bioRxivDevelopmental BiologyPreprint
Modifiers and Mediators of Craniosynostosis Severity Revealed by Differential Gene Expression
Amel DudakoviciD, Hwa Kyung NamiD, André J. van WijneniD, Nan E. HatchiD
Abstract
Severity of craniosynostosis in humans varies widely even in patients with identical genetic mutations. In this study we compared RNA sequencing data from cranial tissues of a severe form of Crouzon craniosynostosis syndrome (C57BL/6 FGFR2C342Y/+ mice) with those of a less severe form of Crouzon craniosynostosis (BALB/c FGFR2C342Y/+ mice) to identify genetic modifiers that influence craniosynostosis phenotype severity. Comparison of the mice revealed neonatal onset of coronal suture fusion in the form of suture obliteration in C57BL/6 mice (88% incidence, p<.001 between genotypes). Coronal suture fusion in the form of point fusions across the suture occurred at approximately 4 weeks after birth, with less severe skull shape abnormalities, in BALB/c mice. Substantially fewer genes were differentially expressed in BALB/c FGFR2+/+ vs. FGFR2C342Y/+ mice (87 out of 15,893 expressed genes) than C57BL/6 FGFR2C+/+ vs. FGFR2C342Y/+ mice (2,043 out of 19,097 expressed genes). Further investigation revealed differential expression of coronal suture fusion associated genes, eph/ephrin boundary genes, cell proliferation genes, osteoblast differentiation genes and epigenetic regulators, among others. The most striking pattern in the data was the minimal change in gene expression seen for most genes in BALB/c FGFR2+/+ vs. FGFR2C342Y/+ mice. Analysis of protein processing and lysosomal components support the hypothesis that the craniosynostosis phenotype is less severe in BALB/c mice because the mutant FGFR2C342Y protein is not expressed to the same extent as that seen in C57BL/6 mice. Together, these results suggest that a strategy aimed at increasing degradation of the mutant receptor or downstream signaling inhibition could lead to diminished phenotype severity.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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