Profiling age and body fluid DNA methylation markers using nanopore adaptive sampling

DNA methylation plays essential roles in regulating physiological processes, from tissue and organ development to gene expression and aging processes and has emerged as a widely used biomarker for the identification of body fluids and age prediction. Currently, methylation markers are targeted independently at specific CpG sites as part of a multiplexed assay rather than through a unified assay. Methylation detection is also dependent on divergent methodologies, ranging from enzyme digestion and affinity enrichment to bisulfite treatment, alongside various technologies for high-throughput profiling, including microarray and sequencing. In this pilot study, we test the simultaneous identification of age-associated and body fluid-specific methylation markers using a single technology, nanopore adaptive sampling. This innovative approach enables the profiling of multiple CpG marker sites across entire gene regions from a single sample without the need for specialized DNA preparation or additional biochemical treatments. Our study demonstrates that adaptive sampling achieves sufficient coverage in regions of interest to accurately determine the methylation status, shows a robust consistency with whole-genome bisulfite sequencing data, and corroborates known CpG markers of age and body fluids. Our work also resulted in the identification of new sites strongly correlated with age, suggesting new possible age methylation markers. This study lays the groundwork for the systematic development of nanopore-based methodologies in both age prediction and body fluid identification, highlighting the feasibility and potential of nanopore adaptive sampling while acknowledging the need for further validation and expansion in future research.

Integrative single-cell expression and functional studies unravels a sensitization to cytarabine-based chemotherapy through HIF pathway inhibition in AML leukemia stem cells

Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML) and is driven by rare therapy-resistant leukemia stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling maintains cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to the chemoresistance of AML-LSCs and may represent a therapeutic target to sensitize AML-LSCs to chemotherapy. Here, we identify HIFhigh and HIFlow specific AML subgroups (inv(16)/t(8;21) and MLLr, respectively) and provide a comprehensive single-cell expression atlas of 119,000 AML cells and AML-LSCs in paired diagnostic-relapse samples from these molecular subgroups. The HIF/hypoxia pathway signature is attenuated in AML-LSCs compared with more differentiated AML cells but is more expressed than in healthy hematopoietic cells. Importantly, chemical inhibition of HIF cooperates with standard-of-care chemotherapy to impair AML growth and to substantially eliminate AML-LSCs in vitro and in vivo. These findings support the HIF pathway in the stem cell-driven drug resistance of AML and unravel avenues for combinatorial targeted and chemotherapy-based approaches to specifically eliminate AML-LSCs.

Formation of an invasion-permissive matrix requires TGFβ/SNAIL1-regulated alternative splicing of fibronectin

BACKGROUND

As in most solid cancers, the emergence of cells with oncogenic mutations in the mammary epithelium alters the tissue homeostasis. Some soluble factors, such as TGFβ, potently modify the behavior of healthy stromal cells. A subpopulation of cancer-associated fibroblasts expressing a TGFβ target, the SNAIL1 transcription factor, display myofibroblastic abilities that rearrange the stromal architecture. Breast tumors with the presence of SNAIL1 in the stromal compartment, and with aligned extracellular fiber, are associated with poor survival prognoses.

METHODS

We used deep RNA sequencing and biochemical techniques to study alternative splicing and human tumor databases to test for associations (correlation t-test) between SNAIL1 and fibronectin isoforms. Three-dimensional extracellular matrices generated from fibroblasts were used to study the mechanical properties and actions of the extracellular matrices on tumor cell and fibroblast behaviors. A metastatic mouse model of breast cancer was used to test the action of fibronectin isoforms on lung metastasis.

RESULTS

In silico studies showed that SNAIL1 correlates with the expression of the extra domain A (EDA)-containing (EDA+) fibronectin in advanced human breast cancer and other types of epithelial cancers. In TGFβ-activated fibroblasts, alternative splicing of fibronectin as well as of 500 other genes was modified by eliminating SNAIL1. Biochemical analyses demonstrated that SNAIL1 favors the inclusion of the EDA exon by modulating the activity of the SRSF1 splicing factor. Similar to Snai1 knockout fibroblasts, EDA- fibronectin fibroblasts produce an extracellular matrix  that does not sustain TGFβ-induced fiber organization, rigidity, fibroblast activation, or tumor cell invasion. The presence of EDA+ fibronectin changes the action of metalloproteinases on fibronectin fibers. Critically, in an mouse orthotopic breast cancer model, the absence of the fibronectin EDA domain completely prevents lung metastasis.

CONCLUSIONS

Our results support the requirement of EDA+ fibronectin in the generation of a metastasis permissive stromal architecture in breast cancers and its molecular control by SNAIL1. From a pharmacological point of view, specifically blocking EDA+ fibronectin deposition could be included in studies to reduce the formation of a pro-metastatic environment.

Hepatitis B virus serum RNA transcript isoform composition and proportion in chronic hepatitis B patients by nanopore long-read sequencing

Introduction

Serum hepatitis B virus (HBV) RNA is a promising new biomarker to manage and predict clinical outcomes of chronic hepatitis B (CHB) infection. However, the HBV serum transcriptome within encapsidated particles, which is the biomarker analyte measured in serum, remains poorly characterized. This study aimed to evaluate serum HBV RNA transcript composition and proportionality by PCR-cDNA nanopore sequencing of samples from CHB patients having varied HBV genotype (gt, A to F) and HBeAg status.

Methods

Longitudinal specimens from 3 individuals during and following pregnancy (approximately 7 months between time points) were also investigated. HBV RNA extracted from 16 serum samples obtained from 13 patients (73.3% female, 84.6% Asian) was sequenced and serum HBV RNA isoform detection and quantification were performed using three bioinformatic workflows; FLAIR, RATTLE, and a GraphMap-based workflow within the Galaxy application. A spike-in RNA variant (SIRV) control mix was used to assess run quality and coverage. The proportionality of transcript isoforms was based on total HBV reads determined by each workflow.

