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Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease logoLink to Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
. 2013 Feb 22;2(1):e005421. doi: 10.1161/JAHA.112.005421

Genetic‐Genomic Replication to Identify Candidate Mouse Atherosclerosis Modifier Genes

Jeffrey Hsu 1,2, Jonathan D Smith 1,2,
PMCID: PMC3603265  PMID: 23525445

Abstract

Objective

Genetics plays a large role in atherosclerosis susceptibility in humans and mice. We attempted to confirm previously determined mouse atherosclerosis‐associated loci and use bioinformatics and transcriptomics to create a catalog of candidate atherosclerosis modifier genes at these loci.

Methods and Results

A strain intercross was performed between AKR and DBA/2 mice on the apoE−/− background generating 166 F2 progeny. Using the phenotype log10 of the aortic root lesion area, we identified 3 suggestive atherosclerosis quantitative trait loci (Ath QTLs). When combined with our prior strain intercross, we confirmed 3 significant Ath QTLs on chromosomes 2, 15, and 17, with combined logarithm of odds scores of 5.9, 5.3, and 5.6, respectively, which each met the genome‐wide 5% false discovery rate threshold. We identified all of the protein coding differences between these 2 mouse strains within the Ath QTL intervals. Microarray gene expression profiling was performed on macrophages and endothelial cells from this intercross to identify expression QTLs (eQTLs), the loci that are associated with variation in the expression levels of specific transcripts. Cross tissue eQTLs and macrophage eQTLs that replicated from a prior strain intercross were identified. These bioinformatic and eQTL analyses produced a comprehensive list of candidate genes that may be responsible for the Ath QTLs.

Conclusions

Replication studies for clinical traits as well as gene expression traits are worthwhile in identifying true versus false genetic associations. We have replicated 3 loci on mouse chromosomes 2, 15, and 17 that are associated with atherosclerosis. We have also identified protein coding differences and multiple replicated eQTLs, which may be useful in the identification of atherosclerosis modifier genes.

Keywords: atherosclerosis, genetics, transcriptomics

Introduction

Atherosclerosis is a complex disease with both environmental and genetic susceptibility components. The heritability of atherosclerotic coronary artery disease (CAD) in humans is evident from family history being a significant risk factor.12 In addition, genome‐wide association studies (GWAS) have identified multiple loci associated with CAD.3 However, these studies have a tremendous statistical burden to overcome to meet the threshold of genome‐wide significance, and thus much of the genetic contribution may underreported. Also, GWAS do not ascertain rare variants, and it is becoming increasingly clear that rare variants in aggregate can account for a significant portion of population variance for complex traits such as plasma triglycerides.4 Thus, there is still impetus to identify novel genes and pathways that play a role in atherosclerosis susceptibility. Genetics also plays a role in lesion development in mouse models of atherosclerosis, as different inbred strains have markedly different aortic lesion areas.5 Mouse models provide an opportunity to tease out the potential genetic modifiers for multigenic phenotypes. We have previously shown that AKR apoE−/− mice have ≈10‐fold smaller aortic root lesions compared with DBA/2 apoE−/− mice when fed a chow diet.5 A previous intercross between these 2 strains identified 2 significant and 4 suggestive quantitative trait loci (QTLs) for aortic root lesion area. Just as lesion area is a quantitative trait that can be used for gene mapping studies, gene expression levels can likewise be treated as a quantitative trait to map the expression QTLs (eQTLs), or the loci that control the expression of specific transcripts.6 We had previously performed an eQTL analysis using macrophages from the F2 cohort of the AKR apoE−/−×DBA/2 apoE−/− strain intercross.7 Here, we report atherosclerosis (Ath) QTL and eQTL findings from a second independent strain intercross of these same 2 strains.

We found that both significant Ath QTLs in the prior cross were replicated in the new cross, whereas only one of the prior suggestive Ath QTLs was replicated. We carefully excluded analysis of transcriptome data from microarray probes that contained strain‐specific sequence polymorphisms, and we still found robust replication of macrophage cis‐acting eQTLs between the prior and new crosses. We also observed many cis‐eQTLs that were conserved between macrophages and endothelial cells (ECs). However, trans‐acting eQTLs were not well replicated between the 2 crosses, leading us to believe that there is a high false‐positive rate for the identification of trans‐eQTLs. We compiled the lists of all protein coding differences between the AKR and DBA/2 strains, as well as the eQTLs, within the replicated Ath QTLs. These genes provide a comprehensive list of candidates that may be responsible for the observed Ath QTLs.

Methods

Mouse and Cell Studies

A DBA/2J apoE−/−×AKR/J apoE−/− reciprocal strain intercross was performed to generate an F1 cohort and the subsequent F2 cohort of 89 males and 77 females. The F2 mice were weaned at 21 days and placed on a chow diet. Mice were killed at 16 weeks of age. Femurs were collected from all mice, and the descending aortas were removed from males for culture of ECs as described later. Tail‐tip DNA was prepared from each F2 mouse by proteinase K digestion followed by ethanol precipitation. Lesion areas of the aortic root were quantified as previously described.8 Genotyping was performed using Illumina Golden Gate mouse genotyping arrays. Genotyping calls were made using Illumina Genome Studio software. In all, 599 informative markers between AKR and DBA/2 were used for QTL and eQTL analyses.

Bone marrow‐derived macrophages (BMMs) were derived as previously described.7 To obtain cultured ECs from the F2 mice, descending aortas were isolated, cut into 2‐mm sections, placed on top of matrigel‐coated plates, and grown to confluence (≈10 to 14 days) in DMEM supplemented as previously described.9 Cells were treated with dispase and passaged twice before RNA isolation. This protocol was successful in obtaining EC cultures in 48 of 89 attempts. RNA was isolated using Qiagen's total RNA kits and digested with DNase I for 12 minutes at room temperature to remove genomic DNA. RNA integrity was confirmed by agarose gel electrophoresis. cDNA was synthesized using Illumina protocols and reagents and hybridized on Illumina Mouse Ref‐8 v2 microarrays. All expression, phenotype, and genotype data are available in GEO (accession No. GSE35676).

Statistical Methods

Ath QTLs, using the log10 of aortic root lesion areas, were mapped using the R package qtl (R/qtl).10 False discovery rates (FDRs) were estimated with 100 000 permutations using the scanone function in R/qtl. The Ath QTL CIs were calculated within the same software using the Bayesian credible interval function.

