Joint inference and alignment of genome structures enables characterization of compartment-independent reorganization across cell types

Lila Rieber, Shaun Mahony

Research output: Contribution to journalArticle

Abstract

Background: Comparisons of Hi-C data sets between cell types and conditions have revealed differences in topologically associated domains (TADs) and A/B compartmentalization, which are correlated with differences in gene regulation. However, previous comparisons have focused on known forms of 3D organization while potentially neglecting other functionally relevant differences. We aimed to create a method to quantify all locus-specific differences between two Hi-C data sets. Results: We developed MultiMDS to jointly infer and align 3D chromosomal structures from two Hi-C data sets, thereby enabling a new way to comprehensively quantify relocalization of genomic loci between cell types. We demonstrate this approach by comparing Hi-C data across a variety of cell types. We consistently find relocalization of loci with minimal difference in A/B compartment score. For example, we identify compartment-independent relocalizations between GM12878 and K562 cells that involve loci displaying enhancer-associated histone marks in one cell type and polycomb-associated histone marks in the other. Conclusions: MultiMDS is the first tool to identify all loci that relocalize between two Hi-C data sets. Our method can identify 3D localization differences that are correlated with cell-type-specific regulatory activities and which cannot be identified using other methods.

Original languageEnglish (US)
Article number61
JournalEpigenetics and Chromatin
Volume12
Issue number1
DOIs
StatePublished - Oct 8 2019

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Joints
Genome
Histone Code
K562 Cells
Datasets
Genes

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics

Cite this

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title = "Joint inference and alignment of genome structures enables characterization of compartment-independent reorganization across cell types",
abstract = "Background: Comparisons of Hi-C data sets between cell types and conditions have revealed differences in topologically associated domains (TADs) and A/B compartmentalization, which are correlated with differences in gene regulation. However, previous comparisons have focused on known forms of 3D organization while potentially neglecting other functionally relevant differences. We aimed to create a method to quantify all locus-specific differences between two Hi-C data sets. Results: We developed MultiMDS to jointly infer and align 3D chromosomal structures from two Hi-C data sets, thereby enabling a new way to comprehensively quantify relocalization of genomic loci between cell types. We demonstrate this approach by comparing Hi-C data across a variety of cell types. We consistently find relocalization of loci with minimal difference in A/B compartment score. For example, we identify compartment-independent relocalizations between GM12878 and K562 cells that involve loci displaying enhancer-associated histone marks in one cell type and polycomb-associated histone marks in the other. Conclusions: MultiMDS is the first tool to identify all loci that relocalize between two Hi-C data sets. Our method can identify 3D localization differences that are correlated with cell-type-specific regulatory activities and which cannot be identified using other methods.",
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