Evidence map›Paper›PMID 35848835›Full record

ArticleJournal of visualized experiments : JoVE2022

ATAC-seq Optimization for Cancer Epigenetics Research.

Mikhala Cooper, Atrayee Ray, Atrayee Bhattacharya, Archana Dhasarathy, Motoki Takaku

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Mikhala Cooper *University of North Dakota School of Medicine and Health Sciences.
Atrayee Ray *University of North Dakota School of Medicine and Health Sciences.
Atrayee BhattacharyaDana-Farber Cancer Institute.
Archana DhasarathyUniversity of North Dakota School of Medicine and Health Sciences.
Motoki TakakuUniversity of North Dakota School of Medicine and Health Sciences; motoki.takaku@und.edu.
University of North Dakota · USDana-Farber Cancer Institute · US

Funding

The role of class IIa Hdac in regulating cell fate choice in early cortical development.P20GM104360 · NIGMS · UNIVERSITY OF NORTH DAKOTA · PI VAUGHAN, ROXANNE A · 2013 to 2023
$21.1M
NIGMS NIH HHS P20 GM104360
6 · The paper itself

Abstract

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the hyperactive Tn5 transposase. Tn5 cuts and ligates adapters for high-throughput sequencing within accessible chromatin regions. In eukaryotic cells, genomic DNA is packaged into chromatin, a complex of DNA, histones, and other proteins, which acts as a physical barrier to the transcriptional machinery. In response to extrinsic signals, transcription factors recruit chromatin remodeling complexes to enable access to the transcriptional machinery for gene activation. Therefore, identifying open chromatin regions is useful when monitoring enhancer and gene promoter activities during biological events such as cancer progression. Since this protocol is easy to use and has a low cell input requirement, ATAC-seq has been widely adopted to define open chromatin regions in various cell types, including cancer cells. For successful data acquisition, several parameters need to be considered when preparing ATAC-seq libraries. Among them, the choice of cell lysis buffer, the titration of the Tn5 enzyme, and the starting volume of cells are crucial for ATAC-seq library preparation in cancer cells. Optimization is essential for generating high-quality data. Here, we provide a detailed description of the ATAC-seq optimization methods for epithelial cell types.

Indexed as

Chromatin Immunoprecipitation SequencingNeoplasmsChromatinDNAEpigenesis, GeneticHigh-Throughput Nucleotide SequencingSequence Analysis, DNATranscription FactorsChromatinDNATranscription Factors

Identifiers

PMID35848835
PMCPMC10064075
OpenAlexW4283762216

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.