Causality in transcription and genome folding: Insights from X inactivation.

The spatial organization of genomes is becoming increasingly understood. In mammals, where it is most investigated, this organization ties in with transcription, so an important research objective is to understand whether gene activity is a cause or a consequence of genome folding in space. In this regard, the phenomena of X-chromosome inactivation and reactivation open a unique window of investigation because of the singularities of the inactive X chromosome. Here we focus on the cause-consequence nexus between genome conformation and transcription and explain how recent results about the structural changes associated with inactivation and reactivation of the X chromosome shed light on this problem.

Chromatin and viral integration in immunity: The challenge of silencing non-self genes.

Several viruses hide in the genome of their host. To complete their replication cycle, they need to integrate in the form of a provirus and express their genes. In vertebrates, integrated viruses can be silenced by chromatin, implying that some specific mechanisms exist to detect non-self genes. The known mechanisms depend on sequence features of retroelements, but the fluctuations of virus expression suggest that other determinants also exist. Here we review the mechanisms allowing chromatin to silence integrated viruses and propose that DNA repair may help flag them as 'non-self' shortly after their genomic insertion.

Strand asymmetry influences mismatch resolution during a single-strand annealing.

BACKGROUND: Biases of DNA repair can shape the nucleotide landscape of genomes at evolutionary timescales. The molecular mechanisms of those biases are still poorly understood because it is difficult to isolate the contributions of DNA repair from those of DNA damage. RESULTS: Here, we develop a genome-wide assay whereby the same DNA lesion is repaired in different genomic contexts. We insert thousands of barcoded transposons carrying a reporter of DNA mismatch repair in the genome of mouse embryonic stem cells. Upon inducing a double-strand break between tandem repeats, a mismatch is generated if the break is repaired through single-strand annealing. The resolution of the mismatch showed a 60-80% bias in favor of the strand with the longest 3' flap. The location of the lesion in the genome and the type of mismatch had little influence on the bias. Instead, we observe a complete reversal of the bias when the longest 3' flap is moved to the opposite strand by changing the position of the double-strand break in the reporter. CONCLUSIONS: These results suggest that the processing of the double-strand break has a major influence on the repair of mismatches during a single-strand annealing.

Chromosome compartments on the inactive X guide TAD formation independently of transcription during X-reactivation.

A hallmark of chromosome organization is the partition into transcriptionally active A and repressed B compartments, and into topologically associating domains (TADs). Both structures were regarded to be absent from the inactive mouse X chromosome, but to be re-established with transcriptional reactivation and chromatin opening during X-reactivation. Here, we combine a tailor-made mouse iPSC reprogramming system and high-resolution Hi-C to produce a time course combining gene reactivation, chromatin opening and chromosome topology during X-reactivation. Contrary to previous observations, we observe A/B-like compartments on the inactive X harbouring multiple subcompartments. While partial X-reactivation initiates within a compartment rich in X-inactivation escapees, it then occurs rapidly along the chromosome, concomitant with downregulation of Xist. Importantly, we find that TAD formation precedes transcription and initiates from Xist-poor compartments. Here, we show that TAD formation and transcriptional reactivation are causally independent during X-reactivation while establishing Xist as a common denominator.

Calibrating Seed-Based Heuristics to Map Short Reads With Sesame.

The increasing throughput of DNA sequencing technologies creates a need for faster algorithms. The fate of most reads is to be mapped to a reference sequence, typically a genome. Modern mappers rely on heuristics to gain speed at a reasonable cost for accuracy. In the seeding heuristic, short matches between the reads and the genome are used to narrow the search to a set of candidate locations. Several seeding variants used in modern mappers show good empirical performance but they are difficult to calibrate or to optimize for lack of theoretical results. Here we develop a theory to estimate the probability that the correct location of a read is filtered out during seeding, resulting in mapping errors. We describe the properties of simple exact seeds, skip seeds and MEM seeds (Maximal Exact Match seeds). The main innovation of this work is to use concepts from analytic combinatorics to represent reads as abstract sequences, and to specify their generative function to estimate the probabilities of interest. We provide several algorithms, which together give a workable solution for the problem of calibrating seeding heuristics for short reads. We also provide a C implementation of these algorithms in a library called Sesame. These results can improve current mapping algorithms and lay the foundation of a general strategy to tackle sequence alignment problems. The Sesame library is open source and available for download at https://github.com/gui11aume/sesame.

Spatially clustered loci with multiple enhancers are frequent targets of HIV-1 integration.