Gene expression data were loaded into the R‐package lumi11 log2 transformed and quantile normalized. eQTLs were mapped using the scanone function in the R/qtl.10 Probes were mapped using BLAT12 against the mouse mm9 reference genome. Probes that matched to multiple locations or annotated transcripts from Ensembl release 63 were discarded. Probes containing polymorphisms, either an indel or a single nucleotide polymorphism (SNP), or probes mapping to known structural variants between DBA/2 and AKR strains1314 were discarded because they could lead to identification of false cis‐eQTLs.15 This was performed by taking the genomic locations from BLAT in the University of California Santa Cruz Genome Browser and using Tabix16 to retrieve sequence variants from the Mouse Genome Sequencing Project.1314 This filtering resulted in the removal of 2749 probes from the data set.

Human–mouse alignments generated previously by Schwarz et al17 were used to obtain the human regions corresponding to our mouse Ath QTLs, and within these regions we identified human GWAS loci18 related to CAD.

To compare eQTLs from the current and previous studies,7 matches between Affymetrix and Illumina's probes were provided by Illumina (http://www.switchtoi.com/probemapping.ilmn). To perform the combined cross‐QTL analyses, the SNPs from each cross were imput to each other using the fill.geno function in R/qtl, with the simple assumption of no double crossovers. In the prior cross, there were 1947 markers, whereas in the new cross, there were 599 markers, of which only 170 overlapped between the 2, leading to 2376 total markers. There is no metric for imputation quality, but we found that using the original set of markers in the second cross versus the combined set of markers did not greatly alter QTL location or strength. A liberal 20‐Mb window was used between studies to determine if an eQTL overlapped. A combined eQTL analysis was done with data from both studies, using cross membership as an additive covariate and sex as an interactive covariate.

Results and Discussion

Atherosclerosis QTL Replication in a New Cross

F2 mice were generated using a reciprocal cross strategy from apoE−/− mice on the AKR and DBA/2 backgrounds. Lesion areas in the aortic root were quantified in 166 F2 mice (77 female and 89 male). A genome scan was performed for each F2 mouse using 599 informative SNPs. We defined significant QTLs as those that have genome‐wide FDRs of <10%, by permutation analysis. Combining both sexes and using sex as an interactive covariate, we identified 3 suggestive Ath QTLs at a logarithm of odds (LOD) score threshold of 2.0 on chromosomes 2, 15, and 17 with FDRs of 15%, 30%, and 16%, respectively (Table 1). Although these Ath QTLs only met the suggestive threshold due to small sample size, each of these Ath QTLs were detected in a prior AKR×DBA/2 strain intercross19: Ath28, a suggestive QTL on chromosome 2; Ath22, a significant QTL on chromosome 15; and Ath26, a significant QTL on chromosome 17. We performed a combined Ath QTL analysis using both crosses with cohort membership as an additive covariate and sex as an interactive covariate. As the platform and markers used to genotype the 2 crosses differed, R/qtl20 was used to impute the genotypes between the 2 crosses. On chromosome 2, Ath28 was replicated and had a combined LOD score of 5.9; on chromosome 15, Ath22 was replicated with a combined LOD score of 5.3; and on chromosome 17, Ath26 was replicated with a combined LOD score of 5.6 (Figure 1). All of these combined LOD scores met the genome‐wide FDR threshold of <10%, and in fact they all had <5% FDR. However, the suggestive Ath QTLs identified in the first cross using sex as an interactive covariate on chromosomes 5, 3, and 1319 were not replicated in the second cross. The approximate 95% Bayesian credible interval was obtained for all 3 loci (Table 1). Thus, the clinical trait mouse QTL model is partially reproducible for a phenotype as complex as lesion area, which has a fairly large coefficient of variation within inbred strains.

Table 1.

Aortic Root Lesion (log10) QTLs in DBA/2×AKR F2 Cohort

Symbol Chromosome Bayesian CI,* Mb Second Cross LOD Score Prior Cross LOD Score FDR Combined Cross LOD FDR
Ath28 2 165.1 to 179.3 2.8 3.2 0.15 5.9 <0.05
Ath22 15 3.6 to 31.9 2.0 2.1 0.30 5.3 <0.05
Ath26 17 12.4 to 64.3 2.7 4.4 0.16 5.6 <0.05

QTL indicates quantitative trait loci; LOD, logarithm of odds; FDR, false discovery rate.

*

Based on the combined cross‐analysis.

Figure 1.

Figure 1.

Log10 aortic root lesion atherosclerosis (Ath) quantitative trait locus (QTL) plots. The pink and blue lines show the logarithm of odds (LOD) plots for the prior and new crosses of AKR apoE−/− and DBA/2 apoE−/− mice, respectively. The black line shows the LOD plot for the combined analysis using cross as an additive covariate. In all analyses, sex was used as an interactive covariate.

We identified the human chromosome segments orthologous to these mouse loci. We examined whether these human orthologous regions contained common genetic variants associated with CAD, myocardial infarction, or related risk factors by searching the National Human Genome Research Institute GWAS catalog18 (Table 2). The known atherosclerosis‐related risk factors included blood lipid levels, subclinical atherosclerosis, type 2 diabetes, and hypertension. There were no human CAD GWAS hits in the region in synteny with Ath28, although ≈21% of the Ath28 interval on chromosome 2 displayed no synteny due to complex expansion in the mouse genome after species divergence. The Ath22 locus on chromosome 15 contains the corresponding segment on human chromosome 5 that has been associated with subclinical atherosclerosis.21 The Ath26 locus on chromosome 17 corresponds to human chromosomes 6 (primarily) and 19, including the major histocompatibility complex locus, and overlaps with multiple human GWAS loci for CAD and related risk factors (Table 2).

Table 2.

