Effects of atherogenic diet on hepatic gene expression across mouse strains

Shockley, Keith R.; Witmer, David R.; Burgess-Herbert, Sarah L.; Paigen, Beverly; Churchill, Gary A.

doi:10.1152/physiolgenomics.90350.2008

Cited by 54 publications

(78 citation statements)

References 42 publications

(39 reference statements)

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“…The strength of the present study is that all strains of mice were studied at the same time, under the same experimental conditions. We do, however, acknowledge that this comparison was carried out with male mice only and there may be sex differences between strains [49].…”

Section: Discussionmentioning

confidence: 99%

Mouse strain-dependent variation in obesity and glucose homeostasis in response to high-fat feeding

et al. 2013

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Aims/hypothesis Metabolic disorders are commonly investigated using knockout and transgenic mouse models. A variety of mouse strains have been used for this purpose. However, mouse strains can differ in their inherent propensities to develop metabolic disease, which may affect the experimental outcomes of metabolic studies. We have investigated straindependent differences in the susceptibility to diet-induced obesity and insulin resistance in five commonly used inbred mouse strains (C57BL/6J, 129X1/SvJ, BALB/c, DBA/2 and FVB/N). Methods Mice were fed either a low-fat or a high-fat diet (HFD) for 8 weeks. Whole-body energy expenditure and body composition were then determined. Tissues were used to measure markers of mitochondrial metabolism, inflammation, oxidative stress and lipid accumulation. Results BL6, 129X1, DBA/2 and FVB/N mice were all susceptible to varying degrees to HFD-induced obesity, glucose intolerance and insulin resistance, but BALB/c mice exhibited some protection from these detrimental effects. This protection could not be explained by differences in mitochondrial metabolism or oxidative stress in liver or muscle, or inflammation in adipose tissue. Interestingly, in contrast with the other strains, BALB/c mice did not accumulate excess lipid (triacylglycerols and diacylglycerols) in the liver; this is potentially related to lower fatty acid uptake rather than differences in lipogenesis or lipid oxidation. Conclusions/interpretation Collectively, our findings indicate that most mouse strains develop metabolic defects on an HFD. However, there are inherent differences between strains, and thus the genetic background needs to be considered carefully in metabolic studies. Keywords

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Section: Discussionmentioning

confidence: 99%

Mouse strain-dependent variation in obesity and glucose homeostasis in response to high-fat feeding

et al. 2013

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“…In addition, although our approach is a powerful way to identify potential QTL candidate genes, our study refl ects the complexity of the identifi cation of QTL genes. The genomic dissection of QTL is usually based on the examination of SNP and gene expression databases ( 36 ) and relies on the accuracy of the comprehensive public databases. In our study, this type of straightforward examination would have missed the novel polymorphism.…”

Section: Discussionmentioning

confidence: 99%

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

Leduc

Blair

Verdugo

et al. 2012

Journal of Lipid Research

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A higher incidence of coronary artery disease (CAD) is associated with a lower level of HDL-cholesterol ( 1, 2 ), which is determined by multiple environmental and genetic factors. In the past few years, new therapeutic approaches have focused on fi nding ways to increase HDL ( 3, 4 ). To date, however, only a few environmental interventions, such as diet and exercise, have been successful in raising HDL level ( 5 ), whereas drug therapy development is still ongoing and has targeted only a limited number of proteins such as CETP ( 3, 4 ). In the search for a potential drug target to raise HDL and decrease CAD, the identifi cation of new genes involved in HDL determination is essential.The genetic basis of HDL-cholesterol variation has been widely studied in various animal models. In humans, recent genome-wide association studies (GWAS) have identifi ed known HDL genes such as LIPG and CETP in addition to new genes such as GALNT2 ( 6 ). These known genes, however, explain only a small proportion of the total variation, indicating that additional genes are yet to be discovered. Mouse models are a powerful strategy for identifying such genes. A large overlap exists among species for quantitative trait loci (QTL) and genes involved in lipid metabolism ( 7 ). Many study methodologies are similar between human and mouse, but mouse studies offer advantages by capitalizing on genomics tools that are not available and practical for studies of human populations. To date, our laboratory and those of others have identifi ed over 35 mouse HDL QTL (as reviewed in Wang et al., Refs. 7,8 ). In addition, we and others have developed bioinformatics tools to narrow the QTL interval to just a few candidate genes ( 9, 10 ). Application of these tools has led to the discovery of single genes underlying QTL for HDL and

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“…To further narrow the list of genes for this QTL, we examined liver expression for strains included in our previously published gene expression strain survey ( 21 ). While liver expression data are not available for two of the strains used to map QTL identifi ed in this cluster (NZW and RF), data are available for NZB, B6, and SM.…”

Section: Identifi Cation Of Etv6 As a Candidate Gene For An Hdl Qtl Omentioning

confidence: 99%

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

Ackert‐Bicknell

Paigen

Korstanje

2013

Journal of Lipid Research

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This article is available online at http://www.jlr.org among these different subpopulations are not understood, and the genes responsible for the subpopulation differences among individuals are unknown.Several approaches, including genetic mapping studies, have been used to identify novel genes involved in the regulation of HDL levels. In mice, the technique of quantitative trait locus (QTL) mapping, which uses crosses between different inbred strains of mice, has been heavily employed over the past 15 years. These results have been summarized in several reviews ( 6, 7 ). One limitation of traditional QTL analysis is low mapping resolution, which is a result of the limited genetic recombination possible in onegeneration backcrosses [i.e., A×(A×B)] and two-generation intercrosses [i.e., (A×B)×(A×B)]. The 95% confi dence interval (CI), the interval in which the causative gene is most likely to reside, is usually very broad. For example, one large study of bone mineral density QTL found that the average CI width for traditionally mapped QTL was 32 cM ( 8 ). As it can be assumed that there are, on average, 20 genes per cM ( 9 ), the number of candidate genes per QTL can be very large, making the identifi cation of the causative gene very diffi cult. In the past few years, several methods have been developed that combine accumulated data from the different crosses, allowing for narrowing of the CI for QTL and reducing candidate gene lists ( 10 ). However, the success of these methods heavily depends on the accuracy of the QTL mapping.The current standard genetic map for the mouse is curated and maintained by the Mouse Genome Informatics (MGI) Group at The Jackson Laboratory (www.informatics. jax.org) ( 11 ). Mapping QTL requires accurate genetic map information for both the relative order of markers and the distances between them ( 12 ). Recently, Shifman and colleagues published a new genetic map based on a large population of a heterogeneous stock ( 13 ). Cox and colleagues integrated a total of 7,080 standard, simplesequence length polymorphism (SSLP) markers to this single-nucleotide polymorphism (SNP)-based map, generating a corrected mouse genetic map ( 14 ). This new map Abstract 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 confi dence 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 identifi ed novel QTL and QTL that were mapped...

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Effects of atherogenic diet on hepatic gene expression across mouse strains

Abstract: GA. Effects of atherogenic diet on hepatic gene expression across mouse strains.

Cited by 54 publications

References 42 publications

Mouse strain-dependent variation in obesity and glucose homeostasis in response to high-fat feeding

Mouse strain-dependent variation in obesity and glucose homeostasis in response to high-fat feeding

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

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

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