Genetic basis of HDL variation in 129/SvImJ and C57BL/6J mice: importance of testing candidate genes in targeted mutant mice

A large-scale genome-lipid association map guides lipid identification

Despite the crucial roles of lipids in metabolism, we are still at the early stages of comprehensively annotating lipid species and their genetic basis. Mass spectrometry-based discovery lipidomics offers the potential to globally survey lipids and their relative abundances in various biological samples. To discover the genetics of lipid features obtained through high-resolution liquid chromatography-tandem mass spectrometry, we analysed liver and plasma from 384 diversity outbred mice, and quantified 3,283 molecular features. These features were mapped to 5,622 lipid quantitative trait loci and compiled into a public web resource termed LipidGenie. The data are cross-referenced to the human genome and offer a bridge between genetic associations in humans and mice. Harnessing this resource, we used genome-lipid association data as an additional aid to identify a number of lipids, for example gangliosides through their association with B4galnt1, and found evidence for a group of sex-specific phosphatidylcholines through their shared locus. Finally, LipidGenie's ability to query either mass or gene-centric terms suggests acyl-chain-specific functions for proteins of the ABHD family.

Influence of allelic differences in Down syndrome

Both trisomic and non-trisomic genes may affect the incidence and severity of phenotypes associated with Down syndrome (DS). The importance of extra (trisomic) genetic material is emphasized in DS, with less emphasis to the allelic composition of candidate trisomic genes in defining the trisomic gene-phenotype relationship in DS. Allelic differences in non-trisomic genes have been shown to be important moderators of cardiac, leukemia, and developmental phenotypes associated with DS. Trisomic mouse models provide an in vivo genetic platform for examining the gene-phenotype relationship, including the influence of allelic variants, on DS-like phenotypes. DS mouse models have differing trisomic genetic makeup, and optimal development, viability and translational value of these mouse models may require a non-inbred genetic background with heterogeneity at many loci. Additionally, understanding the contribution of specific genes or regions to DS phenotypes often requires the utilization of genetically manipulated mice that may be established on a different inbred background than the trisomic mice. The impact of allelic differences of trisomic and background genes in human and model systems may offer insight into the variability in occurrence and severity of trisomic phenotypes.

Deletion of Nrip1 Extends Female Mice Longevity, Increases Autophagy, and Delays Cell Senescence

Using age of female sexual maturation as a biomarker, we previously identified nuclear receptor interacting protein 1 (Nrip1) as a candidate gene that may regulate aging and longevity. In the current report, we found that the deletion of Nrip1 can significantly extend longevity of female mice (log-rank test, p = .0004). We also found that Nrip1 expression is altered differently in various tissues during aging and under diet restriction. Remarkably, Nrip1 expression is elevated with aging in visceral white adipose tissue (WAT), but significantly reduced after 4 months of diet restriction. However, in gastrocnemius muscle, Nrip1 expression is significantly upregulated after the diet restriction. In mouse embryonic fibroblasts, we found that the deletion of Nrip1 can suppress fibroblast proliferation, enhance autophagy under normal culture or amino acid starvation conditions, as well as delay oxidative and replicative senescence. Importantly, in WAT of old animals, the deletion of the Nrip could significantly upregulate autophagy and reduce the number of senescent cells. These results suggest that deleting Nrip1 can extend female longevity, but tissue-specific deletion may have varying effects on health span. The deletion of Nrip1 in WAT may delay senescence in WAT and extend health span.

Mapping and Congenic Dissection of Genetic Loci Contributing to Hyperglycemia and Dyslipidemia in Mice

Background

Patients with dyslipidemia have an increased risk of developing type 2 diabetes, and diabetic patients often have dyslipidemia. Potential genetic connections of fasting plasma glucose with plasma lipid profile were evaluated using hyperlipidemic mice.

Methods

225 male F₂ mice were generated from BALB/cJ (BALB) and SM/J(SM) Apoe-deficient (Apoe^−/−) mice and fed a Western diet for 5 weeks. Fasting plasma glucose and lipid levels of F₂ mice were measured before and after 5 weeks of Western diet and quantitative trait locus (QTL) analysis was performed using data collected from these two time points. 144 SNP(single nucleotide polymorphism) markers across the entire genome were typed.

