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

Abstract

This article is available online at http://www.jlr.org considerable interest has been given to the results of genome-wide association studies of triglycerides and lipids in humans ( 2-5 ). However, these studies often do not control for environment and only explain about 10% of the overall lipid variation, indicating that additional genes involved in lipid metabolism are yet to be discovered ( 5 ).Studies in inbred mice successfully accommodate both genetic and environmental issues. Because we have such a tightly controlled environment in our mouse rooms, any phenotypic variation in triglyceride levels among inbred strains must be attributed primarily to genetic variation. This makes quantitative trait loci (QTL) analysis in inbred mouse strains a powerful approach for identifying loci and genes regulating lipid levels. To date, our laboratory and others have identifi ed more than 30 mouse triglyceride QTL ( 6, 7 ). We continue to improve the ways in which we convert these QTL into the identifi cation of QTL genes (QTG). For example, since 2003 we have used a list of QTG criteria published by the Complex Trait Consortium (CTC) to indentify causal QTL genes ( 8 ). These criteria are based on the premise that a QTG must carry a polymorphism between the parental strains of the mouse cross that affects either the structure/function of the gene (a nonsynonymous coding polymorphism) or the expression of the gene. Still, most of the CTC criteria involve in vitro and in vivo experiments and are not practical strategies when more than 100 genes are located under the QTL, a common characteristic of most QTL.To improve and accelerate the process of gene identification, our laboratory and others developed a set of bioinformatic tools to help narrow QTL in the mouse and Abstract To identify genetic loci infl uencing 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 identifi ed one signifi cant 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 fi nd cis -regulated expression QTL. We then narrowed the list of candidate genes under signifi cant 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, fi ve genes ( Polr3 h, Cyp2d22, Cyp2d26, Tspo, and One of the major predictors of the development of coronary artery disease (CAD) is lipid levels, which are determined by a complex interaction of genetic and environmental factors. High levels of low density lipoprotein (LDL) cholest...

Strain-Dependent Airway Hyperresponsiveness and a Chromosome 7 Locus of Elevated Lymphocyte Numbers in Cystic Fibrosis Transmembrane Conductance Regulator-Deficient Mice

“…The predicted consequence of B6/BALB coding nonsynonymous genetic variation was assessed using SIFT (29) (http://sift.jcvi.org/), PANTHER (30) (http:/www.pantherdb.org/), and PolyPhen (31) (http://genetics.bwh.harvard.edu/pph/) algorithms. This approach to candidate gene identification has been used by others (32)(33)(34).…”

Identification of a QTL in Mus musculus for Alcohol Preference, Withdrawal, and Ap3m2 Expression Using Integrative Functional Genomics and Precision Genetics

“…In the present study, we demonstrate efficient identification of candidate genes for large "legacy" QTL due to the availability of extensive genotype, haplotype, phylogeny, and sequence data coupled with a wealth of functional genomics evidence. Numerous integrative strategies for candidate gene identification have been proposed and applied (Belknap and Atkins 2001;Hitzemann et al 2003Hitzemann et al , 2004Aerts et al 2006;LeNiculescu et al 2007LeNiculescu et al , 2011Ehlers et al 2010;Guan et al 2010;Kurian et al 2011;Leduc et al 2011;Bhandari et al 2012;Chesler et al 2012;Faro et al 2012). Although these approaches have been effective, their application is limited by the scope and state of existing data resources.…”

Current status and future perspectives: TSPO in steroid neuroendocrinology

“…(4) TSPO as a regulator of lipid metabolism. Several studies have correlated TSPO expression to functional changes in lipid metabolism (Wade et al 2005, Leduc et al 2011. It was identified that TSPO deletion could increase fatty acid oxidation in steroidogenic cells .…”

“…First, Tspo was identified as one of the six novel transcripts that showed robust positive correlation with adipocyte differentiation in a differential display RT-PCR screen (Wade et al 2005). Second, Tspo was identified as one of the five genes that could influence triglyceride metabolism in an examination of quantitative trait loci between inbred mouse strains (Leduc et al 2011). In agreement, recent examination of TSPO expression levels in different murine tissues indicated that high TSPO expression correlated with tissues active in lipid storage/metabolism, and was not specific for steroidogenic cells (Fig.…”