Quantitative Trait Locus and Integrative Genomics Revealed Candidate Modifier Genes for Ectopic Mineralization in Mouse Models of Pseudoxanthoma Elasticum

Accepted Manuscript Quantitative Trait Locus and Integrative Genomics Revealed Candidate Modifier Genes for Ectopic Mineralization in Mouse Models of Pseudoxanthoma Elasticum Qiaoli Li, Vivek M. Philip, Timothy M. Stearns, Jason A. Bubier, Benjamin L. King, Benjamin E. Low, Michael V. Wiles, Amir Hossein Saeidian, Beth A. Sundberg, Jouni Uitto, John P. Sundberg PII:

S0022-202X(19)31761-0

DOI:

https://doi.org/10.1016/j.jid.2019.04.023

Reference:

JID 1954

To appear in:

The Journal of Investigative Dermatology

Received Date: 8 January 2019 Revised Date:

28 March 2019

Accepted Date: 26 April 2019

Please cite this article as: Li Q, Philip VM, Stearns TM, Bubier JA, King BL, Low BE, Wiles MV, Saeidian AH, Sundberg BA, Uitto J, Sundberg JP, Quantitative Trait Locus and Integrative Genomics Revealed Candidate Modifier Genes for Ectopic Mineralization in Mouse Models of Pseudoxanthoma Elasticum, The Journal of Investigative Dermatology (2019), doi: https://doi.org/10.1016/j.jid.2019.04.023. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Journal of Investigative Dermatology Research Article 5/9/2019

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Quantitative Trait Locus and Integrative Genomics Revealed Candidate Modifier Genes for Ectopic Mineralization in Mouse Models of Pseudoxanthoma Elasticum

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Qiaoli Li1, Vivek M. Philip2, Timothy M. Stearns2, Jason A. Bubier2, Benjamin L. King3, Benjamin E. Low2, Michael V. Wiles2, Amir Hossein Saeidian1,4, Beth A. Sundberg2, Jouni Uitto1, and John P. Sundberg2 1

Running Title: Modifier genes for PXE

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Department of Dermatology and Cutaneous Biology and the Jefferson Institute of Molecular Medicine, Sidney Kimmel Medical College, and the PXE International Center of Excellence in Research and Clinical Care, Thomas Jefferson University, Philadelphia, PA; 2 The Jackson Laboratory, Bar Harbor, ME; 3 Department of Molecular and Biomedical Sciences, University of Maine, Orono, ME; 4 Genetics, Genomics and Cancer Biology PhD Program, Thomas Jefferson University, Philadelphia, PA

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Keywords: Pseudoxanthoma elasticum; ectopic mineralization; modifier genes; quantitative trait locus Abbreviations: Chr, chromosome; cnSNP, coding non-synonymous single nucleotide polymorphism; IMPC, International Mouse Phenotyping Consortium; KOMP, Knockout Mouse Project; PXE, pseudoxanthoma elasticum; QTL, quantitative trait locus

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Word count: 3,745

Corresponding author: Qiaoli Li, PhD Department of Dermatology and Cutaneous Biology Sidney Kimmel Medical College PXE International Center of Excellence in Research and Clinical Care Thomas Jefferson University 233 S. 10th Street, Suite 431 BLSB Philadelphia, Pennsylvania 19107 Email: [email protected] 1

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ABSTRACT Pseudoxanthoma elasticum (PXE), a prototype of heritable multi-system ectopic mineralization disorders, is caused by mutations in the ABCC6 gene encoding a putative efflux transporter, ABCC6.

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The phenotypic spectrum of PXE varies, and the correlation between genotype and phenotype has not been established. To identify genetic modifiers, we performed quantitative trait locus analysis in inbred mouse strains that carry the same hypomorphic allele in Abcc6 yet with highly variable ectopic

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mineralization phenotypes of PXE. Abcc6 was confirmed as a major determinant for ectopic

mineralization in multiple tissues. Integrative analysis using functional genomics tools that included

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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

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connective tissues.

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INTRODUCTION Ectopic mineralization of connective tissues is a complex process leading to deposition of calcium phosphate complexes in the extracellular matrix, particularly affecting the skin and the arterial blood

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vessels. Ectopic mineralization is a global pathological problem encountered in aging, cancer, diabetes, and autoimmune diseases, causing significant morbidity and mortality. Several Mendelian genetic disorders share phenotypic similarities with the acquired forms of ectopic mineralization, and serve as

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genetically controlled model systems to study various facets of pathological mineralization (Nitschke and Rutsch, 2012). Pseudoxanthoma elasticum (PXE; OMIM#264800), a multi-system disorder

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clinically affecting the skin, eyes, and the cardiovascular system, is characterized by late-onset and slowly progressive connective tissue mineralization (Neldner, 1988; Uitto et al., 2017; Li et al., 2019). PXE is an autosomal recessive disorder with complete penetrance, a slight female preponderance, and prevalence in the 1 in 50,000-70,000 range. The phenotypic spectrum is highly variable with inter- and

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intra-familial heterogeneity in the age at onset and the extent and severity of organ system involvement, adding to the diagnostic difficulty.

Identification of mutations in the ATP-binding cassette, subfamily C, member 6 (ABCC6) gene,

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as the primary genetic basis of PXE, was accomplished in 2000 (Ringpfeil et al., 2000; Le Saux et al., 2000; Bergen et al., 2000). Since then, tremendous progress has been made in understanding the

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molecular genetics, spectrum of clinical phenotypes, and pathogenesis of this disease (Uitto et al., 2017; Li et al., 2019). The ABCC6 gene encodes the transmembrane ABCC6 protein, a putative efflux transporter (Cai et al., 2002; Ilias et al., 2002; Borst et al., 2019), expressed primarily in the liver (Belinsky and Kruh, 1999; Scheffer et al., 2002). PXE was determined in murine models to be a metabolic disorder caused by defective ABCC6 transporter activity leading to ectopic mineralization in soft connective tissues (Jiang et al., 2009; Jiang et al., 2010; Li et al., 2017). 3

