Revealing Long-Range Interconnected Hubs in Human Chromatin Interaction Data Using Graph Theory

Boulos, Rasha E.; Arnéodo, A.; Jensen, Pablo; Audit, Benjamin

doi:10.1103/physrevlett.111.118102

Cited by 41 publications

(42 citation statements)

References 46 publications

(53 reference statements)

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“…Noting that the contact map is equivalent to the weighted adjacency matrix A of an undirected graph G (Boulos et al, 2013), an alternative graphical representation is obtained. Here, nodes n i represent genomic regions and weighted edges e ( n i , n j , w ij ) represent the observed frequency w ij of 3C read-pairs linking regions n i and n j .…”

Section: Methodsmentioning

confidence: 99%

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

DeMaere

Darling

2016

PeerJ

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BackgroundChromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised.MethodsWe developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure.ResultsWhen all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance.DiscussionPreviously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development.

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Section: Methodsmentioning

confidence: 99%

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

DeMaere

Darling

2016

PeerJ

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“…This demonstrates that, at the Mb-scale, the early initiation euchromatin zones at U/N-domains borders actually interact with the late replicating heterochromatin central part. As recently shown using a graph theoretical approach (Boulos et al, 2013), these "master" replication origins are long-range interconnected hubs of chromatin interactions both within and between different chromosomes. The additional observation that the remarkable gene organization previously revealed in skew-N domains , with an over representation of highly expressed genes nearby domain borders, is also present in the MRT-U domains of every cell lines (Julienne et al, 2013a,b;Baker et al, 2012a), sheds light on these U/N domains as chromatin units of highly coordinated regulation of transcription and replication Hyrien et al, 2013).…”

Section: Introductionmentioning

confidence: 96%

Large replication skew domains delimit GC-poor gene deserts in human

Zaghloul¹,

Drillon²,

Boulos³

et al. 2014

Computational Biology and Chemistry

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“…A Hi-C co-localisation frequency matrix is positive and symmetric, it can thus be interpreted as the adjacency matrix of the genome interaction network where the nodes are the chromosome loci (typically non-overlapping windows) and the edges reflect the co-localisation frequency between these regions. This justifies the use of concepts and tools from graph theory to analyse Hi-C data [28, 30, 33, 34, 36–38]. This representation depends on genome assembly only up to the scale used to define the Hi-C matrix, the columns/rows of the Hi-C matrix can be permuted without affecting the output of graph algorithms.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale structural community organisation of the human genome

et al. 2017

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BackgroundStructural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation.ResultsWe deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci.ConclusionsMulti-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1616-x) contains supplementary material, which is available to authorized users.

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Revealing Long-Range Interconnected Hubs in Human Chromatin Interaction Data Using Graph Theory

Cited by 41 publications

References 46 publications

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

Large replication skew domains delimit GC-poor gene deserts in human

Multi-scale structural community organisation of the human genome

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