Evidence map›Paper›PMID 19884314›Full record

ArticleGenetics2010

Detection, validation, and downstream analysis of allelic variation in gene expression.

Daniel C Ciobanu, Lu Lu, Khyobeni Mozhui, Xusheng Wang, Manjunatha Jagalur, John A Morris, William L Taylor, Klaus Dietz, Perikles Simon, Robert W Williams

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

40 citing papers in PubMed, 63 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Ethanol's Effect onFrontiers in genetics · 2018
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. GeneNetwork: A Toolbox for Systems Genetics.Methods in molecular biology (Clifton, N.J.) · 2017
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. The genetics of gene expression in complex mouse crosses as a tool to study the molecular underpinnings of behavior traits.Mammalian genome : official journal of the International Mammalian Genome Society · 2014
    Review
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 6 institutions in 2 countries.

Daniel C CiobanuDepartment of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA. dciobanu2@unl.edu
Lu Lu
Khyobeni Mozhui
Xusheng Wang
Manjunatha Jagalur
John A Morris
William L Taylor
Klaus Dietz
Perikles Simon
Robert W Williams
University of Tennessee Health Science Center · USAllen Institute for Brain Science · USJohannes Gutenberg University Mainz · DEUniversity of Massachusetts Amherst · USUniversity of Nebraska–Lincoln · USUniversity of Tübingen · DE

Funding

Modeling heterogeneity for safe cancer prevention and detectionU01CA105417 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI THREADGILL, DAVID W. · 2004 to 2013
$6.7M
Informatics Center for Mouse NeurogeneticsP20DA021131 · NIDA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI WILLIAMS, ROBERT W. · 2005 to 2009
$5.0M
Systems Genetics of Alcohol Response and Stress Effects in CNSU01AA013499 · NIAAA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI WILLIAMS, ROBERT W. · 2002 to 2016
$4.8M
Genetic Analysis of Ethanol-Mediated Stress ReductionU01AA014425 · NIAAA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI LU, LU · 2004 to 2008
$2.1M
NCI NIH HHS U01 CA105417NCI NIH HHS U01CA105417NIAAA NIH HHS U01 AA013499NIAAA NIH HHS U01AA013499NIAAA NIH HHS U01 AA014425NIAAA NIH HHS U01AA014425NIDA NIH HHS P20 DA021131NIDA NIH HHS P20-DA 21131NINR NIH HHS U01NR 105417
6 · The paper itself

Abstract

Common sequence variants within a gene often generate important differences in expression of corresponding mRNAs. This high level of local (allelic) control-or cis modulation-rivals that produced by gene targeting, but expression is titrated finely over a range of levels. We are interested in exploiting this allelic variation to study gene function and downstream consequences of differences in expression dosage. We have used several bioinformatics and molecular approaches to estimate error rates in the discovery of cis modulation and to analyze some of the biological and technical confounds that contribute to the variation in gene expression profiling. Our analysis of SNPs and alternative transcripts, combined with eQTL maps and selective gene resequencing, revealed that between 17 and 25% of apparent cis modulation is caused by SNPs that overlap probes rather than by genuine quantitative differences in mRNA levels. This estimate climbs to 40-50% when qualitative differences between isoform variants are included. We have developed an analytical approach to filter differences in expression and improve the yield of genuine cis-modulated transcripts to approximately 80%. This improvement is important because the resulting variation can be successfully used to study downstream consequences of altered expression on higher-order phenotypes. Using a systems genetics approach we show that two validated cis-modulated genes, Stk25 and Rasd2, are likely to control expression of downstream targets and affect disease susceptibility.

Indexed as

AllelesComputational BiologyGene Expression Profiling3' Untranslated RegionsAlternative SplicingAnimalsDatabases, GeneticGene ExpressionHumansMiceOligonucleotide Array Sequence AnalysisPolymerase Chain ReactionPolymorphism, Single NucleotideQuantitative Trait LociReproducibility of ResultsRNA, Messenger3' Untranslated RegionsRNA, Messenger

Identifiers

PMID19884314
PMCPMC2802080
OpenAlexW2133927979

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.