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Mapping Data
Experiment
  • Experiment
    TEXT-QTL
  • Chromosome
    1
  • Reference
    J:233490 Ostergren C, et al., Genetic analysis of ligation-induced neointima formation in an F2 intercross of C57BL/6 and FVB/N inbred mouse strains. PLoS One. 2015;10(4):e0121899
  • ID
    MGI:5905159
Genes
GeneAlleleAssay TypeDescription
Tcq11
Notes
  • Experiment
    The recruitment of smooth muscle cells (SMCs) to neointimal lesions after percutaneous coronary intervention (PCI) in humans is partly under genetic control. Similarly, neointimal hyperplasia after different forms of vascular injury or flow-cessation in mice has been found to be highly strain dependent although little is known about the causative gene variants.

    A particularly pronounced difference is seen between FVB/N inbred mice that form abundant neointima after carotid artery ligation, and C57BL/6 (B6) inbred mice that hardly form any. The aim of the present study was to identify the chromosomal locations of genes involved in the recruitment of SMCs to vascular lesions using quantitative trait locus (QTL) analysis of an F2 intercross between these two mouse strains. QTLs affecting total cholesterol levels in the cross were also analyzed.

    Carotid artery ligation and a genome scan using 800 informative SNP markers were performed in 157 female F2 mice. Using quantitative trait loci (QTL) analysis, suggestive QTL were identified on chromosomes 7 and 12 for neointimal cross-sectional area and on chromosome 14 for media area [Table 1].

    Non-fasting total cholesterol was different in the FVB/N (4.150.51 mM) and B6 (2.370.35 mM) parental strains, and the presence of segregating genes affecting plasma cholesterol in the F2 population thus offered a possibility to look for effects of plasma cholesterol on neointima formation. No correlation, however, was found between the traits.

    Further analysis of the cross revealed 4 QTLs for plasma cholesterol, which combined explained 69% of the variation among F2 mice. Both a one-dimensional and a two-dimensional QTL scan were performed. Table 2:

    QTL Tcq11 (total cholesterol QTL 11) mapped to Chromosome 1 with a LOD score of 38.72 at 177.58 Mb (81.65 cM) nearest SNP rs3669108. The confidence interval spanned from 169.31 to 179.82 Mb, p<2 10-16. In an additive mode Tcq11 accounted for 59.76 % of trait variance with the FVB allele reported as the high allele.

    QTL Tcq12 (total cholesterol QTL 12) mapped to Chromosome 3 with a LOD score of 3.65 at 69.01 Mb (32.15 cM) nearest SNP gnf03.015.035. The confidence interval spanned from 16.45 to 130.37 Mb, p=0.0036. In an additive mode Tcq12 accounted for 3.19 % of trait variance with the B6 allele reported as the high allele.

    QTL Tcq13 (total cholesterol QTL 13) mapped to Chromosome 9 with a LOD score of 4.85 at 97.29 Mb (51.01 cM) nearest SNP rs13480365. The confidence interval spanned from 59.99 to 109.26, p=0.00027. In an additive mode Tcq13 accounted for 4.32 % of trait variance with the B6 allele reported as the high allele. This interval includes the hepatic lipase gene Lipc identified in human GWAS as a potential plasma total, LDL and HDL cholesterol modulating gene.

    QTL Tcq14 (total cholesterol QTL 14) mapped to Chromosome 12 with a LOD score of 2.24 at 72.89 Mb (30.30 cM) nearest SNP rs13481527. The confidence interval spanned from 11.61 to 97.21 Mb, p0=.078. In an additive mode Tcq14 accounted for 1.91 % of trait variance with the B6 allele reported as the high allele.

    The physical (megabase (Mb)) positions (GRCm38) of the QTLs and their intervals were obtained using the Map Converter tool (http://cgd.jax.org/mousemapconverter/).








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last database update
11/12/2024
MGI 6.24
The Jackson Laboratory