scholarly journals DiffTAD: Detecting Differential contact frequency in Topologically Associating Domains Hi-C experiments between conditions

2016 ◽  
Author(s):  
Rafal Zaborowski ◽  
Bartek Wilczynski

AbstractMotivationIn recent years, the interest in analyzing chromosome conformation by Hi-C and related techniques has grown. It has been shown that contact frequency matrices obtained by these methods correlate with other methods of measurement of activity such as transcriptomics and histone modification assays. This brings a question of testing for differential contact frequency between experiments to the field.ResultsIn this work, we provide a freely available software that implements two statistical methods for testing the significance of differential contact frequency in topological domains between two experiments. One method follows an empirical, permutation based approach to computing p-values, while the other is a parametric test based on the Poisson-Binomial distribution.AvailabilityThe software is freely available on the GNU General Public License at https://bitbucket.org/rzaborowski/differential-analysisContact[r.zaborowski|bartek]@mimuw.edu.plSupplementary informationSupplementary data are available at Bioinformatics online.


Author(s):  
Peter Ebert ◽  
Marcel H Schulz

Abstract Motivation The generation of genome-wide maps of histone modifications using chromatin immunoprecipitation sequencing (ChIP-seq) is a standard approach to dissect the complexity of the epigenome. Interpretation and differential analysis of histone datasets remains challenging due to regulatory meaningful co-occurrences of histone marks and their difference in genomic spread. To ease interpretation, chromatin state segmentation maps are a commonly employed abstraction combining individual histone marks. We developed the tool SCIDDO as a fast, flexible, and statistically sound method for the differential analysis of chromatin state segmentation maps. Results We demonstrate the utility of SCIDDO in a comparative analysis that identifies differential chromatin domains (DCD) in various regulatory contexts and with only moderate computational resources. We show that the identified DCDs correlate well with observed changes in gene expression and can recover a substantial number of differentially expressed genes. We showcase SCIDDO’s ability to directly interrogate chromatin dynamics such as enhancer switches in downstream analysis, which simplifies exploring specific questions about regulatory changes in chromatin. By comparing SCIDDO to competing methods, we provide evidence that SCIDDO’s performance in identifying differentially expressed genes (DEG) via differential chromatin marking is more stable across a range of cell-type comparisons and parameter cut-offs. Availability The SCIDDO source code is openly available under github.com/ptrebert/sciddo Supplementary information Supplementary data are available at Bioinformatics online.



Genome ◽  
2013 ◽  
Vol 56 (7) ◽  
pp. 415-423 ◽  
Author(s):  
Jingjing Zhao ◽  
Hongbo Shi ◽  
Nadav Ahituv

Tissue-specific gene expression is thought to be one of the major forces shaping mammalian gene order. A recent study that used whole-genome chromosome conformation assays has shown that the mammalian genome is divided into specific topological domains that are shared between different tissues and organisms. Here, we wanted to assess whether gene expression and regulation are involved in shaping these domains and can be used to classify them. We analyzed gene expression and regulation levels in these domains by using RNA-seq and enhancer-associated ChIP-seq datasets for 17 different mouse tissues. We found 162 domains that are active (high gene expression and regulation) in all 17 tissues. These domains are significantly shorter, contain less repeats, and have more housekeeping genes. In contrast, we found 29 domains that are inactive (low gene expression and regulation) in all analyzed tissues and are significantly longer, have more repeats, and gene deserts. Tissue-specific active domains showed some correlation with tissue-type and gene ontology. Domain temporal gene regulation and expression differences also displayed some gene ontology terms fitting their temporal function. Combined, our results provide a catalog of shared and tissue-specific topological domains and suggest that gene expression and regulation could have a role in shaping them.



2020 ◽  
Vol 36 (8) ◽  
pp. 2620-2622 ◽  
Author(s):  
Irina Balaur ◽  
Ludovic Roy ◽  
Alexander Mazein ◽  
S Gökberk Karaca ◽  
Ugur Dogrusoz ◽  
...  

Abstract Motivation CellDesigner is a well-established biological map editor used in many large-scale scientific efforts. However, the interoperability between the Systems Biology Graphical Notation (SBGN) Markup Language (SBGN-ML) and the CellDesigner’s proprietary Systems Biology Markup Language (SBML) extension formats remains a challenge due to the proprietary extensions used in CellDesigner files. Results We introduce a library named cd2sbgnml and an associated web service for bidirectional conversion between CellDesigner’s proprietary SBML extension and SBGN-ML formats. We discuss the functionality of the cd2sbgnml converter, which was successfully used for the translation of comprehensive large-scale diagrams such as the RECON Human Metabolic network and the complete Atlas of Cancer Signalling Network, from the CellDesigner file format into SBGN-ML. Availability and implementation The cd2sbgnml conversion library and the web service were developed in Java, and distributed under the GNU Lesser General Public License v3.0. The sources along with a set of examples are available on GitHub (https://github.com/sbgn/cd2sbgnml and https://github.com/sbgn/cd2sbgnml-webservice, respectively). Supplementary information Supplementary data are available at Bioinformatics online.



