Evidence map›Paper›PMID 29683440›Full record

ArticleJournal of visualized experiments : JoVE2018

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues.

Christopher Terranova, Ming Tang, Elias Orouji, Mayinuer Maitituoheti, Ayush Raman, Samirkumar Amin, Zhiyi Liu, Kunal Rai

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

18 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
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  8. Epigenetics of alcohol-related liver diseases.JHEP reports : innovation in hepatology · 2022
    Review
  9. Article
  10. Review
  11. Article
  12. Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine.Biochimica et biophysica acta. Reviews on cancer · 2021
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

8 authors at 2 institutions in 1 country.

Christopher TerranovaDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center.
Ming TangDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center.
Elias OroujiDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center.
Mayinuer MaitituohetiDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center.
Ayush RamanDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center.
Samirkumar AminThe Jackson Laboratory for Genomic Medicine.
Zhiyi LiuDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center.
Kunal RaiDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center; krai@mdanderson.org.
The University of Texas MD Anderson Cancer Center · USJackson Laboratory · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Epigenetics of Melanoma MetastasisR00CA160578 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RAI, KUNAL · 2015 to 2017
$747k
Epigenetics of Melanoma MetastasisK99CA160578 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RAI, KUNAL · 2011 to 2012
$284k
NCI NIH HHS K99 CA160578NCI NIH HHS P30 CA016672NCI NIH HHS R00 CA160578
6 · The paper itself

Abstract

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.

Indexed as

ChromatinChromatin ImmunoprecipitationChromosome MappingHigh-Throughput Nucleotide SequencingHumansChromatin

Identifiers

PMID29683440
PMCPMC5933412
OpenAlexW2795679464

What OpenQuestion holds

Textmetadata
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.