ACCEPTED MANUSCRIPT Over 400 distinct mutations in ABCC6 have been reported in PXE patients (https://www.ncbi.nlm.nih.gov/clinvar/?term=abcc6[gene]). However, no correlation could be established between the phenotype and the nature or the position of the mutations in ABCC6 (Pfendner

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et al., 2007; Iwanaga et al., 2017; Legrand et al., 2017). Evidence has emerged suggesting the presence of modifier genes for PXE (Dabisch-Ruthe et al., 2014; Li et al., 2009b). Adding to the genetic complexity of PXE, recent findings revealed that the same ABCC6 mutations can also cause type 2

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generalized arterial calcification of infancy (GACI; OMIM#614473), a distinct clinical entity most often caused by ENPP1 mutations (GACI; OMIM#208000), resulting in significant mortality in

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infancy due to early onset of extensive vascular mineralization (Rutsch et al., 2003; Li et al., 2014a; Nitschke et al., 2012). In addition, in an unusually severe vascular case presenting as GACI the patient died at 15 months of age while his older brother developed PXE in adolescence (Le Boulanger et al., 2010). Presumably, the same ABCC6 mutations in the family resulted in two ends of the clinical severity spectrum of ectopic mineralization. These observations indicate a substantial gap in our

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understanding of the genetic factors that modify disease severity. Two Abcc6-/- mouse models of PXE develop late onset, yet progressive, lesions similar to those

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seen in human patients with PXE (Klement et al., 2005; Gorgels et al., 2005). Spontaneous ectopic mineralization, at various degrees of severity, was also identified in four inbred mouse strains in a

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large-scale aging study consisting of 28 inbred strains of mice (Sundberg et al., 2011; Berndt et al., 2013). These strains, 129S1/SvImJ (129), C3H/HeJ (C3), DBA/2J (D2), and KK/HlJ (KK), harbor a non-synonymous coding SNP in the Abcc6 gene (rs32756904) resulting in reduced ABCC6 protein levels in the liver, the primary site of expression of the gene (Li et al., 2012). Among these four inbred strains, KK displayed the most severe multi-system mineralization phenotype similar to that in Abcc6-/mice, therefore providing another model of PXE (Li et al., 2012). The 129 strain developed 4

ACCEPTED MANUSCRIPT mineralization to a much lesser extent while C3 and D2 mice developed extremely mild mineralization. By contrast, B6 mice, wild type for the Abcc6 allele, do not develop PXE-like lesions. As the aging study carefully maintained all the strains under the same environmental and high barrier

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conditions, the variability in severity of mineralization (quantitative difference) among these four strains with the same Abcc6 allelic mutation, suggest that modifier genes regulate phenotypic

presentation. To identify the modifier genes, crosses were carried out between KK and either B6 or D2

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mice and from which a number of Quantitative Trait Loci (QTLs) for ectopic mineralization were identified. As expected, Abcc6 was confirmed as a major player in ectopic mineralization in PXE.

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Integration of functional genomic data of these inbred strains revealed nine additional candidate modifier genes and provided insights into potential networks controlling ectopic mineralization.

RESULTS

hallmark of PXE in mice

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Analysis of F1 hybrid phenotypes suggested recessive QTL for vibrissae mineralization, the

Crosses of the severely affected KK mice with B6, a strain without mineralization, or with D2, a strain

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with mild PXE, were used in QTL analysis to localize genomic intervals that have effects on ectopic mineralization phenotype. Their respective F1 progeny, B6KKF1 and D2KKF1, were analyzed at 12

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weeks of age. The severity of vibrissae mineralization in the muzzle skin, a hallmark of PXE in mice, was scored by semi-quantitative histopathological analysis (Figure 1a). In addition, the degree of mineralization in muzzle skin was quantified by an independent chemical assay of calcium. Linear regression analysis of log2 transformed calcium content and severity score had an adjusted R2 = 0.8957 for the parental B6, D2, KK, B6KKF1 and D2KKF1 mice (Figure S1), indicating the consistency between these two techniques to evaluate the degree of ectopic mineralization. As such, histologic 5

ACCEPTED MANUSCRIPT severity scores were used in the study for muzzle skin and other organs. Severity scores of B6KKF1 and D2KKF1 were not significantly different than the B6 and D2 parental strain (ANOVA, F = 1.80, P = 0.1569), but were significantly different from KK (ANOVA, F = 150.75, P < 0.0001). These results

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suggest that recessive genes cause vibrissae mineralization observed in KK mice. F1 mice were backcrossed with the KK parental strain and N2 progeny, (B6KKF1)KK and (D2KKF1)KK, were generated.

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Analysis of N2 hybrid phenotypes revealed various degrees of mineralization in multiple tissues (quantitative traits)

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The N2 progeny consisting of a total of 183 (B6KKF1)KK mice and 191 (D2KKF1)KK were necropsied at 12 weeks of age. A number of organs known to be affected in PXE, including muzzle skin, heart, kidney, eyes, and lung, were collected for histologic evaluation of ectopic mineralization (Figures 1-3; Figures S2,S3). While there appears to be a slight female preponderance (1.3:1

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Female:Male ratio) for PXE in humans (Neldner, 1988), there is no major sexual dichotomy in mice for the majority of the inbred and hybrid strains.

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QTL analysis identified chromosome regions containing modifier genes We identified 8 organ-specific QTLs for ectopic mineralization. These QTLs were designated as

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Vmm1 to Vmm8 and deposited in the Mouse Genome Database (MGD), a community database resource for laboratory mouse. These QTLs contain 73 to 1,203 genes at each locus, some of which overlap, that contribute to the PXE phenotype in multiple tissues (Table 1). When analyzed by lesion and organ, five of the QTLs were identified on Chr.7 in the KK and B6 cross but not in the KK and D2 cross (Figures 1-3; Figures S2,S3). Among them, Vmm3 and Vmm4 overlapped with Abcc6 (position 46 Mbp on Chr.7) which resided in close proximity to Vmm1, Vmm2, and Vmm6 (Table 1). Thus, the 6

ACCEPTED MANUSCRIPT Abcc6 gene was likely linked to the PXE phenotype in multiple organs, as expected. The remaining three QTLs, one for heart mineralization on Chr.3 (Vmm7) and two overlapping QTLs for kidney mineralization on Chr.5 (Vmm5 and Vmm8), contain genes, yet to be identified, that modify ectopic

Integrative analysis identified candidate modifier genes for PXE

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mineralization in these tissues (Figures 2, 3).