HIV-1 recurrently targets active genes and integrates in the proximity of the nuclear pore compartment in CD4+ T cells. However, the genomic features of these genes and the relevance of their transcriptional activity for HIV-1 integration have so far remained unclear. Here we show that recurrently targeted genes are proximal to super-enhancer genomic elements and that they cluster in specific spatial compartments of the T cell nucleus. We further show that these gene clusters acquire their location during the activation of T cells. The clustering of these genes along with their transcriptional activity are the major determinants of HIV-1 integration in T cells. Our results provide evidence of the relevance of the spatial compartmentalization of the genome for HIV-1 integration, thus further strengthening the role of nuclear architecture in viral infection.

Transcription factors and 3D genome conformation in cell-fate decisions.

How cells adopt different identities has long fascinated biologists. Signal transduction in response to environmental cues results in the activation of transcription factors that determine the gene-expression program characteristic of each cell type. Technological advances in the study of 3D chromatin folding are bringing the role of genome conformation in transcriptional regulation to the fore. Characterizing this role of genome architecture has profound implications, not only for differentiation and development but also for diseases including developmental malformations and cancer. Here we review recent studies indicating that the interplay between transcription and genome conformation is a driving force for cell-fate decisions.

An experimental assay of the interactions of amino acids from orthologous sequences shaping a complex fitness landscape.

Characterizing the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here we determined the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. Just 15% of amino acids found in yeast His3 orthologues were always neutral while the impact on fitness of the remaining 85% depended on the genetic background. Furthermore, at 67% of sites, amino acid replacements were under sign epistasis, having both strongly positive and negative effect in different genetic backgrounds. 46% of sites were under reciprocal sign epistasis. The fitness impact of amino acid replacements was influenced by only a few genetic backgrounds but involved interaction of multiple sites, shaping a rugged fitness landscape in which many of the shortest paths between highly fit genotypes are inaccessible.

Using Barcoded HIV Ensembles (B-HIVE) for Single Provirus Transcriptomics.

The latent HIV reservoir is the main barrier to curing AIDS, because infected cells escape the immune system and antiretroviral therapies. Developing new treatment strategies requires technologies to trace latent proviruses. Here, we describe a genome-wide technique called Barcoded HIV Ensembles (B-HIVE) to measure HIV expression at the single provirus level. The principle of B-HIVE is to tag the genome of HIV with DNA barcodes to trace viral transcripts produced by single proviruses in an infected cell population. This in turn reveals which proviruses are active and which are latent or expressed at low level. B-HIVE is a high-throughput method to identify and quantify thousands of individual viral transcripts per round of infection. It can be applied in different conditions, characterizing the response of single proviruses to different treatments. Overall, B-HIVE gives unprecedented insight into the expression of single proviruses in populations of HIV-infected cells. © 2018 by John Wiley & Sons, Inc.

Theoretical principles of transcription factor traffic on folded chromatin.

All organisms regulate transcription of their genes. To understand this process, a complete understanding of how transcription factors find their targets in cellular nuclei is essential. The DNA sequence and other variables are known to influence this binding, but the distribution of transcription factor binding patterns remains mostly unexplained in metazoan genomes. Here, we investigate the role of chromosome conformation in the trajectories of transcription factors. Using molecular dynamics simulations, we uncover the principles of their diffusion on chromatin. Chromosome contacts play a conflicting role: at low density they enhance transcription factor traffic, but at high density they lower it by volume exclusion. Consistently, we observe that in human cells, highly occupied targets, where protein binding is promiscuous, are found at sites engaged in chromosome loops within uncompacted chromatin. In summary, we provide a framework for understanding the search trajectories of transcription factors, highlighting the key contribution of genome conformation.

OneD: increasing reproducibility of Hi-C samples with abnormal karyotypes.

The three-dimensional conformation of genomes is an essential component of their biological activity. The advent of the Hi-C technology enabled an unprecedented progress in our understanding of genome structures. However, Hi-C is subject to systematic biases that can compromise downstream analyses. Several strategies have been proposed to remove those biases, but the issue of abnormal karyotypes received little attention. Many experiments are performed in cancer cell lines, which typically harbor large-scale copy number variations that create visible defects on the raw Hi-C maps. The consequences of these widespread artifacts on the normalized maps are mostly unexplored. We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities. The method, called OneD, increases reproducibility among replicates of Hi-C samples with abnormal karyotype, outperforming previous methods significantly. On normal karyotypes, OneD fared equally well as state-of-the-art methods, making it a safe choice for Hi-C normalization. OneD is fast and scales well in terms of computing resources for resolutions up to 5 kb.

Transcription factors orchestrate dynamic interplay between genome topology and gene regulation during cell reprogramming.

Chromosomal architecture is known to influence gene expression, yet its role in controlling cell fate remains poorly understood. Reprogramming of somatic cells into pluripotent stem cells (PSCs) by the transcription factors (TFs) OCT4, SOX2, KLF4 and MYC offers an opportunity to address this question but is severely limited by the low proportion of responding cells. We have recently developed a highly efficient reprogramming protocol that synchronously converts somatic into pluripotent stem cells. Here, we used this system to integrate time-resolved changes in genome topology with gene expression, TF binding and chromatin-state dynamics. The results showed that TFs drive topological genome reorganization at multiple architectural levels, often before changes in gene expression. Removal of locus-specific topological barriers can explain why pluripotency genes are activated sequentially, instead of simultaneously, during reprogramming. Together, our results implicate genome topology as an instructive force for implementing transcriptional programs and cell fate in mammals.

A New Quinoline BRD4 Inhibitor Targets a Distinct Latent HIV-1 Reservoir for Reactivation from Other "Shock" Drugs.

Upon HIV-1 infection, a reservoir of latently infected resting T cells prevents the eradication of the virus from patients. To achieve complete depletion, the existing virus-suppressing antiretroviral therapy must be combined with drugs that reactivate the dormant viruses. We previously described a novel chemical scaffold compound, MMQO (8-methoxy-6-methylquinolin-4-ol), that is able to reactivate viral transcription in several models of HIV latency, including J-Lat cells, through an unknown mechanism. MMQO potentiates the activity of known latency-reversing agents (LRAs) or "shock" drugs, such as protein kinase C (PKC) agonists or histone deacetylase (HDAC) inhibitors. Here, we demonstrate that MMQO activates HIV-1 independently of the Tat transactivator. Gene expression microarrays in Jurkat cells indicated that MMQO treatment results in robust immunosuppression, diminishes expression of c-Myc, and causes the dysregulation of acetylation-sensitive genes. These hallmarks indicated that MMQO mimics acetylated lysines of core histones and might function as a bromodomain and extraterminal domain protein family inhibitor (BETi). MMQO functionally mimics the effects of JQ1, a well-known BETi. We confirmed that MMQO interacts with the BET family protein BRD4. Utilizing MMQO and JQ1, we demonstrate how the inhibition of BRD4 targets a subset of latently integrated barcoded proviruses distinct from those targeted by HDAC inhibitors or PKC pathway agonists. Thus, the quinoline-based compound MMQO represents a new class of BET bromodomain inhibitors that, due to its minimalistic structure, holds promise for further optimization for increased affinity and specificity for distinct bromodomain family members and could potentially be of use against a variety of diseases, including HIV infection.IMPORTANCE The suggested "shock and kill" therapy aims to eradicate the latent functional proportion of HIV-1 proviruses in a patient. However, to this day, clinical studies investigating the "shocking" element of this strategy have proven it to be considerably more difficult than anticipated. While the proportion of intracellular viral RNA production and general plasma viral load have been shown to increase upon a shock regimen, the global viral reservoir remains unaffected, highlighting both the inefficiency of the treatments used and the gap in our understanding of viral reactivation in vivo Utilizing a new BRD4 inhibitor and barcoded HIV-1 minigenomes, we demonstrate that PKC pathway activators and HDAC and bromodomain inhibitors all target different subsets of proviral integration. Considering the fundamental differences of these compounds and the synergies displayed between them, we propose that the field should concentrate on investigating the development of combinatory shock cocktail therapies for improved reservoir reactivation.

Methylation of DNA Ligase 1 by G9a/GLP Recruits UHRF1 to Replicating DNA and Regulates DNA Methylation.

DNA methylation is an essential epigenetic mark in mammals that has to be re-established after each round of DNA replication. The protein UHRF1 is essential for this process; it has been proposed that the protein targets newly replicated DNA by cooperatively binding hemi-methylated DNA and H3K9me2/3, but this model leaves a number of questions unanswered. Here, we present evidence for a direct recruitment of UHRF1 by the replication machinery via DNA ligase 1 (LIG1). A histone H3K9-like mimic within LIG1 is methylated by G9a and GLP and, compared with H3K9me2/3, more avidly binds UHRF1. Interaction with methylated LIG1 promotes the recruitment of UHRF1 to DNA replication sites and is required for DNA methylation maintenance. These results further elucidate the function of UHRF1, identify a non-histone target of G9a and GLP, and provide an example of a histone mimic that coordinates DNA replication and DNA methylation maintenance.