Results

One major QTL (logarithm of odds ratio (LOD): 6.46) peaked at 12.7 cM on chromosome 9,Bglu16, and 3 suggestive QTLs on chromosomes 15, 18 and X were identified for fasting glucose, and over 10 loci identified for lipid traits. Bglu16 was adjacent to a major QTL, Hdlq17, for high-density lipoprotein (HDL) cholesterol (LOD: 6.31, peak: 19.1 cM). A congenic strain with a donor chromosomal region harboring Bglu16 and Hdlq17 on the Apoe^−/− background showed elevations in plasma glucose and HDL levels. Fasting glucose levels were significantly correlated with non-HDL cholesterol and triglyceride levels, especially on the Western diet, but only marginally correlated with HDL levels in F₂ mice.

Conclusions

We have demonstrated a correlative relationship between fasting glucose and plasma lipids in a segregating F₂ population under hyperlipidemic conditions, and this correlation is partially due to genetic linkage between the two disorders.

A forest-based feature screening approach for large-scale genome data with complex structures

Background

Genome-wide association studies (GWAS) interrogate large-scale whole genome to characterize the complex genetic architecture for biomedical traits. When the number of SNPs dramatically increases to half million but the sample size is still limited to thousands, the traditional p-value based statistical approaches suffer from unprecedented limitations. Feature screening has proved to be an effective and powerful approach to handle ultrahigh dimensional data statistically, yet it has not received much attention in GWAS. Feature screening reduces the feature space from millions to hundreds by removing non-informative noise. However, the univariate measures used to rank features are mainly based on individual effect without considering the mutual interactions with other features. In this article, we explore the performance of a random forest (RF) based feature screening procedure to emphasize the SNPs that have complex effects for a continuous phenotype.

Results

Both simulation and real data analysis are conducted to examine the power of the forest-based feature screening. We compare it with five other popular feature screening approaches via simulation and conclude that RF can serve as a decent feature screening tool to accommodate complex genetic effects such as nonlinear, interactive, correlative, and joint effects. Unlike the traditional p-value based Manhattan plot, we use the Permutation Variable Importance Measure (PVIM) to display the relative significance and believe that it will provide as much useful information as the traditional plot.

Conclusion

Most complex traits are found to be regulated by epistatic and polygenic variants. The forest-based feature screening is proven to be an efficient, easily implemented, and accurate approach to cope whole genome data with complex structures. Our explorations should add to a growing body of enlargement of feature screening better serving the demands of contemporary genome data.

Genetic linkage of hyperglycemia and dyslipidemia in an intercross between BALB/cJ and SM/J Apoe-deficient mouse strains

BACKGROUND

Individuals with dyslipidemia often develop type 2 diabetes, and diabetic patients often have dyslipidemia. It remains to be determined whether there are genetic connections between the 2 disorders.

METHODS

A female F2 cohort, generated from BALB/cJ (BALB) and SM/J (SM) Apoe-deficient (Apoe(-/-)) strains, was started on a Western diet at 6 weeks of age and maintained on the diet for 12 weeks. Fasting plasma glucose and lipid levels were measured before and after 12 weeks of Western diet. 144 genetic markers across the entire genome were used for quantitative trait locus (QTL) analysis.

RESULTS

One significant QTL on chromosome 9, named Bglu17 [26.4 cM, logarithm of odds ratio (LOD): 5.4], and 3 suggestive QTLs were identified for fasting glucose levels. The suggestive QTL near the proximal end of chromosome 9 (2.4 cM, LOD: 3.12) was replicated at both time points and named Bglu16. Bglu17 coincided with a significant QTL for HDL (high-density lipoprotein) and a suggestive QTL for non-HDL cholesterol levels. Plasma glucose levels were inversely correlated with HDL but positively correlated with non-HDL cholesterol levels in F2 mice on either chow or Western diet. A significant correlation between fasting glucose and triglyceride levels was also observed on the Western diet. Haplotype analysis revealed that "lipid genes" Sik3, Apoa1, and Apoc3 were probable candidates for Bglu17.