GeneWeaver has been used successfully to identify candidate genes related to other phenotypes

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(Delprato et al., 2017; Bubier et al., 2014). Combination of the QTL intervals with transcriptome studies of organs, specifically heart (Lin et al., 2014) and kidney (Rubin et al., 2016) and presence of

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differential SNPs (coding and non-coding) between KK and B6/D2, the number of candidate modifier genes was reduced to 30 and 33 for Vmm7 locus on Chr.3 and Vmm5/Vmm8 loci on Chr.5, respectively (Figure 4a,b). We next performed functional genomics analysis to further narrow down the candidate gene list. The prioritization criteria includes the following: genes consistent with the ectopic mineralization phenotype in either human or mouse in prior studies, genes that interact with Abcc6 at

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String database (Szklarczyk et al., 2017), publicly available information at GeneWeaver and Mouse Genome Informatics including genes that alter bone mineralization and mineral homeostasis. A total of

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nine candidate genes were identified (Figure 4c). Among them, two candidate genes were identified for heart mineralization in the Chr.3 QTL in KK and D2 cross (Figure S4), and seven candidate genes

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fulfilled the selection criteria for kidney mineralization in the Chr.5 QTL in KK crosses with either B6 or D2 (Figure S5).

Generation and expansion of an ectopic mineralization gene network To illustrate the complexity of ectopic mineralization gene network, 22 genes known to be involved in ectopic mineralization phenotypes in humans and/or in mice (Table S1) together with the nine candidate genes for modification of ectopic mineralization phenotype were analyzed as a whole. 7

ACCEPTED MANUSCRIPT Ingenuity Pathway Analysis® revealed the presence of a complex and multi-branched network among 22 known genes including Abcc6 (Figure 5, highlighted in red) and nine candidate genes (Figure 5,

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highlighted in green).

DISCUSSION

Using the mouse to model human disease: the presence of modifier genes for PXE in mice

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Modifier effects are remarkably common in human and model organisms (Nadeau, 2001). Modifier gene research is a subject that attracted much attention representing a paradigm shift in the study of

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monogenic disorders, away from the influence of the primary disease-causing gene. In addition, a recent study of a large group of healthy human “controls” showed that some individuals harbor disease-causing mutations for Mendelian disorders but are disease free (Chen et al., 2016). These observations point to the fundamental phenomenon – genetic modifiers are an integral part of the

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genetic risk landscape of essentially all monogenic disorders, including PXE. The controlled environment of inbred mice bearing the same Abcc6 allelic mutation allows separation of environmental effects from genetics with the recognition that PXE is a complex heritable disorder at

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the genome, environment, and diet interface (Uitto et al., 2001; Pomozi et al., 2018). Characterization of four naturally occurring Abcc6 mutant mouse inbred strains demonstrated that it was possible to

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exclude environmental influences and identify genetic factors that modify the disease phenotype based on marked severity differences between them.

Abcc6 was confirmed as a strong genetic determinant for ectopic mineralization Stepwise bioinformatics analysis reduced the large QTL intervals to a total of ten candidate genes including Abcc6. By comparing crosses of strains that had the same or different Abcc6 alleles, it was 8

ACCEPTED MANUSCRIPT possible to unambiguously demonstrate that the Abcc6 gene on Chr.7 QTL was a strong genetic determinant of ectopic mineralization in multiple organs.

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Integrative bioinformatics to identify modifier genes Geneweaver analysis minimized false discovery rate for QTLs on Chr.3 and Chr.5. We have analyzed the QTLs that are identical by descent by comparing SNP genotypes. To identify candidate genes that

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fell within the QTL intervals, the parental strains were screened for the presence of SNPs in the genes which might affect expression potentially modifying the PXE phenotype. Integrative functional

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genomics analysis, such as genes known to be associated with ectopic mineralization phenotype or interact with Abcc6, and genes that play a role in bone mineralization and homeostasis, facilitated identification of candidate genes. As such, nine genes fulfilled the selection criteria (Figure 4c). Although ectopic soft tissue mineralization, the hallmark of PXE, and aberrant osseous mineralization rarely observed in these mice, it is well known that the pathophysiological mechanisms underlying

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both are alike (Kirsch, 2006). Indeed, studies in murine and human PXE demonstrated that perturbed osteogenic signaling is involved in the ectopic mineralization process (Hosen et al., 2014). While there

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is no evidence that osteogenic changes are a direct consequence of ABCC6 deficiency, it is possible that genes that regulate mineral homeostasis and/or bone mineralization could contribute to the ectopic

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deposition of minerals in soft connective tissues.

Car2 and Postn are candidate modifier genes for heart mineralization on Chr.3 QTL Carbonic anhydrase II (CAR2) is a member of a family of zinc metalloenzymes involved in numerous physiological and pathological processes. CAR2 is known to be associated with ectopic mineralization in both humans and mice (Table S1). Loss-of-function mutations in the CAR2 gene cause an autosomal 9

ACCEPTED MANUSCRIPT recessive disorder that produces osteopetrosis, renal tubular acidosis, and cerebral calcification (Sly et al., 1983), when deleted in mice causes slowly progressive vascular calcification (Spicer et al., 1989). In addition, CAR2 is expressed at high levels in osteoclasts during bone resorption (Laitala and

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Vaananen, 1994). Periostin, encoded by Postn, is a highly conserved matricellular protein expressed in a broad range of tissues including the skeleton. Periostin has multifaceted role in bone homeostasis (Bonnet et al., 2016). Development of Postn null mice elucidated the crucial role of periostin on

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dentinogenesis and osteogenesis (Bonnet et al., 2009).

