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Characterization of distinct classes of differential gene expression in osteoblast cultures from non-syndromic craniosynostosis bone.

Rojas-Peña ML, Olivares-Navarrete R, Hyzy S, Arafat D, Schwartz Z, Boyan BD, Williams J, Gibson G - J Genomics (2014)

Bottom Line: Similar constellations of sub-types were also observed upon re-analysis of a similar dataset of 199 calvarial osteoblast cultures.Annotation of gene function of differentially expressed transcripts strongly implicates physiological differences with respect to cell cycle and cell death, stromal cell differentiation, extracellular matrix (ECM) components, and ribosomal activity.Based on these results, we propose non-syndromic craniosynostosis cases can be classified by differences in their gene expression patterns and that these may provide targets for future clinical intervention.

View Article: PubMed Central - PubMed

Affiliation: 1. Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, GA, USA.

ABSTRACT
Craniosynostosis, the premature fusion of one or more skull sutures, occurs in approximately 1 in 2500 infants, with the majority of cases non-syndromic and of unknown etiology. Two common reasons proposed for premature suture fusion are abnormal compression forces on the skull and rare genetic abnormalities. Our goal was to evaluate whether different sub-classes of disease can be identified based on total gene expression profiles. RNA-Seq data were obtained from 31 human osteoblast cultures derived from bone biopsy samples collected between 2009 and 2011, representing 23 craniosynostosis fusions and 8 normal cranial bones or long bones. No differentiation between regions of the skull was detected, but variance component analysis of gene expression patterns nevertheless supports transcriptome-based classification of craniosynostosis. Cluster analysis showed 4 distinct groups of samples; 1 predominantly normal and 3 craniosynostosis subtypes. Similar constellations of sub-types were also observed upon re-analysis of a similar dataset of 199 calvarial osteoblast cultures. Annotation of gene function of differentially expressed transcripts strongly implicates physiological differences with respect to cell cycle and cell death, stromal cell differentiation, extracellular matrix (ECM) components, and ribosomal activity. Based on these results, we propose non-syndromic craniosynostosis cases can be classified by differences in their gene expression patterns and that these may provide targets for future clinical intervention.

No MeSH data available.


Related in: MedlinePlus

Variance component analysis of gene expression profiles. (A) PC1 differentiates Normal and craniosynostosis samples (t-test, p<0.0001). (B) PC2 largely captures the difference between Cluster B and all other samples (ANOVA, p=0.0043; t-test p-values for comparison with Cluster A and Cluster C are 0.0230 and 0.0069 respectively). (C) Shows the weighted average of the variance captured by the first five principal components that is explained by Cluster, Gender and Code (location of the suture), indicating that most of the variance is among the four clusters A, B, C and N.
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Figure 1: Variance component analysis of gene expression profiles. (A) PC1 differentiates Normal and craniosynostosis samples (t-test, p<0.0001). (B) PC2 largely captures the difference between Cluster B and all other samples (ANOVA, p=0.0043; t-test p-values for comparison with Cluster A and Cluster C are 0.0230 and 0.0069 respectively). (C) Shows the weighted average of the variance captured by the first five principal components that is explained by Cluster, Gender and Code (location of the suture), indicating that most of the variance is among the four clusters A, B, C and N.

Mentions: The first five principal components of transcriptional variation in our 31 RNA-Seq samples capture 59% of the total variance in the expression of 8,025 genes. Notably, PC1 (18.9%) was significantly different between the 8 normal and 23 craniosynostosis samples (p<0.0001; Fig. 1A), strongly suggesting that osteoblasts from fused sutures have different gene expression profiles that persist even in cell culture. In contrast, none of the first 5 PC showed any differential expression with respect to location of the synostosis, indicating that there are no gross differences between these traditionally defined sub-classes of non-syndromic disease.


Characterization of distinct classes of differential gene expression in osteoblast cultures from non-syndromic craniosynostosis bone.

Rojas-Peña ML, Olivares-Navarrete R, Hyzy S, Arafat D, Schwartz Z, Boyan BD, Williams J, Gibson G - J Genomics (2014)

Variance component analysis of gene expression profiles. (A) PC1 differentiates Normal and craniosynostosis samples (t-test, p<0.0001). (B) PC2 largely captures the difference between Cluster B and all other samples (ANOVA, p=0.0043; t-test p-values for comparison with Cluster A and Cluster C are 0.0230 and 0.0069 respectively). (C) Shows the weighted average of the variance captured by the first five principal components that is explained by Cluster, Gender and Code (location of the suture), indicating that most of the variance is among the four clusters A, B, C and N.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4150121&req=5

Figure 1: Variance component analysis of gene expression profiles. (A) PC1 differentiates Normal and craniosynostosis samples (t-test, p<0.0001). (B) PC2 largely captures the difference between Cluster B and all other samples (ANOVA, p=0.0043; t-test p-values for comparison with Cluster A and Cluster C are 0.0230 and 0.0069 respectively). (C) Shows the weighted average of the variance captured by the first five principal components that is explained by Cluster, Gender and Code (location of the suture), indicating that most of the variance is among the four clusters A, B, C and N.
Mentions: The first five principal components of transcriptional variation in our 31 RNA-Seq samples capture 59% of the total variance in the expression of 8,025 genes. Notably, PC1 (18.9%) was significantly different between the 8 normal and 23 craniosynostosis samples (p<0.0001; Fig. 1A), strongly suggesting that osteoblasts from fused sutures have different gene expression profiles that persist even in cell culture. In contrast, none of the first 5 PC showed any differential expression with respect to location of the synostosis, indicating that there are no gross differences between these traditionally defined sub-classes of non-syndromic disease.

Bottom Line: Similar constellations of sub-types were also observed upon re-analysis of a similar dataset of 199 calvarial osteoblast cultures.Annotation of gene function of differentially expressed transcripts strongly implicates physiological differences with respect to cell cycle and cell death, stromal cell differentiation, extracellular matrix (ECM) components, and ribosomal activity.Based on these results, we propose non-syndromic craniosynostosis cases can be classified by differences in their gene expression patterns and that these may provide targets for future clinical intervention.

View Article: PubMed Central - PubMed

Affiliation: 1. Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, GA, USA.

ABSTRACT
Craniosynostosis, the premature fusion of one or more skull sutures, occurs in approximately 1 in 2500 infants, with the majority of cases non-syndromic and of unknown etiology. Two common reasons proposed for premature suture fusion are abnormal compression forces on the skull and rare genetic abnormalities. Our goal was to evaluate whether different sub-classes of disease can be identified based on total gene expression profiles. RNA-Seq data were obtained from 31 human osteoblast cultures derived from bone biopsy samples collected between 2009 and 2011, representing 23 craniosynostosis fusions and 8 normal cranial bones or long bones. No differentiation between regions of the skull was detected, but variance component analysis of gene expression patterns nevertheless supports transcriptome-based classification of craniosynostosis. Cluster analysis showed 4 distinct groups of samples; 1 predominantly normal and 3 craniosynostosis subtypes. Similar constellations of sub-types were also observed upon re-analysis of a similar dataset of 199 calvarial osteoblast cultures. Annotation of gene function of differentially expressed transcripts strongly implicates physiological differences with respect to cell cycle and cell death, stromal cell differentiation, extracellular matrix (ECM) components, and ribosomal activity. Based on these results, we propose non-syndromic craniosynostosis cases can be classified by differences in their gene expression patterns and that these may provide targets for future clinical intervention.

No MeSH data available.


Related in: MedlinePlus