Corresponding GWAS Hits in Human Orthologous Regions

Chromosome Position rsID Author Trait Nearest Gene
2 (Ath28)
No hits
15 (Ath22)
5 13764419 rs2896103 C.J. O'Donnell Subclinical atherosclerosis traits (other) DNAH5
5 13769974 rs7715811 C.J. O'Donnell Subclinical atherosclerosis traits (other) DNAH5
5 13779743 rs1502050 C.J. O'Donnell Subclinical atherosclerosis traits (other) DNAH5
17 (Ath26)
6 160578859 rs1564348 T.M. Teslovich LDL cholesterol LPA
6 160578859 rs1564348 T.M. Teslovich Cholesterol, total LPA
6 160741621 rs3120139 Q. Qi Lp(a) levels SLC22A3
6 160863531 rs2048327 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160863531 rs2048327 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160907133 rs3127599 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160907133 rs3127599 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160910516 rs12214416 Q. Qi Lp(a) levels LPAL2
6 160960358 rs6919346 C. Ober Lp(a) levels LPA
6 160961136 rs3798220 H. Schunkert Coronary heart disease LPA
6 160962502 rs7767084 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160962502 rs7767084 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160969737 rs10755578 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 160969737 rs10755578 D.A. Tregouet Coronary heart disease SLC22A3,LPAL2,LPA
6 161010117 rs10455872 D.I. Chasman Response to statin therapy (LDL cholesterol) LPA
6 161010117 rs10455872 Q. Qi Lp(a) levels LPA
6 161089816 rs1084651 T.M. Teslovich HDL cholesterol LPA
6 161137989 rs783147 Q. Qi Lp(a) levels PLG
6 34546560 rs2814982 T.M. Teslovich Cholesterol, total C6orf106
6 34552797 rs2814944 T.M. Teslovich HDL cholesterol C6orf106
6 35034800 rs17609940 H. Schunkert Coronary heart disease ANKS1A
19 8433196 rs7255436 T.M. Teslovich HDL cholesterol ANGPTL4
19 8469738 rs2967605 S. Kathiresan HDL cholesterol ANGPTL4
6 31184196 rs3869109 R.W. Davies Coronary heart disease HCG27, HLAC
6 32412435 rs3177928 T.M. Teslovich LDL cholesterol HLA
6 32412435 rs3177928 T.M. Teslovich Cholesterol, total HLA
6 32669373 rs11752643 F. Takeuchi Coronary heart disease HLA, DRBDQB
6 33143948 rs2254287 C.J. Willer LDL cholesterol B3GALT4
6 43758873 rs6905288 R.W. Davies Coronary heart disease VEGFA

GWAS indicates genome wide association studies; Lp(a), lipoprotein(a); LDL, low‐density lipoprotein; HDL, high‐density lipoprotein.

Protein Coding Differences Between AKR and DBA/2 Mice Residing in Ath QTLs

We used a variety of bioinformatic and genomic methods to identify candidate genes that may be responsible for the 3 replicated Ath QTLs. Using the mouse sequence data from 15 common inbred strains,1314 we identified all of the nonsynonymous protein changes in these 3 loci. These strain variable genes on chromosomes 2 (11 genes), 15 (23 genes), and 17 (258 genes) are listed in Table S1, with many genes having >1 amino acid substitution between these 2 strains. We identified many more strain variant genes for Ath26 on chromosome 17, because it is a very large 52‐Mb gene‐dense interval that contains the highly polymorphic mouse H2 major histocompatibility region. After exclusion of the major histocompatibility genes, we used Polyphen 222 to ascertain in silico the likelihood that each protein coding change would impair protein function, and we found numerous potential protein functional differences between the 2 strains (Tables 3 and S1).

Table 3.

AKR and DBA/2 Protein Differences Within the Ath28, Ath22, and Ath26 CIs Predicted by Polyphen to Be Detrimental

