Targeted Degradation of CTCF Decouples Local Insulation of Chromosome Domains from Genomic Compartmentalization.

The molecular mechanisms underlying folding of mammalian chromosomes remain poorly understood. The transcription factor CTCF is a candidate regulator of chromosomal structure. Using the auxin-inducible degron system in mouse embryonic stem cells, we show that CTCF is absolutely and dose-dependently required for looping between CTCF target sites and insulation of topologically associating domains (TADs). Restoring CTCF reinstates proper architecture on altered chromosomes, indicating a powerful instructive function for CTCF in chromatin folding. CTCF remains essential for TAD organization in non-dividing cells. Surprisingly, active and inactive genome compartments remain properly segregated upon CTCF depletion, revealing that compartmentalization of mammalian chromosomes emerges independently of proper insulation of TADs. Furthermore, our data support that CTCF mediates transcriptional insulator function through enhancer blocking but not as a direct barrier to heterochromatin spreading. Beyond defining the functions of CTCF in chromosome folding, these results provide new fundamental insights into the rules governing mammalian genome organization.

A de novo transcription-dependent TAD boundary underpins critical multiway interactions during antibody class switch recombination.

Interactions between transcription and cohesin-mediated loop extrusion can influence 3D chromatin architecture. However, their relevance in biology is unclear. Here, we report a direct role for such interactions in the mechanism of antibody class switch recombination (CSR) at the murine immunoglobulin heavy chain locus (Igh). Using Tri-C to measure higher-order multiway interactions on single alleles, we find that the juxtaposition (synapsis) of transcriptionally active donor and acceptor Igh switch (S) sequences, an essential step in CSR, occurs via the interaction of loop extrusion complexes with a de novo topologically associating domain (TAD) boundary formed via transcriptional activity across S regions. Surprisingly, synapsis occurs predominantly in proximity to the 3' CTCF-binding element (3'CBE) rather than the Igh super-enhancer, suggesting a two-step mechanism whereby transcription of S regions is not topologically coupled to synapsis, as has been previously proposed. Altogether, these insights advance our understanding of how 3D chromatin architecture regulates CSR.

Condensin: The Little Motor Protein that Could.

Kong et al. (2020) present the low-resolution structure of the ATPÉ£S-bound human condensin I and II complexes and demonstrate that human condensins can extrude DNA loops in a symmetric and asymmetric fashion and compact nucleosome-bound DNA.

Conformation of sister chromatids in the replicated human genome.

The three-dimensional organization of the genome supports regulated gene expression, recombination, DNA repair, and chromosome segregation during mitosis. Chromosome conformation capture (Hi-C)1,2 analysis has revealed a complex genomic landscape of internal chromosomal structures in vertebrate cells3-7, but the identical sequence of sister chromatids has made it difficult to determine how they topologically interact in replicated chromosomes. Here we describe sister-chromatid-sensitive Hi-C (scsHi-C), which is based on labelling of nascent DNA with 4-thio-thymidine and nucleoside conversion chemistry. Genome-wide conformation maps of human chromosomes reveal that sister-chromatid pairs interact most frequently at the boundaries of topologically associating domains (TADs). Continuous loading of a dynamic cohesin pool separates sister-chromatid pairs inside TADs and is required to focus sister-chromatid contacts at TAD boundaries. We identified a subset of TADs that are overall highly paired and are characterized by facultative heterochromatin and insulated topological domains that form separately within individual sister chromatids. The rich pattern of sister-chromatid topologies and our scsHi-C technology will make it possible to investigate how physical interactions between identical DNA molecules contribute to DNA repair, gene expression, chromosome segregation, and potentially other biological processes.

Bioframe: operations on genomic intervals in Pandas dataframes.

MOTIVATION: Genomic 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. RESULTS: Bioframe 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 IMPLEMENTATION: Bioframe 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.

Hematopoietic Stem Cells Are the Major Source of Multilineage Hematopoiesis in Adult Animals.

