Dataset Information

Gene density and chromosome territory shape.

ABSTRACT: 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.

SUBMITTER: Sehgal N

PROVIDER: S-EPMC5726871 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The spatial organization of a population can influence the spread of information, behaviour and pathogens. Group territory size and territory overlap and components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates and environmental risk (e.g. indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography. Our study aims to identify factors shaping the spatial organization of wildlife populations and assess the impact of epizootics on space use. We further aim to explore the mechanisms by which disease perturbations could cause changes in spatial organization. Here we assessed the seasonal spatial organization of Serengeti lions and Yellowstone wolves at the group level. We use network analysis to describe spatial organization and connectivity of social groups. We then examine the factors predicting mean territory size and mean territory overlap for each population using generalized additive models. We demonstrate that lions and wolves were similar in that group-level factors, such as number of groups and shaped spatial organization more than population-level factors, such as population density. Factors shaping territory size were slightly different than factors shaping territory overlap; for example, wolf pack size was an important predictor of territory overlap, but not territory size. Lion spatial networks were more highly connected, while wolf spatial networks varied seasonally. We found that resource dispersion may be more important for driving territory size and overlap for wolves than for lions. Additionally, canine distemper epizootics may have altered lion spatial organization, highlighting the importance of including infectious disease epizootics in studies of behavioural and movement ecology. We provide insight about when we might expect to observe the impacts of resource dispersion, disease perturbations, and other ecological factors on spatial organization. Our work highlights the importance of monitoring and managing social carnivore populations at the group level. Future research should elucidate the complex relationships between demographics, social and spatial structure, abiotic and biotic conditions and pathogen infections.

Dataset Information

Gene density and chromosome territory shape.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets