Hierarchical chromatin organization detected by TADpole

Author:

Soler-Vila Paula1,Cuscó Pol2,Farabella Irene1ORCID,Di Stefano Marco1ORCID,Marti-Renom Marc A1345ORCID

Affiliation:

1. CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain

2. Gastrointestinal and Endocrine Tumors Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona 08035, Spain

3. Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Dr. Aiguader 88, Barcelona 08003, Spain

4. Universitat Pompeu Fabra (UPF), Pg. Lluis Companys 23, Barcelona 08003, Spain

5. ICREA, Pg. Lluis Companys 23, Barcelona 08010, Spain

Abstract

Abstract The rapid development of Chromosome Conformation Capture (3C-based techniques), as well as imaging together with bioinformatics analyses, has been fundamental for unveiling that chromosomes are organized into the so-called topologically associating domains or TADs. While TADs appear as nested patterns in the 3C-based interaction matrices, the vast majority of available TAD callers are based on the hypothesis that TADs are individual and unrelated chromatin structures. Here we introduce TADpole, a computational tool designed to identify and analyze the entire hierarchy of TADs in intra-chromosomal interaction matrices. TADpole combines principal component analysis and constrained hierarchical clustering to provide a set of significant hierarchical chromatin levels in a genomic region of interest. TADpole is robust to data resolution, normalization strategy and sequencing depth. Domain borders defined by TADpole are enriched in main architectural proteins (CTCF and cohesin complex subunits) and in the histone mark H3K4me3, while their domain bodies, depending on their activation-state, are enriched in either H3K36me3 or H3K27me3, highlighting that TADpole is able to distinguish functional TAD units. Additionally, we demonstrate that TADpole's hierarchical annotation, together with the new DiffT score, allows for detecting significant topological differences on Capture Hi-C maps between wild-type and genetically engineered mouse.

Publisher

Oxford University Press (OUP)

Subject

Genetics

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