Hematopoietic stem cells (HSCs) sustain long-term reconstitution of hematopoiesis in transplantation recipients, yet their role in the endogenous steady-state hematopoiesis remains unclear. In particular, recent studies suggested that HSCs provide a relatively minor contribution to immune cell development in adults. We directed transgene expression in a fraction of HSCs that maintained reconstituting activity during serial transplantations. Inducible genetic labeling showed that transgene-expressing HSCs gave rise to other phenotypic HSCs, confirming their top position in the differentiation hierarchy. The labeled HSCs rapidly contributed to committed progenitors of all lineages and to mature myeloid cells and lymphocytes, but not to B-1a cells or tissue macrophages. Importantly, labeled HSCs gave rise to more than two-thirds of all myeloid cells and platelets in adult mice, and this contribution could be accelerated by an induced interferon response. Thus, classically defined HSCs maintain immune cell development in the steady state and during systemic cytokine responses.

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. The core operations provided by pairtools are parsing of.sam alignments into Hi-C pairs, sorting and removal of PCR duplicates. In addition, pairtools provides 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 restriction-based protocols, 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.

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.

Two independent modes of chromatin organization revealed by cohesin removal.

Imaging and chromosome conformation capture studies have revealed several layers of chromosome organization, including segregation into megabase-sized active and inactive compartments, and partitioning into sub-megabase domains (TADs). It remains unclear, however, how these layers of organization form, interact with one another and influence genome function. Here we show that deletion of the cohesin-loading factor Nipbl in mouse liver leads to a marked reorganization of chromosomal folding. TADs and associated Hi-C peaks vanish globally, even in the absence of transcriptional changes. By contrast, compartmental segregation is preserved and even reinforced. Strikingly, the disappearance of TADs unmasks a finer compartment structure that accurately reflects the underlying epigenetic landscape. These observations demonstrate that the three-dimensional organization of the genome results from the interplay of two independent mechanisms: cohesin-independent segregation of the genome into fine-scale compartments, defined by chromatin state; and cohesin-dependent formation of TADs, possibly by loop extrusion, which helps to guide distant enhancers to their target genes.

Micro-C XL: assaying chromosome conformation from the nucleosome to the entire genome.

We present Micro-C XL, an improved method for analysis of chromosome folding at mononucleosome resolution. Using long crosslinkers and isolation of insoluble chromatin, Micro-C XL increases signal-to-noise ratio. Micro-C XL maps of budding and fission yeast genomes capture both short-range chromosome fiber features such as chromosomally interacting domains and higher order features such as centromere clustering. Micro-C XL provides a single assay to interrogate chromosome folding at length scales from the nucleosome to the full genome.

Chromosome Compaction by Active Loop Extrusion.

During cell division, chromosomes are compacted in length by more than a 100-fold. A wide range of experiments demonstrated that in their compacted state, mammalian chromosomes form arrays of closely stacked consecutive ∼100 kb loops. The mechanism underlying the active process of chromosome compaction into a stack of loops is unknown. Here we test the hypothesis that chromosomes are compacted by enzymatic machines that actively extrude chromatin loops. When such loop-extruding factors (LEF) bind to chromosomes, they progressively bridge sites that are further away along the chromosome, thus extruding a loop. We demonstrate that collective action of LEFs leads to formation of a dynamic array of consecutive loops. Simulations and an analytically solved model identify two distinct steady states: a sparse state, where loops are highly dynamic but provide little compaction; and a dense state, where there are more stable loops and dramatic chromosome compaction. We find that human chromosomes operate at the border of the dense steady state. Our analysis also shows how the macroscopic characteristics of the loop array are determined by the microscopic properties of LEFs and their abundance. When the number of LEFs are used that match experimentally based estimates, the model can quantitatively reproduce the average loop length, the degree of compaction, and the general loop-array morphology of compact human chromosomes. Our study demonstrates that efficient chromosome compaction can be achieved solely by an active loop-extrusion process.

Application of Statistical Thermodynamics To Predict the Adsorption Properties of Polypeptides in Reversed-Phase HPLC.

