Abstract
Many investigations have reported the successful mapping of quantitative trait loci (QTLs) for gene expression phenotypes (eQTLs). Local eQTLs, where expression phenotypes map to the genes themselves, are of especially great interest, because they are direct candidates for previously mapped physiological QTLs. Here we show that many mapped local eQTLs in genetical genomics experiments do not reflect actual expression differences caused by sequence polymorphisms in cis-acting factors changing mRNA levels. Instead they indicate hybridization differences caused by sequence polymorphisms in the mRNA region that is targeted by the microarray probes. Many such polymorphisms can be detected by a sensitive and novel statistical approach that takes the individual probe signals into account. Applying this approach to recent mouse and human eQTL data, we demonstrate that indeed many local eQTLs are falsely reported as “cis-acting” or “cis” and can be successfully detected and eliminated with this approach.
Highlights
Genetical genomics–linkage and association analyses of, for example, gene expression phenotypes with the help of microarray data – is a promising strategy to identify regulatory determinants of complex traits or diseases [1,2,3]
In an extensive genetical genomics experiment using Affymetrix arrays on 57 CEPH individuals, thirteen putative cis eQTLs were found in immortalized lymphoblastoid cells [9]
To assess the utility of our method, we focused on the 32 known SNPs between B6 and D2 in probes of the 100 most significant putative cis eQTLs
Summary
Genetical genomics–linkage and association analyses of, for example, gene expression phenotypes with the help of microarray data – is a promising strategy to identify regulatory determinants of complex traits or diseases [1,2,3]. The genetical genomics approach treats the gene expression phenotypes for each individual gene over microarrays as quantitative trait. Cis eQTLs may identify direct targets for diagnosis and treatment. The mRNA that is identical to the probes on the microarrays hybridizes better than the mRNA that is not identical to those probes This causes a difference in signal between individuals with different mRNA variants, even if they have equal amounts of mRNA (gene expression). We show more examples and clearly demonstrate how in expression data from human and mouse, polymorphisms in the mRNA sequence are often falsely interpreted as cis eQTLs
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