Journal article
A wavelet-based approach generates quantitative, scale-free and hierarchical descriptions of 3D genome structures and new biological insights
PLoS computational biology, Vol.22(1), e1013887
01/20/2026
DOI: 10.1371/journal.pcbi.1013887
PMCID: PMC12829961
PMID: 41557727
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.
Details
- Title: Subtitle
- A wavelet-based approach generates quantitative, scale-free and hierarchical descriptions of 3D genome structures and new biological insights
- Creators
- Ryan Pellow - University of IowaJosep M Comeron - University of Iowa
- Resource Type
- Journal article
- Publication Details
- PLoS computational biology, Vol.22(1), e1013887
- DOI
- 10.1371/journal.pcbi.1013887
- PMID
- 41557727
- PMCID
- PMC12829961
- NLM abbreviation
- PLoS Comput Biol
- ISSN
- 1553-7358
- eISSN
- 1553-7358
- Publisher
- PUBLIC LIBRARY SCIENCE
- Grant note
- National Institute on Aging: R01AG081263 National Science Foundation: DEB1354921
This work was supported by the National Science Foundation DEB1354921 to J.C. (https://nsf.gov/); and the National Institutes of Health's National Institute on Aging R01AG081263-01A1 to J.C. (https://www.nia.nih.gov/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Language
- English
- Date published
- 01/20/2026
- Academic Unit
- Biology
- Record Identifier
- 9985130062202771
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