Chromosome Position Reference Allele Alternate Allele AKR* DBA* Gene Symbol AA Position AA Alteration Polyphen Score*
2 165177862 C T 1/1 0/0 Zfp663 646 G>R 0.98
2 165179205 G A 1/1 0/0 Zfp663 198 T>I 0.969
2 172377285 T C 0/0 1/1 Tcfap2c 143 Y>H 0.917
2 173034738 G C 1/1 0/0 Zbp1 280 T>S 0.944
15 3929418 C T 0/0 1/1 Fbxo4 3 G>R 1
15 4705267 G A 1/1 0/0 C6 205 R>K 1
15 4741106 G T 1/1 0/0 C6 533 R>M 0.591
15 4888423 G T 1/1 0/0 Heatr7b2 981 Q>H 0.989
15 4984193 G A 1/1 0/0 C7 242 T>M 0.78
15 9297067 T G 1/1 0/0 Ugt3a2 380 H>Q 0.966
15 11834935 C T 1/1 0/0 Npr3 154 A>T 1
15 27492564 C T 0/0 1/1 Ank 201 A>V 0.932
15 28275570 C T 0/0 1/1 Dnahc5 2434 R>W 0.908
17 12243519 G C 0/0 1/1 Park2 397 E>Q 1
17 17987504 C T 0/0 1/1 Has1 40 A>T 0.638
17 18048331 T G 1/1 0/0 Gm7535 194 D>A 0.958
17 18048648 C T 1/1 0/0 Gm7535 88 M>I 0.875
17 18395099 A G 1/1 0/0 Vmn2r94 117 S>P 1
17 18719527 C T 0/0 1/1 Vmn2r96 53 A>V 1
17 19084957 G T 1/1 0/0 Vmn2r97 836 L>F 0.951
17 19203418 G T 0/0 1/1 Vmn2r98 405 A>S 0.937
17 19204356 G A 0/0 1/1 Vmn2r98 496 E>K 0.979
17 19814743 C G 1/1 0/0 Vmn2r102 352 P>R 0.806
17 19910406 G C 1/1 0/0 Vmn2r103 27 C>S 1
17 19949143 G T 0/0 1/1 Vmn2r103 738 K>N 1
17 20405284 C T 0/0 1/1 Vmn2r106 606 V>I 0.986
17 20415678 A C 0/0 1/1 Vmn2r106 312 Y>D 0.975
17 20608324 C T 1/1 0/0 Vmn2r108 300 M>I 0.793
17 20639402 T G 1/1 0/0 Vmn1r225 47 L>R 0.998
17 21050607 A T 0/0 1/1 Vmn1r232 232 F>I 0.774
17 21423632 C T 0/0 1/1 Vmn1r236 16 T>I 0.953
17 23496190 G A,T 0/0 1/1 Vmn2r115 557 V>F 0.892
17 23802717 A T 0/0 1/1 Ccdc64b 170 T>S 0.961
17 24558772 G A 1/1 0/0 Rnps1 165 G>E 0.953
17 24701163 A G 1/1 0/0 Pkd1 95 E>G 0.985
17 25240572 C T 1/1 0/0 Telo2 664 V>M 0.946
17 25242093 C T 0/0 1/1 Telo2 531 R>H 1
17 25247204 G A 0/0 1/1 Telo2 301 R>C 0.998
17 25305356 A T 0/0 1/1 Ccdc154 380 Q>L 0.924
17 25305357 G T 0/0 1/1 Ccdc154 380 Q>H 0.996
17 25436769 T C 0/0 1/1 Prss34 260 L>P 0.996
17 25457599 A G 1/1 0/0 Prss29 74 T>A 0.997
17 29018352 G A 1/1 0/0 Pnpla1 416 S>N 0.766
17 29018363 T A 1/1 0/0 Pnpla1 420 L>M 0.94
17 29275100 G T 1/1 0/0 Rab44 86 Q>H 1
17 29296944 C T 1/1 0/0 Cpne5 506 V>M 0.862
17 29994582 C T 1/1 0/0 Mdga1 54 D>N 0.997
17 30814214 C A,T 0/0 1/1 Dnahc8 886 L>M 1
17 31145549 A T 0/0 1/1 Umodl1 1304 I>F 0.933
17 31372493 G A 1/1 0/0 Ubash3a 450 V>M 0.948
17 32838830 C T 1/1 0/0 Cyp4f15 378 S>F 0.827
17 33062306 A G 1/1 0/0 Cyp4f13 453 S>P 0.739
17 33731241 C T 1/1 0/0 Myo1f 658 R>C 0.993
17 34048493 A G 1/1 0/0 Daxx 179 N>S 0.734
17 34057211 C G 0/0 1/1 Tapbp 79 L>V 0.669
17 34069629 C T 0/0 1/1 Rgl2 234 A>V 0.999
17 34072961 G A 0/0 1/1 Rgl2 665 V>I 0.969
17 34102686 A T 0/0 1/1 Vps52 663 S>C 0.996
17 34165995 C T 1/1 0/0 Slc39a7 393 V>M 0.968
17 34195857 G A 1/1 0/0 Col11a2 1044 A>T 0.961
17 34196094 G A 0/0 1/1 Col11a2 1079 V>M 0.996
17 34499618 G A 0/0 1/1 Btnl2 242 E>K 0.904
17 34518474 A C 0/0 1/1 Btnl3 300 K>Q 0.81
17 34597021 A C 1/1 0/0 BC051142 264 Q>P 0.663
17 34645055 G A,T 2/2 0/0 Btnl6 482 A>D 0.996
17 34645142 C G 0/0 1/1 Btnl6 453 S>T 0.936
17 34645839 T C 0/0 1/1 Btnl6 337 Q>R 0.752
17 34652479 C G 0/0 1/1 Btnl6 85 E>Q 0.893
17 34670298 A G 1/1 0/0 Btnl7 426 F>L 0.999
17 34670922 G A 1/1 0/0 Btnl7 334 R>C 0.999
17 34679441 C T 1/1 0/0 Btnl7 132 G>R 0.997
17 34721459 G A 0/0 1/1 Notch4 1469 R>Q 0.997
17 34724653 A G 1/1 0/0 Notch4 1873 Y>C 0.995
17 34735125 G A 1/1 0/0 Ager 31 G>E 1
17 34782359 C T 0/0 1/1 Fkbpl 52 P>L 0.957
17 34787670 G T 0/0 1/1 Atf6b 233 A>S 0.975
17 34808447 A G 0/0 1/1 Tnxb 273 Q>R 0.963
17 34831297 A C 1/1 0/0 Tnxb 1903 E>A 0.944
17 34832575 C G 1/1 0/0 Tnxb 2020 H>D 0.794
17 34833521 C T 0/0 1/1 Tnxb 2167 T>I 0.993
17 34840315 C T 0/0 1/1 Tnxb 2494 P>S 0.992
17 34867829 C T 0/0 1/1 C4b 1442 R>K 0.613
17 35163365 G A 0/0 1/1 Ng23 129 T>M 0.941

AA indicates amino acid; MHC, major histocompatibility complex. Table excludes the MHC genes and several zinc‐finger protein genes.

*

0 is the reference allele; 1 is the first or only alternate allele; and 2 is the second alternate allele.

*

Probability of detrimental amino acid substitution, using >0.5 as the threshold.

On chromosome 2, only 3 protein changes were predicted to be damaging in 1 strain relative to the other strain. Zbp1 is a Z‐DNA binding protein, Tcfap2c is an AP‐2 transcription factor involved in early development, and Zfp663 is a zinc‐finger protein; none of these proteins have been previously implicated in atherosclerosis susceptibility. On chromosome 15, there were several protein coding changes that are predicted to be detrimental in 1 strain versus the other. Two components of the complement system, C6 and C7, have predicted functional differences, both with the AKR version being detrimental. The complement system has potential roles in cardiovascular disease as previously reviewed.23 On chromosome 17, there were 50 genes with predicted detrimental changes, and many additional changes in major histocompatibility complex genes, that were not subjected to the Polyphen analysis. Some notable protein changes were found in Rab44, Collagen 11a2, and Notch4, which can alter cellular vesicular trafficking, extracellular matrix, and signal transduction, respectively, all potential atherosclerosis modifiers.

