Sehgal Nitasha, Fritz Andrew J, Vecerova Jaromira, Ding Hu, Chen Zihe, Stojkovic Branislav, Bhattacharya Sambit, Xu Jinhui, Berezney Ronald
Department of Biological Sciences.
Department of Computer Science and Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA and.
Hum Mol Genet. 2016 Feb 1;25(3):419-36. doi: 10.1093/hmg/ddv479. Epub 2015 Nov 24.
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.
越来越多的证据表明,在包括哺乳动物细胞的细胞核内,染色体领地(CT)具有概率性的非随机排列,包括径向定位和染色体间相互作用的偏好模式,这些模式具有细胞类型特异性。虽然一般认为CT内基因的三维(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的整体3D组织(拓扑结构)的第一步,我们使用跨越人类WI38肺成纤维细胞中每条染色体的六个探针进行了多色荧光原位杂交。选择了六个大小和基因密度不同的CT(1、4、12、17、18和X染色体)。应用内部计算几何算法来测量探针的每一种组合之间的3D距离,并阐明数据挖掘出的结构模式。我们的研究结果表明,单个CT具有高度的非随机排列,不同染色体之间存在差异,并且在细胞周期中表现出明显的变化。应用一种经典的、定义明确的数据挖掘和模式识别方法——“k均值”算法,生成了每个染色体最佳拟合排列的3D模型。这些预测模型与详细的距离测量和分析结果高度相关。我们提出,每个CT独特的3D拓扑结构以及细胞周期中的特征性变化为单个染色体的整体基因表达程序提供了结构框架。