Study of Transcriptional Effects in Cis at the IFIH1 Locus
Hana Zouk1,2, Luc Marchand1, Constantin Polychronakos1,2,3*
1Endocrine Genetics Laboratory, McGill University Health Center, Montreal Children’s Hospital Research Institute, McGill University, Montreal, Quebec, Canada,
2Department of Human Genetics, McGill University, Montreal, Quebec, Canada, 3Department of Paediatrics, McGill University Health Centre, Montreal, Quebec, Canada
Background: The Thr allele at the non-synonymous single-nucleotide polymorphism (nsSNP) Thr946Ala in the IFIH1 gene
confers risk for Type 1 diabetes (T1D). The SNP is embedded in a 236 kb linkage disequilibrium (LD) block that includes four
genes: IFIH1, GCA, FAP and KCNH7. The absence of common nsSNPs in the other genes makes the IFIH1 SNP the strongest
functional candidate, but it could be merely a marker of association, due to LD with a variant regulating expression levels of
IFIH1 or neighboring genes.
Methodology/Principal Findings: We investigated the effect of the T1D-associated variation on mRNA transcript expression
of these genes. Heterozygous mRNA from lymphoblastoid cell lines (LCLs), pancreas and thymus was examined by allelic
expression imbalance, to detect effects in cis on mRNA expression. Using single-nucleotide primer extension, we found no
difference between mRNA transcripts in 9 LCLs, 6 pancreas and 13 thymus samples, suggesting that GCA and FAP are not
involved. On the other hand, KCNH7 was not expressed at a detectable level in all tissues examined. Moreover, the
association of the Thr946Ala SNP with T1D is not due to modulation of IFIH1 expression in organs involved in the disease,
pointing to the IFIH1 nsSNP as the causal variant.
Conclusions/Significance: The mechanism of the association of the nsSNP with T1D remains to be determined, but does
not involve mRNA modulation. It becomes necessary to study differential function of the IFIH1 protein alleles at Thr946Ala
to confirm that it is responsible for the disease association.
Citation: Zouk H, Marchand L, Polychronakos C (2010) Study of Transcriptional Effects in Cis at the IFIH1 Locus. PLoS ONE 5(7): e11564. doi:10.1371/
Editor: Adrian Vella, Mayo Clinic College of Medicine, United States of America
Received April 25, 2010; Accepted June 14, 2010; Published July 13, 2010
Copyright: ? 2010 Zouk et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was funded by the Juvenile Diabetes Research Foundation International. HZ is supported by a doctoral scholarship from the Fonds de
Recherche en Sante du Quebec. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
Type 1 diabetes (T1D) is a complex disease involving both
genetic and environmental factors. This is largely attributed to
genetic variation among individuals at several loci. One of them
involves the IFIH1 gene (interferon-induced helicase 1) where the
Thr allele at the Thr946Ala polymorphism increases T1D risk .
The associated SNP (rs1990760) is embedded in a 236 kb linkage
disequilibrium (LD) block on Chr 2q24.3 that includes four genes:
IFIH1, also known as helicard or MDA-5 (melanoma differentiation
associated gene-5); GCA (grancalcin); FAP (fibroblast activation
protein a subunit) and KCNH7 (potassium voltage gated channel
subfamily H7), any of which could harbor a T1D-associated
functional variant. IFIH1 belongs to a family of RNA helicases
that bind double-stranded viral RNA [2,3] and induces a type I
interferon anti-viral response . This is particularly interesting
given the evidence for a role of enteroviruses in the etiology of
T1D [5–7]. The recent discovery of rare nsSNPs in IFIH1
protective of T1D , two of which involve loss of function ,
strongly supports it as the gene involved, but locus heterogeneity
remains a possibility given that thousands of loci with weak effects
likely account for each complex trait . GCA encodes a calcium
binding protein that is expressed in most immune cells and is
associated with degranulation, and consequently, immune reaction
. FAP encodes a human stromal antigen, which can in turn
activate a T-cell mediated cellular response . KCNH7 encodes
a potassium voltage-gated channel which has many roles, most
notably, the regulation of insulin secretion . Hence, all genes at
the IFIH1 locus may be interesting potential candidates in the
etiology of T1D even though nsSNPs are more likely to have
functional effects. Therefore, the IFIH1 nsSNP obviously remains
the strongest functional candidate; however, the fact that it could
be merely a marker of association that tags another variant
regulating expression levels of IFIH1 or of neighboring genes, must
be ruled out. In the same paper that reported the functional effect
of the rare IFIH1 SNPs, the Thr946Ala nsSNP was not found to
have any effect of protein function . However, because a
transfection system was used, where IFIH1 alleles are over-
expressed, small differences between them may not be detectable.