eQTLs in Bone Marrow–Derived Macrophages and Endothelial Cells

The global profile of gene expression in bone marrow–derived macrophages was assayed using Illumina microarrays from 79 female and 81 male F2 mice. With the same 599 SNPs used to map the Ath QTLs, we mapped eQTLs, or loci that are associated with the expression of each transcript, using sex as an additive covariate. An eQTL was defined as a cis‐eQTL if the eQTL mapped within 20 Mb of the probe position. A trans‐eQTL is defined as the QTL mapping anywhere else on the genome. To eliminate spurious eQTLs, we filtered out 2479 expression array probes that contained an SNP or insertion/deletion between these 2 strains, which could lead to altered probe hybridization impairing an accurate measure of gene expression. We validated that these strain variant probes would indeed lead to false cis‐eQTLs with on average an LOD score that was double the LOD score of comparable probes containing no variant (LOD 14.7 versus 7.6, P<2.2×10−6). In addition, the transcripts with the nonreference SNP allele overlapping the probes were overwhelmingly called with lower expression values versus the transcripts containing the reference allele (Figure S1). After filtering out probes that were not expressed above background in ≥25% of the samples, 9600 probes were evaluated for eQTLs. We used a stringent FDR cut‐off of 5% to identify cis‐eQTLs, which corresponded to an LOD score threshold of 2.4 and found 937 cis‐eQTLs (Table S2). Table 4 shows the top 25 cis‐eQTLs ranked by LOD score. Because trans‐eQTLs are indirect, and often not as strong as cis‐eQTLs, we applied both a liberal FDR cutoff of 30% and a stringent 5% cutoff. The 30% and 5% FDR thresholds corresponded to LOD scores of 2.81 and 3.75, respectively, with 3797 and 551 trans‐eQTLs identified, respectively (Table S3). Table 5 shows the top 25 trans‐eQTLs ranked by LOD score.

Table 4.

Top 25 cis‐eQTLs by LOD Score in BMMs

Gene Symbol QTL Marker QTL Chromosome QTL Marker Position LOD
Rnps1 rs3719497 17 24100880 55.9
Fblim1 rs3688566 4 140026440 54.0
Zfp277 rs13481408 12 35475720 44.7
2210012G02Rik rs3709486 4 109968331 43.9
Atg9b CEL‐5_24211033 5 24211033 42.5
Vill rs3669563 9 117891342 41.2
Gjb4 gnf04.123.367 4 126400415 35.3
Gm962 CEL‐19_5283144 19 5283144 35.0
Insl6 rs3090325 19 26007713 33.3
Gm962 CEL‐19_5283144 19 5283144 32.8
Hint2 CEL‐4_40541402 4 40541402 32.6
Agpat5 rs3657963 8 16576750 32.1
Prss22 rs3726555 17 15215815 31.5
Ccdc163 rs3709486 4 109968331 30.7
Sys1 rs3671849 2 163215888 30.4
Abhd1 rs13469943 5 29486094 30.1
Tuft1 rs13477261 3 92344335 28.0
Usp2 rs4135590 9 43060131 28.0
H2Gs10 rs3682923 17 34343989 27.7
Abhd1 rs13469943 5 29486094 27.5
Zfp420 rs4226520 7 18758740 27.5
H2‐T10 rs6298471 17 35059374 26.9
Pdxdc1 rs4163196 16 13143895 26.5
Fgr rs3663950 4 134187547 26.1
Scamp5 rs13480208 9 55395056 25.7

eQTL indicates expression quantitative trait loci; LOD, logarithm of odds; BMM, bone marrow macrophage.

Table 5.

Top 25 trans‐eQTLs by LOD Score in BMMs

Gene Symbol QTL Chromosome QTL Marker Position QTL Marker LOD Probe Chromosome Probe Location
Akr1e1 4 141638718 rs3023025 28.6 13 4592177
Mcee 7 51544526 rs3714908 16.5 7 71556822
Man2a2 7 65348455 rs13479355 16.4 7 87505769
Gdpd3 7 111285662 rs6275579 16.1 7 133914693
Pde2a 7 87305015 rs13479427 15.1 7 108661076
Alg8 7 80158909 rs4226783 14.7 7 104540400
Gstp2 1 188355284 rs3667164 14.2 19 4041930
Man2a2 7 66776784 rs13479358 13.0 7 87505788
Dgcr6 17 34343989 rs3682923 12.4 16 18070266
Crym 7 104533846 rs13479477 11.7 7 127330117
Iqgap1 7 65348455 rs13479355 10.8 7 87857712
Stab 2 13 63888326 rs4229817 10.7 10 86304140
Heatr5a 12 29204179 rs6223000 10.5 12 52977981
Mlycd 13 70810674 rs13481880 9.8 8 121934766
Arap1 7 77850273 CEL‐7_77850273 9.0 7 108560953
Ifitm6 7 126965988 rs3663988 9.0 7 148201750
Fam168a 7 77850273 CEL‐7_77850273 8.3 7 107987317
Ints3 3 60037290 rs13477138 7.7 3 90195467
Plscr4 9 63239299 gnf09.057.223 7.5 9 92387070
Snrpn 7 33835314 rs8260975 7.3 7 67128021
Fam125b 2 10929543 rs6240512 6.9 2 33585812
Unc45a 7 66776784 rs13479358 6.9 7 87470214
Capn10 17 45506664 rs6409750 6.6 1 94844286
Nasp 4 91308682 rs6271003 6.6 4 116273846

eQTL indicates expression quantitative trait loci; LOD, logarithm of odds; BMM, bone marrow macrophage.

Lusis has proposed that mouse strain effects on EC function may underlie some strain effects on atherosclerosis.24 We successfully cultured primary aortic ECs from 48 male F2 mice used in the atherosclerosis study and assayed global gene expression by microarray. As expected, these cells expressed high levels of canonical EC transcripts encoding the proteins Tie2, the Vegf receptors, and von Willebrand factor, all of which were lowly expressed in BMMs. We applied the same FDR thresholds as in the macrophage analysis to identify EC cis‐ and trans‐eQTLs. At the 5% FDR threshold, corresponding to an LOD score of 2.47, we identified 440 cis‐eQTLs (Table S4 and top 25 in Table 6). For trans‐eQTLs, the 30% and 5% FDR thresholds corresponded to LOD scores of 2.70 and 3.92, with 4894 and 365 trans‐eQTLs identified, respectively (Table S5 and top 25 in Table 7).

Table 6.

