Applying Gene Expression, Proteomics and Single-Nucleotide Polymorphism Analysis for Complex Trait Gene Identification

Stylianou, Ioannis M.; Affourtit, Jason P.; Shockley, Keith R.; Wilpan, Robert Y; Abdi, Fadi; Bhardwaj, Sanjeev K.; Rollins, Jarod; Churchill, Gary A.; Paigen, Beverly

doi:10.1534/genetics.107.081216

Cited by 42 publications

(27 citation statements)

References 51 publications

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“…As previously reported, ACADS protein levels in liver are signifi cantly higher in SM compared with NZB mice ( 14 ). To further investigate if this expression difference also exists between strains NZB and NZW, we measured ACADS levels in livers from NZB and NZW mice fed a high-fat diet for eight weeks.…”

Section: Discussionmentioning

confidence: 78%

“…We dissected liver tissue from three males of each strain, fl ash froze the samples in liquid nitrogen, and performed liver protein extraction and Western blotting as previously described ( 14 ). Rabbit anti-ACADS serum, kindly provided by Dr. Vockley of the Children's Hospital of Pittsburg, was used for the primary immunostain; goat anti-rabbit IgG horseradish peroxidase was used for the secondary immunostain.…”

Section: Western Blot Analysis Of Acadsmentioning

confidence: 99%

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

Leduc

Korstanje

et al. 2010

Journal of Lipid Research

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This article is available online at http://www.jlr.org human populations; these QTL often map to homologous locations in both species ( 1 ). Detecting QTL has been relatively easy. The next step of identifying causal QTL genes, however, has been more challenging, although the development of bioinformatic methods ( 2, 3 ) and improved genomic resources in the mouse ( 4 ) and genomewide association studies in humans ( 5, 6 ) are improving the success of QTL gene identifi cation.QTL that are in close proximity on the same chromosome remain particularly challenging. In such situations, it is particularly diffi cult to identify the causal QTL genes. Although congenic strains are a powerful tool to separate these QTL, they are time consuming; therefore, we used a more effi cient, genomic approach to decipher the presence of one or multiple QTL and identify the QTL genes. At least seven inbred mouse crosses ( 7-12 ) have identifi ed HDL QTL on mouse distal chromosome (Chr) 5 ( Table 1 ). However, the broad confi dence intervals and shape of the logarithm of the odds ratio (LOD) score plots suggest that at least four of these crosses (B6 × 129, NZB × SM, B6 × NZB, and B6 × CAST) may have two closely linked QTL. We used advanced intercross lines between B6 and NZB at F11, which allows the accumulation of recombination events and thus narrows QTL ( 13 ) and confi rmed that two QTL did exist between these two strains on distal Chr 5. These QTL were named Hdlq1 at 125 Mb and Hdlq8 at 113 Mb ( 11 ).In the present study, we fi rst identifi ed Scarb1 as the causal gene for Hdlq1 . We then confi rmed that Hdlq8 is an independent QTL by crossing two closely related strains that do not differ at the Scarb1 locus and thus were expected not to have a QTL at the Hdlq1 region. As expected, this cross detected Hdlq8 but had no QTL at Hdlq1. Subsequently, we used haplotype analysis, gene sequencing, expression studies, and a spontaneous mutation to demonstrate that Acads was the underlying gene for Hdlq8 .Abstract Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identifi ed on mouse distal chromosome 5. Our objective was to identify the underlying genes. We fi rst 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 confi rmed 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 signifi cantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL le...

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Section: Discussionmentioning

confidence: 78%

Section: Western Blot Analysis Of Acadsmentioning

confidence: 99%

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

Leduc

Korstanje

et al. 2010

Journal of Lipid Research

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“…The array data has been deposited at the Gene Expression Omnibus ( www.ncbi.nlm.nih.gov/geo/ ; series number: GSE10493). RNA extraction, quantifi cation, cDNA synthesis, and data analysis were carried out as described previously ( 40 ).…”

Section: Chr 18/ Lipg Locus Expression Analysismentioning

confidence: 99%

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

Ishimori

Chen

et al. 2009

Journal of Lipid Research

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“…A tremendous effort has been made in this direction by using approaches that combine whole genome scans with information generated by gene expression and bioinformatic analyses (76,81,82). In humans, Ͼ100 quantitative trait loci (QTL) influencing high (HDL)-and low (LDL)-density lipoprotein levels as well as triglyceride (TG) concentrations have been found (82).…”

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Mapping of quantitative trait loci for cholesterol, LDL, HDL, and triglyceride serum concentrations in pigs

Gallardo

Pena

Amills

et al. 2008

Physiological Genomics

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The fine mapping of polymorphisms influencing cholesterol (CT), triglyceride (TG), and lipoprotein serum levels in human and mouse has provided a wealth of knowledge about the complex genetic architecture of these traits. The extension of these genetic analyses to pigs would be of utmost importance since they constitute a valuable biological and clinical model for the study of coronary artery disease and myocardial infarction. In the present work, we performed a whole genome scan for serum lipid traits in a half-sib Duroc pig population of 350 individuals. Phenotypic registers included total CT, TG, and low (LDL)-and high (HDL)-density lipoprotein serum concentrations at 45 and 190 days of age. This approach allowed us to identify two genomewide significant quantitative trait loci (QTL) for HDL-to-LDL ratio at 45 days (SSC6, 84 cM) and for TG at 190 days (SSC4, 23 cM) as well as a number of chromosomewide significant QTL. The comparison of QTL locations at 45 and 190 days revealed a notable lack of concordance at these two time points, suggesting that the effects of these QTL are age specific. Moreover, we have observed a considerable level of correspondence among the locations of the most significant porcine lipid QTL and those identified in humans. This finding might suggest that, in mammals, diverse polymorphisms located in a common set of genes are involved in the genetic variation of serum lipid levels.lipoproteins; lipid metabolism; candidate genes IDENTIFICATION of the genetic factors regulating the concentrations of serum lipoproteins has been a major goal in the prevention and treatment of atherosclerosis. A tremendous effort has been made in this direction by using approaches that combine whole genome scans with information generated by gene expression and bioinformatic analyses (76,81,82). In humans, Ͼ100 quantitative trait loci (QTL) influencing high (HDL)-and low (LDL)-density lipoprotein levels as well as triglyceride (TG) concentrations have been found (82). Moreover, the comparison of mouse and human genomic data has shown that LDL, HDL, and TG QTL display a striking positional concordance in these two mammalian species (80 -82).The inclusion of additional mammalian genomes in this human-mouse QTL comparative framework would yield great benefits in the search of genes influencing susceptibility to atherosclerosis. Pigs are an interesting experimental model to tackle this issue for several reasons. First, pigs have been used as a biomedical model of human diseases for decades, with a special impact on those related to myocardial infarction, cerebral ischemia, and atherosclerosis (44). Familial hypercholesterolemia has been reported in pigs, and, unlike other model species, affected individuals develop atherosclerotic lesions in the coronary vasculature that closely match those observed in humans, suggesting that atherosclerosis shares a common pathogenesis in both species (31). Moreover, the existence of a relevant amount of additive genetic variability for serum lipid traits in pigs has been demo...

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Applying Gene Expression, Proteomics and Single-Nucleotide Polymorphism Analysis for Complex Trait Gene Identification

Cited by 42 publications

References 51 publications

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

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

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

Mapping of quantitative trait loci for cholesterol, LDL, HDL, and triglyceride serum concentrations in pigs

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