Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
1
Expression Quantitative Trait Loci: Replication, Tissue- and Sex-Specificity in Mice Atila van Nas1, Leslie Ingram-Drake2, Janet S. Sinsheimer1, Susanna S. Wang6, Eric E. Schadt6, Thomas Drake5, Aldons J. Lusis1,2,3,4
Departments of Human Genetics1, Medicine2, Microbiology, Immunology, & Molecular Genetics3, Molecular Biology Institute4, Pathology & Laboratory Medicine5 David Geffen School of Medicine University of California, Los Angeles, California 90095; and Department of Genetics6, Rosetta Inpharmatics, a wholly owned subsidiary of Merck & Co. Inc., Seattle, Washington 98109 Address all correspondence and requests for reprints to: Aldons J. Lusis University of California, Los Angeles Med-Cardio/Microbio Box 951679, 3730 MRL Los Angeles, California 90095-1679 E-mail: [email protected]
Genetics: Published Articles Ahead of Print, published on May 3, 2010 as 10.1534/genetics.110.116087
2
ABSTRACT
By treating the transcript abundance as a quantitative trait, gene expression can be mapped to local or distant
genomic regions relative to the gene encoding the transcript. Local expression quantitative trait loci (eQTL)
generally act in cis (that is, control the expression of only the contiguous structural gene), whereas distal eQTL act
in trans. Distal eQTL are more difficult to identify with certainty due to the fact that significant thresholds are very
high since all regions of the genome must be tested, and confounding factors such as batch effects can produce
false positives. Here, we compare findings from two large genetic crosses between mice strains C3H/HeJ and
C57BL/6J to evaluate the reliability of distal eQTL detection, including ‘hotspots’ influencing the expression of
multiple genes in trans. We found that >63% of local eQTLs and >18% of distal eQTLs were replicable at a
threshold of LOD> 4.3 between crosses and 76% of local and >24% of distal eQTLs at a threshold of LOD> 6.
Additionally, at LOD> 4.3 four tissues studied (adipose, brain, liver and muscle) exhibited >50% preservation of
local eQTL and >17% preservation of distal eQTLs. We observed replicated distal eQTL hotspots between the
crosses on chromosomes 9 and 17. Finally, >69% of local eQTLs and >10% of distal eQTLs were preserved in
most tissues between sexes. We conclude that most local eQTLs are highly replicable between mouse crosses,
tissues and sex as compared to distal eQTLs, which exhibited modest replicability.
3
INTRODUCTION
Genetic variations in gene expression contribute to the molecular architecture underlying complex diseases such as
atherosclerosis, diabetes, and cancer [1]. Detection of gene expression in segregating populations has lead to the
identification of expression quantitative trait loci (eQTL) [2-4]. Global mapping of gene expression provides a useful
form of functional variation for positional cloning and can facilitate the modeling of causal interactions and biologic
networks [5-9].
Distinguishing between local (sometimes termed “cis”) and distal (sometimes termed “trans”) eQTLs
enhances our understanding of the candidate genes underlying the disease phenotype. Due to their close
proximity, genetic variants underlying local eQTL most likely affect molecular mechanisms involved in transcription,
splicing, or mRNA decay, and most act in cis [10]. Distal eQTLs, on the other hand, generally consist of variants
which act in trans. One variety of trans-eQTL, termed “hotspots”, regulates the levels of many different transcripts.
For example, one mouse study identified genetic variants influencing the transcription factor RUNX1 affecting the
gene expression of a group of distal genes involved in the RUNX1 pathway [11]. Distal eQTLs are of particular
interest to complex trait studies since they may perturb entire pathways and mediate complex gene-gene and gene-
environment interactions. An important example of a trans-effect relevant to complex disease is sex [12], as QTL
studies of males and females have detected striking sex-gene interactions [1, 13].
In this study, we evaluated the reproducibility of eQTL detection of two large genetic crosses of mouse
strains C3H/HeJ and C57BL/6J. We chose these genetic crosses, which had been developed for other, studies
because they were quite similar in overall design as well as genetic backgrounds. We evaluated transcript levels in
adipose, brain, liver and muscle of both sexes. The results have both practical and basic importance. A
complication with human studies is the difficulty of procuring samples from tissues of interest. Thus an important
question is whether accessible tissues such as blood cells act as a proxy for less accessible tissues. A recent
human study of several tissues concluded that conservation of eQTL between tissue was low [14]. Our results are
in agreement for distal eQTL, but they show high conservation of local eQTLs. Our results also provide data
4
relevant to basic questions such as conservation of biologic networks between tissue, the global nature of genetic
regulation, and the basis of sex differences.
RESULTS
To investigate the extent of eQTL preservation, we determined the degree of overlap between two mouse crosses
(cross I and cross II) of inbred strains C57BL/6J and C3H/HeJ. Integrating the genotype and gene expression trait
data, we utilized the linkage software QTL cartographer and calculated the eQTL in the adipose, brain, liver and
skeletal muscle tissue of the crosses. We used LOD> 4.3 as a threshold of significance, LOD> 2.7 as a suggestive
threshold and LOD> 6 as a high threshold of significance. We chose significance thresholds at a suggestive,
significant and high LOD score to capture the commonly used thresholds to determine if these lead to reasonable
replication in eQTL studies. The threshold LOD>4.3, and 2.7 were chosen based on a previous study by Lander
and Kruglyak, who reported the number of false positives detected in a QTL at various significance threshold [15].
Specifically, a LOD>4.3 was defined as the baseline of significance, which is a approximately equivalent to a p-
value<10-5, whereas LOD>2.7 is equivalent to a p-value<10-3, reflecting a more suggestive threshold. The threshold
LOD>6 was chosen based on the results of permutation (n=1000) we performed in this analysis on n=500 randomly
chosen transcripts.
For each eQTL at the various LOD score thresholds, we determined if it was detected in both crosses.
The eQTL in one cross was considered replicated if it was detected within 10Mb of an eQTL in the other
comparison cross of the same tissue. In this study, local eQTL were defined as loci containing the gene of the
transcript abundance that maps within 10Mb of the nearest QTL. To determine the degree of local and distal eQTL
that replicated, we calculated for each LOD score threshold the percent of eQTLs that overlap between the crosses,
tissues and sex. The eQTL hotspots were determined by the enrichment of gene expression traits that mapped to
the same loci.
5
Replication of local eQTLs between crosses
To investigate the degree of local eQTL replication in the mouse crosses, we determined what percent of the local
eQTLs at LOD> 4.3 or LOD> 6 in one cross, could be detected in the other cross at LOD> 2.7. We compared the
crosses in this way in both directions, and the results were highly consistent. At LOD> 4.3, our results showed over
60% of the local eQTLs replicated (63-76%) across all the tissues of the mouse crosses I and II. At LOD> 6 over
76% of the local eQTLs between crosses I and II replicated at this LOD score threshold, reaching as high as 80%
replication (83-86%) in brain, liver and muscle tissue (Figure 1 and Table 1S).
Replication of distal eQTLs between crosses
To determine the degree of replication of distal eQTLs, we ascertained the number of distal eQTLs at LOD> 4.3 or
LOD> 6 in one cross that could be detected at LOD> 2.7 in the other cross. At LOD> 4.3, we detected >18%
replication of distal eQTLs over all tissues between cross I and II, with >21% in brain, liver and muscle. At LOD> 6
the degree of replication among distal eQTLs was greater. Over 25% of the distal eQTLs replicated across tissues,
reaching >30% in liver and >40% in brain (Figure 1 and Table 1S).
Preservation of local eQTLs across tissues
To explore the degree of replication of local eQTLs across tissues, we used the same screening strategy as above.
At LOD>4.3, approximately 50% of the local eQTL were preserved in tissues. The muscle tissue exhibited the
highest degree of preservation (56-66%) compared to the other tissues (adipose: 52-65%; liver: 51-58%) and the
brain the lowest degree of preservation (50-56%). At LOD> 6, we observed a similar pattern of preservation, >56%
of local eQTLs muscle (63-73%), (adipose (62-74%), liver(59-65%) and brain (56-61%) (Figure 2 and Table 2S).
6
Preservation of distal eQTLs across tissues
To investigate the degree of distal eQTLs replication across tissues, we screened each distal eQTL at LOD> 4.3
and LOD> 6 for detection in the comparison tissue at LOD> 2.7. At LOD> 4.3, ~18% of the distal eQTLs were
detected across tissues. Muscle showed the highest preservation (20-22%) compared to the other tissues
(adipose, 19-23%; brain, 19-22%; liver, 18-21%). At LOD> 6 the preservation of distal eQTLs was: adipose, 23%;
brain, 26%; liver, 21%; muscle: 28% (Figure 2 and Table 2S).
Preservation of local eQTLs between female and male mice
To investigate how sex affects the degree of preservation of eQTLs, we determined if eQTLs at LOD>4.3 and LOD>
6 in female mice were detected at LOD>2.7 in male mice and vice versa. At LOD>4.3, approximately 70% of the
local eQTLs were preserved between female and male mice: adipose (69-75%), brain tissue (79-85%), liver (77-
80%) and muscle (75-83%). At LOD> 6, over 79% of local eQTLs (79-92%) were preserved between male and
female mice in all tissues: adipose (79-85%), liver and muscle tissue (84-91%) and brain (87-92%) (Figure 3 and
Table 3S).
Preservation of distal eQTLs between female and male mice
To investigate the degree of preservation of distal eQTLs between females and males, we determined whether for
each distal eQTL at LOD> 4.3 and LOD> 6 in one sex was detected in the other sex at LOD> 2.7. At LOD> 4.3,
over 10% of distal eQTLs were preserved across tissues between females and males: adipose (10-18%), brain
(15-27%), liver (14-17%) and muscle (10-16%). At LOD> 6, over 25% of the distal eQTLs were preserved across
tissues between females and males, with the exception of female adipose tissue in cross I: adipose (15-30%),
brain (48-73%), liver (34-49%), and muscle (33-36%) (Figure 3 and Table 3S).
7
Replication of eQTL Hotspots
To investigate if the distal eQTL hotspots replicate between the crosses, we determined which chromosomes had
the highest relative frequency of distal eQTLs at LOD> 6. The brain consisted of the most pronounced replicated
distal eQTLs hotspots on chromosomes 1, 4, 11 and 17. In the liver tissue replicated hotspots were detected on
chromosomes 4, 6, 9 and 17. In muscle, replicated hotspots were found on chromosome 1, 4, 9 and 17. And in
adipose, distal eQTLs hotspots replicated on chromosomes 8, 9 and 17. Interestingly, the same hotspot on
chromosome 9 (105.18-106.57Mb) was observed in all tissues, although in varying degree. We also detected the
same hotspot across all tissues on chromosome 17 (24.53 Mb) with the exception of adipose tissue (11.64Mb).
These results show that tissue-specific distal eQTLs hotspots as well as those across tissues are replicable in
mouse crosses. (Figure 5).
We also determined if the transcripts mapping to these hotspots were enriched for a biological functional
category. For hotspots observed across tissues on chromosome 17 (11.64-24.53Mb), transcripts were modestly
enriched for ‘integral to plasma membrane’ (p=0.021) as well as ‘non-membrane-bounded organelle' with PDZ
domains found in diverse signaling proteins (p=0.025). For hotspots found in only one tissue, transcripts were
enriched for tissue-specific functions. For example at chromosome 11 (36.82Mb) in brain, two of the transcripts
were shown involved in the regulation of 'glial cell development' (p=0.024); in liver at chromosome 6 (94.46Mb) two
genes were found in the pathway for ‘glucose homeostasis’ (p=0.037) and in adipose at chromosome 8 (84.79-
95.42Mb), seven genes were involved in pathways for 'lipid biosynthetic process' (p=0.0039) and 'palmitate'
(p=0.021) (Figure 1S and Table 5S).
Additionally, we ascertained if these loci harbored genes responsible for regulating a high frequency of
transcripts such as transcription factors. We identified several chromosomes with transcription factors at these
hotspots including: chromosome 1 (174.91-178.85Mb), Usf1, Upstream transcription factor 1 (173.34Mb) and Atf6,
Activating transcription factor 6 (172.62Mb); chromosome 4 (132.40Mb), Runx3, Runt related transcription factor 3
(134.67Mb); chromosome 17 (24.53Mb), E4f1, E4F transcription factor 1 (24.56Mb) (Figure 1S and Table 5S).
8
Although the majority of these genes were not well-annotated, some transcription factors were localized at
or near several hotspot loci. In particular, Atf6, one of the primary genes involved in regulating genes in the
unfolded protein response system resides near a hotspot on chromosome 1 (175.34Mb) which was found to be
enriched for transcripts involved in protein synthesis (p< 6.90E-05) [16].
DISCUSSION
Our results have led to several conclusions: First, local eQTL are highly preserved between studies, whereas distal
eQTL were only modestly replicable. Second, most local eQTL were not tissue specific, in that an eQTL in one
tissue (of the four tissues studied here) was likely to be observed in another tissue. This finding has important
implications for human studies where tissue availability is a problem. Third, although thousands of genes differed in
expression between males and females, most local eQTL were preserved between sexes whereas distal eQTL
were not. Fourth, several ‘hotspots’ were preserved between crosses, sexes, and multiple tissues. The identity of
the underlying genes will be of considerable interest. There were some differences between the two crosses,
notably the presence of an ApoE null mutation in cross I, and these undoubtedly decreased the replication of eQTL
(Table 1).
Previous eQTL reports have shown similarly high levels of replication of local eQTLs between mouse
crosses [17]. Interestingly, the strongest replicated distal eQTL hotspot we observed in brain on chromosome 1
(174-178Mb) was previously reported on chromosome 1 (170-174Mb) in the same tissue [17]. However, a recent
study detected low replicability between human cell lines from different tissues [14]. Since the latter analysis was
performed in only 75 individuals, the power was more limited than in our study. Moreover, these authors used a
relative high threshold for significance for both identification of the eQTL as well as replication in a separate tissue.
The importance of eQTL studies has recently been reviewed [5, 6]. eQTL analyses allow the modeling of
causal interactions which can be used to identify candidate genes influencing biologic pathways [7] and the
construction of directed co-expression networks [18]. The modeling of biologic networks has proven to be
9
particularly informative when combined with genome-wide association studies, making possible the identification of
causal genes at a locus, the annotation of genes of unknown function, and the clarification of new candidate genes
in biologic pathways.
The high level of replication between crosses of distal as well as local eQTL suggests that systems
genetics approaches should be capable of addressing mechanisms governing transcription and RNA processing.
For example, it should be possible to examine control of chromatin structure by integrating eQTL data with ChIP-
chip or - ChIP-seq methodologies [19]. Also, massively parallel sequencing of transcripts from genetic crosses
(RNA-seq) should result in the mapping of loci controlling RNA splicing as well as transcript levels [20, 21].
Although similar eQTL approaches are clearly feasible for human studies, genetic heterogeneity and environmental
factors result in greatly diminished power [5]. It is noteworthy that co-expression networks developed using mouse
data exhibit considerable overlap with human networks [22].
METHODS
Mice inbred strains C57BL/6J (B6) and C3H/HeJ (C3H) F2 reciprocal intercross
Murine F2 population consisting of approximately 300 mice was generated by intercrossing F1 mice of parental
strains B6 and C3H. Mice were fed chow diet containing 4% fat until 8 weeks of age and then were placed on a
“Western” diet containing 42% fat and 0.15% cholesterol for 12 weeks. After a 12 hour fast, the mice were
anesthetized by isoflurane for retro-orbital sinus blood collection, and subsequently euthanized at 20 weeks of age
for tissue collection of adipose, whole brain, liver and muscle. The mice were genotyped at ~1500 single nucleotide
polymorphisms (SNPs) uniformly distributed over the mouse genome at an average density of 1.5cM (Table 1).
Mice inbred strains C57BL/6J ApoE−/− (B6.ApoE−/−) and C3H/HeJ ApoE−/− (C3H.ApoE−/−) F2 intercross data set
The genotype and gene expression data from adipose, brain, liver and muscle of the F2 mouse population used in
this study have been previously described [13]. The C57BL/6J ApoE−/− (B6.ApoE−/−) parental strains were
10
purchased from Jackson Laboratory (Bar Harbor, Maine, United States) and the C3H/HeJ ApoE−/− (C3H.ApoE−/−)
parental strains were generated by backcrossing B6.ApoE−/− to C3H for ten generations. The C3H.ApoE−/− parental
strains were genotyped using ~1300 markers throughout the genome and there was no evidence of contaminating
regions. Since the B6.ApoE−/− parental strains were purchased from JAX labs, no additional genotyping was
performed to confirm the purity of the background strains. The region flanking the ApoE gene is derived from strain
129 in both parents. We previously showed that in ApoE-/- from JAX that the region extended about 5-10Mb
proximal and 15-20Mb distal to the ApoE gene [23]. This region did not contain any significant or suggestive
(LOD>2.7) eQTL in the wildtype cross.
The F2 mouse population consisting of 334 mice (169 female, 165 male) was generated by intercrossing
F1 mice of parental strains B6.apoE−/− and C3H.apoE−/−. Mice were fed chow diet containing 4% fat until 8 weeks
of age and then were placed on a “Western” diet containing 42% fat and 0.15% cholesterol for 16 weeks. After a 4
hour fast, the mice were anesthetized by isoflurane for retro-orbital sinus blood collection, and subsequently
euthanized at 24 weeks of age for tissue collection of adipose, whole brain, liver and muscle. The mice were
genotyped at ~1,300 single nucleotide polymorphisms (SNPs) uniformly distributed over the mouse genome at an
average density of 1.5cM (Table 1).
Gene expression analysis
The RNA and microarray processing, as previously described [24], was performed at Rosetta Inpharmatics (Seattle,
WA). The custom ink-jet microarrays (Agilent Technologies, Palo Alto, CA) contain 2,186 control probes and
23,574 non-control oligonucleotides extracted from mouse Unigene clusters and combined with RefSeq sequences
and RIKEN full-length clones. Total RNA was extracted from homogenized mouse tissues with Trizol reagent
(Invitrogen, Carlsbad, California, United States) according to manufacturer's protocol. Labeled cDNA with either
Cy3 or Cy5 was hybridized to at least two microarray slides with fluor reversal and subsequently scanned using a
laser confocal scanner. Gene expression changes between two samples were quantified on the basis of spot
11
intensity relative to background, adjusted for experimental variation between arrays using average intensity over
multiple channels, and fit to an error model to determine significance (type I error). Gene expression is reported as
the ratio of the mean log10 intensity (ml-ratio) relative to the pool derived from 150 mice randomly selected from the
F2 population. Gene expression data from mice with complete genotype data and at least 95% complete
phenotype and array data were used The microarray data from this study have been deposited to GEO under
accession numbers GSE2814, GSE3086, GSE3087, GSE3088. . GSE11065 GSE11338 GSE12795 and
GSE12798.
eQTL replication analysis
The eQTLs within a cross (sex as an interactive covariate) and in female and male mice were calculated utilizing
the scanone function in RQTL. A thousand permutations of n=500 randomly chosen gene transcripts resulted in a
significance threshold of LOD>6. Genes with eQTLs of LOD> 2.7 were selected for replication comparison
between, the crosses, tissues and female and male mouse crosses I and II. An eQTL detected within 10Mb from
the nearest marker of the gene was identified as a local eQTL, whereas eQTLs outside of 10Mb from the nearest
marker of the gene was defined as distal eQTL. The eQTL with the highest LOD score per chromosome was
chosen for the analysis. For each comparison, between crosses, tissues and sex, the degree of overlap was
calculated by ascertaining if the eQTLs detected in one group at LOD> 4.3 or LOD> 6 can be detected at LOD> 2.7
in the other group. Specifically, the percent of overlap was calculated as the number of genes with eQTLs of
LOD>4.3 or LOD> 6 of one group that intersect with eQTLs at LOD>2.7 of the comparison group over the total
number of genes with LOD>4.3 or LOD> 6 of the first group. The groups that were compared for their eQTLs was
as follows: I vs. II ; adipose vs. brain, adipose vs. liver, adipose vs. muscle, brain vs. liver, brain vs. muscle and
liver vs. muscle; and male vs. female.
The reasons we chose to present our replication results using a less stringent threshold are the following:
12
(1) Replicating a specific genetic linkage or association requires much more power than finding any significant
result in the first place when there are multiple genes that affect trait values. Brian Suarez and colleagues [25]
nicely demonstrate this property and others have also demonstrated this same principle. Suarez and colleagues
argue that in the initial study, a successful result is the detection of any one (or a few) of a number contributing
genes but in the replication a successful result is the much harder problem of finding this (these few) same gene(s)
again. A related problem is that the significance of the results in the first cross are actually inflated (the winner's
curse problem) and so are more difficult to replicate. Thus we use a lower threshold for the second, replication
cross. (2) The reason for using such a high threshold for the first cross is that we are conducting thousands of
tests and need to adjust our significance level accordingly to avoid a severe multiple testing problem. In the
replication, however, we are effectively looking at the limited number of regions that were near significant findings
from the first cross thus the number tests is reduced and we can use a less severe adjustment for multiple testing.
We defined an eQTL hotspot by the highest relative frequency of eQTLs at LOD> 5.7. Specifically, we
searched for loci with eQTLs greater than or equal to three standard deviations above the average frequency of
distal eQTLs in one tissue. The following thresholds were used to detect hotspot loci: adipose > 10; brain > 20; liver
> 13;muscle > 8.
