MiOS, an integrated imaging and computational strategy to model gene folding with nucleosome resolution

MiOS,一种集成成像和计算策略,用于通过核小体分辨率模拟基因折叠

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作者:Maria Victoria Neguembor #, Juan Pablo Arcon #, Diana Buitrago #, Rafael Lema, Jürgen Walther, Ximena Garate, Laura Martin, Pablo Romero, Jumana AlHaj Abed, Marta Gut, Julie Blanc, Melike Lakadamyali, Chao-Ting Wu, Isabelle Brun Heath, Modesto Orozco, Pablo D Dans, Maria Pia Cosma

Abstract

The linear sequence of DNA provides invaluable information about genes and their regulatory elements along chromosomes. However, to fully understand gene function and regulation, we need to dissect how genes physically fold in the three-dimensional nuclear space. Here we describe immuno-OligoSTORM, an imaging strategy that reveals the distribution of nucleosomes within specific genes in super-resolution, through the simultaneous visualization of DNA and histones. We combine immuno-OligoSTORM with restraint-based and coarse-grained modeling approaches to integrate super-resolution imaging data with Hi-C contact frequencies and deconvoluted micrococcal nuclease-sequencing information. The resulting method, called Modeling immuno-OligoSTORM, allows quantitative modeling of genes with nucleosome resolution and provides information about chromatin accessibility for regulatory factors, such as RNA polymerase II. With Modeling immuno-OligoSTORM, we explore intercellular variability, transcriptional-dependent gene conformation, and folding of housekeeping and pluripotency-related genes in human pluripotent and differentiated cells, thereby obtaining the highest degree of data integration achieved so far to our knowledge.

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