vitro. Simulations are consistent with MCMs as abundant, random barriers. We conclude that distinct loop extrusion barriers contribute to shaping 3D genomes. One Sentence SummaryMCM complexes are obstacles that impede the formation of CTCF-anchored loops.

cell biology↗

A Central Role for Canonical PRC1 in Shaping the 3D Nuclear Landscape

Polycomb group (PcG) proteins silence gene expression by chemically and physically modifying chromatin. A subset of PcG target loci are compacted and cluster in the nucleus to form observable bodies; a conformation which is thought to contribute to gene silencing. However, how these interactions influence gross nuclear organisation and their relationship with transcription remains poorly understood. Here we examine the role of Polycomb Repressive Complex 1 (PRC1) in shaping 3D genome organization in mouse embryonic stem cells (mESCs). Using a combination of imaging and Hi-C analyses we show that PRC1-mediated long-range interactions are independent of CTCF and can bridge sites at a megabase scale. Impairment of PRC1 enzymatic activity does not directly disrupt these interactions. We demonstrate that PcG targets coalesce in vivo, and that developmentally induced expression of one of the target loci disrupts this spatial arrangement. Finally, we show that transcriptional activation and the loss of PRC1-mediated interactions are seperable events. These findings provide important insights into the function of PRC1, whilst highlighting the complexity of this regulatory system. HighlightsO_LILoss of RING1B substantially disrupts nuclear architecture. C_LIO_LIPRC1 mediated looping can occur at a Mb scale and is independent of CTCF. C_LIO_LIPolycomb mediated looping is driven by canonical PRC1 complexes. C_LIO_LIMultimeric PRC1-mediated interactions occur in vitro and in vivo. C_LIO_LIDisruption of PRC1-mediated looping is independent of gene activation. C_LI

molecular biology↗

Nuclear organisation and replication timing are coupled through RIF1-PP1 interaction

Three-dimensional genome organisation and replication timing are known to be correlated, however, it remains unknown whether nuclear architecture overall plays an instructive role in the replication-timing program and, if so, how. Here we demonstrate that RIF1 is a molecular hub that co-regulates both processes. Both nuclear organisation and replication timing depend upon the interaction between RIF1 and PP1. However, whereas nuclear architecture requires the full complement of RIF1 and its interaction with PP1, replication timing is not sensitive to RIF1 dosage. RIF1s role in replication timing also extends beyond its interaction with PP1. Availing of this separation-of-function approach, we have therefore identified in RIF1 dual function the molecular bases of the co-dependency of the replication-timing program and nuclear architecture.

genomics↗

Coolpup.py - a versatile tool to perform pile-up analysis of Hi-C data

MotivationHi-C is currently the method of choice to investigate the global 3D organisation of the genome. A major limitation of Hi-C is the sequencing depth required to robustly detect loops in the data. A popular approach used to mitigate this issue, even in single-cell Hi-C data, is genome-wide averaging (piling-up) of peaks, or other features, annotated in high-resolution datasets, to measure their prominence in less deeply sequenced data. However current tools do not provide a computationally efficient and versatile implementation of this approach.\n\nResultsHere we describe coolpup.py - a versatile tool to perform pile-up analysis on Hi-C data. We demonstrate its utility by replicating previously published findings regarding the role of cohesin and CTCF in 3D genome organization, as well as discovering novel details of Polycomb-driven interactions. We also present a novel variation of the pile-up approach that can aid the in statistical analysis of looping interactions. We anticipate that coolpup.py will aid in Hi-C data analysis by allowing easy to use, versatile and efficient generation of pileups.\n\nAvailability and implementationCoolpup.py is cross-platform, open-source and free (MIT licensed) software. Source code is available from https://github.com/Phlya/coolpuppy and it can be installed from the Python Packaging Index.\n\nContactIlya.Flyamer@igmm.ed.ac.uk

bioinformatics↗

DNA methylation directs polycomb-dependent 3D genome re- organisation in naive pluripotency

The DNA hypomethylation that occurs when embryonic stem cells (ESCs) are directed to the ground state of naive pluripotency by culturing in 2i conditions results in redistribution of polycomb (H3K27me3) away from its target loci. Here we demonstrate that 3D genome organisation is also altered in 2i. We found chromatin decompaction at polycomb target loci as well as loss of long-range polycomb interactions. By preventing DNA hypomethylation during the transition to the ground-state, we are able to restore the H3K27me3 distribution, and polycomb-mediated 3D genome organisation that is characteristic of primed ESCs grown in serum, to ESCs in 2i. However, these cells retain the functional characteristics of 2i ground state ESCs. Our findings demonstrate the central role of DNA methylation in shaping major aspects of 3D genome organisation but caution against assuming causal roles for the epigenome and 3D genome in gene regulation and function in ESCs.

cell biology↗

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↗