The theory of critical chromatography for biomacromolecules (BioLCCC) describes polypeptide retention in reversed-phase HPLC using the basic principles of statistical thermodynamics. However, whether this theory correctly depicts a variety of empirical observations and laws introduced for peptide chromatography over the last decades remains to be determined. In this study, by comparing theoretical results with experimental data, we demonstrate that the BioLCCC: (1) fits the empirical dependence of the polypeptide retention on the amino acid sequence length with R(2) > 0.99 and allows in silico determination of the linear regression coefficients of the log-length correction in the additive model for arbitrary sequences and lengths and (2) predicts the distribution coefficients of polypeptides with an accuracy from 0.98 to 0.99 R(2). The latter enables direct calculation of the retention factors for given solvent compositions and modeling of the migration dynamics of polypeptides separated under isocratic or gradient conditions. The obtained results demonstrate that the suggested theory correctly relates the main aspects of polypeptide separation in reversed-phase HPLC.

Iterative correction of Hi-C data reveals hallmarks of chromosome organization.

Extracting biologically meaningful information from chromosomal interactions obtained with genome-wide chromosome conformation capture (3C) analyses requires the elimination of systematic biases. We present a computational pipeline that integrates a strategy to map sequencing reads with a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. We validate this ICE (iterative correction and eigenvector decomposition) technique on published data obtained by the high-throughput 3C method Hi-C, and we demonstrate that eigenvector decomposition of the obtained maps provides insights into local chromatin states, global patterns of chromosomal interactions, and the conserved organization of human and mouse chromosomes.

Rules of engagement for condensins and cohesins guide mitotic chromosome formation.

During mitosis, interphase chromatin is rapidly converted into rod-shaped mitotic chromosomes. Using Hi-C, imaging, proteomics and polymer modeling, we determine how the activity and interplay between loop-extruding SMC motors accomplishes this dramatic transition. Our work reveals rules of engagement for SMC complexes that are critical for allowing cells to refold interphase chromatin into mitotic chromosomes. We find that condensin disassembles interphase chromatin loop organization by evicting or displacing extrusive cohesin. In contrast, condensin bypasses cohesive cohesins, thereby maintaining sister chromatid cohesion while separating the sisters. Studies of mitotic chromosomes formed by cohesin, condensin II and condensin I alone or in combination allow us to develop new models of mitotic chromosome conformation. In these models, loops are consecutive and not overlapping, implying that condensins do not freely pass one another but stall upon encountering each other. The dynamics of Hi-C interactions and chromosome morphology reveal that during prophase loops are extruded in vivo at ~1-3 kb/sec by condensins as they form a disordered discontinuous helical scaffold within individual chromatids.

Combination of Edman degradation of peptides with liquid chromatography/mass spectrometry workflow for peptide identification in bottom-up proteomics.

RATIONALE: High-throughput methods of proteomics are essential for identification of proteins in a cell or tissue under certain conditions. Most of these methods require tandem mass spectrometry (MS/MS). A multidimensional approach including predictive chromatography and partial chemical degradation could be a valuable alternative and/or addition to MS/MS. METHODS: In the proposed strategy peptides are identified in a three-dimensional (3D) search space consisting of retention time (RT), mass, and reduced mass after one-step partial Edman degradation. The strategy was evaluated in silico for two databases: baker's yeast and human proteins. Rates of unambiguous identifications were estimated for mass accuracies from 0.001 to 0.05 Da and RT prediction accuracies from 0.1 to 5 min. Rates of Edman reactions were measured for test peptides. RESULTS: A 3D description of proteolytic peptides allowing unambiguous identification without employing MS/MS of up to 95% and 80% of tryptic peptides from the yeast and human proteomes, respectively, was considered. Further extension of the search space to a four-dimensional one by incorporating the second N-terminal amino acid residue as the fourth dimension was also considered and was shown to result in up to 90% of human peptides being identified unambiguously. CONCLUSIONS: The proposed 3D search space can be a useful alternative to MS/MS-based peptide identification approach. Experimental implementations of the proposed method within the on-line liquid chromatography/mass spectrometry (LC/MS) and off-line matrix-assisted laser desorption/ionization (MALDI) workflows are in progress.

Loop extrusion rules: the next generation.

