Evidence for DNA-mediated nuclear compartmentalization distinct from phase separation.

RNA Polymerase II (Pol II) and transcription factors form concentrated hubs in cells via multivalent protein-protein interactions, often mediated by proteins with intrinsically disordered regions. During Herpes Simplex Virus infection, viral replication compartments (RCs) efficiently enrich host Pol II into membraneless domains, reminiscent of liquid-liquid phase separation. Despite sharing several properties with phase-separated condensates, we show that RCs operate via a distinct mechanism wherein unrestricted nonspecific protein-DNA interactions efficiently outcompete host chromatin, profoundly influencing the way DNA-binding proteins explore RCs. We find that the viral genome remains largely nucleosome-free, and this increase in accessibility allows Pol II and other DNA-binding proteins to repeatedly visit nearby DNA binding sites. This anisotropic behavior creates local accumulations of protein factors despite their unrestricted diffusion across RC boundaries. Our results reveal underappreciated consequences of nonspecific DNA binding in shaping gene activity, and suggest additional roles for chromatin in modulating nuclear function and organization

Detection of t(11;14) using interphase molecular cytogenetics in mantle cell lymphoma and atypical chronic lymphocytic leukemia

The chromosomal translocation t(11;14)(q13;q32) fuses the IGH and CCND1 genes and leads to cyclin D1 overexpression. This genetic abnormality is the hallmark of mantle cell lymphoma (MCL), but is also found in some cases of atypical chronic lymphocytic leukemia (CLL), characterized by a poor outcome. For an unequivocal assessment of this specific chromosomal rearrangement on interphase cells, we developed a set of probes for fluorescence in situ hybridization (FISH). Northern blotting was performed for analysis of the cyclin D1 expression in 18 patients. Thirty-eight patients, with either a typical MCL leukemic phase (17 patients) or atypical CLL with an MCL-type immunophenotype, i.e., CD19+, CD5+, CD23(-/low), CD79b/sIgM(D)++, and FMC7+ (21 patients), were analyzed by dual-color interphase FISH. We selected an IGH-specific BAC probe (covering the JH and first constant regions) and a commercially available CCND1 probe. An IGH-CCND1 fusion was detected in 28 of the 38 patients (17 typical MCL and 11 cases with CLL). Cyclin D1 was not overexpressed in two patients with typical MCL and an IGH- CCND1 fusion. In view of the poor prognosis associated with MCL and t(11;14)- positive CLL, we conclude that this set of probes is a valuable and reliable tool for a rapid diagnosis of these entities

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Une approche probabiliste pour l'assemblage de génomes à partir de données de capture de conformation de chromosomes à haut débit

