Evidence map›Paper›PMID 19919681›Full record

ArticleGenome biology2009

Differential binding and co-binding pattern of FOXA1 and FOXA3 and their relation to H3K4me3 in HepG2 cells revealed by ChIP-seq.

Mehdi Motallebipour, Adam Ameur, Madhu Sudhan Reddy Bysani, Kalicharan Patra, Ola Wallerman, Jonathan Mangion, Melissa A Barker, Kevin J McKernan, Jan Komorowski, Claes Wadelius

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
2.3field-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

46 citing papers in PubMed, 69 citations in OpenAlex.

  1. Article
  2. Veterinary sciences · 2026
    Article
  3. Article
  4. PRKAG2.2 is essential for FoxA1Science advances · 2023
    Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Pioneer transcription factors, chromatin dynamics, and cell fate control.Current opinion in genetics & development · 2016
    Review
  20. 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

10 authors at 2 institutions in 3 countries.

Mehdi MotallebipourDepartment of Genetics and Pathology, Uppsala University, Rudbeck Laboratory, Dag Hammarskjölds väg 20, Uppsala SE-75185, Sweden. mehdi.motallebipour@imperial.ac.uk
Adam Ameur
Madhu Sudhan Reddy Bysani
Kalicharan Patra
Ola Wallerman
Jonathan Mangion
Melissa A Barker
Kevin J McKernan
Jan Komorowski
Claes Wadelius
Uppsala University · SEMicrosystems (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe forkhead box/winged helix family members FOXA1, FOXA2, and FOXA3 are of high importance in development and specification of the hepatic linage and the continued expression of liver-specific genes.

resultsHere, we present a genome-wide location analysis of FOXA1 and FOXA3 binding sites in HepG2 cells through chromatin immunoprecipitation with detection by sequencing (ChIP-seq) studies and compare these with our previous results on FOXA2. We found that these factors often bind close to each other in different combinations and consecutive immunoprecipitation of chromatin for one and then a second factor (ChIP-reChIP) shows that this occurs in the same cell and on the same DNA molecule, suggestive of molecular interactions. Using co-immunoprecipitation, we further show that FOXA2 interacts with both FOXA1 and FOXA3 in vivo, while FOXA1 and FOXA3 do not appear to interact. Additionally, we detected diverse patterns of trimethylation of lysine 4 on histone H3 (H3K4me3) at transcriptional start sites and directionality of this modification at FOXA binding sites. Using the sequence reads at polymorphic positions, we were able to predict allele specific binding for FOXA1, FOXA3, and H3K4me3. Finally, several SNPs associated with diseases and quantitative traits were located in the enriched regions.

conclusionsWe find that ChIP-seq can be used not only to create gene regulatory maps but also to predict molecular interactions and to inform on the mechanisms for common quantitative variation.

Indexed as

AllelesCell LineageChromatin ImmunoprecipitationGene Expression ProfilingGene LibraryGenomeHepatocyte Nuclear Factor 3-alphaHepatocyte Nuclear Factor 3-betaHepatocyte Nuclear Factor 3-gammaHep G2 CellsHistonesHumansLiverModels, GeneticPromoter Regions, GeneticFOXA1 protein, humanFOXA2 protein, humanFOXA3 protein, humanHepatocyte Nuclear Factor 3-alphaHepatocyte Nuclear Factor 3-betaHepatocyte Nuclear Factor 3-gammaHistones

Identifiers

PMID19919681
PMCPMC3091322
OpenAlexW2159228663

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.