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Seven genes, Abcg3, Aldh2, Chek2, Dmp1, Hnf1a, Idua, and TTc28, are candidate modifier genes for renal tubule mineralization on Chr.5 QTL

Abcg3 codes for ATP-binding cassette, sub-family G, member 3. Abcg3 was selected as a candidate because of its interaction with ABCC6 in String database (Szklarczyk et al., 2017). While a recent

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study suggested its association with arthrogryposis-renal dysfunction-cholestasis syndrome in mouse (Chai et al., 2018), the function of ABCG3 relating to ectopic mineralization is not readily relevant. Aldehyde dehydrogenase 2 (ALDH2) is the enzyme that degrades and detoxifies the acetaldehyde

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produced by alcohol metabolism. Disruption of the Aldh2 gene resulted in altered cortical bone structure in mice (Tsuchiya et al., 2013). In addition, an association between an ALDH2 polymorphism

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and osteoporosis and hip fracture has been reported (Takeshima et al., 2017; Yamaguchi et al., 2006). Checkpoint kinase 2 (CHEK2) is the main effector kinase of ataxia telangiectasia mutated (ATM) and is responsible for cell cycle regulation. CHEK2 regulates renal 25-hydroxyvitamin D 1αhydroxylase expression thereby impacting calcium and phosphate metabolism (Fahkri et al., 2015). Dentin matrix acidic phosphoprotein 1 (DMP1) is an extracellular matrix protein and a member of the small integrin binding ligand N-linked glycoprotein family. This protein, present in diverse cells of 10

ACCEPTED MANUSCRIPT bone and tooth tissues, is critical for proper mineralization of bone and dentin. Mutations in DMP1 cause autosomal recessive hypophosphatemia, a disease that manifests as rickets and osteomalacia, and when deleted in mice, results in a hypomineralized bone phenotype (Feng et al., 2006; Feng et al.,

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2003). HNF1 homeobox A (HNF1A) is a member of the hepatocyte nuclear factor (HNF) family of transcription factors that regulate organ development and glucose, amino acid, and lipid homeostasis.

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Human mutations in HNF1A cause type 3 maturity-onset diabetes of the young (MODY), characterized by the onset of diabetes mellitus before the age of 25 (McDonald and Ellard, 2013). Mice deficient in

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Hnf1a showed the typical traits of the human renal Fanconi syndrome characterized by polyuria, glucosuria, aminoaciduria, phosphaturia, and bone hypomineralization (Pontoglio et al., 1996). AlphaL-iduronidase (IDUA) is a lysosomal enzyme that participates in the degradation of dermatan sulfate and heparan sulfate. Mutations in IDUA cause autosomal recessive mucopolysaccharidosis type IHurler (MPS I-H) manifesting with skeletal deformities, hearing loss, corneal clouding, heart failure

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and mental retardation (Scott et al., 1995). The transgenic mice carrying a nonsense mutation analogous to the human p.W402X mutation in IDUA have loss of a-L-iduronidase activity, significant

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increase in glycosaminoglycan levels in multiple tissues, and increase in bone density (Wang et al., 2010). Tetratricopeptide repeat domain-containing protein 28 (TTC28) is a protein required during the

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cell cycle for condensation of spindle midzone microtubules, formation of the mid-body, and completion of cytokinesis. Decreased bone mineral density was reported in the Ttc28 null mice in the repository of International Mouse Phenotyping Consortium. Most, if not all, of the null mutations in mice for these genes were made on one of the C57BL/6 substrains that are naturally resistant to develop PXE lesions. This strain background effect and non-

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ACCEPTED MANUSCRIPT consistent phenotyping may explain why more extensive lesions, consistent with PXE, were not reported.

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Expansion of the ectopic mineralization gene network and relevance to human PXE Functional studies in appropriate model systems are needed to validate the role of candidate modifier genes in the ectopic mineralization process when combined with ABCC6 mutations. In fact, the

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dysregulated interactions between genes known to cause ectopic mineralization are encountered. Some patients with a heterozygous mutation in GGCX and a heterozygous mutation in ABCC6 display PXE-

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like skin features, suggesting digenic inheritance for PXE and implying a role for multiple genetic factors in ectopic mineralization in general (Li et al., 2009a). Therefore, studying interaction and functional networks among the 22 known and nine candidate proteins provides the opportunity to further dissect gene-gene interactions in the process of ectopic mineralization. Because of considerable synteny between the mouse and human genomes, it is likely that some if not all the genes found in

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mice are also applicable to humans modifying the disease phenotype, and this possibility can be tested

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by genotyping cohorts of patients with PXE.

MATERIALS AND METHODS

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Mice and breeding

The parental strains of mice, C57BL/6J (B6), KK/HlJ (KK), and DBA/2J (D2), were obtained from The Jackson Laboratory (Bar Harbor, ME). All mice were housed on standard rodent diet (Laboratory Autoclavable Rodent Diet 5010; PMI Nutritional International, Brentwood, MO) under standard conditions at the Animal Facility of Thomas Jefferson University. All protocols were approved by the Institutional Animal Care and Use Committee of Thomas Jefferson University. 12

ACCEPTED MANUSCRIPT 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. All mice used for phenotyping analysis were placed at

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4 weeks of age post weaning on the “acceleration diet” (Envigo, Rodent diet TD.00442, Madison, WI) which was shown to accelerate ectopic mineralization in mouse models of PXE (Li et al., 2014b; Jiang and Uitto, 2012). At 12 weeks of age, mice were necropsied. A total of 384 mice had samples taken for

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DNA analysis (Table S2). 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

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R/qtlDesign package (Sen et al., 2007).