Results

All chosen isoform detection workflows showed high agreement in transcript proportionality and composition for most samples. HBV pregenomic RNA (pgRNA) was the most frequently observed transcript isoform (93.8% of patient samples), while other detected transcripts included pgRNA spliced variants, 3' truncated variants and HBx mRNA, depending on the isoform detection method. Spliced variants of pgRNA were primarily observed in HBV gtB, C, E, or F-infected patients, with the Sp1 spliced variant detected most frequently. Twelve other pgRNA spliced variant transcripts were identified, including 3 previously unidentified transcripts, although spliced isoform identification was very dependent on the workflow used to analyze sequence data. Longitudinal sampling among pregnant and post-partum antiviral-treated individuals showed increasing proportions of 3' truncated pgRNA variants over time.

Conclusions

This study demonstrated long-read sequencing as a promising tool for the characterization of the serum HBV transcriptome. However, further studies are needed to better understand how serum HBV RNA isoform type and proportion are linked to CHB disease progression and antiviral treatment response.

Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning

The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. In recent years, the development of new high-throughput experimental and computational techniques has been a key driving force in discovering the properties of RNA modifications. Machine learning applications, such as for classification, clustering or de novo identification, have been critical in these advances. Nonetheless, various challenges remain before the full potential of machine learning for epitranscriptomics can be leveraged. In this review, we provide a comprehensive survey of machine learning methods to detect RNA modifications using diverse input data sources. We describe strategies to train and test machine learning methods and to encode and interpret features that are relevant for epitranscriptomics. Finally, we identify some of the current challenges and open questions about RNA modification analysis, including the ambiguity in predicting RNA modifications in transcript isoforms or in single nucleotides, or the lack of complete ground truth sets to test RNA modifications. We believe this review will inspire and benefit the rapidly developing field of epitranscriptomics in addressing the current limitations through the effective use of machine learning.

Tumor suppressor role of RBM22 in prostate cancer acting as a dual-factor regulating alternative splicing and transcription of key oncogenic genes

Prostate cancer (PCa) is one of the leading causes of cancer-related deaths among men. Consequently, the identification of novel molecular targets for treatment is urgently needed to improve patients' outcomes. Our group recently reported that some elements of the cellular machinery controlling alternative-splicing might be useful as potential novel therapeutic tools against advanced PCa. However, the presence and functional role of RBM22, a key spliceosome component, in PCa remains unknown. Therefore, RBM22 levels were firstly interrogated in 3 human cohorts and 2 preclinical mouse models (TRAMP/Pbsn-Myc). Results were validated in in silico using 2 additional cohorts. Then, functional effects in response to RBM22 overexpression (proliferation, migration, tumorspheres/colonies formation) were tested in PCa models in vitro (LNCaP, 22Rv1, and PC-3 cell-lines) and in vivo (xenograft). High throughput methods (ie, RNA-seq, nCounter PanCancer Pathways Panel) were performed in RBM22 overexpressing cells and xenograft tumors. We found that RBM22 levels were down-regulated (mRNA and protein) in PCa samples, and were inversely associated with key clinical aggressiveness features. Consistently, a gradual reduction of RBM22 from non-tumor to poorly differentiated PCa samples was observed in transgenic models (TRAMP/Pbsn-Myc). Notably, RBM22 overexpression decreased aggressiveness features in vitro, and in vivo. These actions were associated with the splicing dysregulation of numerous genes and to the downregulation of critical upstream regulators of cell-cycle (i.e., CDK1/CCND1/EPAS1). Altogether, our data demonstrate that RBM22 plays a critical pathophysiological role in PCa and invites to suggest that targeting negative regulators of RBM22 expression/activity could represent a novel therapeutic strategy to tackle this disease.

Psi promotes Drosophila wing growth via direct transcriptional activation of cell cycle targets and repression of growth inhibitors

The first characterised FUSE Binding Protein family member, FUBP1, binds single-stranded DNA to activate MYC transcription. Psi, the sole FUBP protein in Drosophila, binds RNA to regulate P-element and mRNA splicing. Our previous work revealed pro-growth functions for Psi, which depend, in part, on transcriptional activation of Myc. Genome-wide functions for FUBP family proteins in transcriptional control remain obscure. Here, through the first genome-wide binding and expression profiles obtained for a FUBP family protein, we demonstrate that, in addition to being required to activate Myc to promote cell growth, Psi also directly binds and activates stg to couple growth and cell division. Thus, Psi knockdown results in reduced cell division in the wing imaginal disc. In addition to activating these pro-proliferative targets, Psi directly represses transcription of the growth inhibitor tolkin (tok, a metallopeptidase implicated in TGFβ signalling). We further demonstrate tok overexpression inhibits proliferation, while tok loss of function increases mitosis alone and suppresses impaired cell division caused by Psi knockdown. Thus, Psi orchestrates growth through concurrent transcriptional activation of the pro-proliferative genes Myc and stg, in combination with repression of the growth inhibitor tok.

Cannabinoid signaling modulation through JZL184 restores key phenotypes of a mouse model for Williams-Beuren syndrome

Williams–Beuren syndrome (WBS) is a rare genetic multisystemic disorder characterized by mild-to-moderate intellectual disability and hypersocial phenotype, while the most life-threatening features are cardiovascular abnormalities. Nowadays, there are no pharmacological treatments to directly ameliorate the main traits of WBS. The endocannabinoid system (ECS), given its relevance for both cognitive and cardiovascular function, could be a potential druggable target in this syndrome. We analyzed the components of the ECS in the complete deletion (CD) mouse model of WBS and assessed the impact of its pharmacological modulation in key phenotypes relevant for WBS. CD mice showed the characteristic hypersociable phenotype with no preference for social novelty and poor short-term object-recognition performance. Brain cannabinoid type-1 receptor (CB1R) in CD male mice showed alterations in density and coupling with no detectable change in main endocannabinoids. Endocannabinoid signaling modulation with subchronic (10 days) JZL184, a selective inhibitor of monoacylglycerol lipase, specifically normalized the social and cognitive phenotype of CD mice. Notably, JZL184 treatment improved cardiovascular function and restored gene expression patterns in cardiac tissue. These results reveal the modulation of the ECS as a promising novel therapeutic approach to improve key phenotypic alterations in WBS.