The interphase genome of vertebrates contains roughly 100 000 dynamic loops formed by cohesins. These loops are thought to play important roles in many functions, but their exact contribution in each case remains hotly disputed. The key challenge in studying these loops is the lack of a single experimental technique that could reliably and comprehensively visualize their locations and dynamics. Yet, we can infer them using theoretical models that integrate complementary experimental observations. Modeling proved instrumental in showing that cohesins form loops via extrusion. The loop extrusion model made numerous successful qualitative and quantitative predictions and inspired many experiments. However, it also demonstrated limited accuracy in predicting contact maps. Recent research suggests that the original model did not fully account for the intricate details of the mechanism of loop extrusion and its complex regulation. Here, we review the progress in visualizing extrusion and characterizing the cohesin cofactors. These discoveries can be summarized as 'rules' of cohesin movement along chromosomes and incorporated into the next generation of models. Such improved models will enable more accurate inferences of positions and dynamics of cohesin loops and generate better predictions for designing experiments.

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.

Igh and Igk loci use different folding principles for V gene recombination due to distinct chromosomal architectures of pro-B and pre-B cells.

Extended loop extrusion across the immunoglobulin heavy-chain (Igh) locus facilitates VH-DJH recombination following downregulation of the cohesin-release factor Wapl by Pax5, resulting in global changes in the chromosomal architecture of pro-B cells. Here, we demonstrate that chromatin looping and VK-JK recombination at the Igk locus were insensitive to Wapl upregulation in pre-B cells. Notably, the Wapl protein was expressed at a 2.2-fold higher level in pre-B cells compared with pro-B cells, which resulted in a distinct chromosomal architecture with normal loop sizes in pre-B cells. High-resolution chromosomal contact analysis of the Igk locus identified multiple internal loops, which likely juxtapose VK and JK elements to facilitate VK-JK recombination. The higher Wapl expression in Igµ-transgenic pre-B cells prevented extended loop extrusion at the Igh locus, leading to recombination of only the 6 most 3' proximal VH genes and likely to allelic exclusion of all other VH genes in pre-B cells. These results suggest that pro-B and pre-B cells with their distinct chromosomal architectures use different chromatin folding principles for V gene recombination, thereby enabling allelic exclusion at the Igh locus, when the Igk locus is recombined.

On the utility of predictive chromatography to complement mass spectrometry based intact protein identification.

The amino acid sequence determines the individual protein three-dimensional structure and its functioning in an organism. Therefore, "reading" a protein sequence and determining its changes due to mutations or post-translational modifications is one of the objectives of proteomic experiments. The commonly utilized approach is gradient high-performance liquid chromatography (HPLC) in combination with tandem mass spectrometry. While serving as a way to simplify the protein mixture, the liquid chromatography may be an additional analytical tool providing complementary information about the protein structure. Previous attempts to develop "predictive" HPLC for large biomacromolecules were limited by empirically derived equations based purely on the adsorption mechanisms of the retention and applicable to relatively small polypeptide molecules. A mechanism of the large biomacromolecule retention in reversed-phase gradient HPLC was described recently in thermodynamics terms by the analytical model of liquid chromatography at critical conditions (BioLCCC). In this work, we applied the BioLCCC model to predict retention of the intact proteins as well as their large proteolytic peptides separated under different HPLC conditions. The specific aim of these proof-of-principle studies was to demonstrate the feasibility of using "predictive" HPLC as a complementary tool to support the analysis of identified intact proteins in top-down, middle-down, and/or targeted selected reaction monitoring (SRM)-based proteomic experiments.

Limitation of predictive 2-D liquid chromatography in reducing the database search space in shotgun proteomics: in silico studies.

A two-dimensional (2-D) liquid chromatography (LC) separation of complex peptide mixtures that combines a normal phase utilizing hydrophilic interactions and a reversed phase offers reportedly the highest level of 2-D LC orthogonality by providing an even spread of peptides across multiple LC fractions. Matching experimental peptide retention times to those predicted by empirical models describing chromatographic separation in each LC dimension leads to a significant reduction in a database search space. In this work, we calculated the retention times of tryptic peptides separated in the C18 reversed phase at different separation conditions (pH 2 and pH 10) and in TSK gel Amide-80 normal phase. We show that retention times calculated for different 2-D LC separation schemes utilizing these phases start to correlate once the mass range of peptides under analysis becomes progressively narrow. This effect is explained by high degree of correlation between retention coefficients in the considered phases.