CONCLUSIONS

We have identified multiple QTLs for fasting glucose and lipid levels. The colocalization of QTLs for both phenotypes and the sharing of potential candidate genes demonstrate genetic connections between dyslipidemia and type 2 diabetes.

Body Composition QTLs Identified in Intercross Populations Are Reproducible in Consomic Mouse Strains

Genetic variation contributes to individual differences in obesity, but defining the exact relationships between naturally occurring genotypes and their effects on fatness remains elusive. As a step toward positional cloning of previously identified body composition quantitative trait loci (QTLs) from F2 crosses of mice from the C57BL/6ByJ and 129P3/J inbred strains, we sought to recapture them on a homogenous genetic background of consomic (chromosome substitution) strains. Male and female mice from reciprocal consomic strains originating from the C57BL/6ByJ and 129P3/J strains were bred and measured for body weight, length, and adiposity. Chromosomes 2, 7, and 9 were selected for substitution because previous F2 intercross studies revealed body composition QTLs on these chromosomes. We considered a QTL confirmed if one or both sexes of one or both reciprocal consomic strains differed significantly from the host strain in the expected direction after correction for multiple testing. Using these criteria, we confirmed two of two QTLs for body weight (Bwq5-6), three of three QTLs for body length (Bdln3-5), and three of three QTLs for adiposity (Adip20, Adip26 and Adip27). Overall, this study shows that despite the biological complexity of body size and composition, most QTLs for these traits are preserved when transferred to consomic strains; in addition, studying reciprocal consomic strains of both sexes is useful in assessing the robustness of a particular QTL.

Passenger Mutations Confound Interpretation of All Genetically Modified Congenic Mice

Targeted mutagenesis in mice is a powerful tool for functional analysis of genes. However, genetic variation between embryonic stem cells (ESCs) used for targeting (previously almost exclusively 129-derived) and recipient strains (often C57BL/6J) typically results in congenic mice in which the targeted gene is flanked by ESC-derived passenger DNA potentially containing mutations. Comparative genomic analysis of 129 and C57BL/6J mouse strains revealed indels and single nucleotide polymorphisms resulting in alternative or aberrant amino acid sequences in 1,084 genes in the 129-strain genome. Annotating these passenger mutations to the reported genetically modified congenic mice that were generated using 129-strain ESCs revealed that nearly all these mice possess multiple passenger mutations potentially influencing the phenotypic outcome. We illustrated this phenotypic interference of 129-derived passenger mutations with several case studies and developed a Me-PaMuFind-It web tool to estimate the number and possible effect of passenger mutations in transgenic mice of interest.

A graphical weighted power improving multiplicity correction approach for SNP selections

Controlling for the multiplicity effect is an essential part of determining statistical significance in large-scale single-locus association genome scans on Single Nucleotide Polymorphisms (SNPs). Bonferroni adjustment is a commonly used approach due to its simplicity, but is conservative and has low power for large-scale tests. The permutation test, which is a powerful and popular tool, is computationally expensive and may mislead in the presence of family structure. We propose a computationally efficient and powerful multiple testing correction approach for Linkage Disequilibrium (LD) based Quantitative Trait Loci (QTL) mapping on the basis of graphical weighted-Bonferroni methods. The proposed multiplicity adjustment method synthesizes weighted Bonferroni-based closed testing procedures into a powerful and versatile graphical approach. By tailoring different priorities for the two hypothesis tests involved in LD based QTL mapping, we are able to increase power and maintain computational efficiency and conceptual simplicity. The proposed approach enables strong control of the familywise error rate (FWER). The performance of the proposed approach as compared to the standard Bonferroni correction is illustrated by simulation and real data. We observe a consistent and moderate increase in power under all simulated circumstances, among different sample sizes, heritabilities, and number of SNPs. We also applied the proposed method to a real outbred mouse HDL cholesterol QTL mapping project where we detected the significant QTLs that were highlighted in the literature, while still ensuring strong control of the FWER.