Williams-Beuren syndrome (WBS) is a rare disorder that causes hyper-social behavior, intellectual disability, memory problems, and life-threatening overgrowth of the heart. Behavioral therapies can help improve the cognitive and social aspects of the syndrome and surgery is sometimes used to treat the effects on the heart, although often with limited success. However, there are currently no medications available to treat WBS.

The endocannabinoid system – which consists of cannabis-like chemical messengers that bind to specific cannabinoid receptor proteins – has been shown to influence cognitive and social behaviors, as well as certain functions of the heart. This has led scientists to suspect that the endocannabinoid system may play a role in WBS, and drugs modifying this network of chemical messengers could help treat the rare condition.

To investigate, Navarro-Romero, Galera-López et al. studied mice which had the same genetic deletion found in patients with WBS. Similar to humans, the male mice displayed hyper-social behaviors, had memory deficits and enlarged hearts. Navarro-Romero, Galera-López et al. found that these mutant mice also had differences in the function of the receptor protein cannabinoid type-1 (CB1).

The genetically modified mice were then treated with an experimental drug called JZL184 that blocks the breakdown of endocannabinoids which bind to the CB1 receptor. This normalized the number and function of receptors in the brains of the WBS mice, and reduced their social and memory symptoms. The treatment also restored the animals’ heart cells to a more normal size, improved the function of their heart tissue, and led to lower blood pressure. Further experiments revealed that the drug caused the mutant mice to activate many genes in their heart muscle cells to the same level as normal, healthy mice.

These findings suggest that JZL184 or other drugs targeting the endocannabinoid system may help ease the symptoms associated with WBS. More studies are needed to test the drug’s effectiveness in humans with this syndrome. Furthermore, the dramatic effect JZL184 has on the heart suggests that it might also help treat high blood pressure or conditions that cause the overgrowth of heart cells.

A convergent malignant phenotype in B-cell acute lymphoblastic leukemia involving the splicing factor SRRM1

A significant proportion of infant B-cell acute lymphoblastic leukemia (B-ALL) patients remains with a dismal prognosis due to yet undetermined mechanisms. We performed a comprehensive multicohort analysis of gene expression, gene fusions, and RNA splicing alterations to uncover molecular signatures potentially linked to the observed poor outcome. We identified 87 fusions with significant allele frequency across patients and shared functional impacts, suggesting common mechanisms across fusions. We further identified a gene expression signature that predicts high risk independently of the gene fusion background and includes the upregulation of the splicing factor SRRM1. Experiments in B-ALL cell lines provided further evidence for the role of SRRM1 on cell survival, proliferation, and invasion. Supplementary analysis revealed that SRRM1 potentially modulates splicing events associated with poor outcomes through protein-protein interactions with other splicing factors. Our findings reveal a potential convergent mechanism of aberrant RNA processing that sustains a malignant phenotype independently of the underlying gene fusion and that could potentially complement current clinical strategies in infant B-ALL.

RATTLE: reference-free reconstruction and quantification of transcriptomes from Nanopore sequencing

Nanopore sequencing enables the efficient and unbiased measurement of transcriptomes. Current methods for transcript identification and quantification rely on mapping reads to a reference genome, which precludes the study of species with a partial or missing reference or the identification of disease-specific transcripts not readily identifiable from a reference. We present RATTLE, a tool to perform reference-free reconstruction and quantification of transcripts using only Nanopore reads. Using simulated data and experimental data from isoform spike-ins, human tissues, and cell lines, we show that RATTLE accurately determines transcript sequences and their abundances, and shows good scalability with the number of transcripts.

Uncovering the impacts of alternative splicing on the proteome with current omics techniques

The high‐throughput sequencing of cellular RNAs has underscored a broad effect of isoform diversification through alternative splicing on the transcriptome. Moreover, the differential production of transcript isoforms from gene loci has been recognized as a critical mechanism in cell differentiation, organismal development, and disease. Yet, the extent of the impact of alternative splicing on protein production and cellular function remains a matter of debate. Multiple experimental and computational approaches have been developed in recent years to address this question. These studies have unveiled how molecular changes at different steps in the RNA processing pathway can lead to differences in protein production and have functional effects. New and emerging experimental technologies open exciting new opportunities to develop new methods to fully establish the connection between messenger RNA expression and protein production and to further investigate how RNA variation impacts the proteome and cell function.

This article is categorized under:

RNA Processing > Splicing Regulation/Alternative Splicing

Translation > Regulation

RNA Evolution and Genomics > Computational Analyses of RNA

ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.

Altered regulation of BRCA1 exon 11 splicing is associated with breast cancer risk in carriers of BRCA1 pathogenic variants

Germline pathogenic variants in BRCA1 confer a high risk of developing breast and ovarian cancer. The BRCA1 exon 11 (formally exon 10) is one of the largest exons and codes for the nuclear localization signals of the corresponding gene product. This exon can be partially or entirely skipped during pre-mRNA splicing, leading to three major in-frame isoforms that are detectable in most cell types and tissue, and in normal and cancer settings. However, it is unclear whether the splicing imbalance of this exon is associated with cancer risk. Here we identify a common genetic variant in intron 10, rs5820483 (NC_000017.11:g.43095106_43095108dup), which is associated with exon 11 isoform expression and alternative splicing, and with the risk of breast cancer, but not ovarian cancer, in BRCA1 pathogenic variant carriers. The identification of this genetic effect was confirmed by analogous observations in mouse cells and tissue in which a loxP sequence was inserted in the syntenic intronic region. The prediction that the rs5820483 minor allele variant would create a binding site for the splicing silencer hnRNP A1 was confirmed by pull-down assays. Our data suggest that perturbation of BRCA1 exon 11 splicing modifies the breast cancer risk conferred by pathogenic variants of this gene.

Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a consensus approach, METEORE ( https://github.com/comprna/METEORE ), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.

PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses

Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep-learning algorithm that accurately detects SARS-CoV-2 and other common RNA respiratory viruses from RNA-seq data. Using in silico data, PACIFIC recovers the presence and relative concentrations of viruses with > 99% precision and recall. PACIFIC accurately detects SARS-CoV-2 and other viral infections in 63 independent in vitro cell culture and patient datasets. PACIFIC is an end-to-end tool that enables the systematic monitoring of viral infections in the current global pandemic.

mRNA spindle localization and mitotic translational regulation by CPEB1 and CPEB4

Transition through cell cycle phases requires temporal and spatial regulation of gene expression to ensure accurate chromosome duplication and segregation. This regulation involves dynamic reprogramming of gene expression at multiple transcriptional and posttranscriptional levels. In transcriptionally silent oocytes, the CPEB-family of RNAbinding proteins coordinates temporal and spatial translation regulation of stored maternal mRNAs to drive meiotic progression. CPEB1 mediates mRNA localization to the meiotic spindle, which is required to ensure proper chromosome segregation. Temporal translational regulation also takes place in mitosis, where a large repertoire of transcripts are activated or repressed in specific cell cycle phases. However, whether control of localized translation at the spindle is required for mitosis is unclear, as mitotic and acentriolar-meiotic spindles are functionally and structurally different. Furthermore, the large differences in scale-ratio between cell volume and spindle size in oocytes compared to somatic mitotic cells may generate distinct requirements for gene expression compartmentalization in meiosis and mitosis. Here we show that mitotic spindles contain CPE-localized mRNAs and translating ribosomes. Moreover, CPEB1 and CPEB4 localize in the spindles and they may function sequentially in promoting mitotic stage transitions and correct chromosome segregation. Thus, CPEB1 and CPEB4 bind to specific spindle-associated transcripts controlling the expression and/or localization of their encoded factors that, respectively, drive metaphase and anaphase/cytokinesis.

Ribosome profiling at isoform level reveals evolutionary conserved impacts of differential splicing on the proteome

The differential production of transcript isoforms from gene loci is a key cellular mechanism. Yet, its impact in protein production remains an open question. Here, we describe ORQAS (ORF quantification pipeline for alternative splicing), a pipeline for the translation quantification of individual transcript isoforms using ribosome-protected mRNA fragments (ribosome profiling). We find evidence of translation for 40-50% of the expressed isoforms in human and mouse, with 53% of the expressed genes having more than one translated isoform in human, and 33% in mouse. Differential splicing analysis revealed that about 40% of the splicing changes at RNA level are concordant with changes in translation. Furthermore, orthologous cassette exons between human and mouse preserve the directionality of the change, and are enriched in microexons in a comparison between glia and glioma. ORQAS leverages ribosome profiling to uncover a widespread and evolutionarily conserved impact of differential splicing on translation, particularly of microexon-containing isoforms.

ReorientExpress: reference-free orientation of nanopore cDNA reads with deep learning

We describe ReorientExpress, a method to perform reference-free orientation of transcriptomic long sequencing reads. ReorientExpress uses deep learning to correctly predict the orientation of the majority of reads, and in particular when trained on a closely related species or in combination with read clustering. ReorientExpress enables long-read transcriptomics in non-model organisms and samples without a genome reference without using additional technologies and is available at https://github.com/comprna/reorientexpress.

Systematic Analysis of Splice-Site-Creating Mutations in Cancer

For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases.

Abstract 2362: Comprehensive portrait of canonical and non-canonical splicing in cancer

Current annotation methods typically classify mutations as disruptors of splicing if they fall on either the consensus intronic dinucleotide splice donor, GT, or the splice acceptor, AG. As a group, splice site mutations have been presumed to be invariably deleterious because of their disruption of the conserved sequences that are used to identify exon-intron boundaries. While this classification method has been useful, increasing evidence suggests that mutations outside of the canonical splice site can lead to transcriptional changes beyond disruption of the nearest junction. In this study, we have developed the MiSplice pipeline to determine the local and global effects of genomic mutations on splicing across 33 cancer types. To evaluate the local effects of mutations on splicing, we applied MiSplice to identify splice-disrupting mutations (SDMs) and splice-creating mutations (SCMs), genome-wide. We identified 1,964 novel SCMs, of which 26% and 11% were mis-annotated as missense and silent mutations and validated 10 of 11 genes in a mini-gene splicing assay. SDM identification predicted complex splicing patterns associated with canonical splice site mutations and identified a handful of mutations in proximity to the canonical junction that disrupt splicing factor binding sites. Interestingly, further investigation of the novel neoantigens produced by SCMs and SDMs are likely several folds more immunogenic than missense mutations. To explore the global impact of mutations on splicing we focused on recurrent and adjacent mutations disrupting the spliceosomal complex and related splicing factor genes from over 400 curated splice related genes. In addition, we applied HotSpot3D to identify splice-factor mutations (SFMs) that are significantly proximal to one another. Our analysis has identified novel SFMs that disrupt the spliceosomal complex and globally impact downstream splicing targets creating novel peptide sequences and alter key cancer genes. The current study has greatly extended the insight into the transcriptional ramifications of genomic alterations by integrating DNA and RNA sequencing data and painting the portrait of alternative splicing across cancer genomes.

