颅骨融合(CS)是由于颅骨缝线过早融合而导致的主要出生缺陷。非综合征性CS比综合征性CS发生更频繁,矢状位非综合征性颅骨融合(sNCS)是最常见的CS表型。先前对sNCS的全基因组关联和靶向测序分析已经确定了多个相关基因座,与20号染色体上最强的关联。在这里,我们报告了首次使用63个先证者-亲本三重奏对sNCS进行全基因组测序研究。使用传输不平衡测试(TDT)和罕见变异TDT(rvTDT)分析了这些三重奏的测序数据,以鉴定高风险罕见基因变异。还检查了拷贝数变体(CNV)和从头变体的测序数据。TDT分析在20p12.3确定了一个非常重要的基因座,位于BMP2和非编码RNA基因LINC01428之间的基因间区域。三个变体(rs6054763,rs6054764,rs932517)被鉴定为潜在的因果变体,因为它们是转录因子结合位点的可能性,有害的组合注释依赖消耗分数,先证者中次要等位基因的高度富集。在一个未受影响的队列中,颅骨穹顶形状的形态测量分析验证了这三种单核苷酸变体(SNV)对头颅的影响。没有全基因组显著的罕见变异,从头基因座,或CNV被鉴定。未来确定sNCS风险变异的努力应该包括对更大和更多样化的人群样本进行测序,并增加组学分析。例如RNA-seq和ATAC-seq。
Craniosynostosis (CS) is a major birth defect resulting from premature fusion of cranial sutures. Nonsyndromic CS occurs more frequently than syndromic CS, with sagittal nonsyndromic craniosynostosis (sNCS) presenting as the most common CS phenotype. Previous genome-wide association and targeted sequencing analyses of sNCS have identified multiple associated loci, with the strongest association on chromosome 20. Herein, we report the first whole-genome sequencing study of sNCS using 63 proband-parent trios. Sequencing data for these trios were analyzed using the transmission disequilibrium test (TDT) and rare variant TDT (rvTDT) to identify high-risk rare gene variants. Sequencing data were also examined for copy number variants (CNVs) and de novo variants. TDT analysis identified a highly significant locus at 20p12.3, localized to the intergenic region between BMP2 and the noncoding RNA gene LINC01428. Three variants (rs6054763, rs6054764, rs932517) were identified as potential causal variants due to their probability of being transcription factor binding sites, deleterious combined annotation dependent depletion scores, and high minor allele enrichment in probands. Morphometric analysis of cranial vault shape in an unaffected cohort validated the effect of these three single nucleotide variants (SNVs) on dolichocephaly. No genome-wide significant rare variants, de novo loci, or CNVs were identified. Future efforts to identify risk variants for sNCS should include sequencing of larger and more diverse population samples and increased omics analyses, such as RNA-seq and ATAC-seq.