Histopathological analysis

Muzzle, kidney, heart, eyes, and lung were collected from 468 mice and processed for histology (Table S2). Representative paraffin blocks were serially sectioned and stained with hematoxylin and eosin or

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Alizarin red or von Kossa for mineralization, or Periodic Acid Schiff (PAS) to localize the basement membrane using standard procedures. The severity of lesions was scored by an experienced, board-

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certified veterinary pathologist (JPS). The severity of tissue mineralization is based on a semiquantitative measure of the size of the lesion in different organs (scores: 0 normal; 1 mild; 2 moderate;

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3 severe; 4 extreme). Various degrees of tissue mineralization were found and representative cases were photographed to document the range in severity. Similar grading system was used in prior studies to successful identify modifier genes for other diseases (Sundberg et al., 1994; Jurisic et al., 2010; Swaminathan et al., 2013).

Chemical quantitation of calcium in muzzle skin 13

ACCEPTED MANUSCRIPT Muzzle skin biopsies were harvested and decalcified with 0.15 mol/L HCl for 48 hours at room temperature. The solubilized calcium was determined by colorimetric analysis using the ơcresolphthalein complexone method (calcium (CPC) LiquiColor; Stanbio Laboratory, Boerne, TX).

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The values were normalized to tissue weight.

DNA isolation and genotyping

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A total of 384 samples were included in the DNA genotyping analysis (Table S2). Genomic DNA was extracted from tail tips at The Jackson Laboratory and genotyped at Geneseek using GigaMUGA SNP

Quantitative trait locus (QTL) analysis

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genotyping array (Neogen Corporation, Lincoln NE) consisting of approximately 143,000 probes.

All QTL analyses were performed with the R/qtl software package (http://www.rqtl.org/). Given each phenotype distribution we used a non-parametric model in each of the QTL analyses. For each

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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

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approach from the peak QTL.

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GeneWeaver: Integrated search for candidate genes The protein coding genes within the QTL confidence intervals were exported from MGI into GeneWeaver as QTL Gene Sets (GS352436, GS352533, GS352620). A set of genes was created specific to each of the tissues of interest from NCBI GEO and the primary literature (heart GS352736 (Lin et al., 2014) and kidney GS352510 (Rubin et al., 2016)). A set of genes was created using String database to include all known protein-protein interactions with ABCC6 (GS352441). Finally, sets of 14

ACCEPTED MANUSCRIPT genes containing any SNPs between KK and B6/D2 (GS352512), or just cnSNPS between KK and D2 (GS352739) were created. For each QTL additional Gene Sets related to the phenotype were identified using the Search Tool in GeneWeaver from the Mammalian Phenotype Ontology or Human Phenotype

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Ontology Term. Figure S4 and S5 illustrate the workflow to identify candidate modifier genes. The HiSim Graph tool was subsequently run with default parameters to identify set-set overlap using the

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parablique enumeration algorithm.

Gene network construction

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A gene network of protein-protein and gene-regulatory interactions among the 22 known genes including ABCC6 were built using the custom pathway functionality within the Ingenuity Pathways Analysis® software (http://www.ingenuity.com; QIAGEN, Redwood City, CA). First, the 22 genes were added to the network editing tool, “My Pathways”. Next, the “Connect” tool within “My Pathways” was used to connect the genes by adding direct and indirect edges that represent protein-

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protein and gene-regulatory interactions. As not all genes had edges to the other genes, the “Path Explorer” tool within “My Pathways” was used to add additional genes/proteins to the network so that

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all 22 genes had at least one edge in the network. Finally, the nine additional candidate genes from the QTL studies were added to the network and edges added using the “Connect” tool within “My

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Pathways”.

Statistical analyses

Linear regression and ANOVA analysis was performed using R version 3.5.1 (http://r-project.org). Comparisons between different sexes of mice were performed using the two-sided Kruskal-Wallis

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ACCEPTED MANUSCRIPT nonparametric test using SPSS version 15.0 software (SPSS, Chicago, IL). Statistical significance was assigned at P < 0.05.

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CONFLICT OF INTEREST JPS has or recently completed sponsored research projects with Biocon, Takeda, Theravance, and Curadim. JPS has a consulting agreement with Bioniz. All are unrelated to this project. All other

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investigators state no conflict of interest.

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ORCiDs Qiaoli Li: https://orcid.org/0000-0002-5258-3346

Vivek M. Philip: https://orcid.org/0000-0001-5126-707X

Timothy M. Stearns: https://orcid.org/0000-0002-5533-6076

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Jason A. Bubier: https://orcid.org/0000-0001-5013-1234

Benjamin L. King: https://orcid.org/0000-0001-6463-1336 Benjamin E. Low: https://orcid.org/0000-0003-0350-4602

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Michael V. Wiles: https://orcid.org/0000-0002-3620-8386 Amir Hossein Saeidian: https://orcid.org/0000-0003-3512-0654

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Beth A. Sundberg: https://orcid.org/0000-0002-4261-0750 Jouni Uitto: https://orcid.org/0000-0003-4639-807X John P. Sundberg: https://orcid.org/0000-0002-1523-5430

DATA AVAILABILITY STATEMENT Not applicable. No datasets were generated. 16

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ACKNOWLEDGMENTS The authors thank Dian Wang, Joshua Kingman, Jeffrey Lamont, Wenning Qin, Linda Siracusa, Jieyu

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Zhang, Jingyi Zhao, Victoria E. Kennedy, and Kathleen A. Silva for their technical assistance.

AUTHOR CONTRIBUTIONS

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QL, JU, and JPS designed the study. QL and JPS performed the experiments. QL, VMP, TMS, JAB,

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critically revised the manuscript.

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BLK, BEL, MVW, AHS, and BAS did data analysis. QL and JPS drafted the manuscript. All authors

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Bergen AA, Plomp AS, Schuurman EJ, Terry S, Breuning M, Dauwerse H, et al. Mutations in ABCC6 cause pseudoxanthoma elasticum. Nat Genet 2000;25:228-31.