Citation Format: Reyka G. Jayasinghe, Song Cao, Qingsong Gao, Matthew A. Wyczalkowski, Sohini Sengupta, Matthew J. Walter, Christopher Maher, Michael C. Wendl, Feng Chen, Eduardo Eyras, Alexander J. Lazar, Ken Chen, Ilya Shmulevich, Li Ding, The Splicing Analysis Working Group. Comprehensive portrait of canonical and non-canonical splicing in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2362.

SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data

RNA-protein binding is critical to gene regulation, controlling fundamental processes including splicing, translation, localization and stability, and aberrant RNA-protein interactions are known to play a role in a wide variety of diseases. However, molecular understanding of RNA-protein interactions remains limited; in particular, identification of RNA motifs that bind proteins has long been challenging, especially when such motifs depend on both sequence and structure. Moreover, although RNA binding proteins (RBPs) often contain more than one binding domain, algorithms capable of identifying more than one binding motif simultaneously have not been developed. In this paper we present a novel pipeline to determine binding peaks in crosslinking immunoprecipitation (CLIP) data, to discover multiple possible RNA sequence/structure motifs among them, and to experimentally validate such motifs. At the core is a new semi-automatic algorithm SARNAclust, the first unsupervised method to identify and deconvolve multiple sequence/structure motifs simultaneously. SARNAclust computes similarity between sequence/structure objects using a graph kernel, providing the ability to isolate the impact of specific features through the bulge graph formalism. Application of SARNAclust to synthetic data shows its capability of clustering 5 motifs at once with a V-measure value of over 0.95, while GraphClust achieves only a V-measure of 0.083 and RNAcontext cannot detect any of the motifs. When applied to existing eCLIP sets, SARNAclust finds known motifs for SLBP and HNRNPC and novel motifs for several other RBPs such as AGGF1, AKAP8L and ILF3. We demonstrate an experimental validation protocol, a targeted Bind-n-Seq-like high-throughput sequencing approach that relies on RNA inverse folding for oligo pool design, that can validate the components within the SLBP motif. Finally, we use this protocol to experimentally interrogate the SARNAclust motif predictions for protein ILF3. Our results support a newly identified partially double-stranded UUUUUGAGA motif similar to that known for the splicing factor HNRNPC.

RNA-protein binding is critical to gene regulation, and aberrant RNA-protein interactions play a role in a wide variety of diseases. However, molecular understanding of these interactions remains limited because of the difficulty of ascertaining the motifs that bind each protein. To address this challenge, we have developed a novel algorithm, SARNAclust, to computationally identify combined structure/sequence motifs from immunoprecipitation data. SARNAclust can deconvolve multiple motifs simultaneously and determine the importance of specific features through a graph kernel and bulge graph formalism. We have verified SARNAclust to be effective on synthetic motif data and also tested it on ENCODE eCLIP datasets, identifying known motifs and novel predictions. We have experimentally validated SARNAclust for two proteins, SLBP and ILF3, using RNA Bind-n-Seq measurements. Applying SARNAclust to ENCODE data provides new evidence for previously unknown regulatory interactions, notably splicing co-regulation by ILF3 and the splicing factor hnRNPC.

SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.

The discovery potential of RNA processing profiles

Small non-coding RNAs (sncRNAs) are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing capture the post-transcriptional processing specific to each RNA family, thereby providing functional information independently of sequence and structure. We developed SeRPeNT, a new computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare sncRNAs by harnessing the power of read profiles. We applied SeRPeNT to: (i) generate an extended human annotation with 671 new sncRNAs from known classes and 131 from new potential classes, (ii) show pervasive differential processing of sncRNAs between cell compartments and (iii) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, potentially dependent on the miRNA biogenesis pathway. Furthermore, we validated experimentally four predicted novel non-coding RNAs: a miRNA, a snoRNA-derived miRNA, a processed tRNA and a new uncharacterized sncRNA. SeRPeNT facilitates fast and accurate discovery and characterization of sncRNAs at an unprecedented scale. SeRPeNT code is available under the MIT license at https://github.com/comprna/SeRPeNT.

Systems analysis identifies melanoma-enriched pro-oncogenic networks controlled by the RNA binding protein CELF1

Melanomas are well-known for their altered mRNA expression profiles. Yet, the specific contribution of mRNA binding proteins (mRBPs) to melanoma development remains unclear. Here we identify a cluster of melanoma-enriched genes under the control of CUGBP Elav-like family member 1 (CELF1). CELF1 was discovered with a distinct prognostic value in melanoma after mining the genomic landscape of the 692 known mRBPs across different cancer types. Genome-wide transcriptomic, proteomic, and RNA-immunoprecipitation studies, together with loss-of-function analyses in cell lines, and histopathological evaluation in clinical biopsies, revealed an intricate repertoire of CELF1-RNA interactors with minimal overlap with other malignancies. This systems approach uncovered the oncogene DEK as an unexpected target and downstream effector of CELF1. Importantly, CELF1 and DEK were found to represent early-induced melanoma genes and adverse indicators of overall patient survival. These results underscore novel roles of CELF1 in melanoma, illustrating tumor type-restricted functions of RBPs in cancer.

IRFinder: assessing the impact of intron retention on mammalian gene expression

Intron retention (IR) occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. We have developed a program and database called IRFinder to accurately detect IR from mRNA sequencing data. Analysis of 2573 samples showed that IR occurs in all tissues analyzed, affects over 80% of all coding genes and is associated with cell differentiation and the cell cycle. Frequently retained introns are enriched for specific RNA binding protein sites and are often retained in clusters in the same gene. IR is associated with lower protein levels and intron-retaining transcripts that escape nonsense-mediated decay are not actively translated.

