Revealing Hi-C subcompartments by imputing inter-chromosomal chromatin interactions

Kyle Xiong and Jian Ma ()
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Kyle Xiong: Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology
Jian Ma: Carnegie Mellon University

Nature Communications, 2019, vol. 10, issue 1, 1-12

Abstract: Abstract Higher-order genome organization and its variation in different cellular conditions remain poorly understood. Recent high-coverage genome-wide chromatin interaction mapping using Hi-C has revealed spatial segregation of chromosomes in the human genome into distinct subcompartments. However, subcompartment annotation, which requires Hi-C data with high sequencing coverage, is currently only available in the GM12878 cell line, making it impractical to compare subcompartment patterns across cell types. Here we develop a computational approach, SNIPER (Subcompartment iNference using Imputed Probabilistic ExpRessions), based on denoising autoencoder and multilayer perceptron classifier to infer subcompartments using typical Hi-C datasets with moderate coverage. SNIPER accurately reveals subcompartments using moderate coverage Hi-C datasets and outperforms an existing method that uses epigenomic features in GM12878. We apply SNIPER to eight additional cell lines and find that chromosomal regions with conserved and cell-type specific subcompartment annotations have different patterns of functional genomic features. SNIPER enables the identification of subcompartments without high-coverage Hi-C data and provides insights into the function and mechanisms of spatial genome organization variation across cell types.

Date: 2019
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DOI: 10.1038/s41467-019-12954-4

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