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.

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.

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.

Diverse silent chromatin states modulate genome compartmentalization and loop extrusion barriers

The relationships between chromosomal compartmentalization, chromatin state and function are poorly understood. Here by profiling long-range contact frequencies in HCT116 colon cancer cells, we distinguish three silent chromatin states, comprising two types of heterochromatin and a state enriched for H3K9me2 and H2A.Z that exhibits neutral three-dimensional interaction preferences and which, to our knowledge, has not previously been characterized. We find that heterochromatin marked by H3K9me3, HP1α and HP1β correlates with strong compartmentalization. We demonstrate that disruption of DNA methyltransferase activity greatly remodels genome compartmentalization whereby domains lose H3K9me3-HP1α/β binding and acquire the neutrally interacting state while retaining late replication timing. Furthermore, we show that H3K9me3-HP1α/β heterochromatin is permissive to loop extrusion by cohesin but refractory to CTCF binding. Together, our work reveals a dynamic structural and organizational diversity of the silent portion of the genome and establishes connections between the regulation of chromatin state and chromosome organization, including an interplay between DNA methylation, compartmentalization and loop extrusion.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques

Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification

Effectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.

Making waves: Defining the lead time of wastewater-based epidemiology for COVID-19

Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may shed the virus in stool before developing symptoms, suggesting that measurements of SARS-CoV-2 concentrations in wastewater could be a "leading indicator" of COVID-19 prevalence. Multiple studies have corroborated the leading indicator concept by showing that the correlation between wastewater measurements and COVID-19 case counts is maximized when case counts are lagged. However, the meaning of "leading indicator" will depend on the specific application of wastewater-based epidemiology, and the correlation analysis is not relevant for all applications. In fact, the quantification of a leading indicator will depend on epidemiological, biological, and health systems factors. Thus, there is no single "lead time" for wastewater-based COVID-19 monitoring. To illustrate this complexity, we enumerate three different applications of wastewater-based epidemiology for COVID-19: a qualitative "early warning" system; an independent, quantitative estimate of disease prevalence; and a quantitative alert of bursts of disease incidence. The leading indicator concept has different definitions and utility in each application.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. We collected 24-hour composite wastewater samples from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and measured SARS-CoV-2 RNA concentrations using RT-qPCR. We show that the relationship between wastewater viral titers and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater viral titers and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. We find that the WC ratio increases after key events, providing insight into the balance between disease spread and public health response. We also find that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity. These three metrics could complement a framework for integrating wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Non-parametric Polygenic Risk Prediction via 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 trait's 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 the 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.

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 focus on trans interactions in Drosophila, where homologous chromosomes are paired in somatic cells from embryogenesis through adulthood. We first address long-standing questions regarding the structure of embryonic homolog pairing and, to this end, develop a haplotype-resolved Hi-C approach to minimize homolog misassignment and thus robustly distinguish trans-homolog from cis contacts. This computational approach, which we call Ohm, reveals pairing to be surprisingly structured genome-wide, with trans-homolog domains, compartments, and interaction peaks, many coinciding with analogous cis features. We also find a significant genome-wide correlation between pairing, transcription during zygotic genome activation, and binding of the pioneer factor Zelda. Our findings reveal a complex, highly structured organization underlying homolog pairing, first discovered a century ago in Drosophila. Finally, we demonstrate the versatility of our haplotype-resolved approach by applying it to mammalian embryos.

Two major mechanisms of chromosome organization

The spatial organization of chromosomes has long been connected to their polymeric nature and is believed to be important for their biological functions, including the control of interactions between genomic elements, the maintenance of genetic information, and the compaction and safe transfer of chromosomes to cellular progeny. chromosome conformation capture techniques, particularly Hi-C, have provided a comprehensive picture of spatial chromosome organization and revealed new features and elements of chromosome folding. Furthermore, recent advances in microscopy have made it possible to obtain distance maps for extensive regions of chromosomes (Bintu et al., 2018; Nir et al., 2018 [2^••,3]), providing information complementary to, and in excellent agreement with, Hi-C maps. Not only has the resolution of both techniques advanced significantly, but new perturbation data generated in the last two years have led to the identification of molecular mechanisms behind large-scale genome organization. Two major mechanisms that have been proposed to govern chromosome organization are (i) the active (ATP-dependent) process of loop extrusion by Structural Maintenance of Chromosomes (SMC) complexes, and (ii) the spatial compartmentalization of the genome, which is likely mediated by affinity interactions between heterochromatic regions (Falk et al., 2019 [76^••]) rather than by ATP-dependent processes. Here, we review existing evidence that these two processes operate together to fold chromosomes in interphase and that loop extrusion alone drives mitotic compaction. We discuss possible implications of these mechanisms for chromosome function.

