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Large-scale probabilistic 3D organization of human chromosome territories

机译:人类染色体区域的大规模概率3D组织

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摘要

There is growing evidence that chromosome territories (CT) have a probabilistic non-random arrangement within the cell nucleus of mammalian cells including radial positioning and preferred patterns of interchromosomal interactions that are cell-type specific. While it is generally assumed that the three-dimensional (3D) arrangement of genes within the CT is linked to genomic regulation, the degree of non-random organization of individual CT remains unclear. As a first step to elucidating the global 3D organization (topology) of individual CT, we performed multi-color fluorescence in situ hybridization using six probes extending across each chromosome in human WI38 lung fibroblasts. Six CT were selected ranging in size and gene density (1, 4, 12, 17, 18 and X). In-house computational geometric algorithms were applied to measure the 3D distances between every combination of probes and to elucidate data-mined structural patterns. Our findings demonstrate a high degree of non-random arrangement of individual CT that vary from chromosome to chromosome and display distinct changes during the cell cycle. Application of a classic, well-defined data mining and pattern recognition approach termed the ‘k-means’ generated 3D models for the best fit arrangement of each chromosome. These predicted models correlated well with the detailed distance measurements and analysis. We propose that the unique 3D topology of each CT and characteristic changes during the cell cycle provide the structural framework for the global gene expression programs of the individual chromosomes.
机译:越来越多的证据表明,染色体区域(CT)在哺乳动物细胞的细胞核内具有概率性的非随机排列,包括径向定位和特定于细胞类型的染色体间相互作用的优选模式。尽管通常认为CT中基因的三维(3D)排列与基因组调控有关,但单个CT的非随机组织程度仍不清楚。作为阐明单个CT的全局3D组织(拓扑)的第一步,我们使用六种跨越人WI38肺成纤维细胞中每个染色体的探针进行了多色荧光原位杂交。选择六个CT,大小和基因密度不等(1、4、12、17、18和X)。采用内部计算几何算法来测量探针的每种组合之间的3D距离,并阐明数据挖掘的结构模式。我们的发现表明,单个CT的高度非随机排列会因染色体而异,并在细胞周期中显示出明显的变化。一种经典的,定义明确的数据挖掘和模式识别方法的应用称为“ k-means”生成的3D模型,用于每个染色体的最佳拟合排列。这些预测模型与详细的距离测量和分析密切相关。我们提出,每个CT的独特3D拓扑和细胞周期中的特征变化为单个染色体的全局基因表达程序提供了结构框架。

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