The next-generation sequencing-chess problem.

Abstract

The development of next-generation sequencing (NGS) technologies paved the way for studying the spatiotemporal coordination of cellular processes along the genome. However, data sets are commonly limited to a few time points, and missing information needs to be interpolated. Most models assume that the studied dynamics are similar between individual cells, so that a homogeneous cell culture can be represented by a population-wide average. Here, we demonstrate that this understanding can be inappropriate. We developed a thought experiment-which we call the NGS chess problem-in which we compare the temporal sequencing data analysis to observing a superimposed picture of many independent games of chess at a time. The analysis of the spatiotemporal kinetics advocates for a new methodology that considers DNA-particle interactions in each cell independently even for a homogeneous cell population.