Large-scale probabilistic 3D organization of human chromosome territories
| Autor: | Andrew Fritz, Ronald Berezney, Jaromira Vecerova, Nitasha Sehgal, Jinhui Xu, Hu Ding, Branislav Stojkovic, Sambit Bhattacharya, Zihe Chen |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
0301 basic medicine
Computational biology Biology Genome Cell Line Pattern Recognition Automated 03 medical and health sciences Fetus Gene density Genetics medicine Chromosomes Human Data Mining Humans Molecular Biology Gene Genetics (clinical) In Situ Hybridization Fluorescence Cell Nucleus medicine.diagnostic_test Cell Cycle Probabilistic logic Chromosome Chromosome Mapping General Medicine Articles Fibroblasts 030104 developmental biology Chromosome Territory Pattern recognition (psychology) Algorithms Fluorescence in situ hybridization |
| Zdroj: | Human molecular genetics. 25(3) |
| ISSN: | 1460-2083 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|