Year: 2021
Type: review
Abstract: With a growing understanding of the chromatin structure, many efforts remain focused on bridging the gap between what is suggested by population-averaged data and what is visualized for single cells. A popular approach to traversing these scales is to fit a polymer model to Hi-C contact data. However, Hi-C is an average of millions to billions of cells, and each cell may not contain all population-averaged contacts. Therefore, we employ a novel approach of summing individual chromosome trajectories-determined by our Self-Returning Random Walk model-to create populations of cells. We allow single cells to consist of disparate structures and reproduce a variety of experimentally relevant contact maps. We show that the amount of shared topology between cells, and their mechanism of formation, changes the population-averaged structure. Therefore, we present a modeling technique that, with few constraints and little oversight, can be used to understand which single-cell chromatin structures underlie population-averaged behavior.
Source: Biophysical Reports
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,000
Awards: Reducing Cancer Transcriptional Heterogeneity through Regulation of Chromatin Structure, G5446536580, From the Nuclear Pore Complex to Smart Artificial Nanochannels, EFRI CEE: Macrogenomic engineering via modulation of chromatin nanoenvironment, G6180960641, Translating buccal nanocytology for lung cancer screening into clinical practice
OpenAlex ID: W4200207327