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.

The chromatin landscape at the HIV-1 provirus integration site determines viral expression.

HIV-1 persists lifelong in memory cells of the immune system as latent provirus that rebounds upon treatment interruption. Therefore, the latent reservoir is the main target for an HIV cure. Here, we studied the direct link between integration site and transcription using LEDGINs and Barcoded HIV-ensembles (B-HIVE). LEDGINs are antivirals that inhibit the interaction between HIV-1 integrase and the chromatin-tethering factor LEDGF/p75. They were used as a tool to retarget integration, while the effect on HIV expression was measured with B-HIVE. B-HIVE tracks insert-specific HIV expression by tagging a unique barcode in the HIV genome. We confirmed that LEDGINs retarget integration out of gene-dense and actively transcribed regions. The distance to H3K36me3, the marker recognized by LEDGF/p75, clearly increased. LEDGIN treatment reduced viral RNA expression and increased the proportion of silent provirus. Finally, silent proviruses obtained after LEDGIN treatment were located further away from epigenetic marks associated with active transcription. Interestingly, proximity to enhancers stimulated transcription irrespective of LEDGIN treatment, while the distance to H3K36me3 only changed after treatment with LEDGINs. The fact that proximity to these markers are associated with RNA expression support the direct link between provirus integration site and viral expression.

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.

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.

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.

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.

Starcode: sequence clustering based on all-pairs search.

MOTIVATION: The increasing throughput of sequencing technologies offers new applications and challenges for computational biology. In many of those applications, sequencing errors need to be corrected. This is particularly important when sequencing reads from an unknown reference such as random DNA barcodes. In this case, error correction can be done by performing a pairwise comparison of all the barcodes, which is a computationally complex problem. RESULTS: Here, we address this challenge and describe an exact algorithm to determine which pairs of sequences lie within a given Levenshtein distance. For error correction or redundancy reduction purposes, matched pairs are then merged into clusters of similar sequences. The efficiency of starcode is attributable to the poucet search, a novel implementation of the Needleman-Wunsch algorithm performed on the nodes of a trie. On the task of matching random barcodes, starcode outperforms sequence clustering algorithms in both speed and precision. AVAILABILITY AND IMPLEMENTATION: The C source code is available at http://github.com/gui11aume/starcode.