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      Large-scale 3D chromatin reconstruction from chromosomal contacts

      research-article
      1 , 1 , 2 , 3 , 1 ,
      BMC Genomics
      BioMed Central
      The 17th Asia Pacific Bioinformatics Conference (APBC 2019) (APBC 2019)
      14-16 January 2019
      Hi-C, 3D chromosome structure, Multidimensional scaling, Chromosome conformation capture, 3D genome

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          Abstract

          Background

          Recent advances in genome analysis have established that chromatin has preferred 3D conformations, which bring distant loci into contact. Identifying these contacts is important for us to understand possible interactions between these loci. This has motivated the creation of the Hi-C technology, which detects long-range chromosomal interactions. Distance geometry-based algorithms, such as ChromSDE and ShRec3D, have been able to utilize Hi-C data to infer 3D chromosomal structures. However, these algorithms, being matrix-based, are space- and time-consuming on very large datasets. A human genome of 100 kilobase resolution would involve ∼30,000 loci, requiring gigabytes just in storing the matrices.

          Results

          We propose a succinct representation of the distance matrices which tremendously reduces the space requirement. We give a complete solution, called SuperRec, for the inference of chromosomal structures from Hi-C data, through iterative solving the large-scale weighted multidimensional scaling problem.

          Conclusions

          SuperRec runs faster than earlier systems without compromising on result accuracy. The SuperRec package can be obtained from http://www.cs.cityu.edu.hk/~shuaicli/SuperRec.

          Electronic supplementary material

          The online version of this article (10.1186/s12864-019-5470-2) contains supplementary material, which is available to authorized users.

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          Most cited references31

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          A map of the cis-regulatory sequences in the mouse genome.

          The laboratory mouse is the most widely used mammalian model organism in biomedical research. The 2.6 × 10(9) bases of the mouse genome possess a high degree of conservation with the human genome, so a thorough annotation of the mouse genome will be of significant value to understanding the function of the human genome. So far, most of the functional sequences in the mouse genome have yet to be found, and the cis-regulatory sequences in particular are still poorly annotated. Comparative genomics has been a powerful tool for the discovery of these sequences, but on its own it cannot resolve their temporal and spatial functions. Recently, ChIP-Seq has been developed to identify cis-regulatory elements in the genomes of several organisms including humans, Drosophila melanogaster and Caenorhabditis elegans. Here we apply the same experimental approach to a diverse set of 19 tissues and cell types in the mouse to produce a map of nearly 300,000 murine cis-regulatory sequences. The annotated sequences add up to 11% of the mouse genome, and include more than 70% of conserved non-coding sequences. We define tissue-specific enhancers and identify potential transcription factors regulating gene expression in each tissue or cell type. Finally, we show that much of the mouse genome is organized into domains of coordinately regulated enhancers and promoters. Our results provide a resource for the annotation of functional elements in the mammalian genome and for the study of mechanisms regulating tissue-specific gene expression.
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            Least-squares fitting of two 3-d point sets.

            Two point sets {pi} and {p'i}; i = 1, 2,..., N are related by p'i = Rpi + T + Ni, where R is a rotation matrix, T a translation vector, and Ni a noise vector. Given {pi} and {p'i}, we present an algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix. This new algorithm is compared to two earlier algorithms with respect to computer time requirements.
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              Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

              The discovery of interchromosomal interactions in higher eukaryotes points to a functional interplay between genome architecture and gene expression, challenging the view of transcription as a one-dimensional process. However, the extent of interchromosomal interactions and the underlying mechanisms are unknown. Here we present the first genome-wide analysis of transcriptional interactions using the mouse globin genes in erythroid tissues. Our results show that the active globin genes associate with hundreds of other transcribed genes, revealing extensive and preferential intra- and interchromosomal transcription interactomes. We show that the transcription factor Klf1 mediates preferential co-associations of Klf1-regulated genes at a limited number of specialized transcription factories. Our results establish a new gene expression paradigm, implying that active co-regulated genes and their regulatory factors cooperate to create specialized nuclear hot spots optimized for efficient and coordinated transcriptional control.
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                Author and article information

                Contributors
                yanlin.zhang2@mail.mcgill.ca
                wwliu26@gmail.com
                yu.lin@anu.edu.au
                ykng@utar.edu.my
                shuaicli@cityu.edu.hk
                Conference
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                4 April 2019
                4 April 2019
                2019
                : 20
                Issue : Suppl 2 Issue sponsor : Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.
                : 186
                Affiliations
                [1 ]Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR
                [2 ]ISNI 0000 0001 2180 7477, GRID grid.1001.0, Research School of Computer Science, the Australian National University, ; Canberra, Australia
                [3 ]ISNI 0000 0004 1798 283X, GRID grid.412261.2, Department of Computer Science, Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, ; Kampar, Malaysia
                Article
                5470
                10.1186/s12864-019-5470-2
                6456969
                30967119
                decad6aa-0978-4ae9-a6a7-24c61b783fb8
                © The Author(s) 2019

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                The 17th Asia Pacific Bioinformatics Conference (APBC 2019)
                APBC 2019
                Wuhan, China
                14-16 January 2019
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                Research
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                © The Author(s) 2019

                Genetics
                hi-c,3d chromosome structure,multidimensional scaling,chromosome conformation capture,3d genome

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