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FIGURE LEGEND Figure 1. Histopathology of vibrissae mineralization in muzzle skin and QTL plots. (a),

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Phenotypic scores of the parental strains of mice, F1 and N2 progeny determined by histopathology. Each dot represents a mouse (red, females; blue, males). Only the D2KKF1 hybrid mice differed with sex as female mice had higher severity than males (Chi-square 19.73, P = 0.0006). (b-k),

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Histopathological evaluation of ectopic mineralization. Vertical sections of vibrissae had no evidence of mineralization in the connective tissue sheath or outer root sheath (b, score 0; c, enlarged boxed area

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in d). Mild mineralization was when one or two follicles had faintly evident mineralization in the connective tissue sheath (d, score 1; e, enlarged boxed area in d). Moderate had one or two follicles with obvious but not extensive mineralization (f, score 2; g, enlarged boxed area in f). Severe cases had multiple follicles affected with prominent mineralization (h, score 3; i, enlarged boxed area in h).

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Extreme cases had extensive mineralization often with granuloma formation at the site of mineralization (j, score 4; k, enlarged boxed area in j). Ectopic mineralization is indicated by arrows. Scale bar = 100 µm (panels b, d, f, h, and j). Scale bar = 20 µm (panels c, e, g, I, and k). (l-m), QTL

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plots from KK x B6 and KK x D2 crosses. KK and D2 both have the Abcc6 mutant allele while B6 has the wild type allele. Therefore, in KK x B6 cross, a major QTL was identified on Chr. 7 that involves

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Abcc6 (P < 0.05); however, there is no linkage to Abcc6 in KK x D2 cross.

Figure 2. Histopathology of heart mineralization and QTL plots. (a), Phenotypic scores of the parental strains of mice, F1 and N2 progeny determined by histopathology. Each dot represents a mouse (red, females; blue, males). (b-i), Histopathologic evaluation of ectopic mineralization. The heart in a few mice was normal (b, score 0); however most had small focal lesions of mineralization 23

ACCEPTED MANUSCRIPT within the myocardium (c, score 1), small but multiple areas of mineralization with some degree of fibrosis (d, score 2), extensive areas (e, score 3), or very large and extensive areas (g, score 4). Epicardial mineralization and fibrosis, the more common presentation of dystrophic cardiac calcinosis

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in inbred strains of mice, was relatively infrequent (h). Enlargement of the boxed area in h illustrates the prominent mineralization with some fibrosis and infiltration with macrophages (i). The myocardial mineralization usually contained a variety of inflammatory cells, mostly macrophages, in the moderate

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to severe forms (f, enlargement of boxed area in e). Ectopic mineralization is indicated by arrows. Scale bar = 500 µm (panels b, c, d, e, g, and h). Scale bar = 20 µm (panels f and i). (j-k), QTL plots

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from KK x B6 and KK x D2 crosses. KK and D2 both have the Abcc6 mutant allele while B6 has the wild type allele. Therefore, in KK x B6 cross, a major QTL was identified on Chr. 7 that involves Abcc6 (P < 0.05); however, there is no linkage to Abcc6 in KK x D2 cross. In addition, a QTL on Chr. 3 was identified in KK x D2 cross.

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Figure 3. Histopathology of kidney mineralization and QTL plots. (a), Phenotypic scores of the parental strains of mice, F1 and N2 progeny determined by histopathology. Each dot represents a

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mouse (red, females; blue, males). Kidney mineralization phenotypes were more severe in female mice in B6KKF1 (Chi-square 6.54, P = 0.038), D2KKF1 (Chi-square 8.04, P = 0.045), (B6KKF1)KK (Chi-

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square 9.83, P = 0.044) and (D2KKF1)KK (Chi-square 14.73, P = 0.005) hybrid mice. (b-k), Histopathologic evaluation of ectopic mineralization. Normal kidneys were infrequent in the backcrossed mice (b, score 0). Mild cases of renal tubular mineralization consisted of occasional mineralized foci within tubules (c, score 1). Moderate cases had numerous scattered mineral filled tubules (d, score 2). Severe had many affected tubules, especially in the medulla, but none or few tubules were markedly dilated (e, score 3). Extremely severe cases involved many tubules in both the 24

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infrequent in mild cases and progressively increased in severity often in parallel to the degree of renal tubular mineralization. g, h, i, j and k: enlarged boxed areas of b, c, d, e and f, respectively. Ectopic mineralization is indicated by arrows. Scale bar = 200 µm (panels b-f). Scale bar = 20 µm (panels g-k).

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(l-m), QTL plots from KK x B6 and KK x D2 crosses. KK and D2 both have the Abcc6 mutant allele while B6 has the wild type allele. Therefore, in KK x B6 cross, a major QTL was identified on Chr. 7

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that involves Abcc6 (P < 0.05); however, there is no linkage to Abcc6 in KK x D2 cross. In addition, a QTL on Chr. 5 was identified in both crosses.

Figure 4. Schematic representation of how GeneWeaver was used to prioritize the QTL intervals, using heterogeneous data from various sources. (a,b), The application of genetic mapping technique

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combined with integrative functional genomics facilitated the identification of candidate genes modifying ectopic mineralization. The details of integrative functional genomics data related to bone

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mineralization and homeostasis are the following: Car2 - Mammalian Phenotype Ontology Annotation - Abnormal bone mineral density and Abnormal mineral homeostasis (KOMP phenotyping of

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C57BL/6.Car2tm1(KOMP)Vlcg/J; (Spicer et al., 1989)); Postn - Mammalian Phenotype Ontology Annotation - Abnormal bone mineral density and Abnormal mineral homeostasis (IMPC phenotyping of C57BL/6N-Postntm1.1(KOMP)Vlcg; (Bonnet et al., 2009)); Abcg3 - Abcc6 interacting gene from String database (Evidence of co-expression, co-occurring in PubMed abstracts and experimental evidence of putative homologs interacting in S.cerevisiae); Aldh2 - Mammalian Phenotype Ontology Annotation Abnormal bone mineral density (IMPC phenotyping of C57BL/6N-Aldh2tm1a(EUCOMM)Wtsi/Ieg; (Tsuchiya 25