Identification of a novel polymorphism in X-linked sterol-4-alpha-carboxylate 3-dehydrogenase (Nsdhl) associated with reduced high-density lipoprotein cholesterol levels in I/LnJ mice

Loci controlling plasma lipid concentrations were identified by performing a quantitative trait locus analysis on genotypes from 233 mice from a F2 cross between KK/HlJ and I/LnJ, two strains known to differ in their high-density lipoprotein (HDL) cholesterol levels. When fed a standard diet, HDL cholesterol concentration was affected by two significant loci, the Apoa2 locus on Chromosome (Chr) 1 and a novel locus on Chr X, along with one suggestive locus on Chr 6. Non-HDL concentration also was affected by loci on Chr 1 and X along with a suggestive locus on Chr 3. Additional loci that may be sex-specific were identified for HDL cholesterol on Chr 2, 3, and 4 and for non-HDL cholesterol on Chr 5, 7, and 14. Further investigation into the potential causative gene on Chr X for reduced HDL cholesterol levels revealed a novel, I/LnJ-specific nonsynonymous polymorphism in Nsdhl, which codes for sterol-4-alpha-carboxylate 3-dehydrogenase in the cholesterol synthesis pathway. Although many lipid quantitative trait locus have been reported previously, these data suggest there are additional genes left to be identified that control lipid levels and that can provide new pharmaceutical targets.

Atherosclerosis susceptibility Loci identified in an extremely atherosclerosis-resistant mouse strain

Background

C3H/HeJ (C3H) mice are extremely resistant to atherosclerosis, especially males. To understand the underlying genetic basis, we performed quantitative trait locus (QTL) analysis on a male F₂ (the second generation from an intercross between 2 inbred strains) cohort derived from an intercross between C3H and C57BL/6 (B6) apolipoprotein E–deficient (Apoe^−/−) mice.

Methods and Results

Two hundred forty‐six male F₂ mice were started on a Western diet at 8 weeks of age and kept on the diet for 5 weeks. Atherosclerotic lesions in the aortic root and fasting plasma lipid levels were measured. One hundred thirty‐four microsatellite markers across the entire genome were genotyped. Four significant QTLs on chromosomes (Chr) 2, 4, 9, and 15 and 4 suggestive loci on Chr1, Chr4, and Chr7 were identified for atherosclerotic lesions. Unexpectedly, the C3H allele was associated with increased lesion formation for 2 of the 4 significant QTLs. Six loci for high‐density lipoprotein (HDL), 6 for non‐HDL cholesterol, and 3 for triglycerides were also identified. The QTL for atherosclerosis on Chr9 replicated Ath29, originally mapped in a female F₂ cohort derived from B6 and C3H Apoe^−/− mice. This locus coincided with a QTL for HDL, and there was a moderate, but statistically significant, correlation between atherosclerotic lesion sizes and plasma HDL cholesterol levels in F₂ mice.

Conclusions

These data indicate that most atherosclerosis susceptibility loci are distinct from those for plasma lipids except for the Chr9 locus, which exerts effect through interactions with HDL.

Recalculation of 23 mouse HDL QTL datasets improves accuracy and allows for better candidate gene analysis

In the past 15 years, the quantitative trait locus (QTL) mapping approach has been applied to crosses between different inbred mouse strains to identify genetic loci associated with plasma HDL cholesterol levels. Although successful, a disadvantage of this method is low mapping resolution, as often several hundred candidate genes fall within the confidence interval for each locus. Methods have been developed to narrow these loci by combining the data from the different crosses, but they rely on the accurate mapping of the QTL and the treatment of the data in a consistent manner. We collected 23 raw datasets used for the mapping of previously published HDL QTL and reanalyzed the data from each cross using a consistent method and the latest mouse genetic map. By utilizing this approach, we identified novel QTL and QTL that were mapped to the wrong part of chromosomes. Our new HDL QTL map allows for reliable combining of QTL data and candidate gene analysis, which we demonstrate by identifying Grin3a and Etv6, as candidate genes for QTL on chromosomes 4 and 6, respectively. In addition, we were able to narrow a QTL on Chr 19 to five candidates.

