TopDom: an efficient and deterministic method for identifying topological domains in genomes

Abstract

Genome-wide proximity ligation assays allow the identification of chromatin contacts at unprecedented resolution. Several studies reveal that mammalian chromosomes are composed of topological domains (TDs) in sub-mega base resolution, which appear to be conserved across cell types and to some extent even between organisms. Identifying topological domains is now an important step toward understanding the structure and functions of spatial genome organization. However, current methods for TD identification demand extensive computational resources, require careful tuning and/or encounter inconsistencies in results. In this work, we propose an efficient and deterministic method, TopDom, to identify TDs, along with a set of statistical methods for evaluating their quality. TopDom is much more efficient than existing methods and depends on just one intuitive parameter, a window size, for which we provide easy-to-implement optimization guidelines. TopDom also identifies more and higher quality TDs than the popular directional index algorithm. The TDs identified by TopDom provide strong support for the cross-tissue TD conservation. Finally, our analysis reveals that the locations of housekeeping genes are closely associated with cross-tissue conserved TDs. The software package and source codes of TopDom are available at http://zhoulab.usc.edu/TopDom/.

Reciprocal insulation analysis of Hi-C data shows that TADs represent a functionally but not structurally privileged scale in the hierarchical folding of chromosomes

“…The only parameter in the algorithm is the reciprocal insulation threshold itself, which is systematically varied to define and stratify the entire hierarchy of domains, rather than tuned to identify a single domain set. Moreover, unlike parameters in existing approaches to identify multiscale domain structures in Hi-C data sets (Filippova et al 2014;Lévy-Leduc et al 2014;Shin et al 2015;Weinreb and Raphael 2015;Chen et al 2016;Shavit et al 2016), the reciprocal insulation is a biologically relevant measure estimating how efficiently a domain is physically insulated from its immediate neighbors. CaTCH is provided as an R package at https://github.com/ zhanyinx/CaTCH_R (source code can be found in Supplemental Methods).…”

“…Our approach to partition the genome into nested sets of domains has two main advantages over existing hierarchical TAD callers (Filippova et al 2014;Lévy-Leduc et al 2014;Shin et al 2015;Weinreb and Raphael 2015;Chen et al 2016;Shavit et al 2016): (1) The CaTCH algorithm does not rely on any free parameters, except reciprocal insulation itself that is used to stratify the domains; (2) Unlike other methods that identify hierarchies of domains, where parameters have an unclear structural or biological interpretation, reciprocal insulation estimates how well a domain is segregated from its neighbors. CaTCH is fast and requires less computing power: Identifying a whole hierarchy of domains on a single 100-Mb chromosome takes <4 min on a single CPU, starting from mouse Hi-C data at 20-kb resolution.…”

“…A small number of algorithms that identify hierarchies of topological domains are available (Filippova et al 2014;Lévy-Leduc et al 2014;Shin et al 2015;Weinreb and Raphael 2015;Chen et al 2016;Shavit et al 2016). However, none of them provides a quantitative description of how the various layers of domains differ from one another.…”

MSTD: an efficient method for detecting multi-scale topological domains from symmetric and asymmetric 3D genomic maps

“…In order to compare MSTD with three popular methods including DI 7 , TopDom 16 and HicSeg 14 for identifying TADs, we next applied these four methods onto Hi-C datasets of mouse embryonic stem cells (ESC), intermediate neuronal precursor cells (NPC) and post-mitotic neurons (Neurons) through different differentiation periods (ESC-NPC-Neurons), binned at 50 kb resolution 32 . Since DI has been generally accepted to detect TADs in a number of existing studies, here we regard the size range of its TADs (from 700kb-1200kb) as the standard scale.…”

“…Similarly, Crane et al developed an approach to transform the Hi-C contact matrix into an 1D insulation score vector for detecting topological structures 15 . Shin et al employed an efficient and deterministic method to systematically identify TADs with a set of statistical measures to evaluate their quality 16 . However, these methods were only designed for detecting single-scale domains.…”