Allele-dependent specificities for sequence, length, or other
characteristics of specific viral RNAs would also not have been
Recently, transcriptional effects at the IFIH1 locus were
reported by Liu et al.  involving 40% higher expression of
the predisposing allele in peripheral blood mononuclear cells
(PBMCs) by real-time PCR. Such a large difference in allelic
expression ought to be easily detectable in large-scale, whole
transcriptome searches of quantitative effects in cis. However, in
such a genome wide association study of global gene expression in
lymphoblastoid cell lines (LCLs) of 400 children using more than
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400,000 SNPs, no transcriptional effects in cis were observed on
the IFIH1 locus or any of the surrounding regions . In another
paper using the same methodology as Liu et al. , IFIH1 allelic
expression differences were not observed . This inconsistence
in reported results could be due to the fact that both groups
compared mRNA levels among individuals of different genotypes.
This has the disadvantage of introducing a large amount of
background noise from different individuals’ immune experience,
loci in trans , quality of RNA extraction (including mRNA
degradation), assay variance, loading normalization, etc., making
it difficult to properly detect the typically small functional effects
seen at complex-trait loci. A much more robust approach to
measure mRNA variation, known as allelic expression imbalance
(AI), removes this noise by comparing expression levels of the two
alleles originating from the same individual in samples heterozy-
gous for a transcribed SNP. This method has been well validated
in our laboratory [18,19], and others [17,20–23].
AI could stem from allele-dependent effects of one or more
polymorphisms in cis that alter promoter function as well as that of
other regulatory elements such as enhancers and silencers,
potentially affecting transcription or RNA stability. Thus, the
presence of a regulatory polymorphism that is in LD with the
marker SNP could result in AI .
In AI assays, each allele acts as an internal control for
confounding factors that alter the overall expression of the gene
in question, thus maximizing the sensitivity of detecting effects in
cis on mRNA expression in the same RNA sample, from the same
individual. In samples that are heterozygous for a cis-acting
regulatory variant, one allele will be expressed at a higher level
than the other [21,24,25]. Heterozygous genomic DNA from the
same source is used as a control for 1:1 stoichiometry . It is
worth noting that another advantage of AI is that this assay relies
on the comparison of allelic ratio in DNA and mRNA of each
individual. Thus, it automatically controls for any polymorphisms
present in the primer sites or copy number variation encompassing
the gene studied, which normally exert a similar effect on both
DNA and mRNA .
The purpose of this study was to investigate the effect of the
T1D-associated variation on mRNA expression of IFIH1 and all
other genes in the LD block by allelic expression imbalance, using
single-nucleotide primer extension (SNuPE) on RT-PCR products
of heterozygous lymphocyte, thymic and pancreatic RNA samples,
to cover tissues most important in T1D.
Materials and Methods
The T1D-associated SNP, rs1990760 (T946A), was selected to
assess its effect on IFIH1 expression levels. An intronic SNP was
selected for each of the other 3 genes since there are no suitable
common exonic SNPs. Intronic SNPs have been shown to yield
similar allelic expression levels to those obtained using exonic
SNPs, provided that the genes are highly expressed in the tissue
sample, and that the unspliced mRNA (or heteronuclear RNA
[hnRNA]) can be successfully amplified and detected . The
three selected intronic SNPs were in high LD with each other and
with the rs1990760 SNP (r2=0.513–0.739) (Table 1), and had
higher minor allele frequencies (MAF=0.398–0.492) than the
T1D-associated SNP (MAF=0.392), in order to maximize the
number of heterozygotes obtained.
Lymphoblastoid cell lines (LCLs) from the CEU collection were
used. These were unrelated individuals residing in Utah with
ancestry from western and northern Europe genotyped for
millions of SNPs genome-wide, as part of the HapMap project.
