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Molecular Systems Biology
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Molecular Systems Biology
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Molecular Systems Biology
Article . 2010
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Identifying the genetic determinants of transcription factor activity

Authors: Eunjee Lee; Harmen J Bussemaker;

Identifying the genetic determinants of transcription factor activity

Abstract

Analysis of parallel genotyping and expression profiling data has shown that mRNA expression levels are highly heritable. Currently, only a tiny fraction of this genetic variance can be mechanistically accounted for. The influence of trans ‐acting polymorphisms on gene expression traits is often mediated by transcription factors (TFs). We present a method that exploits prior knowledge about the in vitro DNA‐binding specificity of a TF in order to map the loci (‘aQTLs’) whose inheritance modulates its protein‐level regulatory activity. Genome‐wide regression of differential mRNA expression on predicted promoter affinity is used to estimate segregant‐specific TF activity, which is subsequently mapped as a quantitative phenotype. In budding yeast, our method identifies six times as many locus‐TF associations and more than twice as many trans ‐acting loci as all existing methods combined. Application to mouse data from an F2 intercross identified an aQTL on chromosome VII modulating the activity of Zscan4 in liver cells. Our method has greatly improved statistical power over existing methods, is mechanism based, strictly causal, computationally efficient, and generally applicable.

Related Organizations
Keywords

Medicine (General), QH301-705.5, Quantitative Trait Loci, Article, Chromosomes, Mice, R5-920, transcription factors, Animals, Humans, Biology (General), gene regulatory networks, Alleles, Crosses, Genetic, Genome, Models, Genetic, Mice, Inbred C57BL, Liver, Mice, Inbred DBA, genetic variation, quantitative trait loci, Saccharomycetales, gene expression, Regression Analysis, Transcription Factors

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    popularity
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    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
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gold