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Splicing factor and exon profiling across human tissues.

de la Grange P, Gratadou L, Delord M, Dutertre M, Auboeuf D - Nucleic Acids Res. (2010)

Bottom Line: It has been shown that alternative splicing is especially prevalent in brain and testis when compared to other tissues.To test whether there is a specific propensity of these tissues to generate splicing variants, we used a single source of high-density microarray data to perform both splicing factor and exon expression profiling across 11 normal human tissues.In addition to providing a unique resource on expression profiling of alternative splicing variants and splicing factors across human tissues, this study demonstrates that the higher prevalence of alternative splicing in a subset of tissues originates from the larger number of genes, including splicing factors, being expressed than in other tissues.

View Article: PubMed Central - PubMed

Affiliation: GenoSplice technology, Centre Hayem, Hôpital Saint-Louis, 1 avenue Claude Vellefaux, 75010, Paris, France. didier.auboeuf@inserm.fr

ABSTRACT
It has been shown that alternative splicing is especially prevalent in brain and testis when compared to other tissues. To test whether there is a specific propensity of these tissues to generate splicing variants, we used a single source of high-density microarray data to perform both splicing factor and exon expression profiling across 11 normal human tissues. Paired comparisons between tissues and an original exon-based statistical group analysis demonstrated after extensive RT-PCR validation that the cerebellum, testis, and spleen had the largest proportion of differentially expressed alternative exons. Variations at the exon level correlated with a larger number of splicing factors being expressed at a high level in the cerebellum, testis and spleen than in other tissues. However, this splicing factor expression profile was similar to a more global gene expression pattern as a larger number of genes had a high expression level in the cerebellum, testis and spleen. In addition to providing a unique resource on expression profiling of alternative splicing variants and splicing factors across human tissues, this study demonstrates that the higher prevalence of alternative splicing in a subset of tissues originates from the larger number of genes, including splicing factors, being expressed than in other tissues.

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Functional consequences of differential exon selection. (A) Biological process. Number of genes presenting differentially regulated exons across tissues and associated with specific biological processes as defined by PANTHER (www.pantherdb.org). Biological process analysis was performed using Bonferroni correction. Statistical significance calculated by comparing splicing-regulated genes to the genome or splicing-regulated genes to transcriptional-regulated genes. (B) RT-PCR analysis. The RT-PCR analyses for the PBRM1 and TCF12 transcriptional factors demonstrated that different spliced isoforms were differentially expressed across analyzed tissues. (C) Successive layers of regulation drive an increasing divergence between tissues. Key transcriptional regulators determine the nature and the number of genes being expressed during cell specialization. Tissues expressing a larger number of genes express a larger number of splicing factors that in turn impact the exon content of the gene products (1). Transcriptional regulators may also affect transcript exon content (1’). As a consequence, the transcriptome differs in terms of both transcript expression level and transcript exon content, resulting in a more diversified proteome (2). Outcomes of differentially expressed exons impinge on a third layer of regulation [(3), the ‘functional proteome’] as there was an enrichment of splicing-regulated genes involved in ‘intracellular protein traffic’ and ‘protein metabolism and modification’. This process may be maintained by impacting on transcriptional regulators (4).
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Figure 7: Functional consequences of differential exon selection. (A) Biological process. Number of genes presenting differentially regulated exons across tissues and associated with specific biological processes as defined by PANTHER (www.pantherdb.org). Biological process analysis was performed using Bonferroni correction. Statistical significance calculated by comparing splicing-regulated genes to the genome or splicing-regulated genes to transcriptional-regulated genes. (B) RT-PCR analysis. The RT-PCR analyses for the PBRM1 and TCF12 transcriptional factors demonstrated that different spliced isoforms were differentially expressed across analyzed tissues. (C) Successive layers of regulation drive an increasing divergence between tissues. Key transcriptional regulators determine the nature and the number of genes being expressed during cell specialization. Tissues expressing a larger number of genes express a larger number of splicing factors that in turn impact the exon content of the gene products (1). Transcriptional regulators may also affect transcript exon content (1’). As a consequence, the transcriptome differs in terms of both transcript expression level and transcript exon content, resulting in a more diversified proteome (2). Outcomes of differentially expressed exons impinge on a third layer of regulation [(3), the ‘functional proteome’] as there was an enrichment of splicing-regulated genes involved in ‘intracellular protein traffic’ and ‘protein metabolism and modification’. This process may be maintained by impacting on transcriptional regulators (4).

Mentions: To test whether the genes bearing differentially expressed exons across tissues were involved in specific biological processes, we performed a functional analysis using the PANTHER software (www.pantherdb.org). The 653 analyzed genes containing differentially expressed exons across tissues (Figure 2A) were enriched for Gene Ontology functional categories, including ‘cell structure and motility’, ‘intracellular protein traffic’, ‘protein targeting and localization’ and ‘protein metabolism and modification’ (Figure 7A). Therefore, the functions of genes products that control the fate and post-translational modifications of proteins may be particularly affected by differential exon selection in a tissue-specific manner. Remarkably, by comparing the genes having a differential expression across tissues (Figure 6D), we observed that ‘cell structure and motility’ and’protein targeting and localization’ were processes enriched in the ‘splicing’ list compared to the ‘transcription’ list. Noteworthy, many alternative splicing events affect protein domains that control the intracellular localization of proteins by deletion/insertion of exons coding for subcellular localization signals (10). Therefore, tissue-specific alternative splicing events may impact the proteome, first by affecting protein domains and second by affecting gene products involved in the control of protein modifications and fate.Figure 7.