13
ACKNOWLEDGMENTS: We thank Hong-Xiu Qi for assistance in animal husbandry, including animal care,
collecting plasma, tissues and performing the body fat assays; Larry Castellani for assistance in collecting plasma
and constructive criticism; Sharda Charugundla for performing the lipid assays; Melenie Rosales, Daria Estrada-
Smith, Ping-Zi Wen, Sonal S. Sheth, Sudheer Doss, Xu-Ping Wang, Judy Wu, Xia Yang and Yi-Shou Shi for their
assistance in animal husbandry; Kathleen Ranola, Madlen Ayvasian and Arpa Ghazarian for assistance in
processing the tissues; Eleazar Eskin and Rita Cantor for statistical advice. Calvin Pan for assistance in data
management. Sonia Carlson and Stephen Edwards for help in transfer of tissues and organization of data between
institutions; and Richard C. Davis for guidance, discussions and insight. This work was supported by National
Institutes of Health (NIH) Grants HL28481, HL094322, HL087944, HL30568 (A.J.L.) and 5R01DK72206 (T.D.).
A.V. was supported by NIH Training Grant 5T32HD07228.
Disclosure Statement: The authors have nothing to disclose.
14
FIGURE LEGENDS
Figure 1
Replication of local (a) and distal (b) eQTLs between crosses. The percent of eQTLs that replicated between
crosses at various LOD thresholds is depicted in adipose, brain, liver and muscle tissue. The eQTLs at LOD> 2.7,
4.3 and 6 of the mouse crosses were screened for detection at LOD>2.7 in their respective comparison crosses.
The percent indicates the degree of replication of eQTLs at LOD> 4.3 in cross I that overlap in cross II at LOD> 2.7
over the total number of eQTLs at LOD >4.3 detected in cross I and vice versa. For example, at LOD> 6, over 80%
of the local eQTLs in cross I were preserved in cross II of the adipose tissue.
Figure 2
Preservation of local (a) and distal (b) eQTLs across tissues. The percent of eQTLs that were preserved across
tissues at various LOD thresholds is depicted in adipose, brain, liver and muscle tissue. The eQTLs at LOD> 2.7,
4.3 and 6 of a tissue were screened for detection at LOD>2.7 in their respective comparison tissues (sex and
mouse crosses were combined). The percent indicates the degree of replication of eQTLs at LOD> 4.3 in one
tissue that overlap in its comparison tissue at LOD> 2.7 over the total number of eQTLs at LOD >4.3 detected in the
first tissue and vice versa. For example, for the local eQTLs in cross I, approximately 70% of the local eQTLs found
in adipose at LOD>6 were detected in brain at LOD> 2.7. The bar graph reflects the eQTLs at LOD>4.3 of the
adipose tissue as compared to the eQTLs at LOD> 2.7 of the brain, liver and muscle (brain compared to adipose,
liver and muscle; liver compared to adipose, brain and muscle; and muscle compared to adipose, brain and liver).
Figure 3
Preservation of local (a) and distal (b) eQTLs between females and males. The percent of eQTLs that replicated
between sexes at various LOD thresholds is depicted in adipose, brain, liver and muscle tissue. The eQTLs at
LOD> 2.7, 4.3 and 6 of one sex were screened for detection at LOD>2.7 in the opposite sex. The percent indicates
15
the degree of replication of eQTLs at LOD> 4.3 in females that overlap in males at LOD> 2.7 over the total number
of eQTLs at LOD >4.3 detected in females and vice versa. For example, at LOD> 6, female adipose in cross I
shows >80% of the local eQTLs preserved in the male adipose cross I group.
Figure 4
Replication of distal eQTLs between crosses at different significance thresholds. The percent of eQTLs that
replicated between crosses at various LOD thresholds is depicted in adipose, brain, liver and muscle tissue. The
eQTLs at LOD> 2.7-10 of the mouse crosses were screened for detection at LOD>2.7-10 in their respective
comparison crosses. The heat map reflects the degree of replication as the percent of eQTLs at various LOD
thresholds in cross I that overlap in cross II at various LOD thresholds and vice versa. For example, in adipose
tissue, approximately 80% of eQTLs at LOD >2.7 in cross II were detected in cross I (bottom right corner).