High throughput DNA sequencing technologies are fuelling an accelerating trend to assemble genomes de novo or to complete unfinished assemblies of previously sequenced genomes. Unfortunately, common DNA sequencing technology is limited to reading stretches of a few hundreds or thousands of base pairs only. Therefore, computational methods are needed to assemble entire genomes from large numbers of short DNA strands. However, standard algorithms that piece together DNA strands with overlapping sequences face important limitations due, for example, to regions of repeated sequences, thus leaving many genome assemblies incomplete (Alkan et al., 2011 [2]).We set out to develop a new methodology for genome assembly that promises to address some of these limitations. The method is based on Hi-C, a recent biochemical technique initially developed to analyse the 3D architecture of genomes (Lieberman-Aiden et al., 2009 [78]). In Hi-C experiments, DNA is crosslinked, cut by restriction enzymes, then diluted and religated. In standard Hi-C studies, a previously assembled genome is used to identify chimeric sequences among the ligation products, and map them to pairs of chromosomal loci, thereby yielding a genome-wide matrix of contact frequencies (Cournac et al., 2012 [27]). Our method essentially reverses this approach: Hi-C data are used to test for the physical continuity of the chromatin fibre as expected from a set of DNA segments (representing either a complete or incomplete chromosomal set). Physical-interactions aberrations in the contact matrix reveal structural incongruity, and lead to the reordering of chromosomal segments with respect to the physical properties and continuity of the fibre. This procedure improves genome assembly and/or identification of structural variants in re-sequenced genomes. Our approach uses a probabilistic (Bayesian) framework that assigns probabilities to different assemblies based on the experimental Hi-C data and on laws describing the physical properties of chromosomes (Wong et al. [146]). We will explain the methodology and the developed algorithms and provide results of applications to simulated and real Hi-C data from mutant and natural structural variants of yeast and fungi (Marie-Nelly et al., in prep). We also have developed algorithm that allow us to identify functional sequences in genomes from genomewide contact matrices. Notably, we annotated the centromeric position of the Naumovozyma castellii, an intriguing RNAi-containing yeast where centromere positions could not be determined with standard techniques (Marie-Nelly et al., submitted)Les technologies de séquençage de l'ADN à haut débit alimentent une tendance croissante à l'assemblage de génomes de novo ou à l'achèvement d'assemblages inachevés de génomes déjà séquencés. Malheureusement, la technologie standard de séquençage de l'ADN est limitée à la lecture de tronçons de quelques centaines ou milliers de paires de bases seulement. Par conséquent, des méthodes informatiques sont nécessaires pour assembler des génomes entiers à partir d'un grand nombre de brins d'ADN courts. Cependant, les algorithmes standard qui assemblent des brins d'ADN dont les séquences se chevauchent se heurtent à d'importantes limitations dues, par exemple, aux régions de séquences répétées, ce qui laisse de nombreux assemblages de génomes incomplets (Alkan et al., 2011 [2]).Nous avons entrepris de développer une nouvelle méthodologie pour l'assemblage de génomes qui promet de répondre à certaines de ces limitations. La méthode est basée sur Hi-C, une technique biochimique récente initialement développée pour analyser l'architecture 3D des génomes (Lieberman-Aiden et al., 2009 [78]). Dans les expériences Hi-C, l'ADN est réticulé, coupé par des enzymes de restriction, puis dilué et religé. Dans les études Hi-C standard, un génome préalablement assemblé est utilisé pour identifier les séquences chimériques parmi les produits de ligature, et les cartographier à des paires de loci chromosomiques, produisant ainsi une matrice de fréquences de contact à l'échelle du génome (Cournac et al., 2012 [27]). Notre méthode inverse essentiellement cette approche : Les données Hi-C sont utilisées pour tester la continuité physique de la fibre chromatinienne telle qu'attendue à partir d'un ensemble de segments d'ADN (représentant un ensemble chromosomique complet ou incomplet). Les aberrations des interactions physiques dans la matrice de contact révèlent une incongruité structurelle, et conduisent à la réorganisation des segments chromosomiques par rapport aux propriétés physiques et à la continuité de la fibre. Cette procédure améliore l'assemblage des génomes et/ou l'identification des variants structurels dans les génomes reséquencés. Notre approche utilise un cadre probabiliste (bayésien) qui attribue des probabilités aux différents assemblages en se basant sur les données expérimentales Hi-C et sur des lois décrivant les propriétés physiques des chromosomes (Wong et al. [146]). Nous expliquerons la méthodologie et les algorithmes développés et fournirons des résultats d'applications à des données Hi-C simulées et réelles provenant de mutants et de variantes structurelles naturelles de levures et de champignons (Marie-Nelly et al., en préparation). Nous avons également développé un algorithme qui nous permet d'identifier des séquences fonctionnelles dans les génomes à partir de matrices de contact à l'échelle du génome. Notamment, nous avons annoté la position centromérique de la Naumovozyma castellii, une levure intrigante contenant de l'ARNi où la position des centromères n'a pas pu être déterminée avec les techniques standard (Marie-Nelly et al., soumis)

Une approche probabiliste pour l'assemblage de génomes à partir de données de capture de conformation de chromosomes à haut débit