Automatic analysis and 3D-modelling of Hi-C data using TADbit reveals structural features of the fly chromatin colors.

The sequence of a genome is insufficient to understand all genomic processes carried out in the cell nucleus. To achieve this, the knowledge of its three-dimensional architecture is necessary. Advances in genomic technologies and the development of new analytical methods, such as Chromosome Conformation Capture (3C) and its derivatives, provide unprecedented insights in the spatial organization of genomes. Here we present TADbit, a computational framework to analyze and model the chromatin fiber in three dimensions. Our package takes as input the sequencing reads of 3C-based experiments and performs the following main tasks: (i) pre-process the reads, (ii) map the reads to a reference genome, (iii) filter and normalize the interaction data, (iv) analyze the resulting interaction matrices, (v) build 3D models of selected genomic domains, and (vi) analyze the resulting models to characterize their structural properties. To illustrate the use of TADbit, we automatically modeled 50 genomic domains from the fly genome revealing differential structural features of the previously defined chromatin colors, establishing a link between the conformation of the genome and the local chromatin composition. TADbit provides three-dimensional models built from 3C-based experiments, which are ready for visualization and for characterizing their relation to gene expression and epigenetic states. TADbit is an open-source Python library available for download from https://github.com/3DGenomes/tadbit.

Clustering of Drosophila housekeeping promoters facilitates their expression.

Housekeeping genes of animal genomes cluster in the same chromosomal regions. It has long been suggested that this organization contributes to their steady expression across all the tissues of the organism. Here, we show that the activity of Drosophila housekeeping gene promoters depends on the expression of their neighbors. By measuring the expression of ∼85,000 reporters integrated in Kc167 cells, we identified the best predictors of expression as chromosomal contacts with the promoters and terminators of active genes. Surprisingly, the chromatin composition at the insertion site and the contacts with enhancers were less informative. These results are substantiated by the existence of genomic "paradoxical" domains, rich in euchromatic features and enhancers, but where the reporters are expressed at low level, concomitant with a deficit of interactions with promoters and terminators. This indicates that the proper function of housekeeping genes relies not on contacts with long distance enhancers but on spatial clustering. Overall, our results suggest that spatial proximity between genes increases their expression and that the linear architecture of the Drosophila genome contributes to this effect.

Position effects influence HIV latency reversal.

The main obstacle to curing HIV is the presence of latent proviruses in the bodies of infected patients. The partial success of reactivation therapies suggests that the genomic context of integrated proviruses can interfere with treatment. Here we developed a method called Barcoded HIV ensembles (B-HIVE) to map the chromosomal locations of thousands of individual proviruses while tracking their transcriptional activities in an infected cell population. B-HIVE revealed that, in Jurkat cells, the expression of HIV is strongest close to endogenous enhancers. The insertion site also affects the response to latency-reversing agents, because we found that phytohemagglutinin and vorinostat reactivated proviruses inserted at distinct genomic locations. From these results, we propose that combinations of drugs targeting all areas of the genome will be most effective. Overall, our data suggest that the insertion context of HIV is a critical determinant of the viral response to reactivation therapies.

Zerone: a ChIP-seq discretizer for multiple replicates with built-in quality control.

MOTIVATION: Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard method to investigate chromatin protein composition. As the number of community-available ChIP-seq profiles increases, it becomes more common to use data from different sources, which makes joint analysis challenging. Issues such as lack of reproducibility, heterogeneous quality and conflicts between replicates become evident when comparing datasets, especially when they are produced by different laboratories. RESULTS: Here, we present Zerone, a ChIP-seq discretizer with built-in quality control. Zerone is powered by a Hidden Markov Model with zero-inflated negative multinomial emissions, which allows it to merge several replicates into a single discretized profile. To identify low quality or irreproducible data, we trained a Support Vector Machine and integrated it as part of the discretization process. The result is a classifier reaching 95% accuracy in detecting low quality profiles. We also introduce a graphical representation to compare discretization quality and we show that Zerone achieves outstanding accuracy. Finally, on current hardware, Zerone discretizes a ChIP-seq experiment on mammalian genomes in about 5 min using less than 700 MB of memory. AVAILABILITY AND IMPLEMENTATION: Zerone is available as a command line tool and as an R package. The C source code and R scripts can be downloaded from https://github.com/nanakiksc/zerone The information to reproduce the benchmark and the figures is stored in a public Docker image that can be downloaded from https://hub.docker.com/r/nanakiksc/zerone/ CONTACT: : guillaume.filion@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.