LCL samples heterozygous for all of the chosen SNPs were grown
in RPMI 1640 medium (Gibco, CA, USA), supplemented with
penicillin/streptomycin, 2mM L-glutamine, non-essential amino
acids, and 15% heat-inactivated fetal bovine serum (Multicell, RI,
USA). Cells were pelleted when they reached a density of about
1.06106cells/ml. Thymic and pancreatic samples were obtained
from our collection of frozen fetal tissues as previously described
[18,27]. Written informed consent was obtained from all
individuals included in this study and was approved by the
Research Ethics Board of the hospitals where the recruitments
took place: for LCLs, under the auspices of the Centre de L’ ’e ´tude
du Polymorphisme Humain, Paris, France; for thymic and
pancreatic samples, by the Royal Victoria Hospital Research
Ethics Board (McGill University Health Centre), Montre ´al,
Que ´bec, Canada.
DNA and RNA extraction
Extraction of nucleic acids from pancreatic and thymic tissues
has been described elsewhere , and RNA integrity was
assessed by the 2100 Bioanalyzer (Agilent, CA, USA). LCL
genomic DNA was extracted using the QIAamp DNA Mini Kit
(Qiagen, Germany) and RNA was isolated using the RNeasy Plus
Mini Kit (Qiagen, Germany) following the manufacturer’s
cDNA synthesis and PCR
In a typical reaction, 2.5 mg aliquots of total RNA were treated
with 1 U of DNAse I for 30 minutes at 37uC following the
manufacturer’s protocol (Ambion, TX, USA). Reverse transcrip-
tion (RT) was carried out under standard conditions using random
hexamer primers (Invitrogen, CA, USA) and 1000 ng of total
unfragmented RNA, or RNA that has been subjected to chemical
fragmentation according to the manufacturer’s protocol (Ambion,
TX, USA), along with SuperScript II reverse transcriptase
according to the manufacturer’s instructions (Invitrogen, CA,
USA). RNA was also primed with oligo-dt primers. No detectable
Table 1. Pairwise Linkage Disequilibrium Coefficients of SNPs at the IFIH1 locus.
SNPsrs1990760 (IFIH1)rs7587426 (GCA)rs2075302 (FAP)rs2068330 (KCNH7)
rs1990760 (IFIH1)-0.700 0.5130.738
rs7587426 (GCA) 0.959- 0.5860.643
rs2075302 (FAP)0.908 0.846- 0.370
Numbers in bold represent D9 values (lower diagonal), upper diagonal represent R2values.
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levels of RT-PCR product were observed in RNA samples if
reverse transcriptase was omitted. PCR amplification for genomic
DNA and cDNA samples for IFIH1, (along with a minus-RT
control) was carried out using primers that amplify exon 15 and
thus are capable of amplifying both DNA and cDNA. All other
genes were studied using primers located in intronic regions, thus
amplifying hnRNA and DNA. Primer and probe sequences are
listed in Table S1. To ensure uniform conditions, each cDNA
sample was assayed with its corresponding heterozygous genomic
Briefly, 40 ng of DNA or cDNA were combined with 10 mM of
each primer pair, 10 mM dNTPs, 50 mM MgCl2, 16 PCR
Buffer, and 0.3 U of Taq Polymerase (Invitrogen, CA, USA), in a
total volume of 25 mL. Each PCR reaction consisted of an initial
denaturation step at 94uC for 5 min, followed by 35 cycles of
denaturation at 94uC for 30 s; annealing at 49.5uC for IFIH1 for
30 s and extension at 72uC for 30 s, as well as a final extension
step of 7 min. GCA, FAP and KCNH7 were amplified using the
same conditions as described above, with an annealing temper-
ature of 56.5uC. PCR products were subjected to electrophoresis
in a 1.5% agarose gel. All samples were run in parallel for each
gene in each tissue type.
Single nucleotide primer extension (SNuPE)
In order to identify heterozygotes for the chosen marker
polymorphisms, 38 thymic and 23 pancreatic samples were initially
genotyped using single nucleotide primer extension with dideoxy-
to each allele[23,29,30].Briefly, the PCR amplicons wereextracted
and purified from agarose gels using columns from the QIAquick
Gel Extraction Kit (Qiagen, Germany), following the manufactur-
er’s protocol. Primer extension was then carried out by combining
2 mL of the purified PCR product with 5 mL of the ABI Prism
SNaPshot Multiplex Kit (Applied Biosystems, CA, USA), 2.5 mM of
the appropriate extension probe, and 3 mL of water, in a total
volume of 10 mL. Primer extension thermocycling conditions
consisted of an initial step of 95uC for 2 minutes, followed by 25
cycles of 95uC for 10s, and 60uC for 35 s for IFIH1. For the other
genes, the denaturation step of 95uC for 10s was followed by cycling
at 50uC for 5s then 60uC for 30s. Following primer extension, the
products were treated with 1 U of shrimp alkaline phosphatase
(Roche, IN, USA) to remove unincorporated ddNTPs, for 1 hr at
37uC, and then the enzyme was deactivated for 15 min at 75uC.
