RNAmotifs: prediction of multivalent RNA motifs that control alternative splicing

Cereda, Matteo; Pozzoli, Uberto; Rot, Gregor; Juvan, Peter; Schweitzer, Anthony; Clark, Tyson A.; Ule, Jernej

doi:10.1186/gb-2014-15-1-r20

Cited by 53 publications

(75 citation statements)

References 41 publications

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“…The separation of the antagonistic cis-elements enables nSR100 binding to overcome Ptbp1-mediated repression, facilitating rapid switch-like changes in inclusion levels of target exons. Comparison of RNA splicing maps revealed similar opposing regulatory relationships between Ptbp1 and Nova proteins (Cereda et al, 2014) and between Ptbp1 and Rbfox proteins ( Figure 1B) (Li et al, 2015). In contrast to the aforementioned antagonistic activities, a subset of Novadependent exons is also synergistically regulated by Rbfox ( Figure 1B) (Zhang et al, 2010).…”

Section: Combinatorial Action Of Trans-factors Regulates Neural Splicmentioning

confidence: 87%

“…It is worth noting that analyses of CLIP-Seq data are subject to technical challenges associated with nucleotide crosslinking biases, unique mapping of short reads, and the abundance of target transcripts. Establishing RNA splicing maps using computational approaches is therefore a valuable complementary approach because it can also be used to analyze sets of splicing events associated with specific motifs or transcripts (i.e., those of low abundance) that are not amenable to detection by CLIP-Seq procedures (Barash et al, 2010;Cereda et al, 2014;Raj et al, 2014;Xiong et al, 2015;Zhang et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Alternative Splicing in the Mammalian Nervous System: Recent Insights into Mechanisms and Functional Roles

Raj

Blencowe

2015

Neuron

421

392

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High-throughput transcriptomic profiling approaches have revealed that alternative splicing (AS) of precursor mRNAs, a fundamental process by which cells expand their transcriptomic diversity, is particularly widespread in the nervous system. AS events detected in the brain are more highly conserved than those detected in other tissues, suggesting that they more often provide conserved functions. Our understanding of the mechanisms and functions of neural AS events has significantly advanced with the coupling of various computational and experimental approaches. These studies indicate that dynamic regulation of AS in the nervous system is critical for modulating protein-protein interactions, transcription networks, and multiple aspects of neuronal development. Furthermore, several underappreciated classes of AS with the aforementioned roles in neuronal cells have emerged from unbiased, global approaches. Collectively, these findings emphasize the importance of characterizing neural AS in order to gain new insight into pathways that may be altered in neurological diseases and disorders.

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Section: Combinatorial Action Of Trans-factors Regulates Neural Splicmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Alternative Splicing in the Mammalian Nervous System: Recent Insights into Mechanisms and Functional Roles

Raj

Blencowe

2015

Neuron

421

392

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“…Recently, Cereda et al. (26) have developed RNAmotifs for predicting de-novo clusters of RNA motifs that control alternative splicing. Zhang et al.…”

Section: Introductionmentioning

confidence: 99%

RBPmap: a web server for mapping binding sites of RNA-binding proteins

Paz

Kosti

Ares

et al. 2014

Nucleic Acids Research

451

395

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Regulation of gene expression is executed in many cases by RNA-binding proteins (RBPs) that bind to mRNAs as well as to non-coding RNAs. RBPs recognize their RNA target via specific binding sites on the RNA. Predicting the binding sites of RBPs is known to be a major challenge. We present a new webserver, RBPmap, freely accessible through the website http://rbpmap.technion.ac.il/ for accurate prediction and mapping of RBP binding sites. RBPmap has been developed specifically for mapping RBPs in human, mouse and Drosophila melanogaster genomes, though it supports other organisms too. RBPmap enables the users to select motifs from a large database of experimentally defined motifs. In addition, users can provide any motif of interest, given as either a consensus or a PSSM. The algorithm for mapping the motifs is based on a Weighted-Rank approach, which considers the clustering propensity of the binding sites and the overall tendency of regulatory regions to be conserved. In addition, RBPmap incorporates a position-specific background model, designed uniquely for different genomic regions, such as splice sites, 5’ and 3’ UTRs, non-coding RNA and intergenic regions. RBPmap was tested on high-throughput RNA-binding experiments and was proved to be highly accurate.

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“…In human and mouse, several computational tools have been developed to integrate protein-RNA binding data with splicing patterns to define the splicing code [15], including tissue-specific splicing code [16], and to infer co-splicing networks for specific regulatory SFs (e.g., NOVA [17]). Computational pipelines have been implemented to identify conserved RNA-binding motifs for individual RBPs using these types of data [18, 19]. Since direct protein-RNA binding data is lacking for other organisms [4, 20], computational tools are needed that can systematically identify putative SFs, predict RNA-binding sites for the corresponding pre-mRNA targets of SFs of interest, and infer global networks of co-spliced product transcripts.…”

Section: Introductionmentioning

confidence: 99%

CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

Aghamirzaie

Collakova

et al. 2016

BMC Genomics

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BackgroundAlternative splicing has been proposed to increase transcript diversity and protein plasticity in eukaryotic organisms, but the extent to which this is the case is currently unclear, especially with regard to the diversification of molecular function. Eukaryotic splicing involves complex interactions of splicing factors and their targets. Inference of co-splicing networks capturing these types of interactions is important for understanding this crucial, highly regulated post-transcriptional process at the systems level.ResultsFirst, several transcript and protein attributes, including coding potential of transcripts and differences in functional domains of proteins, were compared between splice variants and protein isoforms to assess transcript and protein diversity in a biological system. Alternative splicing was shown to increase transcript and function-related protein diversity in developing Arabidopsis embryos. Second, CoSpliceNet, which integrates co-expression and motif discovery at splicing regulatory regions to infer co-splicing networks, was developed. CoSpliceNet was applied to temporal RNA sequencing data to identify candidate regulators of splicing events and predict RNA-binding motifs, some of which are supported by prior experimental evidence. Analysis of inferred splicing factor targets revealed an unexpected role for the unfolded protein response in embryo development.ConclusionsThe methods presented here can be used in any biological system to assess transcript diversity and protein plasticity and to predict candidate regulators, their targets, and RNA-binding motifs for splicing factors. CoSpliceNet is freely available at http://delasa.github.io/co-spliceNet/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3172-6) contains supplementary material, which is available to authorized users.

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RNAmotifs: prediction of multivalent RNA motifs that control alternative splicing

Cited by 53 publications

References 41 publications

Alternative Splicing in the Mammalian Nervous System: Recent Insights into Mechanisms and Functional Roles

Alternative Splicing in the Mammalian Nervous System: Recent Insights into Mechanisms and Functional Roles

RBPmap: a web server for mapping binding sites of RNA-binding proteins

CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

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