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    Home > Biochemistry News > Biotechnology News > A new method for extracting high-resolution 3D genome structure sourcing high-resolution Hi-C data.

    A new method for extracting high-resolution 3D genome structure sourcing high-resolution Hi-C data.

    • Last Update: 2020-08-08
    • Source: Internet
    • Author: User
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    The nuclear activity of higher eukaryotic organisms, from gene transcription and DNA replication to DNA damage repair, are closely related to the three-dimensional spatial structure of the genome.
    , 3D genomic research has become a hot spot in recent years.
    Hi-C is the most common genomic detection of chromatin 3D structure of the hemictechnology technology.
    However, because Hi-C has relatively low resolution and high sequencing requirements, high-precision 3D genomic research is almost impossible to achieve in large-scale projects such as precision medicine population queues.
    how to obtain high-resolution chromatin spatial structure sized at low cost and quickly has become a bottleneck in large-scale 3D genome research.
    , Zhang Zhihua Research Group of the Beijing Genomics Research Institute of the Chinese Academy of Sciences, in collaboration with li Ansheng Research Group of the Software Research Institute of the Chinese Academy of Sciences, developed a new method for predicting high-resolution chromatin domain and chromatin interaction using low-resolution Hi-C combined with other episotypes data, making it possible to obtain high-precision chromatin structures quickly and cost-effectively in large samples.
    the study was published online August 15 in The Nature Communications with The Decoding Topoly Associated Domains with Ultra-Low resolution Hi-C Data by Graph R. Entropy.
    the method mainly uses low-resolution Hi-C to predict high-resolution chromatin topology domain (TAD).
    based on the theory of structural information entropy developed by Leonson's team, the study creatively viewed Hi-C data as a interconnected network and developed the deDoc algorithm.
    the new algorithm is significantly different from other current methods, you can use the original sequencing data directly without the need for normalization.
    the right method of normalization is critical to other software, and inappropriate normalization often leads to bad or even wrong results.
    In addition, the new algorithm relies very little on the total amount of data.
    tests found that even with Hi-C data aggregations as low as ten, a structure similar to a topology domain can be clearly identified.
    because of these two important features of deDoc, deDoc can become an important tool for high-precision 3D genome research in large population queues.
    Zhang Zhihua team has been committed to the study of chromatin 3D structure, after the research and development of accurate prediction of chromatin interaction algorithm CISD_loop, the algorithm uses the non-uniformity of eukaryotic bionuclear small body in the genome, from the nuclear small body arrangement method to infer high-precision chromosomal interaction sites, and further introduce low-resolution HI-C data to predict chromatic interaction.
    undersampling experiments, it is found that as long as the very low resolution of Hi-C data, CISD_loop can predict the interaction of chromatin in high resolution.
    the above source code can be downloaded through github, research by the National Nature Fund Commission and the Ministry of Science and Technology "973" project funding.
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