Splicing factor and exon profiling across human tissues.

de la Grange P, Gratadou L, Delord M, Dutertre M, Auboeuf D - Nucleic Acids Res. (2010)

Functional consequences of differential exon selection. (A) Biological process. Number of genes presenting differentially regulated exons across tissues and associated with specific biological processes as defined by PANTHER (www.pantherdb.org). Biological process analysis was performed using Bonferroni correction. Statistical significance calculated by comparing splicing-regulated genes to the genome or splicing-regulated genes to transcriptional-regulated genes. (B) RT-PCR analysis. The RT-PCR analyses for the PBRM1 and TCF12 transcriptional factors demonstrated that different spliced isoforms were differentially expressed across analyzed tissues. (C) Successive layers of regulation drive an increasing divergence between tissues. Key transcriptional regulators determine the nature and the number of genes being expressed during cell specialization. Tissues expressing a larger number of genes express a larger number of splicing factors that in turn impact the exon content of the gene products (1). Transcriptional regulators may also affect transcript exon content (1’). As a consequence, the transcriptome differs in terms of both transcript expression level and transcript exon content, resulting in a more diversified proteome (2). Outcomes of differentially expressed exons impinge on a third layer of regulation [(3), the ‘functional proteome’] as there was an enrichment of splicing-regulated genes involved in ‘intracellular protein traffic’ and ‘protein metabolism and modification’. This process may be maintained by impacting on transcriptional regulators (4).
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Figure 7: Functional consequences of differential exon selection. (A) Biological process. Number of genes presenting differentially regulated exons across tissues and associated with specific biological processes as defined by PANTHER (www.pantherdb.org). Biological process analysis was performed using Bonferroni correction. Statistical significance calculated by comparing splicing-regulated genes to the genome or splicing-regulated genes to transcriptional-regulated genes. (B) RT-PCR analysis. The RT-PCR analyses for the PBRM1 and TCF12 transcriptional factors demonstrated that different spliced isoforms were differentially expressed across analyzed tissues. (C) Successive layers of regulation drive an increasing divergence between tissues. Key transcriptional regulators determine the nature and the number of genes being expressed during cell specialization. Tissues expressing a larger number of genes express a larger number of splicing factors that in turn impact the exon content of the gene products (1). Transcriptional regulators may also affect transcript exon content (1’). As a consequence, the transcriptome differs in terms of both transcript expression level and transcript exon content, resulting in a more diversified proteome (2). Outcomes of differentially expressed exons impinge on a third layer of regulation [(3), the ‘functional proteome’] as there was an enrichment of splicing-regulated genes involved in ‘intracellular protein traffic’ and ‘protein metabolism and modification’. This process may be maintained by impacting on transcriptional regulators (4).
Mentions: To test whether the genes bearing differentially expressed exons across tissues were involved in specific biological processes, we performed a functional analysis using the PANTHER software (www.pantherdb.org). The 653 analyzed genes containing differentially expressed exons across tissues (Figure 2A) were enriched for Gene Ontology functional categories, including ‘cell structure and motility’, ‘intracellular protein traffic’, ‘protein targeting and localization’ and ‘protein metabolism and modification’ (Figure 7A). Therefore, the functions of genes products that control the fate and post-translational modifications of proteins may be particularly affected by differential exon selection in a tissue-specific manner. Remarkably, by comparing the genes having a differential expression across tissues (Figure 6D), we observed that ‘cell structure and motility’ and’protein targeting and localization’ were processes enriched in the ‘splicing’ list compared to the ‘transcription’ list. Noteworthy, many alternative splicing events affect protein domains that control the intracellular localization of proteins by deletion/insertion of exons coding for subcellular localization signals (10). Therefore, tissue-specific alternative splicing events may impact the proteome, first by affecting protein domains and second by affecting gene products involved in the control of protein modifications and fate.Figure 7.

Bottom Line: It has been shown that alternative splicing is especially prevalent in brain and testis when compared to other tissues.To test whether there is a specific propensity of these tissues to generate splicing variants, we used a single source of high-density microarray data to perform both splicing factor and exon expression profiling across 11 normal human tissues.In addition to providing a unique resource on expression profiling of alternative splicing variants and splicing factors across human tissues, this study demonstrates that the higher prevalence of alternative splicing in a subset of tissues originates from the larger number of genes, including splicing factors, being expressed than in other tissues.

View Article: PubMed Central - PubMed

Affiliation: GenoSplice technology, Centre Hayem, Hôpital Saint-Louis, 1 avenue Claude Vellefaux, 75010, Paris, France. didier.auboeuf@inserm.fr

ABSTRACT
It has been shown that alternative splicing is especially prevalent in brain and testis when compared to other tissues. To test whether there is a specific propensity of these tissues to generate splicing variants, we used a single source of high-density microarray data to perform both splicing factor and exon expression profiling across 11 normal human tissues. Paired comparisons between tissues and an original exon-based statistical group analysis demonstrated after extensive RT-PCR validation that the cerebellum, testis, and spleen had the largest proportion of differentially expressed alternative exons. Variations at the exon level correlated with a larger number of splicing factors being expressed at a high level in the cerebellum, testis and spleen than in other tissues. However, this splicing factor expression profile was similar to a more global gene expression pattern as a larger number of genes had a high expression level in the cerebellum, testis and spleen. In addition to providing a unique resource on expression profiling of alternative splicing variants and splicing factors across human tissues, this study demonstrates that the higher prevalence of alternative splicing in a subset of tissues originates from the larger number of genes, including splicing factors, being expressed than in other tissues.

Show MeSH
Related in: MedlinePlus