Aliquots of 1 mL of SnaPshot product and 9 mL of Hi-Di formamide
were loaded into a 3100 DNA sequencer (Applied Biosystems,
CA,USA). Products were electrophoresed on a 36-cm capillary
array at 60uC. As with cDNA synthesis and PCR steps, all samples
were run simultaneously for each gene in each tissue type. Data was
processed using Genescan Analysis version 3.7 software (Applied
Biosystems, CA,USA). Peak heights representing allele-specific
extended primers were calculated using GeneScan in order to
generate a ratio of allelic representation. The area under the curve
of the peak representing a particular allele is proportional to the
abundance of that allele in the sample. Once heterozygous samples
were identified, they were re-run simultaneously with their
corresponding cDNA to evaluate the relative abundance of the
two alleles at a particular polymorphism, using the same protocol.
from genomic DNA as a control for 1:1 stoichiometry, or a 50:50
allele ratio. For reproducibility purposes, all samples showing a
relative alleledifferencegreaterthan 40% thanthegenomic average
would be retested two more times, in two separate RT-PCR
reactions, along with the corresponding genomic DNA. This was
not necessary, as all allele ratios fell within the 40% range.
The ratio of one allele over the other for each SNP was calculated
genomic ratio for that assay batch in order to account for differences
in probe and fluorochrome efficiencies. Peak height ratios corre-
sponding to each allele in individual DNA samples ranged from 0.79
to 1.21 for IFIH1, from 0.80 to 1.35 for GCA, and from 0.93 to 1.06
for FAP SNP.Allelicexpression differences between DNA and cDNA
were evaluated by the student t test for statistical significance. A two-
tailed level of 0.05 was chosen for a type I error rate. Power analysis
was calculated for detection of a 40% difference in relativeexpression
of the two alleles, at a=0.01 (similar to Liu et al. ).
Our working sample was comprised of 9 LCL, 13 thymus, and 6
pancreas samples that were found to be heterozygous for all four
SNPs. IFIH1 and GCA gene expression was detected in all LCL,
thymus and pancreas samples. FAP was exclusively expressed in
pancreas and thymus, but not LCLs. We were not able to detect
KCNH7 expression in any of the three tissues.
The calculated allelic ratios for each SNP representing each gene
in the IFIH1 locus and their distribution in the different tissues that
were assayed are shown in Table 2 and Figure 1 respectively. The
allelic ratio distribution of IFIH1, GCA, and FAP cDNA do not
significantly differ from that of their corresponding DNA. After
correction by the genomic DNA allele proportion, the average ratio
(mean 6SEM) ofthemajorallele(T) over the minorallele(C)ofthe
rs1990760 SNP in IFIH1 in LCLs is 1.002960.0106, p=0.8477
(Table 2), indicating the absence of an AI effect due to a common
genetic variation at the IFIH1 gene in LCLs. The same is observed
in pancreas and thymus. No evidence of significant transcriptional
effect was seen in any of the othergenes inallthe assayed tissues and
cells (Table 2).Our approach had a 99% power to detect a
transcriptional effect of rs1990760 on IFIH1 in LCLs, of the
magnitude reported by Liu et al.  (40% allelic difference at
a=0.01). We also have 99% power to detect a 25% difference in
expression between the two IFIH1alleles. Since all RNA samples
were DNAse-treated prior to RT-PCR and did not generate
detectable PCR product in the absence of an RT step, it is highly
improbable that our results were influenced in some way by
genomic DNA contamination. It has been recently suggested 
that differential secondary structure of RNA alleles may interfere
with quantitative comparisons through a differential effect on the
efficiency of reverse transcription, creating spurious allelic imbal-
ance or conceivably masking true imbalance (if it happens to be
exactly equal and in the opposite direction). To deal with this,
minimization of secondary structure by fragmenting the RNA prior
to reverse transcription (RT) was recommended. To see whether
this may be a problem in the specific case of IFIH1, we compared
allelic ratios obtained with or without fragmentation of the RNA
prior to RT. In twelve independent comparisons, the mean allelic
ratio (normalized for the average DNA ratio) was 0.9560.07 (SEM)
for unfragmented vs. 1.0060.05 for fragmented RNA (p=0.56,
99% power to detect a 40% effect at a=0.01, 86.7% power to
detect a 25% effect at a=0.05). Oligo-dT priming of the RT,
suggested as an alternative, also gave nearly-identical results
(0.9860.05 [SEM]). We, therefore, concluded that interference by
secondary structure was not an issue in allelic IFIH1 measurements.