Publisher Correction: Immune genes are primed for robust transcription by proximal long noncoding RNAs located in nuclear compartments

In the version of this article initially published, '+' and '-' labels were missing from the graph keys at the bottom of Fig. 8d. The error has been corrected in the HTML and PDF versions of the article.

Immune genes are primed for robust transcription by proximal long noncoding RNAs located in nuclear compartments

Accumulation of trimethylation of histone H3 at lysine 4 (H3K4me3) on immune-related gene promoters underlies robust transcription during trained immunity. However, the molecular basis for this remains unknown. Here we show three-dimensional chromatin topology enables immune genes to engage in chromosomal contacts with a subset of long noncoding RNAs (lncRNAs) we have defined as immune gene-priming lncRNAs (IPLs). We show that the prototypical IPL, UMLILO, acts in cis to direct the WD repeat-containing protein 5 (WDR5)-mixed lineage leukemia protein 1 (MLL1) complex across the chemokine promoters, facilitating their H3K4me3 epigenetic priming. This mechanism is shared amongst several trained immune genes. Training mediated by β-glucan epigenetically reprograms immune genes by upregulating IPLs in manner dependent on nuclear factor of activated T cells. The murine chemokine topologically associating domain lacks an IPL, and the Cxcl genes are not trained. Strikingly, the insertion of UMLILO into the chemokine topologically associating domain in mouse macrophages resulted in training of Cxcl genes. This provides strong evidence that lncRNA-mediated regulation is central to the establishment of trained immunity.

Chromatin organization by an interplay of loop extrusion and compartmental segregation

Mammalian chromatin is spatially organized at many scales showing two prominent features in interphase: (i) alternating regions (1-10 Mb) of active and inactive chromatin that spatially segregate into different compartments, and (ii) domains (<1 Mb), that is, regions that preferentially interact internally [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 compartmentalization is established according to local chromatin states. Here, we use polymer simulations to examine how loop extrusion and compartmental segregation work collectively and potentially interfere in shaping global chromosome organization. A model with differential attraction between euchromatin and heterochromatin leads to phase separation and reproduces compartmentalization as observed in Hi-C. Loop extrusion, essential for TAD formation, in turn, interferes with compartmentalization. Our integrated model faithfully reproduces Hi-C data from puzzling experimental observations where altering loop extrusion also led to changes in compartmentalization. Specifically, depletion of chromatin-associated cohesin reduced TADs and revealed finer compartments, while increased processivity of cohesin strengthened large 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. Our results suggest that chromatin organization on the megabase scale emerges from competition of nonequilibrium active loop extrusion and epigenetically defined compartment structure.

Diminished PRRX1 Expression Is Associated With Increased Risk of Atrial Fibrillation and Shortening of the Cardiac Action Potential

BACKGROUND

Atrial fibrillation (AF) affects over 33 million individuals worldwide. Genome-wide association studies have identified at least 30 AF loci, but the mechanisms through which individual variants lead to altered disease risk have remained unclear for the majority of these loci. At the 1q24 locus, we hypothesized that the transcription factor PRRX1 could be a strong candidate gene as it is expressed in the pulmonary veins, a source of AF in many individuals. We sought to identify the molecular mechanism, whereby variation at 1q24 may lead to AF susceptibility.

METHODS AND RESULTS

We sequenced a ≈158 kb region encompassing PRRX1 in 962 individuals with and without AF. We identified a broad region of association with AF at the 1q24 locus. Using in silico prediction and functional validation, we identified an enhancer that interacts with the promoter of PRRX1 in cells of cardiac lineage. Within this enhancer, we identified a single-nucleotide polymorphism, rs577676, which alters enhancer activity in a mouse atrial cell line and in embryonic zebrafish and differentially regulates PRRX1 expression in human left atria. We found that suppression of PRRX1 in human embryonic stem cell-derived cardiomyocytes and embryonic zebrafish resulted in shortening of the atrial action potential duration, a hallmark of AF.

