Evidence map›Paper›PMID 22323522›Full record

ArticleNucleic acids research2012

A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq.

Elizabeth G Wilbanks, David J Larsen, Russell Y Neches, Andrew I Yao, Chia-Ying Wu, Rachel A S Kjolby, Marc T Facciotti

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

32 citing papers in PubMed, 54 citations in OpenAlex.

  1. Article
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  8. Biology · 2022
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  9. Article
  10. ChIP-Seq Occupancy Mapping of the Archaeal Transcription Machinery.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  11. Article
  12. Identifying Components of aFrontiers in microbiology · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Frontiers in microbiology · 2019
    Article
  18. Article
  19. Article
  20. Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells.Methods in molecular biology (Clifton, N.J.) · 2018
    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

7 authors at 1 institution in 1 country.

Elizabeth G WilbanksUniversity of California Davis, Department of Biomedical Engineering and Genome Center, One Shields Avenue, Davis, CA 95616, USA. egwilbanks@ucdavis.edu
David J Larsen
Russell Y Neches
Andrew I Yao
Chia-Ying Wu
Rachel A S Kjolby
Marc T Facciotti
University of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deciphering the structure of gene regulatory networks across the tree of life remains one of the major challenges in postgenomic biology. We present a novel ChIP-seq workflow for the archaea using the model organism Halobacterium salinarum sp. NRC-1 and demonstrate its application for mapping the genome-wide binding sites of natively expressed transcription factors. This end-to-end pipeline is the first protocol for ChIP-seq in archaea, with methods and tools for each stage from gene tagging to data analysis and biological discovery. Genome-wide binding sites for transcription factors with many binding sites (TfbD) are identified with sensitivity, while retaining specificity in the identification the smaller regulons (bacteriorhodopsin-activator protein). Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors. The Pique package, an open-source bioinformatics method, is presented for identification of binding events. Relative to ChIP-Chip and qPCR, this workflow offers a robust catalog of protein-DNA binding events with improved spatial resolution and significantly decreased cost. While this study focuses on the application of ChIP-seq in H. salinarum sp. NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools.

Indexed as

Chromatin ImmunoprecipitationHigh-Throughput Nucleotide SequencingSequence Analysis, DNAArchaeal ProteinsBinding SitesGenome, ArchaealHalobacterium salinarumSoftwareTranscription FactorsArchaeal ProteinsTranscription Factors

Identifiers

PMID22323522
PMCPMC3378898
OpenAlexW2130248929

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.