The role of alternative splicing in cancer

The functional capacity of cells is defined by the transcriptome. Many recent studies have identified variations in the transcriptome of tumors due to alternative splicing changes, as well as mutations in splicing factors and regulatory signals in most tumor types. Some of these alterations have been linked to tumor progression, metastasis, therapy resistance, and other oncogenic processes. Here, we describe the different mechanisms that drive splicing changes in tumors and their impact in cancer. Motivated by the current evidence, we propose a model whereby a subset of the splicing patterns contributes to the definition of specific tumor phenotypes, and may hold potential for the development of novel clinical biomarkers and therapeutic approaches.

The RNA-binding landscape of RBM10 and its role in alternative splicing regulation in models of mouse early development

Mutations in the RNA-binding protein, RBM10, result in a human syndromic form of cleft palate, termed TARP syndrome. A role for RBM10 in alternative splicing regulation has been previously demonstrated in human cell lines. To uncover the cellular functions of RBM10 in a cell line that is relevant to the phenotype observed in TARP syndrome, we used iCLIP to identify its endogenous RNA targets in a mouse embryonic mandibular cell line. We observed that RBM10 binds to pre-mRNAs with significant enrichment in intronic regions, in agreement with a role for this protein in pre-mRNA splicing. In addition to protein-coding transcripts, RBM10 also binds to a variety of cellular RNAs, including non-coding RNAs, such as spliceosomal small nuclear RNAs, U2 and U12. RNA-seq was used to investigate changes in gene expression and alternative splicing in RBM10 KO mouse mandibular cells and also in mouse ES cells. We uncovered a role for RBM10 in the regulation of alternative splicing of common transcripts in both cell lines but also identified cell-type specific events. Importantly, those pre-mRNAs that display changes in alternative splicing also contain RBM10 iCLIP tags, suggesting a direct role of RBM10 in these events. Finally, we show that depletion of RBM10 in mouse ES cells leads to proliferation defects and to gross alterations in their differentiation potential. These results demonstrate a role for RBM10 in the regulation of alternative splicing in two cell models of mouse early development and suggests that mutations in RBM10 could lead to splicing changes that affect normal palate development and cause human disease.

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.

The RNA-binding profile of Acinus, a peripheral component of the exon junction complex, reveals its role in splicing regulation

Acinus (apoptotic chromatin condensation inducer in the nucleus) is an RNA-binding protein (RBP) originally identified for its role in apoptosis. It was later found to be an auxiliary component of the exon junction complex (EJC), which is deposited at exon junctions as a consequence of pre-mRNA splicing. To uncover the cellular functions of Acinus and investigate its role in splicing, we mapped its endogenous RNA targets using the cross-linking immunoprecipitation protocol (iCLIP). We observed that Acinus binds to pre-mRNAs, associating specifically to a subset of suboptimal introns, but also to spliced mRNAs. We also confirmed the presence of Acinus as a peripheral factor of the EJC. RNA-seq was used to investigate changes in gene expression and alternative splicing following siRNA-mediated depletion of Acinus in HeLa cells. This analysis revealed that Acinus is preferentially required for the inclusion of specific alternative cassette exons and also controls the faithful splicing of a subset of introns. Moreover, a large number of splicing changes can be related to Acinus binding, suggesting a direct role of Acinus in exon and intron definition. In particular, Acinus regulates the splicing of DFFA/ICAD transcript, a major regulator of DNA fragmentation. Globally, the genome-wide identification of RNA targets of Acinus revealed its role in splicing regulation as well as its involvement in other cellular pathways, including cell cycle progression. Altogether, this study uncovers new cellular functions of an RBP transiently associated with the EJC.

The prognostic potential of alternative transcript isoforms across human tumors

BACKGROUND

Phenotypic changes during cancer progression are associated with alterations in gene expression, which can be exploited to build molecular signatures for tumor stage identification and prognosis. However, it is not yet known whether the relative abundance of transcript isoforms may be informative for clinical stage and survival.

METHODS

Using information theory and machine learning methods, we integrated RNA sequencing and clinical data from The Cancer Genome Atlas project to perform the first systematic analysis of the prognostic potential of transcript isoforms in 12 solid tumors to build new signatures for stage and prognosis. This study was also performed in breast tumors according to estrogen receptor (ER) status and melanoma tumors with proliferative and invasive phenotypes.

RESULTS

Transcript isoform signatures accurately separate early from late-stage groups and metastatic from non-metastatic tumors, and are predictive of the survival of patients with undetermined lymph node invasion or metastatic status. These signatures show similar, and sometimes better, accuracies compared with known gene expression signatures in retrospective data and are largely independent of gene expression changes. Furthermore, we show frequent transcript isoform changes in breast tumors according to ER status, and in melanoma tumors according to the invasive or proliferative phenotype, and derive accurate predictive models of stage and survival within each patient subgroup.

CONCLUSIONS

Our analyses reveal new signatures based on transcript isoform abundances that characterize tumor phenotypes and their progression independently of gene expression. Transcript isoform signatures appear especially relevant to determine lymph node invasion and metastasis and may potentially contribute towards current strategies of precision cancer medicine.

The alternative splicing program of differentiated smooth muscle cells involves concerted non-productive splicing of post-transcriptional regulators

Alternative splicing (AS) is a key component of gene expression programs that drive cellular differentiation. Smooth muscle cells (SMCs) are important in the function of a number of physiological systems; however, investigation of SMC AS has been restricted to a handful of events. We profiled transcriptome changes in mouse de-differentiating SMCs and observed changes in hundreds of AS events. Exons included in differentiated cells were characterized by particularly weak splice sites and by upstream binding sites for Polypyrimidine Tract Binding protein (PTBP1). Consistent with this, knockdown experiments showed that that PTBP1 represses many smooth muscle specific exons. We also observed coordinated splicing changes predicted to downregulate the expression of core components of U1 and U2 snRNPs, splicing regulators and other post-transcriptional factors in differentiated cells. The levels of cognate proteins were lower or similar in differentiated compared to undifferentiated cells. However, levels of snRNAs did not follow the expression of splicing proteins, and in the case of U1 snRNP we saw reciprocal changes in the levels of U1 snRNA and U1 snRNP proteins. Our results suggest that the AS program in differentiated SMCs is orchestrated by the combined influence of auxiliary RNA binding proteins, such as PTBP1, along with altered activity and stoichiometry of the core splicing machinery.

Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks

Alternative splicing is regulated by multiple RNA-binding proteins and influences the expression of most eukaryotic genes. However, the role of this process in human disease, and particularly in cancer, is only starting to be unveiled. We systematically analyzed mutation, copy number, and gene expression patterns of 1348 RNA-binding protein (RBP) genes in 11 solid tumor types, together with alternative splicing changes in these tumors and the enrichment of binding motifs in the alternatively spliced sequences. Our comprehensive study reveals widespread alterations in the expression of RBP genes, as well as novel mutations and copy number variations in association with multiple alternative splicing changes in cancer drivers and oncogenic pathways. Remarkably, the altered splicing patterns in several tumor types recapitulate those of undifferentiated cells. These patterns are predicted to be mainly controlled by MBNL1 and involve multiple cancer drivers, including the mitotic gene NUMA1 We show that NUMA1 alternative splicing induces enhanced cell proliferation and centrosome amplification in nontumorigenic mammary epithelial cells. Our study uncovers novel splicing networks that potentially contribute to cancer development and progression.

AtRTD - a comprehensive reference transcript dataset resource for accurate quantification of transcript-specific expression in Arabidopsis thaliana

RNA-sequencing (RNA-seq) allows global gene expression analysis at the individual transcript level. Accurate quantification of transcript variants generated by alternative splicing (AS) remains a challenge. We have developed a comprehensive, nonredundant Arabidopsis reference transcript dataset (AtRTD) containing over 74 000 transcripts for use with algorithms to quantify AS transcript isoforms in RNA-seq. The AtRTD was formed by merging transcripts from TAIR10 and novel transcripts identified in an AS discovery project. We have estimated transcript abundance in RNA-seq data using the transcriptome-based alignment-free programmes Sailfish and Salmon and have validated quantification of splicing ratios from RNA-seq by high resolution reverse transcription polymerase chain reaction (HR RT-PCR). Good correlations between splicing ratios from RNA-seq and HR RT-PCR were obtained demonstrating the accuracy of abundances calculated for individual transcripts in RNA-seq. The AtRTD is a resource that will have immediate utility in analysing Arabidopsis RNA-seq data to quantify differential transcript abundance and expression.

Leveraging transcript quantification for fast computation of alternative splicing profiles

Alternative splicing plays an essential role in many cellular processes and bears major relevance in the understanding of multiple diseases, including cancer. High-throughput RNA sequencing allows genome-wide analyses of splicing across multiple conditions. However, the increasing number of available data sets represents a major challenge in terms of computation time and storage requirements. We describe SUPPA, a computational tool to calculate relative inclusion values of alternative splicing events, exploiting fast transcript quantification. SUPPA accuracy is comparable and sometimes superior to standard methods using simulated as well as real RNA-sequencing data compared with experimentally validated events. We assess the variability in terms of the choice of annotation and provide evidence that using complete transcripts rather than more transcripts per gene provides better estimates. Moreover, SUPPA coupled with de novo transcript reconstruction methods does not achieve accuracies as high as using quantification of known transcripts, but remains comparable to existing methods. Finally, we show that SUPPA is more than 1000 times faster than standard methods. Coupled with fast transcript quantification, SUPPA provides inclusion values at a much higher speed than existing methods without compromising accuracy, thereby facilitating the systematic splicing analysis of large data sets with limited computational resources. The software is implemented in Python 2.7 and is available under the MIT license at https://bitbucket.org/regulatorygenomicsupf/suppa.

Leveraging transcript quantification for fast computation of alternative splicing profiles

Alternative splicing plays an essential role in many cellular processes and bears major relevance in the understanding of multiple diseases, including cancer. High-throughput RNA sequencing allows genome-wide analyses of splicing across multiple conditions. However, the increasing number of available data sets represents a major challenge in terms of computation time and storage requirements. We describe SUPPA, a computational tool to calculate relative inclusion values of alternative splicing events, exploiting fast transcript quantification. SUPPA accuracy is comparable and sometimes superior to standard methods using simulated as well as real RNA-sequencing data compared with experimentally validated events. We assess the variability in terms of the choice of annotation and provide evidence that using complete transcripts rather than more transcripts per gene provides better estimates. Moreover, SUPPA coupled with de novo transcript reconstruction methods does not achieve accuracies as high as using quantification of known transcripts, but remains comparable to existing methods. Finally, we show that SUPPA is more than 1000 times faster than standard methods. Coupled with fast transcript quantification, SUPPA provides inclusion values at a much higher speed than existing methods without compromising accuracy, thereby facilitating the systematic splicing analysis of large data sets with limited computational resources. The software is implemented in Python 2.7 and is available under the MIT license at https://bitbucket.org/regulatorygenomicsupf/suppa.

