Data Processing, Structure Prediction And Functional Analysis Of Genome Structure In Three-Dimensional Space

To study the spatial organization of the genome and its relation to the regulation of nuclear functions, a variety of experimental approaches, such as electron microscopy strategy, fluorescent in situ hybridization (FISH) and chromosome conformation capture (3C)-based methods, are utilized together to probe the hierarchical order of genomic organization with resolution ranging from single atom to chromosomal segment. The advances of experiments are providing us with more information on the global genomic architecture, and opening the opportunities to predict the three-dimensional structure of the genome by computational methods of data integration. However, integrating data from these disparate experiments is a challenge due to the significant differences and even discrepancies among them, e.g. available data number, resolution scale, credibility and noise. We introduced a scoring approach to computationally predict the genome-wide3D structure of chromosomes according to the detailed analysis of noise and discrepancy in source data. Finally we analyzed the relation of genomic organization in the3D space to gene co-expression and gene functions. We found that the genes with high co-expression levels are more likely to interact in the3D space.