ACCEPTED MANUSCRIPT et al., 2013)); Chek2 - Mammalian Phenotype Ontology Annotation - Abnormal mineral homeostasis (IMPC phenotyping of C57BL/6N-Chek2tm1b(EUCOMM)Hmgu/J; (Fahkri et al., 2015)); Dmp1 - Mammalian Phenotype Ontology Annotation - Abnormal bone mineral density (Feng et al., 2003; Feng et al.,

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2006); Hnf1a - Mammalian Phenotype Ontology Annotation - Abnormal bone mineral density (Pontoglio et al., 1996); Idua - Mammalian Phenotype Ontology Annotation - Abnormal bone mineral density (Wang et al., 2010); Ttc28 - Mammalian Phenotype Ontology Annotation - Abnormal bone

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mineral density (IMPC phenotyping of C57BL/6N-Ttc28tm1b(EUCOMM)Hmgu/Tcp). Chr, Chromosome. cnSNP, coding non-synonymous single nucleotide polymorphism; IMPC, International Mouse

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Phenotyping Consortium. KOMP, Knockout Mouse Project. QTL, quantitative trait locus. (c), Summary of the candidate modifier genes from Geneweaver analysis. For detailed stepwise hierarchical illustrations, see Fig. S4 and Fig. S5.

Figure 5. Complex ectopic mineralization gene network. Twenty-two genes from Table S1

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associated with ectopic mineralization (highlighted in red) and nine candidate genes (highlighted in green) linked by direct (solid lines) and indirect (dashed line) protein-protein and gene regulatory

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interactions using Ingenuity Pathways Analysis. Note that the mouse does not have the corresponding ortholog of human SAMD9 gene and human do not have an ortholog of mouse Abcg3. Alp is the same

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gene as ALPL which encodes tissue non-specific alkaline phosphatase.

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Table 1. All statistically significant QTLs in the two backcross studies Chr

LOD

KK x B6 cross QTL Pval

Muzzle Heart Lung Kidney

7 7 7 7 5 7

15.67 10.50 3.64 7.37 4.12 6.11

Vmm1 Vmm2 Vmm3 Vmm4 Vmm5 Vmm6

Eye

0.000 0.000 0.006 0.000 0.006 0.000

Chr Interval (Mbp)* 47.5 – 56.9 47.5 - 74.5 37.6 - 72.4 37.6 - 87.4 76.9 - 125.3 62.2 - 103.1

Chr

LOD

KK x D2 cross QTL Pval

3

3.37

Vmm7

0.038

5

5.67

Vmm8

0.000

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Chr Interval (Mbp)* 13.5 - 76.3

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Organ

97.9 - 128.3

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Human Disease‡

Gene Name ATP-binding cassette, family C, member 6

PXE

Human skin, eye, kidney, heart, aorta

UNK

UNK

Ahsg

Adiponectin, C1Q and collagen domain containing Alpha-2-HS-glycoprotein

UNK

UNK

Ank

Progressive ankylosis

Apoe

Apolipoprotein E

Atherosclerosis

Atf4 Car2

Activating transcription factor 4 Carbonic anhydrase II

Casr

Calcium-sensing receptor

Atherosclerosis CA II deficiency syndrome HHC1

Fgf23 Galnt3

Ggcx

Kl

cartilage

skin, heart, kidney, muscle, lung, tongue cartilage

aorta

aorta

aorta brain

UNK arteries in multiple organs

(Jahnen-Dechent et al., 1997),(Merx et al., 2005),(Schafer et al., 2003) (Pendleton et al., 2002),(Sweet and Green, 1981),(Villa-Bellosta et al., 2011),(Ho et al., 2000) (Sullivan et al., 1998),(Matsushima et al., 1999) (Masuda et al., 2016) (Sly et al., 1983),(Spicer et al., 1989)

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(Ma et al., 2002; Streeper et al., 2006)

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Fam20a

aorta

Ectonucleotide pyrophosphatase/phosphodiesterase 1

GACI

arteries

Family with sequence similarity 20, member A Fibroblast growth factor 23 UDP-N-acetyl-alpha-Dgalactosamine:polypeptide Nacetylgalactosaminyltransferase 3 Gamma-glutamyl carboxylase

UNK

UNK

HFTC HFTC

skin skin

muzzle skin, heart, aorta, kidney, muscle, tongue, testis, ovary, colon skin, muzzle skin, eye, kidney, heart, aorta, cartilage, ligament, tendon eye, kidney, heart, lung, muscle, testis heart, kidney no lesions

PXE/VKCFD1

skin

no lesions

HFTC

skin

skin, aorta, kidney, heart, lung, testis aorta, cartilage

Klotho

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Enpp1

CMDD

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Adipoq

Sites of Ectopic Mineralization Mouse Ref skin, muzzle skin, eye, kidney, (Klement et al., 2005; Uitto et al., 2017) heart, aorta

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Gene Symbol Abcc6

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Table S1. A list of 22 genes, which when mutated in humans and/or mice, result in ectopic mineralization phenotypes. Some of these arose or were made in mouse inbred (congenic) strain backgrounds prone to these conditions, such as C3 or 129 substrains, which carry a hypomorphic allele of Abcc6 and therefore had lesions that could interfere with interpretation of the phenotype for the gene in question (Berndt et al., 2013; Li et al., 2014b).

no lesions

Mgp

Matrix Gla protein

KTLS

aorta

Nt5e

5' nucleotidase, ecto

ACDC

arteries, cartilage, ligament, tendon

cartilage, ligament, tendon

(Hough et al., 2004) (Uitto et al., 2017),(Li et al., 2014a),(Li et al., 2013) (Vogel et al., 2012) (Chefetz et al., 2005),(Shimada et al., 2004) (Topaz et al., 2006; Ichikawa et al., 2007)

(Li et al., 2009),(Vanakker et al., 2007),(Shiba et al., 2014),(Azuma et al., 2014),(Zhu et al., 2007) (Kuro-o et al., 1997),(Ichikawa et al., 2007),(Hu et al., 2011) (Munroe et al., 1999),(Luo et al., 1997) (Eltzschig and Robson, 2011),(Li et al., 2014b)

