Dataset Information

Large scale study of protein domain distribution in the context of alternative splicing.

ABSTRACT: Alternative splicing plays an important role in processes such as development, differentiation and cancer. With the recent increase in the estimates of the number of human genes that undergo alternative splicing from 5 to 35-59%, it is becoming critical to develop a better understanding of its functional consequences and regulatory mechanisms. We conducted a large scale study of the distribution of protein domains in a curated data set of several thousand genes and identified protein domains disproportionately distributed among alternatively spliced genes. We also identified a number of protein domains that tend to be spliced out. Both the proteins having the disproportionately distributed domains as well as those with spliced-out domains are predominantly involved in the processes of cell communication, signaling, development and apoptosis. These proteins function mostly as enzymes, signal transducers and receptors. Somewhat surprisingly, 28% of all occurrences of spliced-out domains are not effected by straightforward exclusion of exons coding for the domains but by inclusion or exclusion of other exons to shift the reading frame while retaining the exons coding for the domains in the final transcripts.

SUBMITTER: Liu S

PROVIDER: S-EPMC169920 | biostudies-literature | 2003 Aug

REPOSITORIES: biostudies-literature

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Large scale study of protein domain distribution in the context of alternative splicing.

Liu Shuo S Altman Russ B RB

Nucleic acids research 20030801 16

Alternative splicing plays an important role in processes such as development, differentiation and cancer. With the recent increase in the estimates of the number of human genes that undergo alternative splicing from 5 to 35-59%, it is becoming critical to develop a better understanding of its functional consequences and regulatory mechanisms. We conducted a large scale study of the distribution of protein domains in a curated data set of several thousand genes and identified protein domains dis ...[more]

PMID: 12907725

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Project description:BackgroundMultiple Sclerosis (MS) is an autoimmune neurodegenerative disease affecting approximately 3 million people globally. Despite rigorous research on MS, aspects of its development and progression remain unclear. Understanding molecular mechanisms underlying MS is crucial to providing insights into disease pathways, identifying potential biomarkers for early diagnosis, and revealing novel therapeutic targets for improved patient outcomes.MethodsWe utilized publicly available RNA-seq data (GSE138614) from post-mortem white matter tissues of five donors without any neurological disorder and ten MS patient donors. This data was interrogated for differential gene expression, alternative splicing and single nucleotide variants as well as for functional enrichments in the resulting datasets.ResultsA comparison of non-MS white matter (WM) to MS samples yielded differentially expressed genes involved in adaptive immune response, cell communication, and developmental processes. Genes with expression changes positively correlated with tissue inflammation were enriched in the immune system and receptor interaction pathways. Negatively correlated genes were enriched in neurogenesis, nervous system development, and metabolic pathways. Alternatively spliced transcripts between WM and MS lesions included genes that play roles in neurogenesis, myelination, and oligodendrocyte differentiation, such as brain enriched myelin associated protein (BCAS1), discs large MAGUK scaffold protein 1 (DLG1), KH domain containing RNA binding (QKI), and myelin basic protein (MBP). Our approach to comparing normal appearing WM (NAWM) and active lesion (AL) from one donor and NAWM and chronic active (CA) tissues from two donors, showed that different IgH and IgK gene subfamilies were differentially expressed. We also identified pathways involved in white matter injury repair and remyelination in these tissues. Differentially spliced genes between these lesions were involved in axon and dendrite structure stability. We also identified exon skipping events and spontaneous single nucleotide polymorphisms in membrane associated ring-CH-type finger 1 (MARCHF1), UDP glycosyltransferase 8 (UGT8), and other genes important in autoimmunity and neurodegeneration.ConclusionOverall, we identified unique genes, pathways, and novel splicing events affecting disease progression that can be further investigated as potential novel drug targets for MS treatment.