2020 ◽  
Vol 36 (12) ◽  
pp. 3645-3651
Author(s):  
Lyam Baudry ◽  
Gaël A Millot ◽  
Agnes Thierry ◽  
Romain Koszul ◽  
Vittore F Scolari

Abstract Motivation Hi-C contact maps reflect the relative contact frequencies between pairs of genomic loci, quantified through deep sequencing. Differential analyses of these maps enable downstream biological interpretations. However, the multi-fractal nature of the chromatin polymer inside the cellular envelope results in contact frequency values spanning several orders of magnitude: contacts between loci pairs separated by large genomic distances are much sparser than closer pairs. The same is true for poorly covered regions, such as repeated sequences. Both distant and poorly covered regions translate into low signal-to-noise ratios. There is no clear consensus to address this limitation. Results We present Serpentine, a fast, flexible procedure operating on raw data, which considers the contacts in each region of a contact map. Binning is performed only when necessary on noisy regions, preserving informative ones. This results in high-quality, low-noise contact maps that can be conveniently visualized for rigorous comparative analyses. Availability and implementation Serpentine is available on the PyPI repository and https://github.com/koszullab/serpentine; documentation and tutorials are provided at https://serpentine.readthedocs.io/en/latest/. Supplementary information Supplementary data are available at Bioinformatics online.



2019 ◽  
Vol 36 (7) ◽  
pp. 2280-2281 ◽  
Author(s):  
Sarah Lutteropp ◽  
Alexey M Kozlov ◽  
Alexandros Stamatakis

Abstract Motivation Recently, Lemoine et al. suggested the transfer bootstrap expectation (TBE) branch support metric as an alternative to classical phylogenetic bootstrap support for taxon-rich datasets. However, the original TBE implementation in the booster tool is compute- and memory-intensive. Results We developed a fast and memory-efficient TBE implementation. We improve upon the original algorithm by Lemoine et al. via several algorithmic and technical optimizations. On empirical as well as on random tree sets with varying taxon counts, our implementation is up to 480 times faster than booster. Furthermore, it only requires memory that is linear in the number of taxa, which leads to 10× to 40× memory savings compared with booster. Availability and implementation Our implementation has been partially integrated into pll-modules and RAxML-NG and is available under the GNU Affero General Public License v3.0 at https://github.com/ddarriba/pll-modules and https://github.com/amkozlov/raxml-ng. The parallel version that also computes additional TBE-related statistics is available at: https://github.com/lutteropp/raxml-ng/tree/tbe. Supplementary information Supplementary data are available at Bioinformatics online.



2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingjiao Li ◽  
Harianto Tjong ◽  
Xiao Li ◽  
Ke Gong ◽  
Xianghong Jasmine Zhou ◽  
...  

Abstract Background Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome’s organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Results Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. Conclusions Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.



2019 ◽  
Author(s):  
Rafał Zaborowski ◽  
Bartek Wilczyński

AbstractHigh throughput Chromosome Conformation Capture experiments have become the standard technique to assess the structure and dynamics of chromosomes in living cells. As any other sufficiently advanced biochemical technique, Hi-C datasets are complex and contain multiple documented biases, with the main ones being the non-uniform read coverage and the decay of contact coverage with genomic distance. Both of these effects have been studied and there are published methods that are able to normalize different Hi-C data to mitigate these biases to some extent. It is crucial that this is done properly, or otherwise the results of any comparative analysis of two or more Hi-C experiments are bound to be biased. In this paper we study both mentioned biases present in the Hi-C data and show that normalization techniques aimed at alleviating the coverage bias are at the same time exacerbating the problems with contact decay bias. We also postulate that it is possible to use generalized linear models to directly compare non-normalized data an that it is giving better results in identification of differential contacts between Hi-C matrices than using the normalized data.



2019 ◽  
Author(s):  
JDP Rhodes ◽  
A Feldmann ◽  
B Hernández-Rodríguez ◽  
N Díaz ◽  
JM Brown ◽  
...  

AbstractHow chromosome organisation is related to genome function remains poorly understood. Cohesin, loop-extrusion, and CTCF have been proposed to create structures called topologically associating domains (TADs) to regulate gene expression. Here, we examine chromosome conformation in embryonic stem cells lacking cohesin and find as in other cell types that cohesin is required to create TADs and regulate A/B compartmentalisation. However, in the absence of cohesin we identify a series of long-range chromosomal interactions that persist. These correspond to regions of the genome occupied by the polycomb repressive system, depend on PRC1, and we discover that cohesin counteracts these interactions. This disruptive activity is independent of CTCF and TADs, and regulates gene repression by the polycomb system. Therefore, in contrast to the proposal that cohesin creates structure in chromosomes, we discover a new role for cohesin in disrupting polycomb-dependent chromosome interactions to regulate gene expression.



2019 ◽  
Author(s):  
Kristin Abramo ◽  
Anne-Laure Valton ◽  
Sergey V. Venev ◽  
Hakan Ozadam ◽  
A. Nicole Fox ◽  
...  

SummaryChromosome folding is extensively modulated as cells progress through the cell cycle. During mitosis, condensin complexes fold chromosomes in helically arranged nested loop arrays. In interphase, the cohesin complex generates loops that can be stalled at CTCF sites leading to positioned loops and topologically associating domains (TADs), while a separate process of compartmentalization drives the spatial segregation of active and inactive chromatin domains. We used synchronized cell cultures to determine how the mitotic chromosome conformation is transformed into the interphase state. Using Hi-C, chromatin binding assays, and immunofluorescence we show that by telophase condensin-mediated loops are lost and a transient folding intermediate devoid of most loops forms. By late telophase, cohesin-mediated CTCF-CTCF loops and positions of TADs start to emerge rapidly. Compartment boundaries are also established in telophase, but long-range compartmentalization is a slow process and proceeds for several hours after cells enter G1. Our results reveal the kinetics and order of events by which the interphase chromosome state is formed and identify telophase as a critical transition between condensin and cohesin driven chromosome folding.



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