Identification of novel mouse genes conferring posthypoxic pauses

Although central to the susceptibility of adult diseases characterized by abnormal rhythmogenesis, characterizing the genes involved is a challenge. We took advantage of the C57BL/6J (B6) trait of hypoxia-induced periodic breathing and its absence in the C57BL/6J-Chr 1(A/J)/NaJ chromosome substitution strain to test the feasibility of gene discovery for this abnormality. Beginning with a genetic and phenotypic analysis of an intercross study between these strains, we discovered three quantitative trait loci (QTLs) on mouse chromosome 1, with phenotypic effects. Fine-mapping reduced the genomic intervals and gene content, and the introgression of one QTL region back onto the C57BL/6J-Chr 1(A/J)/NaJ restored the trait. mRNA expression of non-synonymous genes in the introgressed region in the medulla and pons found evidence for differential expression of three genes, the highest of which was apolipoprotein A2, a lipase regulator; the apo a2 peptide fragment (THEQLTPLVR), highly expressed in the liver, was expressed in low amounts in the medulla but did not correlate with trait expression. This work directly demonstrates the impact of elements on mouse chromosome 1 in respiratory rhythmogenesis.

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a "toolbox" of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits.

Combining genome-wide data from humans and animal models of dyslipidemia and atherosclerosis

PURPOSE OF REVIEW

Comparative genomics allows researchers to combine genome-wide association data from humans with studies in animal models in order to assist in the identification of the genes and the genetic variants that modify susceptibility to dyslipidemia and atherosclerosis.

RECENT FINDINGS

Association and linkage studies in human and rodent species have been successful in identifying genetic loci associated with complex traits, but have been less robust in identifying and validating the responsible gene and/or genetic variants. Recent technological advancements have assisted in the development of comparative genomic approaches, which rely on the combination of human and rodent datasets and bioinformatics tools, followed by the narrowing of concordant loci and improved identification of candidate genes and genetic variants. Additionally, candidate genes and genetic variants identified by these methods have been further validated and functionally investigated in animal models, a process that is not feasible in humans.

SUMMARY

Comparative genomic approaches have led to the identification and validation of several new genes, including a few not previously implicated, as modifiers of plasma lipid levels and atherosclerosis, yielding new insights into the biological mechanisms of these complex traits.

Genetic, epigenetic, and gene-by-diet interaction effects underlie variation in serum lipids in a LG/JxSM/J murine model

Variation in serum cholesterol, free-fatty acids, and triglycerides is associated with cardiovascular disease (CVD) risk factors. There is great interest in characterizing the underlying genetic architecture of these risk factors, because they vary greatly within and among human populations and between the sexes. We present results of a genome-wide scan for quantitative trait loci (QTL) affecting serum cholesterol, free-fatty acids, and triglycerides in an F(16) advanced intercross line of LG/J and SM/J (Wustl:LG,SM-G16). Half of the population was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. Here we examine genetic, environmental, and genetic-by-environmental interactions of QTL overlapping previously identified loci associated with CVD risk factors, and we add to the serum lipid QTL landscape by identifying new loci.

Untangling HDL quantitative trait loci on mouse chromosome 5 and identifying Scarb1 and Acads as the underlying genes

Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identified on mouse distal chromosome 5. Our objective was to identify the underlying genes. We first used bioinformatics to narrow the Hdlq1 locus to 56 genes. The most likely candidate, Scarb1 (scavenger receptor B1), was supported by gene expression data consistent with knockout and transgenic mouse models. Then we confirmed Hdlq8 as an independent QTL by detecting it in an intercross between NZB and NZW (LOD = 12.7), two mouse strains that have identical genotypes for Scarb1. Haplotyping narrowed this QTL to 9 genes; the most likely candidate was Acads (acyl-coenzymeA dehydrogenase, short chain). Sequencing showed that Acads had an amino acid polymorphism, Gly94Asp, in a conserved region; Western blotting showed that protein levels were significantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL levels were significantly elevated in BALB/cBy compared with BALB/c mice and that this HDL difference cosegregated with the Acads mutation. We confirmed that Hdlq1 and Hdlq8 are independent QTL on mouse chromosome 5 and demonstrated that Scarb1 and Acads are the underlying genes.

Identifying quantitative trait loci (QTLs) and genes (QTGs) for alcohol-related phenotypes in mice

Alcoholism is a complex clinical disorder with genetic and environmental contributions. Although no animal model duplicates alcoholism, models for specific factors, such as the withdrawal syndrome, are useful to identify potential genetic determinants of liability in humans. Murine models have been invaluable to identify quantitative trait loci (QTLs) that influence a variety of alcohol responses. However, the QTL regions are typically large, at least initially, and contain numerous genes, making identification of the causal quantitative trait gene(s) (QTGs) challenging. Here, we present QTG identification strategies currently used in the field of alcohol genetics and discuss relevance to alcoholic human populations.

