Computational challenges, tools, and resources for analyzing co- and post-transcriptional events in high throughput

Physiological RNA dynamics in RNA-Seq analysis

Physiological RNA dynamics cause problems in transcriptome analysis. Physiological RNA accumulation affects the analysis of RNA quantification, and physiological RNA degradation affects the analysis of the RNA sequence length, feature site and quantification. In the present article, we review the effects of physiological degradation and accumulation of RNA on analysing RNA sequencing data. Physiological RNA accumulation and degradation probably led to such phenomena as incorrect estimations of transcription quantification, differential expressions, co-expressions, RNA decay rates, alternative splicing, boundaries of transcription, novel genes, new single-nucleotide polymorphisms, small RNAs and gene fusion. Thus, the transcriptomic data obtained up to date warrant further scrutiny. New and improved techniques and bioinformatics software are needed to produce accurate data in transcriptome research.

Visualization and analysis of RNA-Seq assembly graphs

RNA-Seq is a powerful transcriptome profiling technology enabling transcript discovery and quantification. Whilst most commonly used for gene-level quantification, the data can be used for the analysis of transcript isoforms. However, when the underlying transcript assemblies are complex, current visualization approaches can be limiting, with splicing events a challenge to interpret. Here, we report on the development of a graph-based visualization method as a complementary approach to understanding transcript diversity from short-read RNA-Seq data. Following the mapping of reads to a reference genome, a read-to-read comparison is performed on all reads mapping to a given gene, producing a weighted similarity matrix between reads. This is used to produce an RNA assembly graph, where nodes represent reads and edges similarity scores between them. The resulting graphs are visualized in 3D space to better appreciate their sometimes large and complex topology, with other information being overlaid on to nodes, e.g. transcript models. Here we demonstrate the utility of this approach, including the unusual structure of these graphs and how they can be used to identify issues in assembly, repetitive sequences within transcripts and splice variants. We believe this approach has the potential to significantly improve our understanding of transcript complexity.

miR-125a-5p Functions as Tumor Suppressor microRNA And Is a Marker of Locoregional Recurrence And Poor prognosis in Head And Neck Cancer

MicroRNAs (miRNAs) are short single-stranded RNAs, measuring 21 to 23 nucleotides in length and regulate gene expression at the post-transcriptional level through mRNA destabilization or repressing protein synthesis. Dysregulation of miRNAs can lead to tumorigenesis through changes in regulation of key cellular processes such as cell proliferation, cell survival, and apoptosis. miR-125a-5p has been implicated as a tumor suppressor miRNA in malignancies such as non-small cell lung cancer and colon cancer. However, the role of miR-125a-5p has not been fully investigated in head and neck squamous cell carcinoma (HNSCC). We performed microRNA microarray profiling of HNSCC tumor samples obtained from a prospective clinical trial evaluating the role of postoperative radiotherapy in head and neck cancer. We also mined through The Cancer Genome Atlas to evaluate expression and survival data. Biological experiments, including cell proliferation, flow cytometry, cell migration and invasion, clonogenic survival, and fluorescent microscopy, were conducted using HN5 and UM-SCC-22B cell lines. miR-125a-5p downregulation was associated with recurrent disease in a panel of high-risk HNSCC and then confirmed poor survival associated with low expression in HNSCC via the Cancer Genome Atlas, suggesting that miR-125a-5p acts as a tumor suppressor miRNA. We then demonstrated that miR-125a-5p regulates cell proliferation through cell cycle regulation at the G₁/S transition. We also show that miR-125a-5p can alter cell migration and modulate sensitivity to ionizing radiation. Finally, we identified putative mRNA targets of miR-125a-5p, including ERBB2, EIF4EBP1, and TXNRD1, which support the tumor suppressive mechanism of miR-125a-5p. Functional validation of ERBB2 suggests that miR-125a-5p affects cell proliferation and sensitivity to ionizing radiation, in part, through ERBB2. Our data suggests that miR-125a-5p acts as a tumor suppressor miRNA, has potential as a diagnostic tool and may be a potential therapeutic target for the management and treatment of squamous cell carcinoma of the head and neck.

Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes

Gene expression is tightly regulated at the post-transcriptional level through splicing, transport, translation, and decay. RNA-binding proteins (RBPs) play key roles in post-transcriptional gene regulation, and genetic variants that alter RBP-RNA interactions can affect gene products and functions. We developed a computational method ASPRIN (Allele-Specific Protein-RNA Interaction) that uses a joint analysis of CLIP-seq (cross-linking and immunoprecipitation followed by high-throughput sequencing) and RNA-seq data to identify genetic variants that alter RBP-RNA interactions by directly observing the allelic preference of RBP from CLIP-seq experiments as compared to RNA-seq. We used ASPRIN to systematically analyze CLIP-seq and RNA-seq data for 166 RBPs in two ENCODE (Encyclopedia of DNA Elements) cell lines. ASPRIN identified genetic variants that alter RBP-RNA interactions by modifying RBP binding motifs within RNA. Moreover, through an integrative ASPRIN analysis with population-scale RNA-seq data, we showed that ASPRIN can help reveal potential causal variants that affect alternative splicing via allele-specific protein-RNA interactions.

CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome

Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We present CLAM (CLIP-seq Analysis of Multi-mapped reads). CLAM uses an expectation–maximization algorithm to assign multi-mapped reads and calls peaks combining uniquely and multi-mapped reads. To demonstrate the utility of CLAM, we applied it to a wide range of public CLIP-seq/RIP-seq datasets involving numerous splicing factors, microRNAs and m⁶A RNA methylation. CLAM recovered a large number of novel RNA regulatory sites inaccessible by uniquely mapped reads. The functional significance of these sites was demonstrated by consensus motif patterns and association with alternative splicing (splicing factors), transcript abundance (AGO2) and mRNA half-life (m⁶A). CLAM provides a useful tool to discover novel protein–RNA interactions and RNA modification sites from CLIP-seq and RIP-seq data, and reveals the significant contribution of repetitive elements to the RNA regulatory landscape of the human transcriptome.

Functional genomics analyses of RNA-binding proteins reveal the splicing regulator SNRPB as an oncogenic candidate in glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most common and aggressive type of brain tumor. Currently, GBM has an extremely poor outcome and there is no effective treatment. In this context, genomic and transcriptomic analyses have become important tools to identify new avenues for therapies. RNA-binding proteins (RBPs) are master regulators of co- and post-transcriptional events; however, their role in GBM remains poorly understood. To further our knowledge of novel regulatory pathways that could contribute to gliomagenesis, we have conducted a systematic study of RBPs in GBM.

RESULTS

By measuring expression levels of 1542 human RBPs in GBM samples and glioma stem cell samples, we identified 58 consistently upregulated RBPs. Survival analysis revealed that increased expression of 21 RBPs was also associated with a poor prognosis. To assess the functional impact of those RBPs, we modulated their expression in GBM cell lines and performed viability, proliferation, and apoptosis assays. Combined results revealed a prominent oncogenic candidate, SNRPB, which encodes core spliceosome machinery components. To reveal the impact of SNRPB on splicing and gene expression, we performed its knockdown in a GBM cell line followed by RNA sequencing. We found that the affected genes were involved in RNA processing, DNA repair, and chromatin remodeling. Additionally, genes and pathways already associated with gliomagenesis, as well as a set of general cancer genes, also presented with splicing and expression alterations.

CONCLUSIONS

Our study provides new insights into how RBPs, and specifically SNRPB, regulate gene expression and directly impact GBM development.

Comprehensive identification of translation start sites by tetracycline-inhibited ribosome profiling

Tetracycline-inhibited ribosome profiling (TetRP) provides a powerful new experimental tool for comprehensive genome-wide identification of translation initiation sites in bacteria. We validated TetRP by confirming the translation start sites of protein-coding genes in accordance with the 2006 version of Escherichia coli K-12 annotation record (GenBank U00096.2) and found ∼150 new start sites within 60 nucleotides of the annotated site. This analysis revealed 72 per cent of the genes whose initiation site annotations were changed from the 2006 GenBank record to the newer 2014 annotation record (GenBank U00096.3), indicating a high sensitivity. Also, results from reporter fusion and proteomics of N-terminally enriched peptides showed high specificity of the TetRP results. In addition, we discovered over 300 translation start sites within non-coding, intergenic regions of the genome, using a threshold that retains ∼2,000 known coding genes. While some appear to correspond to pseudogenes, others may encode small peptides or have previously unforeseen roles. In summary, we showed that ribosome profiling upon translation inhibition by tetracycline offers a simple, reliable and comprehensive experimental tool for precise annotation of translation start sites of expressed genes in bacteria.

High-throughput analyses of hnRNP H1 dissects its multi-functional aspect

hnRNPs are polyvalent RNA binding proteins that have been implicated in a range of regulatory roles including splicing, mRNA decay, translation, and miRNA metabolism. A variety of genome wide studies have taken advantage of methods like CLIP and RIP to identify the targets and binding sites of RNA binding proteins. However, due to the complex nature of RNA-binding proteins, these studies are incomplete without assays that characterize the impact of RBP binding on mRNA target expression. Here we used a suite of high-throughput approaches (RIP-Seq, iCLIP, RNA-Seq and shotgun proteomics) to provide a comprehensive view of hnRNP H1s ensemble of targets and its role in splicing, mRNA decay, and translation. The combination of RIP-Seq and iCLIP allowed us to identify a set of 1,086 high confidence target transcripts. Binding site motif analysis of these targets suggests the TGGG tetramer as a prevalent component of hnRNP H1 binding motif, with particular enrichment around intronic hnRNP H1 sites. Our analysis of the target transcripts and binding sites indicates that hnRNP H1s involvement in splicing is 2-fold: it directly affects a substantial number of splicing events, but also regulates the expression of major components of the splicing machinery and other RBPs with known roles in splicing regulation. The identified mRNA targets displayed function enrichment in MAPK signaling and ubiquitin mediated proteolysis, which might be main routes by which hnRNP H1 promotes tumorigenesis.