Project description:BackgroundAlternative splicing (AS), as a potent and pervasive mechanism of transcriptional regulatory, expands the genome's coding capacity and involves in the initiation and progression of cancer. Systematic analysis of alternative splicing in colorectal cancer (CRC) is lacking and greatly needed.MethodsRNA-Seq data and corresponding clinical information of CRC cohort were downloaded from the TCGA data portal. Then, a java application, known as SpliceSeq, was used to evaluate the RNA splicing patterns and calculate the Percent Spliced In (PSI) value. Differently expressed AS events (DEAS) were identified based on PSI value between paired CRC and adjacent tissues. DEAS and its splicing networks were further analyzed by bioinformatics methods. Kaplan-Meier, Cox proportional regression and unsupervised clustering analysis were used to evaluate the association between DEAS and patients' clinical features.ResultsAfter strict filtering, a total of 34,334 AS events were identified, among which 421 AS events were found expressed differently. Parent genes of these DEAS play a important role in regulating CRC-related processes such as protein kinase activity (FDR<0.0001), PI3K-Akt signaling pathway (FDR?=?0.0024) and p53 signaling pathway (FDR?=?0.0143). 37 DEAS events were found to be associated with OS, and 68 DEAS events were found to be associated with DFS. Stratifying patients according to the PSI value of AT in CXCL12 and RI in CSTF3 formed significant Kaplan-Meier curves in both OS and DFS survival analysis. Unsupervised clustering analysis using DEAS revealed four clusters with distinct survival patterns, and associated with consensus molecular subtypes.ConclusionsLarge differences of AS events in CRC appear to exist, and these differences are likely to be important determinants of both prognosis and biological regulation. Our identified CRC-related AS events and uncovered splicing networks are valuable in deciphering the underlying mechanisms of AS in CRC, and provide clues of therapeutic targets to further validations.

Project description:Several genome-wide studies demonstrated that alternative splicing (AS) significantly increases the transcriptome complexity in plants. However, the impact of AS on the functional diversity of proteins is difficult to assess using genome-wide approaches. The availability of detailed sequence annotations for specific genes and gene families allows for a more detailed assessment of the potential effect of AS on their function. One example is the plant MADS-domain transcription factor family, members of which interact to form protein complexes that function in transcription regulation. Here, we perform an in silico analysis of the potential impact of AS on the protein-protein interaction capabilities of MIKC-type MADS-domain proteins. We first confirmed the expression of transcript isoforms resulting from predicted AS events. Expressed transcript isoforms were considered functional if they were likely to be translated and if their corresponding AS events either had an effect on predicted dimerisation motifs or occurred in regions known to be involved in multimeric complex formation, or otherwise, if their effect was conserved in different species. Nine out of twelve MIKC MADS-box genes predicted to produce multiple protein isoforms harbored putative functional AS events according to those criteria. AS events with conserved effects were only found at the borders of or within the K-box domain. We illustrate how AS can contribute to the evolution of interaction networks through an example of selective inclusion of a recently evolved interaction motif in the MADS AFFECTING FLOWERING1-3 (MAF1-3) subclade. Furthermore, we demonstrate the potential effect of an AS event in SHORT VEGETATIVE PHASE (SVP), resulting in the deletion of a short sequence stretch including a predicted interaction motif, by overexpression of the fully spliced and the alternatively spliced SVP transcripts. For most of the AS events we were able to formulate hypotheses about the potential impact on the interaction capabilities of the encoded MIKC proteins.

Project description:Purpose: Alternative splicing (AS) was reported to play a vital role in development and progression of glioblastoma (GBM), the most common and fatal brain tumor. Systematic analysis of survival-associated AS event profiles and prognostic prediction model based on multiple AS events in GBM was needed. Methods: Genome-wide AS and RNA sequencing profiles were generated in 152 patients with GBM in the cancer genome atlas (TCGA). Prognosis-associated AS events were screened by integrated Cox regression analysis to construct the prognostic risk score model in the training cohort (n = 101). The AS-based signature and clinicopathologic parameters were applied to construct a prognostic nomogram for 0.5-, 1-, and 3-year OS prediction. Finally, the regulatory networks between prognostic AS events and splicing factors (SFs) were constructed. Results: A total of 1,598 prognosis-related AS events from 1,183 source genes were determined. Eight prognostic risk score model based on integrated AS events and 7 AS types were established, respectively. Concordance index (C-index) and receiver operating characteristic (ROC) curve analysis demonstrated powerful ability in distinguishing patients' outcomes. Only Alternate Donor site (AD) and Exon Skip (ES) signature out of the eight types of AS signature were identified as independent prognostic factors for GBM, which was validated in the internal validation cohort. The nomogram with age, new event, pharmaceutical therapy, radiation therapy, AD signature and ES signature were constructed, with C-index of 0.892 (95% CI, 0.853-0.931; P = 5.13 × 10-15). Calibration plots, ROC, and decision curve analysis suggested excellent predictive performance for the nomogram in both TCGA training cohort and validation cohort. Splicing network indicated distinguished correlations between prognostic AS events and SFs in GBM patients. Conclusions: AS-based prediction model could serve as a promising prognostic predictor and potential therapeutic target for GBM, facilitating better treatment strategies in clinical practice.

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Large scale study of protein domain distribution in the context of alternative splicing.

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Large scale study of protein domain distribution in the context of alternative splicing.

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