Preferential binding of a stable G3BP ribonucleoprotein complex to intron-retaining transcripts in mouse brain and modulation of their expression in the cerebellum

Neuronal granules play an important role in the localization and transport of translationally silenced messenger ribonucleoproteins in neurons. Among the factors associated with these granules, the RNA-binding protein G3BP1 (stress-granules assembly factor) is involved in neuronal plasticity and is induced in Alzheimer's disease. We immunopurified a stable complex containing G3BP1 from mouse brain and performed high-throughput sequencing and cross-linking immunoprecipitation to identify the associated RNAs. The G3BP-complex contained the deubiquitinating protease USP10, CtBP1 and the RNA-binding proteins Caprin-1, G3BP2a and splicing factor proline and glutamine rich, or PSF. The G3BP-complex binds preferentially to transcripts that retain introns, and to non-coding sequences like 3'-untranslated region and long non-coding RNAs. Specific transcripts with retained introns appear to be enriched in the cerebellum compared to the rest of the brain and G3BP1 depletion decreased this intron retention in the cerebellum of G3BP1 knockout mice. Among the enriched transcripts, we found an overrepresentation of genes involved in synaptic transmission, especially glutamate-related neuronal transmission. Notably, G3BP1 seems to repress the expression of the mature Grm5 (metabotropic glutamate receptor 5) transcript, by promoting the retention of an intron in the immature transcript in the cerebellum. Our results suggest that G3BP is involved in a new functional mechanism to regulate non-coding RNAs including intron-retaining transcripts, and thus have broad implications for neuronal gene regulation, where intron retention is widespread.

A new view of transcriptome complexity and regulation through the lens of local splicing variations

Alternative splicing (AS) can critically affect gene function and disease, yet mapping splicing variations remains a challenge. Here, we propose a new approach to define and quantify mRNA splicing in units of local splicing variations (LSVs). LSVs capture previously defined types of alternative splicing as well as more complex transcript variations. Building the first genome wide map of LSVs from twelve mouse tissues, we find complex LSVs constitute over 30% of tissue dependent transcript variations and affect specific protein families. We show the prevalence of complex LSVs is conserved in humans and identify hundreds of LSVs that are specific to brain subregions or altered in Alzheimer's patients. Amongst those are novel isoforms in the Camk2 family and a novel poison exon in Ptbp1, a key splice factor in neurogenesis. We anticipate the approach presented here will advance the ability to relate tissue-specific splice variation to genetic variation, phenotype, and disease.

A semi-supervised approach uncovers thousands of intragenic enhancers differentially activated in human cells

Background

Transcriptional enhancers are generally known to regulate gene transcription from afar. Their activation involves a series of changes in chromatin marks and recruitment of protein factors. These enhancers may also occur inside genes, but how many may be active in human cells and their effects on the regulation of the host gene remains unclear.

Results

We describe a novel semi-supervised method based on the relative enrichment of chromatin signals between 2 conditions to predict active enhancers. We applied this method to the tumoral K562 and the normal GM12878 cell lines to predict enhancers that are differentially active in one cell type. These predictions show enhancer-like properties according to positional distribution, correlation with gene expression and production of enhancer RNAs. Using this model, we predict 10,365 and 9777 intragenic active enhancers in K562 and GM12878, respectively, and relate the differential activation of these enhancers to expression and splicing differences of the host genes.

Conclusions

We propose that the activation or silencing of intragenic transcriptional enhancers modulate the regulation of the host gene by means of a local change of the chromatin and the recruitment of enhancer-related factors that may interact with the RNA directly or through the interaction with RNA binding proteins. Predicted enhancers are available at http://regulatorygenomics.upf.edu/Projects/enhancers.html.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1704-0) contains supplementary material, which is available to authorized users.

AVISPA: a web tool for the prediction and analysis of alternative splicing

Transcriptome complexity and its relation to numerous diseases underpins the need to predict in silico splice variants and the regulatory elements that affect them. Building upon our recently described splicing code, we developed AVISPA, a Galaxy-based web tool for splicing prediction and analysis. Given an exon and its proximal sequence, the tool predicts whether the exon is alternatively spliced, displays tissue-dependent splicing patterns, and whether it has associated regulatory elements. We assess AVISPA's accuracy on an independent dataset of tissue-dependent exons, and illustrate how the tool can be applied to analyze a gene of interest. AVISPA is available at http://avispa.biociphers.org.

Hog1 bypasses stress-mediated down-regulation of transcription by RNA polymerase II redistribution and chromatin remodeling

Background

Cells are subjected to dramatic changes of gene expression upon environmental changes. Stress causes a general down-regulation of gene expression together with the induction of a set of stress-responsive genes. The p38-related stress-activated protein kinase Hog1 is an important regulator of transcription upon osmostress in yeast.

Results

Genome-wide localization studies of RNA polymerase II (RNA Pol II) and Hog1 showed that stress induced major changes in RNA Pol II localization, with a shift toward stress-responsive genes relative to housekeeping genes. RNA Pol II relocalization required Hog1, which was also localized to stress-responsive loci. In addition to RNA Pol II-bound genes, Hog1 also localized to RNA polymerase III-bound genes, pointing to a wider role for Hog1 in transcriptional control than initially expected. Interestingly, an increasing association of Hog1 with stress-responsive genes was strongly correlated with chromatin remodeling and increased gene expression. Remarkably, MNase-Seq analysis showed that although chromatin structure was not significantly altered at a genome-wide level in response to stress, there was pronounced chromatin remodeling for those genes that displayed Hog1 association.

Conclusion

Hog1 serves to bypass the general down-regulation of gene expression that occurs in response to osmostress, and does so both by targeting RNA Pol II machinery and by inducing chromatin remodeling at stress-responsive loci.

Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data

Motivation: High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein–DNA and protein–RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing.

Results: We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics.

Availability: Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxy

Contact:eduardo.eyras@upf.edu

Supplementary Information:Supplementary data are available at Bioinformatics online.