CONCLUSIONS

We have identified a functional genetic variant that alters PRRX1 expression, ultimately resulting in electrophysiological alterations in atrial myocytes that may promote AF.

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 structural maintenance of chromosomes complexes.

A mechanism of cohesin-dependent loop extrusion organizes zygotic genome architecture

Fertilization triggers assembly of higher-order chromatin structure from a condensed maternal and a naïve paternal genome to generate a totipotent embryo. Chromatin loops and domains have been detected in mouse zygotes by single-nucleus Hi-C (snHi-C), but not bulk Hi-C. It is therefore unclear when and how embryonic chromatin conformations are assembled. Here, we investigated whether a mechanism of cohesin-dependent loop extrusion generates higher-order chromatin structures within the one-cell embryo. Using snHi-C of mouse knockout embryos, we demonstrate that the zygotic genome folds into loops and domains that critically depend on Scc1-cohesin and that are regulated in size and linear density by Wapl. Remarkably, we discovered distinct effects on maternal and paternal chromatin loop sizes, likely reflecting differences in loop extrusion dynamics and epigenetic reprogramming. Dynamic polymer models of chromosomes reproduce changes in snHi-C, suggesting a mechanism where cohesin locally compacts chromatin 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 onward.

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

Chromosome conformation capture (3C) and fluorescence in situ hybridization (FISH) are two widely used technologies that provide distinct readouts of 3D chromosome organization. While both technologies can assay locus-specific organization, how to integrate views from 3C, or genome-wide Hi-C, and FISH is far from solved. Contact frequency, measured by Hi-C, and spatial distance, measured by FISH, are often assumed to quantify the same phenomena and used interchangeably. Here, however, we demonstrate that contact frequency is distinct from average spatial distance, both in polymer simulations and in experimental data. Performing a systematic analysis of the technologies, we show that this distinction can create a seemingly paradoxical relationship between 3C and FISH, both in minimal polymer models with dynamic looping interactions and in loop-extrusion simulations. Together, our results indicate that cross-validation of Hi-C and FISH should be carefully designed, and that jointly considering contact frequency and spatial distance is crucial for fully understanding chromosome organization.

Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition

Chromatin is reprogrammed after fertilization to produce a totipotent zygote with the potential to generate a new organism. The maternal genome inherited from the oocyte and the paternal genome provided by sperm coexist as separate haploid nuclei in the zygote. How these two epigenetically distinct genomes are spatially organized is poorly understood. Existing chromosome conformation capture-based methods are not applicable to oocytes and zygotes owing to a paucity of material. To study three-dimensional chromatin organization in rare cell types, we developed a single-nucleus Hi-C (high-resolution chromosome conformation capture) protocol that provides greater than tenfold more contacts per cell than the previous method. Here we show that chromatin architecture is uniquely reorganized during the oocyte-to-zygote transition in mice and is distinct in paternal and maternal nuclei within single-cell zygotes. Features of genomic organization including compartments, topologically associating domains (TADs) and loops are present in individual oocytes when averaged over the genome, but the presence of each feature at a locus varies between cells. At the sub-megabase level, we observed stochastic clusters of contacts that can occur across TAD boundaries but average into TADs. Notably, we found that TADs and loops, but not compartments, are present in zygotic maternal chromatin, suggesting that these are generated by different mechanisms. Our results demonstrate that the global chromatin organization of zygote nuclei is fundamentally different from that of other interphase cells. An understanding of this zygotic chromatin 'ground state' could potentially provide insights into reprogramming cells to a state of totipotency.

Formation of Chromosomal Domains by Loop Extrusion

Topologically associating domains (TADs) are fundamental structural and functional building blocks of human interphase chromosomes, yet the mechanisms of TAD formation remain unclear. Here, we propose that loop extrusion underlies TAD formation. In this process, cis-acting loop-extruding factors, likely cohesins, form progressively larger loops but stall at TAD boundaries due to interactions with boundary proteins, including CTCF. Using polymer simulations, we show that this model produces TADs and finer-scale features of Hi-C data. Each TAD emerges from multiple loops dynamically formed through extrusion, contrary to typical illustrations of single static loops. Loop extrusion both explains diverse experimental observations-including the preferential orientation of CTCF motifs, enrichments of architectural proteins at TAD boundaries, and boundary deletion experiments-and makes specific predictions for the depletion of CTCF versus cohesin. Finally, loop extrusion has potentially far-ranging consequences for processes such as enhancer-promoter interactions, orientation-specific chromosomal looping, and compaction of mitotic chromosomes.