The association of the IFIH1 locus with T1D is supported by a
large number of genetic studies [1,32,33]. Yet, the presence of
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Table 2. Summary of difference in allelic variation at the IFIH1 locus.
Gene SNP Alleles Tissue Mean allelic ratio DNA ± SEMa
Mean allelic ratio cDNA ± SEMa
IFIH1 rs1990760T/C LCL1.000060.0077 1.002960.0106 0.8477 100.0%
IFIH1rs1990760 T/CThymus 1.000060.05961.085560.03410.2002 99.9%
IFIH1 rs1990760T/CPancreas 1.000060.1009 1.063060.07910.633470.7%
GCA rs7587426C/T LCL 1.000060.0415 1.093960.06370.237399.6%
GCA rs7587426C/T Thymus1.000060.0435 0.999960.0427 0.9994100.0%
GCArs7587426C/T Pancreas1.000060.17510.884060.0429 0.439336.1%
FAP rs2075302 T/C LCLcould not be detected by PCR,
not expressed in B lymphocytes
FAPrs2075302T/CThymus 1.000060.0375 0.983560.04080.8387100.0%
FAP rs2075302 T/CPancreas 1.000060.0030 1.025160.03210.6606 100.0%
KCNH7 rs2068330 C/G LCLcould not be detected by PCR,
not expressed in B lymphocytes
KCNH7rs2068330C/GThymuscould not be detected by PCR,
not expressed in thymus
KCNH7 rs2068330C/G Pancreas could not be detected by PCR,
not expressed in pancreas
an=9 for LCLs, n=13 for thymus, n=6 for pancreas.
bstatistical significance as measured by the two-tailed student t test.
cstatistical power to detect a 40% difference of expression between alleles, at an a=0.01.
Figure 1. Allelic ratio distribution at the IFIH1 locus. 9 Lymphoblastoid cell lines (LCL), 6 pancreas (Panc.) and 13 thymus (Thym.) tissue from
individuals heterozygous for the selected marker SNPs for each gene were used to assess allelic imbalance at the IFIH1 locus. Relative allelic
abundance in individual samples has been normalized to the mean genomic DNA ratio (equal to1) and normalized sample RNA ratios were compared
to those of normalized genomic DNA for each gene in each tissue. The average means 6 SEM are summarized in table 2, along with the statistical
analysis. Our power to detect a difference of 40% in the means of DNA and LCL RNA was .99%.
Transcription at IFIH1 Locus
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strong LD in the block has made it far more challenging to identify
the disease-causing polymorphism or haplotype. Thus, detailed
functional analysis is required. A recent study that showed higher
IFIH1 mRNA levels in PBMCs of individuals with the susceptible
genotype of the T1D associated SNP by real-time RT-PCR
suggested that a differential regulation of IFIH1 expression could
be, at least in part, responsible for the T1D risk , while another
study was not able to show any difference in IFIH1 allelic
expression using the same technology . This approach,
comparing IFIH1 levels across individuals with different genotypes
[14,16], introduces substantial noise from inter-individual vari-
ability and by factors such as assay and batch variance, trans-acting
genetic factors, immune experience, cell proportions in the PBMC
mixtures and the presence of polymorphisms in other genes that
may alter the expression level in trans [23,34], thus diluting the
effect of cis-acting influences in expression studies . In order to
resolve this controversy, we used SNuPE, a method that relies on
the comparison of alleles within rather than between samples,
which removes external confounding factors. The SNuPE
technique is quite accurate and thus allows small differences in
allelic ratios to be reliably detected . We have previously
validated the accuracy of this method by showing an excellent
correlation between observed and expected allelic ratios .
