QTL mapping for genetic determinants of lipoprotein cholesterol levels in combined crosses of inbred mouse strains

Wittenburg, Henning; Lyons, Malcolm A.; Li, Renhua; Kurtz, Ulrike; Wang, Xiaosong; Mössner, Joachim; Churchill, Gary A.; Carey, Martin C.; Paigen, Beverly

doi:10.1194/jlr.m500544-jlr200

Cited by 29 publications

(27 citation statements)

References 69 publications

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“…Although the difference was not signifi cant, Scarb1 expression was somewhat higher in B6 mice than that in CAST mice. This observation is consistent with the scavenger receptor B1 (SR-B1) function, since Scarb1 -defi cient mice have increased HDL levels ( 15 ). Partial to complete SR-B1 defi ciency results in an increase in plasma HDL ( 16 ), while hepatic overexpression of SR-BI in mice markedly reduces plasma HDL levels.…”

Section: Scarb1 Is the Gene Underlying Hdlq1supporting

confidence: 66%

“…We also analyzed the haplotypes of the parental strains for two crosses that failed to detect a QTL at this location, the PERA/EiJ (PERA) × I/LnJ (I/Ln) and the B6 × C3H/ HeJ (C3H) crosses ( 9,15 ). Haplotyping is often helpful with crosses that do not detect a QTL because the parental strains must share the identical haplotype for the QTL gene.…”

Section: Scarb1 Is the Gene Underlying Hdlq1mentioning

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: Scarb1 Is the Gene Underlying Hdlq1supporting

confidence: 66%

Section: Scarb1 Is the Gene Underlying Hdlq1mentioning

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

Self Cite

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“…Interestingly, two of the Tir QTLs, namely Tir2 and Tir3, are located in chromosomal regions where QTLs for cholesterol absorption and high-density lipoprotein levels are mapped. [25][26][27][28][29] Although trypanotolerance was significantly associated with the activation of the classical complement cascade and cholesterol and bile acid pathways, no specific pathway seemed to be linked to susceptibility. Failure to control parasitaemia might be owing to the inadequate metabolic adaptation and an overactivation of the immune system rather than specific initiation.…”

Section: Discussionmentioning

confidence: 99%

Gene expression profiling in a mouse model for African trypanosomiasis

Kierstein¹,

Noyes²,

Naessens³

et al. 2006

Genes Immun

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This study aimed to provide the foundation for an integrative approach to the identification of the mechanisms underlying the response to infection with Trypanosoma congolense, and to identify pathways that have previously been overlooked. We undertook a large-scale gene expression analysis study comparing susceptible A/J and more tolerant C57BL/6 mice. In an initial time course experiment, we monitored the development of parasitaemia and anaemia in every individual. Based on the kinetics of disease progression, we extracted total RNA from liver at days 0, 4, 7, 10 and 17 post infection and performed a microarray analysis. We identified 64 genes that were differentially expressed in the two strains in non-infected animals, of which nine genes remained largely unaffected by the disease. Gene expression profiling at stages of low, peak, clearance and recurrence of parasitaemia suggest that susceptibility is associated with high expression of genes coding for chemokines (e.g. Ccl24, Ccl27 and Cxcl13), complement components (C1q and C3) and interferon receptor alpha (Ifnar1). Additionally, susceptible A/J mice expressed higher levels of some potassium channel genes. In contrast, messenger RNA levels of a few immune response, metabolism and protease genes (e.g. Prss7 and Mmp13) were higher in the tolerant C57BL/6 strain as compared to A/J.

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“…By looking at additional crosses, we can sample more allelic variation; thus, we have an opportunity to detect additional loci that can be implicated in a disease model. In addition, combined analysis of data from multiple F2 crosses were recently suggested as a means to achieve greater sample size and power for detecting and localizing the QTLs (29)(30)(31). The combined analyses have also indicated increased resolution of the shared QTLs, which is major bottleneck in the ultimate goal of a QTL analysis: identification of the underlying gene (29).…”

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Mapping genetic loci that regulate lipid levels in a NZB/B1NJ×RF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

Wergedal

Ackert‐Bicknell

Beamer

et al. 2007

Journal of Lipid Research

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The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZB3RF/J (RF) intercross and in a combined data set that included NZB3RF and MRL/MpJ3SJL/J intercrosses. In the NZB3 RF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZB3RF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.-Wergedal, J. E., C. L. AckertBicknell, W. G. Beamer, S. Mohan, D. J. Baylink, and A. K. Srivastava. Mapping genetic loci that regulate lipid levels in a NZB/B1NJ3RF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains.

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QTL mapping for genetic determinants of lipoprotein cholesterol levels in combined crosses of inbred mouse strains

Cited by 29 publications

References 69 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

Gene expression profiling in a mouse model for African trypanosomiasis

Mapping genetic loci that regulate lipid levels in a NZB/B1NJ×RF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

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