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Whole genome sequencing identifies associations for nonsyndromic sagittal craniosynostosis with the intergenic region of BMP2 and noncoding RNA gene LINC01428.

Authors :
Musolf, Anthony M.
Justice, Cristina M.
Erdogan-Yildirim, Zeynep
Goovaerts, Seppe
Cuellar, Araceli
Shaffer, John R.
Marazita, Mary L.
Claes, Peter
Weinberg, Seth M.
Li, Jae
Senders, Craig
Zwienenberg, Marike
Simeonov, Emil
Kaneva, Radka
Roscioli, Tony
Di Pietro, Lorena
Barba, Marta
Lattanzi, Wanda
Cunningham, Michael L.
Romitti, Paul A.
Source :
Scientific Reports; 4/12/2024, Vol. 14 Issue 1, p1-11, 11p
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
14
Issue :
1
Database :
Complementary Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
176583930
Full Text :
https://doi.org/10.1038/s41598-024-58343-w