ArticleNAR genomics and bioinformatics2020
Analysis of the structural variability of topologically associated domains as revealed by Hi-C.
Article in NAR genomics and bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 42 citations in OpenAlex.
- Systematic evaluation of the heterogeneity of topologically associating domain boundaries in a large genomic context in humans.NAR genomics and bioinformatics · 2026Article
- Integrating Hi-C data and RNA-seq data to reveal the 3D genome in sheep.BMC genomics · 2025Article
- A 3D genome compendium of breast cancer progression.iScience · 2025Article
- HiC4D-SPOT: a spatiotemporal outlier detection tool for Hi-C data.Briefings in bioinformatics · 2025Article
- Article
- RobusTAD: reference panel based annotation of nested topologically associating domains.Genome biology · 2025Article
- Hi-C profiling in tissues reveals 3D chromatin-regulated breast tumor heterogeneity informing a looping-mediated therapeutic avenue.Cell reports · 2025Article
- An integrative TAD catalog in lymphoblastoid cell lines discloses the functional impact of deletions and insertions in human genomes.Genome research · 2024Article
- A constitutive heterochromatic region shapes genome organization and impacts gene expression in Neurospora crassa.BMC genomics · 2024Article
- A Constitutive Heterochromatic Region Shapes Genome Organization and Impacts Gene Expression inbioRxiv : the preprint server for biology · 2024Article
- Machine Learning Reveals the Diversity of Human 3D Chromatin Contact Patterns.Molecular biology and evolution · 2024Article
- DiffGR: Detecting Differentially Interacting Genomic Regions from Hi-C Contact Maps.Genomics, proteomics & bioinformatics · 2024Article
- The 3D Genome in Brain Development: An Exploration of Molecular Mechanisms and Experimental Methods.Neuroscience insights · 2024Review
- Machine learning reveals the diversity of human 3D chromatin contact patterns.bioRxiv : the preprint server for biology · 2023Article
- A comparison of topologically associating domain callers over mammals at high resolution.BMC bioinformatics · 2022Article
- Epigenetic landscapes of intracranial aneurysm risk haplotypes implicate enhancer function of endothelial cells and fibroblasts in dysregulated gene expression.BMC medical genomics · 2021Article
- Deciphering hierarchical organization of topologically associated domains through change-point testing.BMC bioinformatics · 2021Article
- A TAD Skeptic: Is 3D Genome Topology Conserved?Trends in genetics : TIG · 2021Review
- Topologically associating domain boundaries that are stable across diverse cell types are evolutionarily constrained and enriched for heritability.American journal of human genetics · 2021Article
- Profiling of 3D Genome Organization in Nasopharyngeal Cancer Needle Biopsy Patient Samples by a Modified Hi-C Approach.Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Three-dimensional chromosome structure plays an integral role in gene expression and regulation, replication timing, and other cellular processes. Topologically associated domains (TADs), building blocks of chromosome structure, are genomic regions with higher contact frequencies within the region than outside the region. A central question is the degree to which TADs are conserved or vary between conditions. We analyze 137 Hi-C samples from 9 studies under 3 measures to quantify the effects of various sources of biological and experimental variation. We observe significant variation in TAD sets between both non-replicate and replicate samples, and provide initial evidence that this variability does not come from genetic sequence differences. The effects of experimental protocol differences are also measured, demonstrating that samples can have protocol-specific structural changes, but that TADs are generally robust to lab-specific differences. This study represents a systematic quantification of key factors influencing comparisons of chromosome structure, suggesting significant variability and the potential for cell-type-specific structural features, which has previously not been systematically explored. The lack of observed influence of heredity and genetic differences on chromosome structure suggests that factors other than the genetic sequence are driving this structure, which plays an important role in human disease and cellular functioning.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.