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Slc20a2 Slc29a1 Spp1 Tnfrsf11b Trim24

Sterile alpha motif domain containing 9 Solute carrier family 20, member 2 Solute carrier family 29 (nucleotide transporters), member 1 Secreted phosphoprotein 1 Tumor necrosis factor receptor superfamily, member 11b Tripartite motif-containing 24

NFTC

skin

no mouse equivalent

IBGC1 UNK

brain UNK

brain spinal tissues

Atherosclerosis HTC1

aorta UNK

UNK

UNK

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Samd9

aorta aorta

skin, muzzle skin, eye, heart, aorta, kidney, lung, tongue

(Chefetz et al., 2008),(Topaz et al., 2006),(Sprecher, 2010) (Jensen et al., 2013), (Jensen et al., 2016) (Warraich et al., 2013) (Shao et al., 2011) (Fantauzzo et al., 2008),(Callegari et al., 2013),(Yun et al., 2001) (Ignat et al., 2008)

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PXE, pseudoxanthoma elasticum; HOPS, hypophosphatasia, childhood and hypophosphatasia, infantile; CMDD, craniometaphyseal dysplasia, autosomal dominant; HHC1, hypocalciuric hypercalcemia, familial, type 1; GACI, generalized arterial calcification of infancy; HFTC, hyperphosphatemic familial tumoral calcinosis; PXE/VKCFD1, PXE-like disorder with multiple coagulation factor deficiency; KTLS, Keutel syndrome; ACDC, arterial calcification due to CD73 deficiency; NFTC, normophosphatemic tumoral calcinosis; IBGC1, idiopathic basal ganglia calcification 1; DISH, diffuse idiopathic skeletal hyperostosis; HTC1, hypertrichosis universalis congenita, Ambras type. UNK, unknown.

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Table S2. Numbers of mice evaluated by sex and strain/cross for phenotype and/or genotyping Phenotyping Tissues DNA Collected for GigaMuga Arrays Females Males Total Females Males Total C57BL/6J 14 9 23 1 1 2 DBA/2J 11 10 21 1 1 2 KK/HlJ 5 5 10 1 1 2 B6KKF1 12 9 21 1 1 2 D2KKF1 10 9 19 1 1 1 (B6KKF1)KK 91 92 183 91 92 183 (D2KKF1)KK 97 94 191 97 94 191 *strain/cross designations assigned by the International Mouse Genetic Nomenclature Committee (http://www.informatics.jax.org/mgihome/nomen/strains.shtml

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SUPPLEMENTARY FIGURE LEGEND Figure S1. Linear regression analysis of the correlation between the calcium content and the mineralization score in the parental strains and the F1 hybrid mice.

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For the number of mice analyzed, see Table S2.

Figure S2. Histopathology of lung mineralization and QTL plots.

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(a), Phenotypic scores of the parental strains of mice, F1 and N2 progeny determined by

histopathology. Each dot represents a mouse (red, females; blue, males). (b-F), Histopathologic

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evaluation of ectopic mineralization. Normal lungs were infrequent with mineralization (b, score 0). Most of mice had some minor form of mineralization in their lungs. These consisted of purple crystalline structures within alveoli (c, score 1, arrow), to amorphous purple structures within the alveolar wall (d, score 1, arrow). The few moderately affected mice had multiple crystalline

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purple structures that often fragmented as a sectioning artifact. These were larger than the occasional mild forms (e, score 2). f, enlarged boxed area in e. Ectopic mineralization is indicated by arrows. Scale bar – 100 µm. (g-h), QTL plots from KK x B6 and KK x D2 crosses.

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KK and D2 both have the Abcc6 mutant allele while B6 has the wild type allele. Therefore, in KK x B6 cross, a major QTL was identified on Chr. 7 that involves Abcc6 (P < 0.05); however,

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there is no linkage to Abcc6 in KK x D2 cross.

Figure S3. Histopathology of eye mineralization and QTL plots. (a), Phenotypic scores of the parental strains of mice, F1 and N2 progeny determined by histopathology. Each dot represents a mouse (red, females; blue, males). (b-o), Histopathologic evaluation of ectopic mineralization. Corneal stroma mineralization developed to various degrees within the corneal stroma (b-i, score 0 to score 3). Early mild lesions appeared to involve the

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Decemet’s membrane but periodic acid shiff (PAS) staining (basement membrane) demonstrated mineralization was in the stroma (j, k). Von Kossa (l, m) and Alizarin Red (n, o) confirm the crystalline material is mineralization. Ectopic mineralization is indicated by arrows. Scale bar =

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100 µm (panels b, d, f, h, j, l, and n). Scale bar = 10 µm (panels c, e, g, I, k, m, and o). (p-q), QTL plots from KK x B6 and KK x D2 crosses. KK and D2 both have the Abcc6 mutant allele while B6 has the wild type allele. Therefore, in KK x B6 cross, a major QTL was identified on

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Chr. 7 that involves Abcc6 (P < 0.05); however, there is no linkage to Abcc6 in KK x D2 cross.

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Figure S4. Demonstration of Car2 and Postn as candidate genes in Chr.3 QTL using GeneWeaver.

A hierarchical similarity chart of ectopic mineralization-related gene sets. At the bottom of the chart are individual gene sets derived from QTL studies, existing cardiac transcriptome data,

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Sanger SNP database, and String database. Each successive level from the bottom to the top of the chart represents increasingly higher order intersections among these gene sets, with the most

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highly connected genes at the top.

Figure S5. Demonstration of Abcg3, Chek2, Aldh2, Ttc28, Hnf1a, Idua, and Dmp1 as

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candidate genes in Chr.5 QTL using GeneWeaver. A hierarchical similarity chart of ectopic mineralization-related gene sets. At the bottom of the chart are individual gene sets derived from QTL studies, existing kidney transcriptome data, Sanger SNP database, and String database. Each successive level from the bottom to the top of the chart represents increasingly higher order intersections among these gene sets, with the most highly connected genes at the top.