Top 25 cis‐eQTLs by LOD Score in ECs

Gene Symbol QTL Chromosome QTL Marker Position QTL Marker LOD
Thumpd1 7 107424656 rs3709679 31.7
Mod1 9 90513305 gnf09.087.298 29.2
Mff 1 85865441 rs3723062 28.0
Paip1 13 115056838 rs13482035 27.5
Ercc5 1 44668113 CEL‐1_44668113 24.3
Lrrc57 2 117074373 rs13476723 24.1
G430022H21Rik 3 122002332 rs3659836 23.1
Aqr 2 111095530 rs13476698 22.2
Atpbd3 7 33574760 rs8255275 21.1
Abhd1 5 29486094 rs13469943 18.9
Scoc 8 82188194 rs13479863 17.1
Zfp277 12 34954150 rs13481406 16.7
Grwd1 7 33574760 rs8255275 16.2
Ugt1a6a 1 87104170 UT_1_89.100476 16.0
2610019P18Rik 5 135836567 rs4225536 15.0
Rnf41 10 122911418 rs13480803 15.0
Slc25a3 10 93288075 rs13480712 14.9
Pdxdc1 16 12215630 rs4162800 14.8
4930455C21Rik 16 30855920 rs4168640 14.6
Il3ra 14 7401248 rs3150398 14.6
Tpmt 13 46624183 rs6411274 14.5
Arid4b 13 12961456 rs13481697 14.2
Pdxdc1 16 12215630 rs4162800 14.0
BC031748 X 129847872 rs13484031 13.0

eQTL indicates expression quantitative trait loci; LOD, logarithm of odds; EC, endothelial cells.

Table 7.

Top 25 trans‐eQTLs by LOD Score in ECs

Gene Symbol QTL Marker QTL Chromosome QTL Marker Position LOD Probe Chromosome Probe Location
Tob2 rs13480854 11 7518795 7.24 15 81679613
Adi1 rs6344105 12 63022076 6.90 12 29366235
Mrgprg rs13482407 14 114388484 6.46 7 150950410
Rb1 rs3663355 4 47358427 6.39 14 73595412
P2ry6 rs3707067 7 85992410 6.20 7 108086188
Slc10a7 rs13477617 4 27105003 5.99 8 81230781
Trp53bp1 rs13482418 15 3498960 5.94 2 121025364
Mgst3 rs6279930 1 137268795 5.92 1 169303924
Fam168a rs13479324 7 57878499 5.89 7 107987317
Eml1 rs6393948 11 103272243 5.84 12 109726577
Mrvi1 rs13476928 2 174162530 5.82 7 118012039
Tprn rs3669563 9 117891342 5.78 2 25125227
Cdk2ap2 rs6290836 14 9149500 5.71 19 4098608
Spcs3 gnf18.051.412 18 53592447 5.64 8 55606073
Trap1 rs3699561 1 130962369 5.54 16 4040058
Eral1 gnf04.123.367 4 126400415 5.50 11 77887218
BC013529 rs13477617 4 27105003 5.47 10 7487771
Tcf20 rs13483085 17 66984514 5.43 15 82640181
Prpsap2 rs13482673 15 82560799 5.42 11 61543254
Rin3 rs3721056 9 71328971 5.38 12 103628978
Dhcr24 rs3664408 2 161443571 5.37 4 106259325
Nxt1 rs3663950 4 134187547 5.36 2 148501307
Rtn2 rs13476928 2 174162530 5.34 7 19881245
Mlst8 rs13482035 13 115056838 5.33 17 24610627

eQTL indicates expression quantitative trait loci; LOD, logarithm of odds; EC, endothelial cells.

To evaluate cross‐tissue eQTLs, we counted the number of cis‐eQTLs (5% FDR) and trans‐eQTLs (30% FDR) that were found in both macrophages and ECs. We identified 156 cis‐eQTLs (Table S6) common in both tissues, although our power was limited by the relatively small number of EC samples. We identified 12 cross‐tissue cis‐eQTLs that were located in the 3 replicated Ath QTLs in chromosomes 2, 15, and 17 (Table 8). An example of a cross‐tissue cis‐eQTL within an Ath QTL interval is Sys1, coding for the Golgi‐localized integral membrane protein homolog (Figure 2). In contrast to the 156 cross‐tissue cis‐eQTLs, there were only 18 cross‐tissue trans‐eQTLs at the 30% FDR threshold that overlapped the 2 tissues (Table 9). A replicated trans‐eQTL is defined one in which the trans‐eQTL markers map within 10 Mb of each other. On inspection, it appears that 3 of these cross‐tissue trans‐eQTLs on chromosome 7 may in fact be cis‐eQTLs, because the positions of the gene and the markers were on the chromosome 7 and only slightly greater that the 20‐Mb cutoff used to classify cis‐eQTLs. The low number of cross‐tissue trans‐eQTLs has been noted in previous studies.25 One of these cross‐tissue trans‐eQTLs mapped to the Ath22 interval on chromosome 15, which was associated with the expression of the Klf2 transcription factor on chromosome 8.

Table 8.

cis‐eQTLs That Are Found in Both ECs and BMMs at <5% FDR That Also Reside Within the AthQTLs

Probe_ID Gene Symbols QTL Chromosome BMM eQTL Position EC eQTL Position BMM LOD EC LOD
ILMN_2674425 Sys1 2 163215888 163215888 30.45 10.91
ILMN_1216029 Cstf1 2 174162530 174162530 3.87 3.67
ILMN_2869312 Fbxo4 15 5744460 4222769 7.06 10.81
ILMN_3123120 Rnps1 17 24100880 15215815 55.90 11.24
ILMN_2601877 Brd4 17 34343989 34343989 2.97 4.60
ILMN_2810539 H2‐Gs10 17 34343989 39772541 27.72 9.78
ILMN_2691360 Mrps10 17 39772541 43897393 6.98 3.99
ILMN_1256171 Tmem63b 17 43897393 43897393 16.68 8.49
ILMN_2734045 Mrpl14 17 45506664 35059374 20.28 5.97
ILMN_2804487 Aif1 17 45506664 39772541 2.62 3.49
ILMN_2761876 Fez2 17 62066360 72668814 3.69 3.25
ILMN_3090123 Dync2li1 17 82051202 87503632 22.79 6.35

eQTL indicates expression quantitative trait loci; EC, endothelial cells; BMM, bone marrow macrophage; FDR, false discovery rate; LOD, logarithm of odds.

Figure 2.

Figure 2.

Example of a replicated cis‐eQTL between tissues (A and C) and between studies (A and B) of Sys1, an integral Golgi‐associated membrane protein. Means±SEM are shown adjacent to the individual values. P and R2 values were obtained by linear regression with sex as an additive covariate. eQTL indicates expression quantitative trait loci; BMM, bone marrow macrophage; EC, endothelial cell.

