ArticleMethods (San Diego, Calif.)2018
Using DNase Hi-C techniques to map global and local three-dimensional genome architecture at high resolution.
Article in Methods (San Diego, Calif.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 30 citations in OpenAlex.
- Article
- The pathway of autophagy in the epigenetic landscape ofAutophagy · 2025Review
- A chromosome-level reference genome assembly and a full-length transcriptome assembly of the giant freshwater prawn (Macrobrachium rosenbergii).G3 (Bethesda, Md.) · 2024Article
- dcHiC detects differential compartments across multiple Hi-C datasets.Nature communications · 2022Article
- The macro and micro of chromosome conformation capture.Wiley interdisciplinary reviews. Developmental biology · 2021Review
- A cookbook for DNase Hi-C.Epigenetics & chromatin · 2021Article
- Stress Conditions Modulate the Chromatin Interactions Network inFrontiers in genetics · 2021Article
- Targeted DNase Hi-C.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Methods for mapping 3D chromosome architecture.Nature reviews. Genetics · 2020Review
- HIFI: estimating DNA-DNA interaction frequency from Hi-C data at restriction-fragment resolution.Genome biology · 2020Article
- Sci-Hi-C: A single-cell Hi-C method for mapping 3D genome organization in large number of single cells.Methods (San Diego, Calif.) · 2020Article
- Article
- OCEAN-C: mapping hubs of open chromatin interactions across the genome reveals gene regulatory networks.Genome biology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 3 institutions in 1 country.
Funding
Abstract
The folding and three-dimensional (3D) organization of chromatin in the nucleus critically impacts genome function. The past decade has witnessed rapid advances in genomic tools for delineating 3D genome architecture. Among them, chromosome conformation capture (3C)-based methods such as Hi-C are the most widely used techniques for mapping chromatin interactions. However, traditional Hi-C protocols rely on restriction enzymes (REs) to fragment chromatin and are therefore limited in resolution. We recently developed DNase Hi-C for mapping 3D genome organization, which uses DNase I for chromatin fragmentation. DNase Hi-C overcomes RE-related limitations associated with traditional Hi-C methods, leading to improved methodological resolution. Furthermore, combining this method with DNA capture technology provides a high-throughput approach (targeted DNase Hi-C) that allows for mapping fine-scale chromatin architecture at exceptionally high resolution. Hence, targeted DNase Hi-C will be valuable for delineating the physical landscapes of cis-regulatory networks that control gene expression and for characterizing phenotype-associated chromatin 3D signatures. Here, we provide a detailed description of method design and step-by-step working protocols for these two methods.
Indexed as
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.