Evidence map›Paper›PMID 20061373›Full record

SynthesisNucleic acids research2010

Genome-wide identification of hypoxia-inducible factor binding sites and target genes by a probabilistic model integrating transcription-profiling data and in silico binding site prediction.

Amaya Ortiz-Barahona, Diego Villar, Nuria Pescador, Jorge Amigo, Luis del Peso

Open access · goldAbstract readMeta-AnalysisValidation Study
In one paragraph

Synthesis in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
125citing papers in PubMed, 2 pooled it
4.4field-weighted citation impact, top 5% 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

125 citing papers in PubMed, 2 syntheses or guidelines pooled it, 215 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  6. Placental mitochondria in high-altitude pregnancy: metabolic adaptations and a toolkit for respiratory assessment.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
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  11. Article
  12. Article
  13. Review
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  15. Article
  16. Structure-guided optimisation ofChemical science · 2023
    Article
  17. Article
  18. Review
  19. Article
  20. Review

65 more citing papers are in PubMed but not listed here.

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.

Amaya Ortiz-BarahonaDepartment of Biochemistry, Universidad Autónoma de Madrid-Instituto de Investigaciones Biomédicas CSIC, Madrid, Spain.
Diego Villar
Nuria Pescador
Jorge Amigo
Luis del Peso
Universidad Autónoma de Madrid · ESFundación Pública Galega de Medicina Xenómica · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transcriptional response driven by Hypoxia-inducible factor (HIF) is central to the adaptation to oxygen restriction. Hence, the complete identification of HIF targets is essential for understanding the cellular responses to hypoxia. Herein we describe a computational strategy based on the combination of phylogenetic footprinting and transcription profiling meta-analysis for the identification of HIF-target genes. Comparison of the resulting candidates with published HIF1a genome-wide chromatin immunoprecipitation indicates a high sensitivity (78%) and specificity (97.8%). To validate our strategy, we performed HIF1a chromatin immunoprecipitation on a set of putative targets. Our results confirm the robustness of the computational strategy in predicting HIF-binding sites and reveal several novel HIF targets, including RE1-silencing transcription factor co-repressor (RCOR2). In addition, mapping of described polymorphisms to the predicted HIF-binding sites identified several single-nucleotide polymorphisms (SNPs) that could alter HIF binding. As a proof of principle, we demonstrate that SNP rs17004038, mapping to a functional hypoxia response element in the macrophage migration inhibitory factor (MIF) locus, prevents induction of this gene by hypoxia. Altogether, our results show that the proposed strategy is a powerful tool for the identification of HIF direct targets that expands our knowledge of the cellular adaptation to hypoxia and provides cues on the inter-individual variation in this response.

Indexed as

Gene Expression ProfilingGene Expression RegulationModels, StatisticalBinding SitesCell HypoxiaCell LineChromatin ImmunoprecipitationCo-Repressor ProteinsGenome, HumanGenomicsHumansHypoxia-Inducible Factor 1, alpha SubunitPolymorphism, Single NucleotideCo-Repressor ProteinsHypoxia-Inducible Factor 1, alpha SubunitRcor2 protein, human

Identifiers

PMID20061373
PMCPMC2853119
OpenAlexW2131078129

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.