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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

Volcano plots contrasting gene expression in clusters of samples. Each plot indicates the significance on the y-axis (negative log P) against the magnitude differential expression on the log2 scale. Each gene is indicated by a circle, and the q-value 5% FDR cutoff is indicated by the horizontal line at NLP 2.64 for the comparisons of the craniosynostosis clusters in (A) through (C). Plot (D) contrasts normal and all craniosynostosis samples, and is drawn to a different scale since the differentiation of some genes is much stronger.
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Figure 3: Volcano plots contrasting gene expression in clusters of samples. Each plot indicates the significance on the y-axis (negative log P) against the magnitude differential expression on the log2 scale. Each gene is indicated by a circle, and the q-value 5% FDR cutoff is indicated by the horizontal line at NLP 2.64 for the comparisons of the craniosynostosis clusters in (A) through (C). Plot (D) contrasts normal and all craniosynostosis samples, and is drawn to a different scale since the differentiation of some genes is much stronger.

Mentions: Having identified three subgroups of craniosynostosis samples, we next used ANOVA to identify genes that were differentially expressed relative to normal osteoblasts and genes differentially expressed between the sub-groups. Differential expression is visualized as volcano plots (Fig. 3A-D) showing the significance (negative logarithm of the p-value, NLP) on the y-axis, relative to the difference in transcript abundance on the x-axis. Fig. 3D confirms that the greatest differentiation (1768 genes at a FDR of 10%) is observed between the normal samples and the craniosynostosis samples consistent with the clustering analysis. Genes more highly expressed in craniosynostosis osteoblast cultures than in cultures of normal osteoblasts are to the right and genes down regulated in comparison are to the left, with high significance to the top. Note the difference in scale of the y-axis compared with 3A-C.


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)

Volcano plots contrasting gene expression in clusters of samples. Each plot indicates the significance on the y-axis (negative log P) against the magnitude differential expression on the log2 scale. Each gene is indicated by a circle, and the q-value 5% FDR cutoff is indicated by the horizontal line at NLP 2.64 for the comparisons of the craniosynostosis clusters in (A) through (C). Plot (D) contrasts normal and all craniosynostosis samples, and is drawn to a different scale since the differentiation of some genes is much stronger.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4150121&req=5

Figure 3: Volcano plots contrasting gene expression in clusters of samples. Each plot indicates the significance on the y-axis (negative log P) against the magnitude differential expression on the log2 scale. Each gene is indicated by a circle, and the q-value 5% FDR cutoff is indicated by the horizontal line at NLP 2.64 for the comparisons of the craniosynostosis clusters in (A) through (C). Plot (D) contrasts normal and all craniosynostosis samples, and is drawn to a different scale since the differentiation of some genes is much stronger.
Mentions: Having identified three subgroups of craniosynostosis samples, we next used ANOVA to identify genes that were differentially expressed relative to normal osteoblasts and genes differentially expressed between the sub-groups. Differential expression is visualized as volcano plots (Fig. 3A-D) showing the significance (negative logarithm of the p-value, NLP) on the y-axis, relative to the difference in transcript abundance on the x-axis. Fig. 3D confirms that the greatest differentiation (1768 genes at a FDR of 10%) is observed between the normal samples and the craniosynostosis samples consistent with the clustering analysis. Genes more highly expressed in craniosynostosis osteoblast cultures than in cultures of normal osteoblasts are to the right and genes down regulated in comparison are to the left, with high significance to the top. Note the difference in scale of the y-axis compared with 3A-C.

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