Genome-wide detection of alternative splicing in expressed sequences using partial order multiple sequence alignment graphs

A statistical method for the detection of alternative splicing using RNA-seq

Deep sequencing of transcriptome (RNA-seq) provides unprecedented opportunity to interrogate plausible mRNA splicing patterns by mapping RNA-seq reads to exon junctions (thereafter junction reads). In most previous studies, exon junctions were detected by using the quantitative information of junction reads. The quantitative criterion (e.g. minimum of two junction reads), although is straightforward and widely used, usually results in high false positive and false negative rates, owning to the complexity of transcriptome. Here, we introduced a new metric, namely Minimal Match on Either Side of exon junction (MMES), to measure the quality of each junction read, and subsequently implemented an empirical statistical model to detect exon junctions. When applied to a large dataset (>200M reads) consisting of mouse brain, liver and muscle mRNA sequences, and using independent transcripts databases as positive control, our method was proved to be considerably more accurate than previous ones, especially for detecting junctions originated from low-abundance transcripts. Our results were also confirmed by real time RT-PCR assay. The MMES metric can be used either in this empirical statistical model or in other more sophisticated classifiers, such as logistic regression.

Deletion of many yeast introns reveals a minority of genes that require splicing for function

Splicing regulates gene expression and contributes to proteomic diversity in higher eukaryotes. However, in yeast only 283 of the 6000 genes contain introns and their impact on cell function is not clear. To assess the contribution of introns to cell function, we initiated large-scale intron deletions in yeast with the ultimate goal of creating an intron-free model eukaryote. We show that about one-third of yeast introns are not essential for growth. Only three intron deletions caused severe growth defects, but normal growth was restored in all cases by expressing the intronless mRNA from a heterologous promoter. Twenty percent of the intron deletions caused minor phenotypes under different growth conditions. Strikingly, the combined deletion of all introns from the 15 cytoskeleton-related genes did not affect growth or strain fitness. Together, our results show that although the presence of introns may optimize gene expression and provide benefit under stress, a majority of introns could be removed with minor consequences on growth under laboratory conditions, supporting the view that many introns could be phased out of Saccharomyces cerevisiae without blocking cell growth.

Depolarization and CaM kinase IV modulate NMDA receptor splicing through two essential RNA elements

Alternative splicing controls the activity of many proteins important for neuronal excitation, but the signal-transduction pathways that affect spliced isoform expression are not well understood. One particularly interesting system of alternative splicing is exon 21 (E21) of the NMDA receptor 1 (NMDAR1 E21), which controls the trafficking of NMDA receptors to the plasma membrane and is repressed by Ca(++)/calmodulin-dependent protein kinase (CaMK) IV signaling. Here, we characterize the splicing of NMDAR1 E21. We find that E21 splicing is reversibly repressed by neuronal depolarization, and we identify two RNA elements within the exon that function together to mediate the inducible repression. One of these exonic elements is similar to an intronic CaMK IV-responsive RNA element (CaRRE) originally identified in the 3' splice site of the BK channel STREX exon, but not previously observed within an exon. The other element is a new RNA motif. Introduction of either of these two motifs, called CaRRE type 1 and CaRRE type 2, into a heterologous constitutive exon can confer CaMK IV-dependent repression on the new exon. Thus, either exonic CaRRE can be sufficient for CaMK IV-induced repression. Single nucleotide scanning mutagenesis defined consensus sequences for these two CaRRE motifs. A genome-wide motif search and subsequent RT-PCR validation identified a group of depolarization-regulated alternative exons carrying CaRRE consensus sequences. Many of these exons are likely to alter neuronal function. Thus, these two RNA elements define a group of co-regulated splicing events that respond to a common stimulus in neurons to alter their activity.

ASPIC: a web resource for alternative splicing prediction and transcript isoforms characterization

Alternative splicing (AS) is now emerging as a major mechanism contributing to the expansion of the transcriptome and proteome complexity of multicellular organisms. The fact that a single gene locus may give rise to multiple mRNAs and protein isoforms, showing both major and subtle structural variations, is an exceptionally versatile tool in the optimization of the coding capacity of the eukaryotic genome. The huge and continuously increasing number of genome and transcript sequences provides an essential information source for the computational detection of genes AS pattern. However, much of this information is not optimally or comprehensively used in gene annotation by current genome annotation pipelines. We present here a web resource implementing the ASPIC algorithm which we developed previously for the investigation of AS of user submitted genes, based on comparative analysis of available transcript and genome data from a variety of species. The ASPIC web resource provides graphical and tabular views of the splicing patterns of all full-length mRNA isoforms compatible with the detected splice sites of genes under investigation as well as relevant structural and functional annotation. The ASPIC web resource—available at —is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility.

ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences

Background:

Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems – hence the need to develop novel strategies.

Results:

We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations.

We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility.

Conclusion:

Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at .