Genome-wide transcription start site mapping of Bradyrhizobium japonicum grown free-living or in symbiosis - a rich resource to identify new transcripts, proteins and to study gene regulation

BACKGROUND

Differential RNA-sequencing (dRNA-seq) is indispensable for determination of primary transcriptomes. However, using dRNA-seq data to map transcriptional start sites (TSSs) and promoters genome-wide is a bioinformatics challenge. We performed dRNA-seq of Bradyrhizobium japonicum USDA 110, the nitrogen-fixing symbiont of soybean, and developed algorithms to map TSSs and promoters.

RESULTS

A specialized machine learning procedure for TSS recognition allowed us to map 15,923 TSSs: 14,360 in free-living bacteria, 4329 in symbiosis with soybean and 2766 in both conditions. Further, we provide proteomic evidence for 4090 proteins, among them 107 proteins corresponding to new genes and 178 proteins with N-termini different from the existing annotation (72 and 109 of them with TSS support, respectively). Guided by proteomics evidence, previously identified TSSs and TSSs experimentally validated here, we assign a score threshold to flag 14 % of the mapped TSSs as a class of lower confidence. However, this class of lower confidence contains valid TSSs of low-abundant transcripts. Moreover, we developed a de novo algorithm to identify promoter motifs upstream of mapped TSSs, which is publicly available, and found motifs mainly used in symbiosis (similar to RpoN-dependent promoters) or under both conditions (similar to RpoD-dependent promoters). Mapped TSSs and putative promoters, proteomic evidence and updated gene annotation were combined into an annotation file.

CONCLUSIONS

The genome-wide TSS and promoter maps along with the extended genome annotation of B. japonicum represent a valuable resource for future systems biology studies and for detailed analyses of individual non-coding transcripts and ORFs. Our data will also provide new insights into bacterial gene regulation during the agriculturally important symbiosis between rhizobia and legumes.

Super-resolution imaging reveals distinct chromatin folding for different epigenetic states

Metazoan genomes are spatially organized at multiple scales, from packaging of DNA around individual nucleosomes to segregation of whole chromosomes into distinct territories^1–5. At the intermediate scale of kilobases to megabases, which encompasses the sizes of genes, gene clusters and regulatory domains, the three-dimensional (3D) organization of DNA is implicated in multiple gene regulatory mechanisms^2–4,6–8, but understanding this organization remains a challenge. At this scale, the genome is partitioned into domains of different epigenetic states that are essential for regulating gene expression^9–11. Here, we investigate the 3D organization of chromatin in different epigenetic states using super-resolution imaging. We classified genomic domains in Drosophila cells into transcriptionally active, inactive, or Polycomb-repressed states and observed distinct chromatin organizations for each state. Remarkably, all three types of chromatin domains exhibit power-law scaling between their physical sizes in 3D and their domain lengths, but each type has a distinct scaling exponent. Polycomb-repressed chromatin shows the densest packing and most intriguing folding behaviour in which packing density increases with domain length. Distinct from the self-similar organization displayed by transcriptionally active and inactive chromatin, the Polycomb-repressed domains are characterized by a high degree of chromatin intermixing within the domain. Moreover, compared to inactive domains, Polycomb-repressed domains spatially exclude neighbouring active chromatin to a much stronger degree. Computational modelling and knockdown experiments suggest that reversible chromatin interactions mediated by Polycomb-group proteins plays an important role in these unique packaging properties of the repressed chromatin. Taken together, our super-resolution images reveal distinct chromatin packaging for different epigenetic states at the kilobase-to-megabase scale, a length scale that is directly relevant to genome regulation.

Genome-wide maps of nuclear lamina interactions in single human cells

Mammalian interphase chromosomes interact with the nuclear lamina (NL) through hundreds of large lamina-associated domains (LADs). We report a method to map NL contacts genome-wide in single human cells. Analysis of nearly 400 maps reveals a core architecture consisting of gene-poor LADs that contact the NL with high cell-to-cell consistency, interspersed by LADs with more variable NL interactions. The variable contacts tend to be cell-type specific and are more sensitive to changes in genome ploidy than the consistent contacts. Single-cell maps indicate that NL contacts involve multivalent interactions over hundreds of kilobases. Moreover, we observe extensive intra-chromosomal coordination of NL contacts, even over tens of megabases. Such coordinated loci exhibit preferential interactions as detected by Hi-C. Finally, the consistency of NL contacts is inversely linked to gene activity in single cells and correlates positively with the heterochromatic histone modification H3K9me3. These results highlight fundamental principles of single-cell chromatin organization. VIDEO ABSTRACT.

