Fig 1.
Specific rare genomic copy number variants may influence BAV disease severity.
Aortic events, thoracic aortic aneurysm, thoracic aortic dissection, or aortic valve stenosis or regurgitation requiring aortic valve repair or replacement.
Fig 2.
Overview of pipeline for CNV identification and validation.
SNP, single nucleotide polymorphism; QC, Quality control; CNV, copy number variant. Illumina B-allele frequency and signal intensity data was trimmed and exported using GenomeStudio. Three different algorithms (PennCNV [27], cnvPartition, and QuantiSNP [28]) were used to generate initial CNV calls and sample-level statistics. Sample-level quality control analysis was performed using PennCNV. PLINK [29] was used to define CNV regions for subsequent burden, enrichment, and replication tests. Raw CNV calls were individually screened for CNVs intersecting with genes implicated in BAV and enriched in case-control tests. CNVs were validated by examining the raw data in GenomeStudio.
Table 1.
Characteristics of EBAV and BAVGWAS probands.
Table 2.
Burden analysis of EBAV CNVs.
Table 3.
Burden analysis of BAVGWAS CNVs.
Table 4.
Burden of rare EBAV CNVs.
Table 5.
CNVs affecting congenital heart disease genes in EBAV.
Table 6.
CNVs affecting congenital heart disease genes in BAVGWAS.
Fig 3.
UCSC genome browser plots of GATA4 and DSCAM variants.
Each bar represents a copy number variant (CNV). Blue, EBAV CNVs; Red: CNVs BAVGWAS CNVs. (a) Ideogram of Chromosome 8 with CNV region highlighted red; (b) Plot of GATA4 CNVs; (c) Ideogram of Chromosome 21 with CNV region highlighted red; (d) Plot of DSCAM CNVs. Figures were constructed using the UCSC Genome Browser (http://genome.ucsc.edu) [35].