Figure 5
Replication of eQTL hotspots between crosses. The chromosomes were screened for the highest relative
frequency of distal eQTLs at LOD>5.7 of the crosses (cross I vs cross II). The detection of loci with eQTLs greater
than or equal to three standard deviations above the average frequency of distal eQTLs in one tissue alluded to the
presence of an eQTL hotspot. A. Adipose. B. Brain. C. Liver. D. Muscle.
Table 1
Comparison of experimental design between the crosses.
16
REFERENCES
1. Lusis, A.J., A.D. Attie, and K. Reue, Metabolic syndrome: from epidemiology to systems biology. Nat Rev Genet,
2008. 9(11): p. 819-30. 2. de Vienne, D., et al., Mapping factors controlling genetic expression. Cell Mol Biol (Noisy-le-grand), 1994. 40(1): p.
29-39. 3. Damerval, C., et al., Quantitative trait loci underlying gene product variation: a novel perspective for analyzing
regulation of genome expression. Genetics, 1994. 137(1): p. 289-301. 4. Machleder, D., et al., Complex genetic control of HDL levels in mice in response to an atherogenic diet. Coordinate
regulation of HDL levels and bile acid metabolism. J Clin Invest, 1997. 99(6): p. 1406-19. 5. Cookson, W., et al., Mapping complex disease traits with global gene expression. Nat Rev Genet, 2009. 10(3): p.
184-94. 6. Rockman, M.V. and L. Kruglyak, Genetics of global gene expression. Nat Rev Genet, 2006. 7(11): p. 862-72. 7. Schadt, E.E., et al., An integrative genomics approach to infer causal associations between gene expression and
disease. Nat Genet, 2005. 37(7): p. 710-7. 8. Montgomery, S.B. and E.T. Dermitzakis, The resolution of the genetics of gene expression. Hum Mol Genet, 2009.
18(R2): p. R211-5. 9. Ghazalpour, A., et al., Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS
Genet, 2006. 2(8): p. e130. 10. Doss, S., et al., Cis-acting expression quantitative trait loci in mice. Genome Res, 2005. 15(5): p. 681-91. 11. Bystrykh, L., et al., Uncovering regulatory pathways that affect hematopoietic stem cell function using 'genetical
genomics'. Nat Genet, 2005. 37(3): p. 225-32. 12. van Nas, A., et al., Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks.
Endocrinology, 2009. 150(3): p. 1235-49. 13. Wang, S., et al., Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex
specificity. PLoS Genet, 2006. 2(2): p. e15. 14. Dimas, A.S., et al., Common regulatory variation impacts gene expression in a cell type-dependent manner. Science,
2009. 325(5945): p. 1246-50. 15. Lander, E. and L. Kruglyak, Genetic dissection of complex traits: guidelines for interpreting and reporting linkage
results. Nat Genet, 1995. 11(3): p. 241-7. 16. Davenport, E.L., G.J. Morgan, and F.E. Davies, Untangling the unfolded protein response. Cell Cycle, 2008. 7(7): p.
865-9. 17. Peirce, J.L., et al., How replicable are mRNA expression QTL? Mamm Genome, 2006. 17(6): p. 643-56. 18. Chen, Y., et al., Variations in DNA elucidate molecular networks that cause disease. Nature, 2008. 452(7186): p.
429-35. 19. Zhu, J., et al., Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks.
Nat Genet, 2008. 40(7): p. 854-61. 20. Veyrieras, J.B., et al., High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS
Genet, 2008. 4(10): p. e1000214. 21. Heinzen, E.L., et al., Tissue-specific genetic control of splicing: implications for the study of complex traits. PLoS Biol,
2008. 6(12): p. e1. 22. Emilsson, V., et al., Genetics of gene expression and its effect on disease. Nature, 2008. 452(7186): p. 423-8. 23. Lusis, A.J., J. Yu, and S.S. Wang, The problem of passenger genes in transgenic mice. Arterioscler Thromb Vasc
Biol, 2007. 27(10): p. 2100-3. 24. He, Y.D., et al., Microarray standard data set and figures of merit for comparing data processing methods and
experiment designs. Bioinformatics, 2003. 19(8): p. 956-65. 25. Suarez, B.K., Hampe, C.L., Van Eerdewegh, P., Problems of Replicating Linkage Claims in Psychiatry in Genetic
Approaches to Mental Disorders, ed. E.S. Gershon, Cloninger, C.R. Vol. 23. 1994, Washington, DC: American Psychiatric Press.