Muscleblind proteins regulate alternative splicing

Although the muscleblind (MBNL) protein family has been implicated in myotonic dystrophy (DM), a specific function for these proteins has not been reported. A key feature of the RNA-mediated pathogenesis model for DM is the disrupted splicing of specific pre-mRNA targets. Here we demonstrate that MBNL proteins regulate alternative splicing of two pre-mRNAs that are misregulated in DM, cardiac troponin T (cTNT) and insulin receptor (IR). Alternative cTNT and IR exons are also regulated by CELF proteins, which were previously implicated in DM pathogenesis. MBNL proteins promote opposite splicing patterns for cTNT and IR alternative exons, both of which are antagonized by CELF proteins. CELF- and MBNL-binding sites are distinct and regulation by MBNL does not require the CELF-binding site. The results are consistent with a mechanism for DM pathogenesis in which expanded repeats cause a loss of MBNL and/or gain of CELF activities, leading to misregulation of alternative splicing of specific pre-mRNA targets.     

Bioinformatics analysis of alternative splicing

Over the past few years, the analysis of alternative splicing using bioinformatics has emerged as an important new field, and has significantly changed our view of genome function. One exciting front has been the analysis of microarray data to measure alternative splicing genome-wide. Pioneering studies of both human and mouse data have produced algorithms for discerning evidence of alternative splicing and clustering genes and samples by their alternative splicing patterns. Moreover, these data indicate the presence of alternative splice forms in up to 80 per cent of human genes. Comparative genomics studies in both mammals and insects have demonstrated that alternative splicing can in some cases be predicted directly from comparisons of genome sequences, based on heightened sequence conservation and exon length. Such studies have also provided new insights into the connection between alternative splicing and a variety of evolutionary processes such as Alu-based exonisation, exon creation and loss. A number of groups have used a combination of bioinformatics, comparative genomics and experimental validation to identify new motifs for splice regulatory factors, analyse the balance of factors that regulate alternative splicing, and propose a new mechanism for regulation based on the interaction of alternative splicing and nonsense-mediated decay. Bioinformatics studies of the functional impact of alternative splicing have revealed a wide range of regulatory mechanisms, from NAGNAG sites that add a single amino acid; to short peptide segments that can play surprisingly complex roles in switching protein conformation and function (as in the Piccolo C2A domain); to events that entirely remove a specific protein interaction domain or membrane anchoring domain. Common to many bioinformatics studies is a new emphasis on graph representations of alternative splicing structures, which have many advantages for analysis.     

Epigenetics in alternative pre-mRNA splicing

Alternative splicing plays critical roles in differentiation, development, and disease and is a major source for protein diversity in higher eukaryotes. Analysis of alternative splicing regulation has traditionally focused on RNA sequence elements and their associated splicing factors, but recent provocative studies point to a key function of chromatin structure and histone modifications in alternative splicing regulation. These insights suggest that epigenetic regulation determines not only what parts of the genome are expressed but also how they are spliced.     

RBM10 regulates alternative splicing

RBM10, originally called S1-1, is a nuclear RNA-binding protein with domains characteristic of RNA processing proteins. It has been reported that RBM10 constitutes spliceosome complexes and that RBM5, a close homologue of RBM10, regulates alternative splicing of apoptosis-related genes, Fas and cFLIP. In this study, we examined whether RBM10 has a regulatory function in splicing similar to RBM5, and determined that it indeed regulates alternative splicing of Fas and Bcl-x genes. RBM10 promotes exon skipping of Fas pre-mRNA as well as selection of an internal 5′-splice site in Bcl-x pre-mRNA. We propose a consensus RBM10-binding sequence at 5′-splice sites of target exons and a mechanistic model of RBM10 action in the alternative splicing.     

Rbm20 regulates titin alternative splicing as a splicing repressor

Titin, a sarcomeric protein expressed primarily in striated muscles, is responsible for maintaining the structure and biomechanical properties of muscle cells. Cardiac titin undergoes developmental size reduction from 3.7 megadaltons in neonates to primarily 2.97 megadaltons in the adult. This size reduction results from gradually increased exon skipping between exons 50 and 219 of titin mRNA. Our previous study reported that Rbm20 is the splicing factor responsible for this process. In this work, we investigated its molecular mechanism. We demonstrate that Rbm20 mediates exon skipping by binding to titin pre-mRNA to repress the splicing of some regions; the exons/introns in these Rbm20-repressed regions are ultimately skipped. Rbm20 was also found to mediate intron retention and exon shuffling. The two Rbm20 speckles found in nuclei from muscle tissues were identified as aggregates of Rbm20 protein on the partially processed titin pre-mRNAs. Cooperative repression and alternative 3′ splice site selection were found to be used by Rbm20 to skip different subsets of titin exons, and the splicing pathway selected depended on the ratio of Rbm20 to other splicing factors that vary with tissue type and developmental age.     

Accurate prediction of NAGNAG alternative splicing

Alternative splicing (AS) involving NAGNAG tandem acceptors is an evolutionarily widespread class of AS. Recent predictions of alternative acceptor usage reported better results for acceptors separated by larger distances, than for NAGNAGs. To improve the latter, we aimed at the use of Bayesian networks (BN), and extensive experimental validation of the predictions. Using carefully constructed training and test datasets, a balanced sensitivity and specificity of ≥92% was achieved. A BN trained on the combined dataset was then used to make predictions, and 81% (38/47) of the experimentally tested predictions were verified. Using a BN learned on human data on six other genomes, we show that while the performance for the vertebrate genomes matches that achieved on human data, there is a slight drop for Drosophila and worm. Lastly, using the prediction accuracy according to experimental validation, we estimate the number of yet undiscovered alternative NAGNAGs. State of the art classifiers can produce highly accurate prediction of AS at NAGNAGs, indicating that we have identified the major features of the ‘NAGNAG-splicing code’ within the splice site and its immediate neighborhood. Our results suggest that the mechanism behind NAGNAG AS is simple, stochastic, and conserved among vertebrates and beyond.