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Tissue-specific splicing factor gene expression signatures.

ABSTRACT: The alternative splicing code that controls and coordinates the transcriptome in complex multicellular organisms remains poorly understood. It has long been argued that regulation of alternative splicing relies on combinatorial interactions between multiple proteins, and that tissue-specific splicing decisions most likely result from differences in the concentration and/or activity of these proteins. However, large-scale data to systematically address this issue have just recently started to become available. Here we show that splicing factor gene expression signatures can be identified that reflect cell type and tissue-specific patterns of alternative splicing. We used a computational approach to analyze microarray-based gene expression profiles of splicing factors from mouse, chimpanzee and human tissues. Our results show that brain and testis, the two tissues with highest levels of alternative splicing events, have the largest number of splicing factor genes that are most highly differentially expressed. We further identified SR protein kinases and small nuclear ribonucleoprotein particle (snRNP) proteins among the splicing factor genes that are most highly differentially expressed in a particular tissue. These results indicate the power of generating signature-based predictions as an initial computational approach into a global view of tissue-specific alternative splicing regulation.

SUBMITTER: Grosso AR

PROVIDER: S-EPMC2528195 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature

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Tissue-specific splicing factor gene expression signatures.

Grosso Ana Rita AR Gomes Anita Q AQ Barbosa-Morais Nuno L NL Caldeira Sandra S Thorne Natalie P NP Grech Godfrey G von Lindern Marieke M Carmo-Fonseca Maria M

Nucleic acids research 20080724 15

The alternative splicing code that controls and coordinates the transcriptome in complex multicellular organisms remains poorly understood. It has long been argued that regulation of alternative splicing relies on combinatorial interactions between multiple proteins, and that tissue-specific splicing decisions most likely result from differences in the concentration and/or activity of these proteins. However, large-scale data to systematically address this issue have just recently started to bec ...[more]

PMID: 18653532

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Project description:IntroductionMeningiomas are the most common primary central nervous system (CNS) tumors in adults, representing approximately one-third of all primary adult CNS tumors. Although several recent publications have proposed alternative grading systems of meningiomas that incorporate genomic and/or epigenomic data to better predict meningioma recurrence and progression-free survival, our understanding of driving forces of meningioma development is still limited.ObjectiveTo define gene expression signatures of the most common subtypes of meningiomas to better understand cellular processes and signaling pathways specific for each tumor genotype.MethodsWe used RNA sequencing (RNA-seq) to determine whole transcriptome profiles of twenty meningiomas with genomic alterations including NF2 inactivation, loss of chr1p, and missense mutations in TRAF7, AKT1 and KLF4.ResultsThe analysis revealed that meningiomas with NF2 gene inactivation expressed higher levels of BCL2 and GLI1 compared with tumors harboring TRAF7 missense mutations. Moreover, NF2 meningiomas were subdivided into two distinct groups based on additional loss of chr1p. NF2 tumors with intact chr1p were characterized by the high expression of tumor suppressor PTCH2 compared to NF2 tumors with chr1p loss. Taken together with the high expression of BCL2 and GLI1, these results suggest that activation of Sonic Hedgehog pathway may contribute to NF2 meningioma development. In contrast, NF2 tumors with chr1p loss expressed high levels of transcription factor FOXD3 and its antisense RNA FOXD3-AS1. Examination of TRAF7 tumors demonstrated that TRAF7 regulates a number of biomechanically responsive genes (KRT6a, KRT16, IL1RL1, and AQP3 among others). Interestingly, AKT1 and KLF4 meningiomas expressed genes specific for PI3K/AKT signaling pathway, suggesting overlapping gene signatures between the two subtypes. In addition, KLF4 meningiomas had high expression of carcinoembryonic antigen family members CEACAM6 and CEACAM5.ConclusionsEach group of meningiomas displayed a unique gene expression signature suggesting signaling pathways potentially implicated in tumorigenesis. These findings will improve our understanding of meningioma tumorigenesis and prognosis.

Dataset Information

Tissue-specific splicing factor gene expression signatures.

Publications

Tissue-specific splicing factor gene expression signatures.

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