Guardian of Genetic Messenger-RNA-Binding Proteins

RNA in cells is always associated with RNA-binding proteins that regulate all aspects of RNA metabolism including RNA splicing, export from the nucleus, RNA localization, mRNA turn-over as well as translation. Given their diverse functions, cells express a variety of RNA-binding proteins, which play important roles in the pathologies of a number of diseases. In this review we focus on the effect of alcohol on different RNA-binding proteins and their possible contribution to alcohol-related disorders, and discuss the role of these proteins in the development of neurological diseases and cancer. We further discuss the conventional methods and newer techniques that are employed to identify RNA-binding proteins.

A web application for the unspecific detection of differentially expressed DNA regions in strand-specific expression data

Genomic technologies allow laboratories to produce large-scale data sets, either through the use of next-generation sequencing or microarray platforms. To explore these data sets and obtain maximum value from the data, researchers view their results alongside all the known features of a given reference genome. To study transcriptional changes that occur under a given condition, researchers search for regions of the genome that are differentially expressed between different experimental conditions. In order to identify these regions several algorithms have been developed over the years, along with some bioinformatic platforms that enable their use. However, currently available applications for comparative microarray analysis exclusively focus on changes in gene expression within known transcribed regions of predicted protein-coding genes, the changes that occur in non-predictable genetic elements, such as non-coding RNAs. Here, we present a web application for the visualization of strand-specific tiling microarray or next-generation sequencing data that allows customized detection of differentially expressed regions all along the genome in an unspecific manner, that allows identification of all RNA sequences, predictable or not.

AVAILABILITY AND IMPLEMENTATION

The web application is freely accessible at http://tilingscan.uv.es/. TilingScan is implemented in PHP and JavaScript.

CONTACT

vicente.arnau@uv.es

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA-Binding Protein Musashi1 Is a Central Regulator of Adhesion Pathways in Glioblastoma

The conserved RNA-binding protein Musashi1 (MSI1) has emerged as a key oncogenic factor in numerous solid tumors, including glioblastoma. However, its mechanism of action has not yet been established comprehensively. To identify its target genes comprehensively and determine the main routes by which it influences glioblastoma phenotypes, we conducted individual-nucleotide resolution cross-linking and immunoprecipitation (iCLIP) experiments. We confirmed that MSI1 has a preference for UAG sequences contained in a particular structural context, especially in 3' untranslated regions. Although numerous binding sites were also identified in intronic sequences, our RNA transcriptome sequencing analysis does not favor the idea that MSI1 is a major regulator of splicing in glioblastoma cells. MSI1 target mRNAs encode proteins that function in multiple pathways of cell proliferation and cell adhesion. Since these associations indicate potentially new roles for MSI1, we investigated its impact on glioblastoma cell adhesion, morphology, migration, and invasion. These processes are known to underpin the spread and relapse of glioblastoma, in contrast to other tumors where metastasis is the main driver of recurrence and progression.

Design and bioinformatics analysis of genome-wide CLIP experiments

The past decades have witnessed a surge of discoveries revealing RNA regulation as a central player in cellular processes. RNAs are regulated by RNA-binding proteins (RBPs) at all post-transcriptional stages, including splicing, transportation, stabilization and translation. Defects in the functions of these RBPs underlie a broad spectrum of human pathologies. Systematic identification of RBP functional targets is among the key biomedical research questions and provides a new direction for drug discovery. The advent of cross-linking immunoprecipitation coupled with high-throughput sequencing (genome-wide CLIP) technology has recently enabled the investigation of genome-wide RBP–RNA binding at single base-pair resolution. This technology has evolved through the development of three distinct versions: HITS-CLIP, PAR-CLIP and iCLIP. Meanwhile, numerous bioinformatics pipelines for handling the genome-wide CLIP data have also been developed. In this review, we discuss the genome-wide CLIP technology and focus on bioinformatics analysis. Specifically, we compare the strengths and weaknesses, as well as the scopes, of various bioinformatics tools. To assist readers in choosing optimal procedures for their analysis, we also review experimental design and procedures that affect bioinformatics analyses.