Table 9.

trans‐eQTLs That Are Found in Both ECs and BMMs at <30% FDR

Probe_ID Gene Symbols QTL Chromosome BMM eQTL Position EC eQTL Position BMM LOD EC LOD Probe Chromosome Probe Position
ILMN_2759167 Gtpbp5 1 152747565 160294867 4.65 2.98 2 179820490
ILMN_2629375 1110038F14Rik 3 41838640 41838640 3.32 4.03 15 76780014
ILMN_2740285 Fancl 3 126894715 132189425 2.85 2.86 11 26371341
ILMN_2602837 Akr1e1 4 141638718 134187547 28.63 2.82 13 4592177
ILMN_1245307 Fbln2 5 39608047 39608047 3.04 2.79 6 91221963
ILMN_2685329 Hspg2 5 39608047 39608047 2.87 2.88 4 137126406
ILMN_2622057 Tsen2 5 117374791 111603432 3.16 4.78 6 115527976
ILMN_2791578 Gspt1 5 131766121 135836567 3.14 2.96 16 11220678
ILMN_1255175 Unc45a 7 66776784 65348455 6.09 3.31 7 87470402
ILMN_2893879 Gdpd3 7 111285662 112152410 16.13 5.25 7 133914693
ILMN_2689056 Cd2bp2 7 112152410 112152410 6.11 5.08 7 134335721
ILMN_2751354 Pde4dip 8 84344531 86397354 4.17 3.17 3 97542917
ILMN_2604029 Klf2 15 34383985 41359817 3.17 3.10 8 74844875
ILMN_1256434 Pigk 15 72483350 72483350 3.08 3.85 3 152448803
ILMN_2836924 Wdr45 15 95679367 92664963 2.97 2.74 20 7305117
ILMN_3114998 Zfp658 15 95679367 92664963 3.44 3.70 7 50830408
ILMN_2672778 Abhd1 17 66984514 69670995 3.11 3.18 5 31255322
ILMN_3038459 Morf4l1 19 21112530 29540192 2.86 2.76 9 89998557

eQTL indicates expression quantitative trait loci; LOD, logarithm of odds; EC, endothelial cell; BMM, bone marrow macrophage; FDR, false discovery rate.

Macrophage eQTL Replication Between Different Crosses and Different Platforms

A macrophage eQTL study was performed in the previous AKR×DBA/2 F2 intercross; however, different genetic markers and different expression array platforms were used. To examine replication of macrophage eQTLs between the current and previous study, we reanalyzed the prior data by imputing to the currently used 599 strain‐specific SNPs and mapping the Affymetrix gene expression probes to the currently used Illumina probes. After filtering out probes not mapped to the Illumina platform or those that were excluded in our new cross, only 5678 probes remained for analysis. We then performed the eQTL analysis of the prior dataset using sex as an additive covariate and obtained cis‐ and trans‐eQTLs at the same FDRs as described earlier (summary statistics in Table 10). Of the 738 and 482 cis‐eQTLs identified in the prior and new crosses, respectively, 265 were replicated, representing 36% and 55% of the input cis‐eQTLs in the old and new cross, respectively (Figure 3, Table S7). The cis‐eQTL replication percentage range (36% to 55%) in our study is somewhat lower than that of previously published replication study by van Nas et al that found a cis‐eQTL replication rate of ≈50% to 60%.25 However, van Nas et al used the same platform and genotyping markers across their 2 studies, whereas we used separate platforms. In addition, van Nas et al probably overestimated the replication rate, because they did not remove probes containing strain polymorphic SNPs as we did in our study. We demonstrated that inclusion of the strain‐polymorphic probes leads to strong false‐positive eQTLs. Sys1 not only had a cross‐tissue cis‐eQTL, but it is also an example of a cross‐study replicated cis‐eQTL in BMMs (Figure 2). The SNP rs3671849, within the Ath28 locus, displayed a strong additive effect on the expression of Sys1, with the DBA/2 allele expressed higher. This marker was associated with 51% and 42% of the variation in BMM Sys1 gene expression in the new and prior crosses, respectively, and 63% of the variation in EC Sys1 gene expression.

Table 10.

Summary Statistics and Replication of Bone Marrow Macrophage cis‐ and trans‐eQTLs for the Prior and New Crosses Using the Restricted Set of Common Probes

cis‐eQTLs trans‐eQTLs
No. of eQTLs (5% FDR) prior cross 738 281
No. of eQTLs (5% FDR) new cross 482 274
No. of eQTLs common between old and new (5%) 265 5
No. of eQTLs common between old and new (30%) ND 23
No. of eQTLs in combined analysis (5% FDR)* 783 703
No. of eQTLs in combined analysis (30% FDR)* ND 3158

eQTL indicates expression quantitative trait loci; FDR, false discovery rate; ND, not determined.

*

Combined sex eQTL analysis in both crosses using sex as an additive covariate.

Figure 3.

Figure 3.

Venn diagram of the overlap between the cis‐eQTL in the new cross and the old cross. Transcripts were limited to only the transcripts that were called present in both and had corresponding probe between the platforms. eQTL indicates expression quantitative trait loci.

There were only 5 trans‐eQTLs that replicated between the 2 crosses, or 0.9% and 0.6% of the old cross and new cross trans‐eQTLs, respectively, at a 5% FDR LOD score cutoff (Table 11). The LOD plots and allele effects on gene expression for the Lamb2 gene, which had a replicated trans‐eQTL, is shown in Figure 4. Relaxing the FDR to 30% in both crosses resulted in 23 trans‐eQTLs that replicated between the studies, or 6% and 4% of the old cross and new cross trans‐eQTLs, respectively. This is lower than the ≈19% trans‐eQTL replication rate observed by van Nas et al; however, the same caveats apply to our analysis concerning our use of 2 expression array and SNP platforms.25

Table 11.

Replicated trans‐eQTL Between Crosses at the 5% FDR Level

Prior Probe ID New Probe ID QTL Chromosome Prior QTL Marker Position, Mb New QTL Marker Position, Mb Prior LOD Score New LOD Score Gene Symbol Probe Chromosome Probe Position, Mb
1416513_at ILMN_2699488 1 11.3 4.5 5.0 6.4 Lamb2 9 108.4
1419423_at ILMN_2737368 13 74.5 63.9 6.3 10.7 Stab 2 10 86.3
1437470_at ILMN_2780759 1 169.2 188.4 7.1 4.1 Pknox1 17 31.7
1448609_at ILMN_2493175 1 8.1 13.0 13.9 5.1 Tst 15 78.2
1451343_at ILMN_1240149 8 44.5 43.9 5.8 4.1 Vps36 8 23.4

eQTL indicates expression quantitative trait loci; LOD, logarithm of odds; FDR, false discovery rate.

