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      The methodology study of three-dimensional (3D) genome research.

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          Abstract

          Multiple dimensions of genome organization play critical roles in the regulation of non-coding regions in gene expression in cell/organ development and pathogenesis. Precise measurements of multi-dimensional genome structure ensure data quality and fully depend upon the study design. We here overview the number of methodologies used in the detection and analysis of genome structure and compare advantages and disadvantages of 3C-based, PCR amplification-based, and sequencing-based measurements. We discuss about the optimization of various techniques according to targeted genomic sites, the required resolution, and possible technique biases. Comparison of different analysis tools and computational system-based automatic analysis is evaluated to define more opportunities and challenges of data analysis in 3D genome research. The genome structure is visualized in levels of single genome organized by enhancer-promoter interactions, TAD, and intra-chromosomal and inter-chromosomal interactions between TADs. Thus, methodologies of genome organization multi-dimensions are not only critical in studies on 3D genome-regulated transcriptions, but also in the discovery of disease-specific biomarkers and targets for diagnosis and therapies.

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          Author and article information

          Journal
          Semin. Cell Dev. Biol.
          Seminars in cell & developmental biology
          Elsevier BV
          1096-3634
          1084-9521
          Jul 05 2018
          Affiliations
          [1 ] Zhongshan Hospital Institute of Clinical Science, Fudan University Medical School, Shanghai Institute of Clinical Bioinformatics Shanghai, China.
          [2 ] Zhongshan Hospital Institute of Clinical Science, Fudan University Medical School, Shanghai Institute of Clinical Bioinformatics Shanghai, China. Electronic address: Xiangdong.wang@clintransmed.org.
          Article
          S1084-9521(17)30594-3
          10.1016/j.semcdb.2018.07.003
          29981900
          23f1fc72-1565-44bf-b01d-8f91cf526ba5
          History

          3D genome,analysis tool,detection method
          3D genome, analysis tool, detection method

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