Chromatin loops as allosteric modulators of enhancer-promoter interactions

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.

In eukaryotes, enhancers directly contact promoters over large genomic distances to regulate gene expression. Characterizing the principles underlying these long-range enhancer-promoter contacts is crucial for a full understanding of gene expression. Recent experimental mapping of chromosomal interactions by the Hi-C method shows an intricate network of local looping interactions surrounding enhancers and promoters. We model a region of chromatin fiber as a long polymer and study how the formation of loops between certain regulatory elements can insulate or facilitate enhancer-promoter interactions. We find 2–5 fold insulation or facilitation, depending on the location of looping elements relative to an enhancer-promoter pair. These effects originate from the polymer nature of chromatin, without requiring additional mechanisms beyond the formation of a chromatin loop. Our findings suggest that loop-mediated gene regulation by elements in the vicinity of an enhancer-promoter pair can be understood as an allosteric effect. This highlights the complex effects that local chromatin organization can have on gene regulation.

Organization of the mitotic chromosome

Mitotic chromosomes are among the most recognizable structures in the cell, yet for over a century their internal organization remains largely unsolved. We applied chromosome conformation capture methods, 5C and Hi-C, across the cell cycle and revealed two distinct three-dimensional folding states of the human genome. We show that the highly compartmentalized and cell type-specific organization described previously for nonsynchronous cells is restricted to interphase. In metaphase, we identified a homogenous folding state that is locus-independent, common to all chromosomes, and consistent among cell types, suggesting a general principle of metaphase chromosome organization. Using polymer simulations, we found that metaphase Hi-C data are inconsistent with classic hierarchical models and are instead best described by a linearly organized longitudinally compressed array of consecutive chromatin loops.

Hi-C: a method to study the three-dimensional architecture of genomes

The three-dimensional folding of chromosomes compartmentalizes the genome and and can bring distant functional elements, such as promoters and enhancers, into close spatial proximity ^2-6. Deciphering the relationship between chromosome organization and genome activity will aid in understanding genomic processes, like transcription and replication. However, little is known about how chromosomes fold. Microscopy is unable to distinguish large numbers of loci simultaneously or at high resolution. To date, the detection of chromosomal interactions using chromosome conformation capture (3C) and its subsequent adaptations required the choice of a set of target loci, making genome-wide studies impossible ^7-10.

We developed Hi-C, an extension of 3C that is capable of identifying long range interactions in an unbiased, genome-wide fashion. In Hi-C, cells are fixed with formaldehyde, causing interacting loci to be bound to one another by means of covalent DNA-protein cross-links. When the DNA is subsequently fragmented with a restriction enzyme, these loci remain linked. A biotinylated residue is incorporated as the 5' overhangs are filled in. Next, blunt-end ligation is performed under dilute conditions that favor ligation events between cross-linked DNA fragments. This results in a genome-wide library of ligation products, corresponding to pairs of fragments that were originally in close proximity to each other in the nucleus. Each ligation product is marked with biotin at the site of the junction. The library is sheared, and the junctions are pulled-down with streptavidin beads. The purified junctions can subsequently be analyzed using a high-throughput sequencer, resulting in a catalog of interacting fragments.

Direct analysis of the resulting contact matrix reveals numerous features of genomic organization, such as the presence of chromosome territories and the preferential association of small gene-rich chromosomes. Correlation analysis can be applied to the contact matrix, demonstrating that the human genome is segregated into two compartments: a less densely packed compartment containing open, accessible, and active chromatin and a more dense compartment containing closed, inaccessible, and inactive chromatin regions. Finally, ensemble analysis of the contact matrix, coupled with theoretical derivations and computational simulations, revealed that at the megabase scale Hi-C reveals features consistent with a fractal globule conformation.

Comprehensive mapping of long-range interactions reveals folding principles of the human genome

We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free, polymer conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes.

Comprehensive mapping of long-range interactions reveals folding principles of the human genome

We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free, polymer conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes.