# A wavelet-based approach generates quantitative, scale-free and hierarchical descriptions of 3D genome structures and new biological insights

## TL;DR

This paper introduces WaveTAD, a new method to analyze 3D genome structures, offering more accurate and detailed insights into how DNA is organized in the nucleus.

## Contribution

WaveTAD provides a resolution-free, probabilistic, and hierarchical approach to infer 3D genome structures with increased accuracy and sensitivity.

## Key findings

- WaveTAD reveals the widespread presence of embryonic 3D organization before zygotic genome activation.
- The method shows how multiple CTCF units affect the stability of loops and TADs.
- WaveTAD identifies associations between gene expression and TAD structures in conditions like COVID-19 and sex-specific transcription in Drosophila.

## Abstract

Eukaryotic genomes are organized within nuclei in three-dimensional space, forming structures such as loops, topologically associating domains (TADs), and chromosome territories. This 3D architecture impacts gene regulation and development, stress responses, and disease. However, current methods to infer these 3D structures from genomic data have multiple drawbacks, including varying outcomes depending on the resolution of the analysis and sequencing depth, qualitative outputs that limit statistical comparisons, and insufficient insight into structure frequency within samples. These challenges hinder rigorous comparisons of 3D properties across genomes, conditions, or species. To overcome these issues, we developed WaveTAD, a wavelet transform-based method that provides a resolution-free, probabilistic, and hierarchical description of 3D organization. WaveTAD generates TAD strengths, capturing the variable frequency of intrachromosomal interactions within samples, and shows increased accuracy and sensitivity over existing methods. We applied WaveTAD to multiple datasets from Drosophila, mouse, and humans to illustrate new biological insights that our more sensitive and quantitative approach provides, such as the widespread presence of embryonic 3D organization before zygotic genome activation, the effect of multiple CTCF units on the stability of loops and TADs, and the association between gene expression and TAD structures in COVID-19 patients or sex-specific transcription in Drosophila.

Human cells package meters of DNA into micron-sized nuclei through a series of coordinated multiscale looping structures that compose the 3D nuclear organization. At the same time, this complex compression requires dynamic and precise control to maintain biological processes in a manner that safeguards developmental and tissue-specific programs. Aberrations in this undertaking underlie diseases, aging, and cancer. Despite the vital importance of the 3D nuclear organization and regulation, methodologies to infer it robustly and quantitatively from sequencing data are still lacking. To address this need, we developed WaveTAD, a wavelet transform-based method to identify DNA looping structures and assign quantitative strengths in a resolution-free manner. We demonstrate that these strengths correlate with the frequency with which such structures occur in samples and that our methodology is robust to noise and reproducible across biological and technical replicates. The application of WaveTAD to publicly available fruit fly, mouse, and human datasets revealed key insights into the establishment and maintenance of DNA looping structures, as well as the interplay between these structures and gene expression.