The concern that allelic expression in transformed cultured cell
lines may not accurately represent what occurs in human tissues
was addressed in a recent paper that explored whether different
culture conditions (passage number, pH, nutrient concentration,
cell density, etc.) influence AI results . It was found that
estimations of AI after different passages were not significantly
different from one another. Another potential limitation of our
study was our use of total pancreas rather than islets. Since AI of
some genes may be tissue specific, we may have missed an islet-
specific effect. This, however, seems unlikely since both endocrine
and exocrine pancreatic tissues are of similar origins, and likely
exhibit similar allelic expression.
We were unable to replicate the results reported by Liu et al.
, using a much more sensitive, accurate and reproducible
method that has the power to detect an effect that is similar to that
was reported. This is in accordance with the expectation that the
nsSNP is the most likely functional candidate.
In summary, our results suggest that GCA and FAP are not
involved in T1D since we observed no AI and there are no nsSNPs
of high enough frequency to explain the effect . This reinforces
the role of the IFIH1 nsSNP as a potential causal variant. In
addition, KCNH7 was not expressed in LCLs, fetal pancreas or
thymus, and thus could not be assayed for AI. Therefore, a
transcriptional effect of the Thr946Ala SNP, or any variant in LD
with it, on KCNH7 cannot be ruled out.
While our study shows no transcriptional effects of the Thr946Ala
SNP or the other chosen variants that were in tight LD with it on the
three assayed genes, we cannot exclude the possibility of the presence
of other cis-regulatory variants with a lower minor allele frequency
exerting transcriptional effects on these genes, and being detected by
our AI assay. While in some samples, the cDNA allelic ratio deviates
by at least 20% from the genomic ratio (Figure 1), we are unable to
conclude whether we are observing transcriptional effects of such a
polymorphism in cis, or whether these merely reflect measurement
error. Nonetheless, the IFIH1 gene has been sequenced extensively,
and no rarevariants have been found that can explainthe association
of the common Thr946Ala SNP to T1D .
Thus, the mechanism of the observed association of the
rs1990760 with T1D remains to be determined, but does not
involve modulation of mRNA. Although the IFIH1 nsSNP,
rs1990760 (Thr946Ala substitution), does not reside in either the
signaling CARD domain or RNA binding helicase domain of the
protein, this region of the protein is conserved between mammals
and may have other, unknown functions or have an effect on the
active domains through changes in tertiary structure , which may
well be affected by the Thr946Ala SNP. This is a non-conservative
substitution, changing the polarity of the amino acid from polar to
non-polar. Recently, four rare mutations have been identified in
IFIH1, each of which separately lowered the risk of developing T1D
,independently of the effect of the Thr946Ala SNP. Twoof these
four variants have been shown to be loss of function mutations,
dramatically reducing IFIH1 protein activity or its RNA binding
ability . That loss of IFIH1 function protects from T1D would
indicate that the risk allele is related to an exaggerated immune
response rather than imperfect anti-viral defense. By implication, if
Thr946Ala itself is indeed the functional variant responsible for its
T1D association, one would expect the diabetes-predisposing Ala
allele to represent gain of function even though it was derived by
mutation of the conserved ancestral Thr allele. However, such a
mutation needs not to result in diminished protein function, as
conservation is driven by fitness of the organism, not higher level of
protein function. Such an example can be found in one of the
strongest T1D associations, which involves the R620W SNP in
PTPN22 (protein tyrosine phosphatase, non-receptor type 22),
wherethe 620W disease-associated variant,derived inanevenmore
conserved context, is a gain-of-function variant, with increased
catalytic activity . In the same paper which showed that two of
the four rare IFIH1 variants are loss of function mutations, the
Thr946Ala nsSNP was not found to affect dsRNA binding or
consequent IFN gene activation in mouse embryonic fibroblast cells
expressed above the threshold where small allelic differences in
dsRNA binding affinity and/or IFN response can be detected,
subtle effects could have been missed. It may also be that the SNP
altersinteraction with specificdsRNA structures not modeled by the
mimic used. Alternatively, the Thr946Ala nsSNP could affect
translational efficiency or may even be involved in the post-
translational processing of the IFIH1 protein. Additional work on
the Thr946Ala SNP is therefore necessary to discover how it alters
IFIH1 function and gain insight on how it affects T1D pathogenesis.