Figure 4.

Figure 4.

An example of a replicating trans‐eQTL on chromosome 4 for the Lamb2 gene residing on chromosome 9. eQTL indicates expression quantitative trait loci; LOD, logarithm of odds.

As an alternative to examining replication of eQTLs, we combined the data from both F2 cohorts and performed a combined analysis of cis‐ and trans‐macrophage eQTLs using sex and cross as additive covariates. The combined method has more power to identify eQTLs than the replication method because it uses a larger sample size and thus is not penalized by a near‐miss false‐negative result in 1 of the 2 crosses. In the combined analysis, there were 783 cis‐eQTLs at a 5% FDR threshold (Tables 10 and S8). An example of a significant cis‐eQTL found in the combined analysis, but not in the replicated analysis, is an eQTL for Wdr70, a WD40 repeat adapter protein. In the combined analysis, there were 160 cis‐eQTLs that were found that were not found in either analysis. Furthermore, there were 703 and 3158 trans‐eQTLs at the 5% and 30% FDR thresholds in the combined analysis, respectively (Tables 10 and S9).

We systematically searched for replicated eQTLs within the Ath QTL regions to identify potential atherosclerosis modifier candidate genes. In total, there were 14 genes that met this criterion, and for each we determined the correlation of macrophage gene expression and lesion area within the F2 mice of the prior and current crosses. Twelve of these correlations had conserved directions in the 2 crosses (Table 12). At the Ath28 locus on chromosome 2, we identified 2 replicated macrophage cis‐eQTLs, of which Sys1 may have a connection to cholesterol ester metabolism. Sys1, whose expression was positively associated with lesion area, is a Golgi‐localized integral membrane protein that is essential for the targeting for several proteins to the Golgi complex and membrane vesicles26 including the small GTPases Arl3p and Arfrp1. Deletion of Arfrp1 results in loss of lipid droplet formation in adipocytes27; lipid droplets in macrophages store cholesterol esters and thus may play an important role in modifying atherosclerosis. At the Ath26 locus on chromosome 17, there were 9 replicated eQTLs with a shared direction of lesion area correlation, 2 of which have some prior link to atherosclerosis. Prss22 is a serine protease that converts prourokinase‐type plasminogen activator into its enzymatically active form, abbreviated as uPA.28 We found that Prss22 expression was inversely correlated with atherosclerosis; thus, we would predict that uPA activity may also be inversely correlated with atherosclerosis. However, this is not the case, as previous studies have shown that macrophage expression of uPA is positively associated with atherosclerosis in apoE‐deficient mice.2930 Ltb, encoding lymphotoxin‐β (a member of the tumor necrosis factor gene family), resides in the Ath26 locus, and its expression was positively correlated with lesion area. Lymphotoxin‐β receptor signaling in the arterial media beneath atherosclerotic plauques has been found to promote tertiary lymphoid organogenesis.31 In addition, circulating levels of lymphotoxin‐β receptor in humans were positively associated with coronary artery calcium scores.32 However, it is difficult to interpret whether these findings are relevant to our observed correlation of macrophage Ltb expression and lesion area. None of the other replicated eQTLs at the Ath loci had obvious known connections to pathways implicated in atherosclerosis.

Table 12.

Replicated cis‐eQTL Within Replicated Ath QTL Intervals That Have Replicated Direction of Expression–Lesion Correlation

Illumina Probe ID Affymetrix Probe ID Gene Symbol QTL Chromosome Expression–Lesion Correlation New Cross* Expression–Lesion Correlation Old Cross*
ILMN_2674425 1450057_at Sys1 2 0.06 0.18
ILMN_1216029 1448597_at Cstf1 2 −0.16 −0.13
ILMN_2710121 1416441_at Pgcp 15 −0.19 −0.12
ILMN_2688287 1420352_at Prss22 17 −0.04 −0.18
ILMN_2615207 1418321_at Eci1 17 −0.29 −0.15
ILMN_1219908 1418344_at Tmem8 17 0.11 0.18
ILMN_1218891 1419547_at Fahd1 17 −0.06 −0.13
ILMN_2667889 1417173_at Atf6b 17 0.02 0.13
ILMN_1241923 1449537_at Msh5 17 −0.18 −0.26
ILMN_2726308 1449021_at Rpp21 17 −0.26 −0.10
ILMN_1258283 1419135_at Ltb 17 0.16 0.16
ILMN_2761876 1434348_at Fez2 17 −0.08 −0.07

eQTL indicates expression quantitative trait loci; Ath QTL, atherosclerosis quantitative trait loci.

*

Pearson's correlation R value.

Conclusions

We found that phenotypic QTLs for the complex trait of atherosclerosis were partially reproducible. Of the 6 Ath QTLs indentified in the prior cross, the 2 significant QTLs replicated, as did 1 of 4 suggestive QTLs in a combined analysis with the new cross. In the new and smaller cross, all 3 of the suggestive Ath QTLs were found in the prior cross. Based on these results, it may be prudent to replicate phenotypic QTLs before embarking on extensive gene discovery and fine mapping studies.

We also report here than many cis‐eQTLs can be replicated in independent crosses even when the genotyping and gene expression platforms used differed between the studies. This is not unexpected because the cis‐eQTLs are direct and often have very strong effects on gene expression. However, we found a lower rate of trans‐eQTL replication compared with another replication study.25,33 Our conclusion is that many trans‐eQTLs identified in mouse studies may be false positives, or very sensitive to environmental effects, making replication less likely.

Sources of Funding

This work was supported by National Institutes of Health (NIH), National Heart, Lung, and Blood Institute grant HL098193. Jeffrey Hsu was supported by the Howard Hughes Medical Institute Med‐Into‐Grad Scholars Program and Molecular Medicine training grant T32GM088088 from the NIH National Institute of General Medical Sciences.

Disclosures

None.

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