A Quantitative Profiling Tool for Diverse Genomic Data Types Reveals Potential Associations between Chromatin and Pre-mRNA Processing

High-throughput sequencing, and genome-based datasets in general, are often represented as profiles centered at reference points to study the association of protein binding and other signals to particular regulatory mechanisms. Although these profiles often provide compelling evidence of these associations, they do not provide a quantitative assessment of the enrichment, which makes the comparison between signals and conditions difficult. In addition, a number of biases can confound profiles, but are rarely accounted for in the tools currently available. We present a novel computational method, ProfileSeq, for the quantitative assessment of biological profiles to provide an exact, nonparametric test that specific regions of the test profile have higher or lower signal densities than a control set. The method is applicable to high-throughput sequencing data (ChIP-Seq, GRO-Seq, CLIP-Seq, etc.) and to genome-based datasets (motifs, etc.). We validate ProfileSeq by recovering and providing a quantitative assessment of several results reported before in the literature using independent datasets. We show that input signal and mappability have confounding effects on the profile results, but that normalizing the signal by input reads can eliminate these biases while preserving the biological signal. Moreover, we apply ProfileSeq to ChIP-Seq data for transcription factors, as well as for motif and CLIP-Seq data for splicing factors. In all examples considered, the profiles were robust to biases in mappability of sequencing reads. Furthermore, analyses performed with ProfileSeq reveal a number of putative relationships between transcription factor binding to DNA and splicing factor binding to pre-mRNA, adding to the growing body of evidence relating chromatin and pre-mRNA processing. ProfileSeq provides a robust way to quantify genome-wide coordinate-based signal. Software and documentation are freely available for academic use at https://bitbucket.org/regulatorygenomicsupf/profileseq/.

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.

A chromatin code for alternative splicing involving a putative association between CTCF and HP1α proteins

Background

Alternative splicing is primarily controlled by the activity of splicing factors and by the elongation of the RNA polymerase II (RNAPII). Recent experiments have suggested a new complex network of splicing regulation involving chromatin, transcription and multiple protein factors. In particular, the CCCTC-binding factor (CTCF), the Argonaute protein AGO1, and members of the heterochromatin protein 1 (HP1) family have been implicated in the regulation of splicing associated with chromatin and the elongation of RNAPII. These results raise the question of whether these proteins may associate at the chromatin level to modulate alternative splicing.

Results

Using chromatin immunoprecipitation sequencing (ChIP-Seq) data for CTCF, AGO1, HP1α, H3K27me3, H3K9me2, H3K36me3, RNAPII, total H3 and 5metC and alternative splicing arrays from two cell lines, we have analyzed the combinatorial code of their binding to chromatin in relation to the alternative splicing patterns between two cell lines, MCF7 and MCF10. Using Machine Learning techniques, we identified the changes in chromatin signals that are most significantly associated with splicing regulation between these two cell lines. Moreover, we have built a map of the chromatin signals on the pre-mRNA, that is, a chromatin-based RNA-map, which can explain 606 (68.55%) of the regulated events between MCF7 and MCF10. This chromatin code involves the presence of HP1α, CTCF, AGO1, RNAPII and histone marks around regulated exons and can differentiate patterns of skipping and inclusion. Additionally, we found a significant association of HP1α and CTCF activities around the regulated exons and a putative DNA binding site for HP1α.

Conclusions

Our results show that a considerable number of alternative splicing events could have a chromatin-dependent regulation involving the association of HP1α and CTCF near regulated exons. Additionally, we find further evidence for the involvement of HP1α and AGO1 in chromatin-related splicing regulation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-015-0141-5) contains supplementary material, which is available to authorized users.

The BioMart community portal: an innovative alternative to large, centralized data repositories

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Nuclear matrix protein Matrin3 regulates alternative splicing and forms overlapping regulatory networks with PTB

Matrin3 is an RNA- and DNA-binding nuclear matrix protein found to be associated with neural and muscular degenerative diseases. A number of possible functions of Matrin3 have been suggested, but no widespread role in RNA metabolism has yet been clearly demonstrated. We identified Matrin3 by its interaction with the second RRM domain of the splicing regulator PTB. Using a combination of RNAi knockdown, transcriptome profiling and iCLIP, we find that Matrin3 is a regulator of hundreds of alternative splicing events, principally acting as a splicing repressor with only a small proportion of targeted events being co-regulated by PTB. In contrast to other splicing regulators, Matrin3 binds to an extended region within repressed exons and flanking introns with no sharply defined peaks. The identification of this clear molecular function of Matrin3 should help to clarify the molecular pathology of ALS and other diseases caused by mutations of Matrin3.

Detection of recurrent alternative splicing switches in tumor samples reveals novel signatures of cancer

The determination of the alternative splicing isoforms expressed in cancer is fundamental for the development of tumor-specific molecular targets for prognosis and therapy, but it is hindered by the heterogeneity of tumors and the variability across patients. We developed a new computational method, robust to biological and technical variability, which identifies significant transcript isoform changes across multiple samples. We applied this method to more than 4000 samples from the The Cancer Genome Atlas project to obtain novel splicing signatures that are predictive for nine different cancer types, and find a specific signature for basal-like breast tumors involving the tumor-driver CTNND1. Additionally, our method identifies 244 isoform switches, for which the change occurs in the most abundant transcript. Some of these switches occur in known tumor drivers, including PPARG, CCND3, RALGDS, MITF, PRDM1, ABI1 and MYH11, for which the switch implies a change in the protein product. Moreover, some of the switches cannot be described with simple splicing events. Surprisingly, isoform switches are independent of somatic mutations, except for the tumor-suppressor FBLN2 and the oncogene MYH11. Our method reveals novel signatures of cancer in terms of transcript isoforms specifically expressed in tumors, providing novel potential molecular targets for prognosis and therapy. Data and software are available at: http://dx.doi.org/10.6084/m9.figshare.1061917 and https://bitbucket.org/regulatorygenomicsupf/iso-ktsp.

Approaches to link RNA secondary structures with splicing regulation

In higher eukaryotes, alternative splicing is usually regulated by protein factors, which bind to the pre-mRNA and affect the recognition of splicing signals. There is recent evidence that the secondary structure of the pre-mRNA may also play an important role in this process, either by facilitating or hindering the interaction with factors and small nuclear ribonucleoproteins (snRNPs) that regulate splicing. Moreover, the secondary structure could play a fundamental role in the splicing of yeast species, which lack many of the regulatory splicing factors present in metazoans. This chapter describes the steps in the analysis of the secondary structure of the pre-mRNA and its possible relation to splicing. As a working example, we use the case of yeast and the problem of the recognition of the 3' splice site (3'ss).