Gene density and chromosome territory shape
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Despite decades of study of chromosome territories (CT) in the interphase nucleus of mammalian cells, our understanding of the global shape and 3-D organization of the individual CT remains very limited. Past microscopic analysis of CT suggested that while many of the CT appear to be very regular ellipsoid-like shapes, there were also those with more irregular shapes. We have undertaken a comprehensive analysis to determine the degree of shape regularity of different CT. To be representative of the whole human genome, 12 different CT (~41 % of the genome) were selected that ranged from the largest (CT 1) to the smallest (CT 21) in size and from the highest (CT 19) to lowest (CT Y) in gene density. Using both visual inspection and algorithms that measure the degree of shape ellipticity and regularity, we demonstrate a strong inverse correlation between the degree of regular CT shape and gene density for those CT that are most gene-rich (19, 17, 11) and gene-poor (18, 13, Y). CT more intermediate in gene density showed a strong negative correlation with shape regularity, but not with ellipticity. An even more striking correlation between gene density and CT shape was determined for the nucleolar-associated NOR-CT. Correspondingly, striking differences in shape between the X active and inactive CT implied that aside from gene density, the overall global level of gene transcription on individual CT is also an important determinant of chromosome territory shape.
This research was supported by grants from the National Institute of Health (GM-072131) to R.B, the National Science Foundation (IIS-0713489, IIS-1115220, and IIS-1422591) to J.X. and R.B., and the University at Buffalo Foundation account # 9351-1157-26 to R.B.
Conflict of interest
The authors declare that they have no conflict of interest.
- Berg Md, Cheong O, Kreveld Mv, Overmars M (2008) Computational geometry: algorithms and applications. 3rd edn. Springer Santa Clara, CA, USAGoogle Scholar
- Kreth G, Finsterle J, von Hase J, Cremer M, Cremer C (2004) Radial arrangement of chromosome territories in human cell nuclei: a computer model approach based on gene density indicates a probabilistic global positioning code. Biophys J 86:2803–2812. doi:10.1016/S0006-3495(04)74333-7 PubMedCrossRefPubMedCentralGoogle Scholar
- Rosin PL (2005) Computing global shape measures. In: Chen CH, Wang PSP (eds) Handbook of Pattern Recognition and Computer Vision. World Scientific, Singapore pp 177–196Google Scholar