Novel ENU-induced point mutation in scavenger receptor class B, member 1, results in liver specific loss of SCARB1 protein

Cardiovascular disease (CVD) is the largest cause of premature death in human populations throughout the world. Circulating plasma lipid levels, specifically high levels of LDL or low levels of HDL, are predictive of susceptibility to CVD. The scavenger receptor class B member 1 (SCARB1) is the primary receptor for the selective uptake of HDL cholesterol by liver and steroidogenic tissues. Hepatic SCARB1 influences plasma HDL-cholesterol levels and is vital for reverse cholesterol transport. Here we describe the mapping of a novel N-ethyl-N-nitrosourea (ENU) induced point mutation in the Scarb1 gene identified in a C57BL/6J background. The mutation is located in a highly conserved amino acid in the extracellular loop and leads to the conversion of an isoleucine to an asparagine (I179N). Homozygous mutant mice express normal Scarb1 mRNA levels and are fertile. SCARB1 protein levels are markedly reduced in liver (∼90%), but not in steroidogenic tissues. This leads to ∼70% increased plasma HDL levels due to reduced HDL cholesteryl ester selective uptake. Pdzk1 knockout mice have liver-specific reduction of SCARB1 protein as does this mutant; however, in vitro analysis of the mutation indicates that the regulation of SCARB1 protein in this mutant is independent of PDZK1. This new Scarb1 model may help further our understanding of post-translational and tissue-specific regulation of SCARB1 that may aid the important clinical goal of raising functional HDL.

Four additional mouse crosses improve the lipid QTL landscape and identify Lipg as a QTL gene

To identify genes controlling plasma HDL and triglyceride levels, quantitative trait locus (QTL) analysis was performed in one backcross, (NZO/H1Lt x NON/LtJ) x NON/LtJ, and three intercrosses, C57BL/6J x DBA/2J, C57BL/6J x C3H/HeJ, and NZB/B1NJ x NZW/LacJ. HDL concentrations were affected by 25 QTL distributed on most chromosomes (Chrs); those on Chrs 1, 8, 12, and 16 were newly identified, and the remainder were replications of previously identified QTL. Triglyceride concentrations were controlled by nine loci; those on Chrs 1, 2, 3, 7, 16, and 18 were newly identified QTL, and the remainder were replications. Combining mouse crosses with haplotype analysis for the HDL QTL on Chr 18 reduced the list of candidates to six genes. Further expression analysis, sequencing, and quantitative complementation testing of these six genes identified Lipg as the HDL QTL gene on distal Chr 18. The data from these crosses further increase the ability to perform haplotype analyses that can lead to the identification of causal lipid genes.

Farp2 and Stk25 are candidate genes for the HDL cholesterol locus on mouse chromosome 1

OBJECTIVE

To identify the gene responsible for the quantitative trait locus (QTL) Hdlq14, a high-density lipoprotein cholesterol (HDL) QTL previously identified in a C57BL/6Jx129S1/SvImJ cross.

METHODS AND RESULTS

Hdlq14 was first confirmed as an independent QTL by detecting it in an intercross between NZB/B1NJ and NZW/LacJ, 2 strains that had identical genotypes at nearby QTL genes on chromosome 1. Using the bioinformatics tools of combined cross data and haplotype analysis, we narrowed this QTL from a 45-Mb 225-gene region to 2 genes, Farp2 and Stk25. Sequencing and expression studies showed that Farp2 had an amino acid polymorphism in an important plekstrin domain and that Stk25 had a significant expression difference between the parental strains. These 2 genes are immediately adjacent to each other and share the same haplotype over 45 inbred strains. The haplotype was associated with a significant difference in HDL levels among these strains.

CONCLUSIONS

We confirmed Hdlq14 as a separate independent QTL for HDL and narrowed the region to 2 genes, Farp2 and Stk25, with considerable evidence for both. Additional studies are needed to choose between these 2 genes or to show that both are important in determining HDL levels.