High throughput DNA sequencing technologies are fuelling an accelerating trend to assemble genomes de novo or to complete unfinished assemblies of previously sequenced genomes. Unfortunately, common DNA sequencing technology is limited to reading stretches of a few hundreds or thousands of base pairs only. Therefore, computational methods are needed to assemble entire genomes from large numbers of short DNA strands. However, standard algorithms that piece together DNA strands with overlapping sequences face important limitations due, for example, to regions of repeated sequences, thus leaving many genome assemblies incomplete (Alkan et al., 2011 [2]).We set out to develop a new methodology for genome assembly that promises to address some of these limitations. The method is based on Hi-C, a recent biochemical technique initially developed to analyse the 3D architecture of genomes (Lieberman-Aiden et al., 2009 [78]). In Hi-C experiments, DNA is crosslinked, cut by restriction enzymes, then diluted and religated. In standard Hi-C studies, a previously assembled genome is used to identify chimeric sequences among the ligation products, and map them to pairs of chromosomal loci, thereby yielding a genome-wide matrix of contact frequencies (Cournac et al., 2012 [27]). Our method essentially reverses this approach: Hi-C data are used to test for the physical continuity of the chromatin fibre as expected from a set of DNA segments (representing either a complete or incomplete chromosomal set). Physical-interactions aberrations in the contact matrix reveal structural incongruity, and lead to the reordering of chromosomal segments with respect to the physical properties and continuity of the fibre. This procedure improves genome assembly and/or identification of structural variants in re-sequenced genomes. Our approach uses a probabilistic (Bayesian) framework that assigns probabilities to different assemblies based on the experimental Hi-C data and on laws describing the physical properties of chromosomes (Wong et al. [146]). We will explain the methodology and the developed algorithms and provide results of applications to simulated and real Hi-C data from mutant and natural structural variants of yeast and fungi (Marie-Nelly et al., in prep). We also have developed algorithm that allow us to identify functional sequences in genomes from genomewide contact matrices. Notably, we annotated the centromeric position of the Naumovozyma castellii, an intriguing RNAi-containing yeast where centromere positions could not be determined with standard techniques (Marie-Nelly et al., submitted)Les technologies de séquençage de l'ADN à haut débit alimentent une tendance croissante à l'assemblage de génomes de novo ou à l'achèvement d'assemblages inachevés de génomes déjà séquencés. Malheureusement, la technologie standard de séquençage de l'ADN est limitée à la lecture de tronçons de quelques centaines ou milliers de paires de bases seulement. Par conséquent, des méthodes informatiques sont nécessaires pour assembler des génomes entiers à partir d'un grand nombre de brins d'ADN courts. Cependant, les algorithmes standard qui assemblent des brins d'ADN dont les séquences se chevauchent se heurtent à d'importantes limitations dues, par exemple, aux régions de séquences répétées, ce qui laisse de nombreux assemblages de génomes incomplets (Alkan et al., 2011 [2]).Nous avons entrepris de développer une nouvelle méthodologie pour l'assemblage de génomes qui promet de répondre à certaines de ces limitations. La méthode est basée sur Hi-C, une technique biochimique récente initialement développée pour analyser l'architecture 3D des génomes (Lieberman-Aiden et al., 2009 [78]). Dans les expériences Hi-C, l'ADN est réticulé, coupé par des enzymes de restriction, puis dilué et religé. Dans les études Hi-C standard, un génome préalablement assemblé est utilisé pour identifier les séquences chimériques parmi les produits de ligature, et les cartographier à des paires de loci chromosomiques, produisant ainsi une matrice de fréquences de contact à l'échelle du génome (Cournac et al., 2012 [27]). Notre méthode inverse essentiellement cette approche : Les données Hi-C sont utilisées pour tester la continuité physique de la fibre chromatinienne telle qu'attendue à partir d'un ensemble de segments d'ADN (représentant un ensemble chromosomique complet ou incomplet). Les aberrations des interactions physiques dans la matrice de contact révèlent une incongruité structurelle, et conduisent à la réorganisation des segments chromosomiques par rapport aux propriétés physiques et à la continuité de la fibre. Cette procédure améliore l'assemblage des génomes et/ou l'identification des variants structurels dans les génomes reséquencés. Notre approche utilise un cadre probabiliste (bayésien) qui attribue des probabilités aux différents assemblages en se basant sur les données expérimentales Hi-C et sur des lois décrivant les propriétés physiques des chromosomes (Wong et al. [146]). Nous expliquerons la méthodologie et les algorithmes développés et fournirons des résultats d'applications à des données Hi-C simulées et réelles provenant de mutants et de variantes structurelles naturelles de levures et de champignons (Marie-Nelly et al., en préparation). Nous avons également développé un algorithme qui nous permet d'identifier des séquences fonctionnelles dans les génomes à partir de matrices de contact à l'échelle du génome. Notamment, nous avons annoté la position centromérique de la Naumovozyma castellii, une levure intrigante contenant de l'ARNi où la position des centromères n'a pas pu être déterminée avec les techniques standard (Marie-Nelly et al., soumis)

Contact genomics: scaffolding and phasing (meta)genomes using chromosome 3D physical signatures.

International audienceHigh-throughput DNA sequencing technologies are fuelling an accelerating trend to assemble de novo or resequence the genomes of numerous species as well as to complete unfinished assemblies. While current DNA sequencing technologies remain limited to reading stretches of a few hundreds or thousands of base pairs, experimental and computational methods are continuously improving with the goal of assembling entire genomes from large numbers of short DNA sequences. However, the algorithms that piece together DNA strands face important limitations due, notably, to the presence of repeated sequences or of multiple haplotypes within one genome, thus leaving many assemblies incomplete. Recently, the realization that the physical contacts experienced by a portion of a DNA molecule could be used as a robust and quantitative assay to determine its genomic position has led to the emerging field of contact genomics, which promises to revolutionize current genome assembly approaches by exploiting the flexible polymer properties of chromosomes. Here we review the current applications of contact genomics to genome scaffolding, haplotyping and metagenomic assembly, then outline the future developments we envision