Found at: doi:10.1371/journal.pone.0011564.s001 (0.02 MB
Primer sequences and probes for each SNP
Conceived and designed the experiments: HZ CP. Performed the
experiments: HZ. Analyzed the data: HZ CP. Contributed reagents/
materials/analysis tools: LM CP. Wrote the paper: HZ CP. Provided
technical expertise with experiments and interpretation of data, helped
revise the manuscript critically: LM.
1. Smyth DJ, Cooper JD, Bailey R, Field S, Burren O, et al. (2006) A genome-
wide association study of nonsynonymous SNPs identifies a type 1 diabetes
locus in the interferon-induced helicase (IFIH1) region. Nat Genet 38:
2. Kang DC, Gopalkrishnan RV, Lin L, Randolph A, Valerie K, et al. (2004)
Expression analysis and genomic characterization of human melanoma
differentiation associated gene-5, mda-5: a novel type I interferon-responsive
apoptosis-inducing gene. Oncogene 23: 1789–1800.
Transcription at IFIH1 Locus
PLoS ONE | www.plosone.org5 July 2010 | Volume 5 | Issue 7 | e11564
3. Kang DC, Gopalkrishnan RV, Wu Q, Jankowsky E, Pyle AM, et al. (2002) mda- Download full-text
5: An interferon-inducible putative RNA helicase with double-stranded RNA-
dependent ATPase activity and melanoma growth-suppressive properties. Proc
Natl Acad Sci U S A 99: 637–642.
4. Yoneyama M, Kikuchi M, Matsumoto K, Imaizumi T, Miyagishi M, et al.
(2005) Shared and unique functions of the DExD/H-box helicases RIG-I,
MDA5, and LGP2 in antiviral innate immunity. J Immunol 175: 2851–2858.
5. Hyoty H, Taylor KW (2002) The role of viruses in human diabetes.
Diabetologia 45: 1353–1361.
6. Roivainen M (2006) Enteroviruses: new findings on the role of enteroviruses in
type 1 diabetes. Int J Biochem Cell Biol 38: 721–725.
7. van der Werf N, Kroese FG, Rozing J, Hillebrands JL (2007) Viral infections as
potential triggers of type 1 diabetes. Diabetes Metab Res Rev 23: 169–183.
8. Nejentsev S, Walker N, Riches D, Egholm M, Todd JA (2009) Rare variants of
IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes.
Science 324: 387–389.
9. Shigemoto T, Kageyama M, Hirai R, Zheng J, Yoneyama M, et al. (2009)
Identification of loss of function mutations in human genes encoding RIG-I and
MDA5: implications for resistance to type I diabetes. J Biol Chem 284:
10. Goldstein DB (2009) Common genetic variation and human traits. N Engl J Med
11. Boyhan A, Casimir CM, French JK, Teahan CG, Segal AW (1992) Molecular
cloning and characterization of grancalcin, a novel EF-hand calcium-binding
protein abundant in neutrophils and monocytes. J Biol Chem 267: 2928–2933.
12. Fassnacht M, Lee J, Milazzo C, Boczkowski D, Su Z, et al. (2005) Induction of
CD4(+) and CD8(+) T-cell responses to the human stromal antigen, fibroblast
activation protein: implication for cancer immunotherapy. Clin Cancer Res 11:
13. Muhlbauer E, Bazwinsky I, Wolgast S, Klemenz A, Peschke E (2007) Circadian
changes of ether-a-go-go-related-gene (Erg) potassium channel transcripts in the
rat pancreas and beta-cell. Cell Mol Life Sci 64: 768–780.
14. Liu S, Wang H, Jin Y, Podolsky R, Reddy MV, et al. (2009) IFIH1
polymorphisms are significantly associated with type 1 diabetes and IFIH1
gene expression in peripheral blood mononuclear cells. Hum Mol Genet 18:
15. Dixon AL, Liang L, Moffatt MF, Chen W, Heath S, et al. (2007) A genome-wide
association study of global gene expression. Nat Genet 39: 1202–1207.
16. Marinou I, Montgomery DS, Dickson MC, Binks MH, Moore DJ, et al. (2007)
The interferon induced with helicase domain 1 A946T polymorphism is not
associated with rheumatoid arthritis. Arthritis Res Ther 9: R40.
