Thermo ebook on eQTL - 11

tested show remarkable concordance to microarray data (Figure
5). We confirmed rs10493821,
rs61894779, rs55823844, and
rs6060535 as eQTLs affecting
the expression of GBP3, XRRA1,
LRRC37A17P, and RBM12, respectively. Of the four eQTLs identified in this study, rs10493821,
rs61894779, and rs55823844
have previously been identified
and listed as eQTLs affecting expression of GBP3, XRRA1, and LRRC37A17P, respectively, in lung
tissues in the Genotype-Tissue
Expression (GTEx) project.11
The GTEx project is an ongoing
effort to build a comprehensive public resource to study
tissue-specific gene expression
and regulation. SNP rs6060535,
however, has not been previously reported as an eQTL affecting
RBM12, and this is a potentially
new finding. Note that the direction of signal plots between
microarray and qPCR data in Figure 3 and 5 appear to be mirror
images, since microarrays report
expression levels as signal intensities where higher signal corresponds to higher expression,
while qPCR reports expression
as Ct where lower Ct corresponds
to higher expression. Although
qPCR data for the other SNPs
agreed with microarray data, the
results did not rise to the level of
statistical significance with this

Figure 4. A three-cluster allelic discrimination plot generated by TaqMan
Genotyping Assay C__89363602_10 targeting SNP rs55823844. Scatter plot
showing genotype calls for 93 samples tested in quadruplicate. A TaqMan SNP
Genotyping Assay was used to confirm SNP genotyping calls for rs55823844.
qPCR was run on the ViiA 7 system, and data was analyzed on the GT app. In
the plot, each of the homozygous alleles are represented by red (GG) or blue
(AA) dots, while heterozygous alleles are in green (G/A). Samples that did not
amplify are highlighted by yellow rings.
number of samples. Analysis of
more samples may confirm or reject these putative eQTLs as being statistically significant.

Summary
Although GWAS studies have
been instrumental in identifying
SNPs that are associated with
diseases or phenotypic traits,

up to 90% of these SNPs map
to noncoding regions, making
the molecular mechanisms of
these associations difficult to interpret. It is possible that these
SNPs function by altering the
expression of genes. These SNPs
may therefore be categorized as
eQTLs, which have become extremely valuable tools in understanding molecular mechanisms

Thermo ebook on eQTL

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