Normalization of a chromosomal contact map

International audienceBackgroundChromatin organization has been increasingly studied in relation with its important influence on DNA-related metabolic processes such as replication or regulation of gene expression. Since its original design ten years ago, capture of chromosome conformation (3C) has become an essential tool to investigate the overall conformation of chromosomes. It relies on the capture of long-range trans and cis interactions of chromosomal segments whose relative proportions in the final bank reflect their frequencies of interactions, hence their spatial proximity in a population of cells. The recent coupling of 3C with deep sequencing approaches now allows the generation of high resolution genome-wide chromosomal contact maps. Different protocols have been used to generate such maps in various organisms. This includes mammals, drosophila and yeast. The massive amount of raw data generated by the genomic 3C has to be carefully processed to alleviate the various biases and byproducts generated by the experiments. Our study aims at proposing a simple normalization procedure to minimize the influence of these unwanted but inevitable events on the final results.ResultsCareful analysis of the raw data generated previously for budding yeast S. cerevisiae led to the identification of three main biases affecting the final datasets, including a previously unknown bias resulting from the circularization of DNA molecules. We then developed a simple normalization procedure to process the data and allow the generation of a normalized, highly contrasted, chromosomal contact map for S. cerevisiae. The same method was then extended to the first human genome contact map. Using the normalized data, we revisited the preferential interactions originally described between subsets of discrete chromosomal features. Notably, the detection of preferential interactions between tRNA in yeast and CTCF, PolII binding sites in human can vary with the normalization procedure used.ConclusionsWe quantitatively reanalyzed the genomic 3C data obtained for S. cerevisiae, identified some of the biases inherent to the technique and proposed a simple normalization procedure to analyse them. Such an approach can be easily generalized for genomic 3C experiments in other organisms. More experiments and analysis will be necessary to reach optimal resolution and accuracies of the maps generated through these approaches. Working with cell population presenting highest levels of homogeneity will prove useful in this regards

A predictive computational model of the dynamic 3D interphase yeast nucleus.

International audienceBackgroundDespite the absence of internal membranes, the nucleus of eukaryotic cells is spatially organized, with chromosomes and individual loci occupying dynamic, but nonrandom, spatial positions relative to nuclear landmarks and to each other. These positional preferences correlate with gene expression and DNA repair, recombination, and replication. Yet the principles that govern nuclear organization remain poorly understood and detailed predictive models are lacking.ResultsWe present a computational model of dynamic chromosome configurations in the interphase yeast nucleus that is based on first principles and is able to statistically predict the positioning of any locus in nuclear space. Despite its simplicity, the model agrees with extensive previous and new measurements on locus positioning and with genome-wide DNA contact frequencies. Notably, our model recapitulates the position and morphology of the nucleolus, the observed variations in locus positions, and variations in contact frequencies within and across chromosomes, as well as subchromosomal contact features. The model is also able to correctly predict nuclear reorganization accompanying a reduction in ribosomal DNA transcription, and sites of chromosomal rearrangements tend to occur where the model predicted high contact frequencies.ConclusionsOur results suggest that large-scale yeast nuclear architecture can be largely understood as a consequence of generic properties of crowded polymers rather than of specific DNA-binding factors and that configurations of chromosomes and DNA contacts are dictated mainly by genomic location and chromosome lengths. Our model provides a quantitative framework to understand and predict large-scale spatial genome organization and its interplay with functional processes

Filling annotation gaps in yeast genomes using genome-wide contact maps.

International audienceMOTIVATIONS:De novo sequencing of genomes is followed by annotation analyses aiming at identifying functional genomic features such as genes, non-coding RNAs or regulatory sequences, taking advantage of diverse datasets. These steps sometimes fail at detecting non-coding functional sequences: for example, origins of replication, centromeres and rDNA positions have proven difficult to annotate with high confidence. Here, we demonstrate an unconventional application of Chromosome Conformation Capture (3C) technique, which typically aims at deciphering the average 3D organization of genomes, by showing how functional information about the sequence can be extracted solely from the chromosome contact map.RESULTS:Specifically, we describe a combined experimental and bioinformatic procedure that determines the genomic positions of centromeres and ribosomal DNA clusters in yeasts, including species where classical computational approaches fail. For instance, we determined the centromere positions in Naumovozyma castellii, where these coordinates could not be obtained previously. Although computed centromere positions were characterized by conserved synteny with neighboring species, no consensus sequences could be found, suggesting that centromeric binding proteins or mechanisms have significantly diverged. We also used our approach to refine centromere positions in Kuraishia capsulata and to identify rDNA positions in Debaryomyces hansenii. Our study demonstrates how 3C data can be used to complete the functional annotation of eukaryotic genomes.AVAILABILITY AND IMPLEMENTATION:The source code is provided in the Supplementary Material. This includes a zipped file with the Python code and a contact matrix of Saccharomyces cerevisiae.CONTACT:[email protected] INFORMATION:Supplementary data are available at Bioinformatics online