17. Yan H, Yuan W, Velculescu VE, Vogelstein B, Kinzler KW (2002) Allelic
variation in human gene expression. Science 297: 1143.
18. Vafiadis P, Bennett ST, Todd JA, Nadeau J, Grabs R, et al. (1997) Insulin
expression in human thymus is modulated by INS VNTR alleles at the IDDM2
locus. Nat Genet 15: 289–292.
19. Anjos SM, Shao W, Marchand L, Polychronakos C (2005) Allelic effects on gene
regulation at the autoimmunity-predisposing CTLA4 locus: a re-evaluation of
the 39 +6230G.A polymorphism. Genes Immun 6: 305–311.
20. Pastinen T, Hudson TJ (2004) Cis-acting regulatory variation in the human
genome. Science 306: 647–650.
21. Pastinen T, Sladek R, Gurd S, Sammak A, Ge B, et al. (2004) A survey of genetic
and epigenetic variation affecting human gene expression. Physiol Genomics 16:
22. Singer-Sam J, LeBon JM, Dai A, Riggs AD (1992) A sensitive, quantitative assay
for measurement of allele-specific transcripts differing by a single nucleotide.
PCR Methods Appl 1: 160–163.
23. Bray NJ, O’Donovan MC (2006) Investigating cis-acting regulatory variation
using assays of relative allelic expression. Psychiatr Genet 16: 173–177.
24. Buckland PR (2004) Allele-specific gene expression differences in humans. Hum
Mol Genet 13 Spec No 2: R255–R260.
25. Singer-Sam J, Chapman V, LeBon JM, Riggs AD (1992) Parental imprinting
studied by allele-specific primer extension after PCR: paternal X chromosome-
linked genes are transcribed prior to preferential paternal X chromosome
inactivation. Proc Natl Acad Sci U S A 89: 10469–10473.
26. Serre D, Gurd S, Ge B, Sladek R, Sinnett D, et al. (2008) Differential allelic
expression in the human genome: a robust approach to identify genetic and
epigenetic cis-acting mechanisms regulating gene expression. PLoS Genet 4:
27. Marchand L, Polychronakos C (2007) Evaluation of polymorphic splicing in the
mechanism of the association of the insulin gene with diabetes. Diabetes 56:
28. McCann JA, Zheng H, Islam A, Goodyer CG, Polychronakos C (2001)
Evidence against GRB10 as the gene responsible for Silver-Russell syndrome.
Biochem Biophys Res Commun 286: 943–948.
29. Hoogendoorn B, Norton N, Kirov G, Williams N, Hamshere ML, et al. (2000)
Cheap, accurate and rapid allele frequency estimation of single nucleotide
polymorphisms by primer extension and DHPLC in DNA pools. Hum Genet
30. Norton N, Williams NM, Williams HJ, Spurlock G, Kirov G, et al. (2002)
Universal, robust, highly quantitative SNP allele frequency measurement in
DNA pools. Hum Genet 110: 471–478.
31. Dendrou CA, Plagnol V, Fung E, Yang JH, Downes K, et al. (2009) Cell-specific
protein phenotypes for the autoimmune locus IL2RA using a genotype-
selectable human bioresource. Nat Genet 41: 1011–1015.
32. Qu HQ, Marchand L, Grabs R, Polychronakos C (2008) The association
between the IFIH1 locus and type 1 diabetes. Diabetologia 51: 473–475.
33. Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, et al. (2007) Robust
associations of four new chromosome regions from genome-wide analyses of type
1 diabetes. Nat Genet 39: 857–864.
34. Bray NJ, Buckland PR, Owen MJ, O’Donovan MC (2003) Cis-acting variation
in the expression of a high proportion of genes in human brain. Hum Genet 113:
35. Pastinen T, Ge B, Gurd S, Gaudin T, Dore C, et al. (2005) Mapping common
regulatory variants to human haplotypes. Hum Mol Genet 14: 3963–3971.
36. Vang T, Congia M, Macis MD, Musumeci L, Orru V, et al. (2005)
Autoimmune-associated lymphoid tyrosine phosphatase is a gain-of-function
variant. Nat Genet 37: 1317–1319.
Transcription at IFIH1 Locus
PLoS ONE | www.plosone.org6 July 2010 | Volume 5 | Issue 7 | e11564