Integrative Genome Modeling Platform reveals essentialityof rare contact events in 3D genome organizations

Abstract

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional (3D) organization of genomes and key regulatory processes of genome function. However, it remains a major challenge to systematically integrate all available data sources to characterize the nuclear organization of genomes across different spatial scales. Here, we develop a multi-modal data integration approach to produce genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction, and spatial segregation of functionally related chromatin. By performing a quantitative assessment of the predictive power of genome structures generated from different data combinations, we demonstrate that multimodal data integration can compensate for systematic errors and missing values in some of the data and thus, greatly increases accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency inter-chromosomal contacts (e.g., "rare" contact events) to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multi-modal data integration for genome structure analysis, available through the Integrative Genome structure Modeling (IGM) software package that we introduce here.