Experiment
Pseudoxanthoma elasticum (PXE), a prototype of heritable multisystem ectopic mineralization disorders, is caused by mutations in the ABCC6 gene encoding a putative efflux transporter, ABCC6. The phenotypic spectrum of pseudoxanthoma elasticum varies, and the correlation between genotype and phenotype has not been established. To identify genetic modifiers, the authors performed QTL analysis in inbred mouse strains that carry the same hypomorphic allele in Abcc6 yet with highly variable ectopic mineralization phenotypes of pseudoxanthoma elasticum.
The parental strains of mice, C57BL/6J (B6), KK/HlJ (KK), and DBA/2J (D2), were obtained from The Jackson Laboratory (Bar Harbor, ME). B6 or D2 females were mated with KK male mice to produce B6KKF1 and D2KKF1 progeny, respectively. These F1 females were then backcrossed to KK males to produce N2 progeny, (B6KKF1)KK and (D2KKF1)KK, respectively. The two backcrosses were designed to have at least 180 N2 individuals each to achieve 93% power to detect QTL with additive effects exceeding 13% of the variance using the R/qtlDesign package. A total of 384 mice had samples taken for DNA genotyping analysis. DNA samples were genotyped at Geneseek using the GigaMUGA SNP genotyping array (Neogen Corporation, Lincoln, NE) consisting of approximately 143,000 probes.
Crosses of the severely affected KK mice with B6, a strain without mineralization, or with D2, a strain with mild PXE, were used in QTL analysis to localize genomic intervals that have effects on ectopic mineralization phenotype. Muzzle, kidney, heart, eyes, and lung were collected from 468 mice and processed for histology. The severity of lesions was scored by an experienced, board-certified veterinary pathologist (JPS). The severity of tissue mineralization is based on a semi-quantitative measure of the size of the lesion in different organs (scores: normal, 0; mild, 1; moderate, 2; severe, 3; extreme, 4). The severity of mineralization of the connective tissue sheath of vibrissae in the muzzle skin, a hallmark of PXE in mice, was scored by semi-quantitative histopathologic analysis. In addition, the degree of mineralization in muzzle skin was quantified by an independent chemical assay of calcium.
All QTL analyses were performed with the R/qtl software package (http://www.rqtl.org/). Given each phenotype distribution, the authors used a nonparametric model in each of the QTL analyses. For each phenotype, genome-wide significance thresholds of 0.01, 0.05, 0.10, and 0.63 were obtained following 1000 permutations. Candidate intervals for each phenotype were defined using a two-LOD drop approach from the peak QTL.
The authors identified eight organ-specific QTL for ectopic mineralization (relative to GRCm38/mm10):
Vmm1 (variable multisystem mineralization 1, muzzle) maps to Chr 7: 47.5 - 56.9 Mbp with a peak LOD score of 15.67 in (B6KKF1)KK mice.
Vmm2 (variable multisystem mineralization 2, heart) maps to Chr 7: 47.5 - 74.5 Mbp with a peak LOD score of 10.50 in (B6KKF1)KK mice.
Vmm3 (variable multisystem mineralization 3, lung) maps to Chr 7: 37.6 - 72.4 Mbp with a peak LOD score of 3.64 in (B6KKF1)KK mice.
Vmm4 (variable multisystem mineralization 4, kidney) maps to Chr 7: 37.6 - 87.4 Mbp with a peak LOD score of 7.37 in (B6KKF1)KK mice.
Vmm5 (variable multisystem mineralization 5, kidney) maps to Chr 5: 76.9 - 125.3 Mbp with a peak LOD score of 4.12 in (B6KKF1)KK mice.
Vmm6 (variable multisystem mineralization 6, eye) maps to Chr 7: 62.2 - 103.1 Mbp with a peak LOD score of 6.11 in (B6KKF1)KK mice.
Vmm7 (variable multisystem mineralization 7, heart) maps to Chr 3: 13.5 - 76.3 Mbp with a peak LOD score of 3.37 in (D2KKF1)KK mice.
Vmm8 (variable multisystem mineralization 8, kidney) maps to Chr 5: 97.9 - 128.3 Mbp with a peak LOD score of 5.67 in (D2KKF1)KK mice.
KK and D2 both have the Abcc6 mutant allele, whereas B6 has the wild type allele. Therefore, in KK and B6 cross, a major QTL was identified on Chr 7 that involves Abcc6 (P < 0.05); however, there is no linkage on Chr 7 in KK and D2 cross. Thus, Abcc6 was confirmed as a major determinant for ectopic mineralization in multiple tissues.
Integrative analysis using functional genomics tools that included GeneWeaver, String, and Mouse Genome Informatics identified a total of nine additional candidate modifier genes that could influence the organ-specific ectopic mineralization phenotypes. Integration of the candidate genes into the existing ectopic mineralization gene network expands the current knowledge on the complexity of the network that, as a whole, governs ectopic mineralization in soft connective tissues.
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