Upstream analysis of alternative splicing: a review of computational approaches to predict context-dependent splicing factors

Muscle transcriptome analysis reveal candidate genes and pathways related to fat and lipid metabolism in Yunling cattle

Yunling cattle (YL) is a recently developed beef breed harboring a quarter of Yunnan ancestral cattle genome, spanning over past 30 years. Compared with Diqing cattle (DQ), a Yunnan native cattle breed, YL presents various advantages, including rapid growth and exquisite meat quality. However, the molecular mechanisms underlying these phenotypic differences are not clearly understood. To further identify the candidate genes responsible for the quality of the meat in the muscle, longissimus dorsi (LD) muscle was used for RNA-Seq analysis. A total of 508 differentially expressed genes (DEGs) were identified in YL (adjusted p-value <0.01 and log2FoldChange >1), of which 243 were up-regulated and 265 were down-regulated. Functional association analysis showed that the identified DEGs mainly enriched the lipid and fat metabolism pathways. Moreover, it was also observed that several fat-related genes were differentially expressed in both cattle breeds, including three up-regulated genes (MOGAT1, ACSM3, PLPP2) and two down-regulated genes (ADIG, GPAT3). In addition, alternative splice analysis was also performed revealing an important 9-11 exon skipping variation of GPAM gene (crucial for beef marbling) in YL, which is three times higher than that in DQ, suggesting that this variation might have played the central role in the 'snow beef' effect in YL. We believe that our results will help in understanding the mechanism of muscle development and promote the further breeding programs in YL cattle.

A serpin gene from a parasitoid wasp disrupts host immunity and exhibits adaptive alternative splicing

Alternative splicing (AS) is a major source of protein diversity in eukaryotes, but less is known about its evolution compared to gene duplication (GD). How AS and GD interact is also largely understudied. By constructing the evolutionary trajectory of the serpin gene PpSerpin-1 (Pteromalus puparum serpin 1) in parasitoids and other insects, we found that both AS and GD jointly contribute to serpin protein diversity. These two processes are negatively correlated and show divergent features in both protein and regulatory sequences. Parasitoid wasps exhibit higher numbers of serpin protein/domains than nonparasitoids, resulting from more GD but less AS in parasitoids. The potential roles of AS and GD in the evolution of parasitoid host-effector genes are discussed. Furthermore, we find that PpSerpin-1 shows an exon expansion of AS compared to other parasitoids, and that several isoforms are involved in the wasp immune response, have been recruited to both wasp venom and larval saliva, and suppress host immunity. Overall, our study provides an example of how a parasitoid serpin gene adapts to parasitism through AS, and sheds light on the differential features of AS and GD in the evolution of insect serpins and their associations with the parasitic life strategy.

Position-dependent effects of RNA-binding proteins in the context of co-transcriptional splicing

Alternative splicing is an important step in eukaryotic mRNA pre-processing which increases the complexity of gene expression programs, but is frequently altered in disease. Previous work on the regulation of alternative splicing has demonstrated that splicing is controlled by RNA-binding proteins (RBPs) and by epigenetic DNA/histone modifications which affect splicing by changing the speed of polymerase-mediated pre-mRNA transcription. The interplay of these different layers of splicing regulation is poorly understood. In this paper, we derived mathematical models describing how splicing decisions in a three-exon gene are made by combinatorial spliceosome binding to splice sites during ongoing transcription. We additionally take into account the effect of a regulatory RBP and find that the RBP binding position within the sequence is a key determinant of how RNA polymerase velocity affects splicing. Based on these results, we explain paradoxical observations in the experimental literature and further derive rules explaining why the same RBP can act as inhibitor or activator of cassette exon inclusion depending on its binding position. Finally, we derive a stochastic description of co-transcriptional splicing regulation at the single-cell level and show that splicing outcomes show little noise and follow a binomial distribution despite complex regulation by a multitude of factors. Taken together, our simulations demonstrate the robustness of splicing outcomes and reveal that quantitative insights into kinetic competition of co-transcriptional events are required to fully understand this important mechanism of gene expression diversity.

Splicing signature database development to delineate cancer pathways using literature mining and transcriptome machine learning

Alternative splicing (AS) events modulate certain pathways and phenotypic plasticity in cancer. Although previous studies have computationally analyzed splicing events, it is still a challenge to uncover biological functions induced by reliable AS events from tremendous candidates. To provide essential splicing event signatures to assess pathway regulation, we developed a database by collecting two datasets: (i) reported literature and (ii) cancer transcriptome profile. The former includes knowledge-based splicing signatures collected from 63,229 PubMed abstracts using natural language processing, extracted for 202 pathways. The latter is the machine learning-based splicing signatures identified from pan-cancer transcriptome for 16 cancer types and 42 pathways. We established six different learning models to classify pathway activities from splicing profiles as a learning dataset. Top-ranked AS events by learning model feature importance became the signature for each pathway. To validate our learning results, we performed evaluations by (i) performance metrics, (ii) differential AS sets acquired from external datasets, and (iii) our knowledge-based signatures. The area under the receiver operating characteristic values of the learning models did not exhibit any drastic difference. However, random-forest distinctly presented the best performance to compare with the AS sets identified from external datasets and our knowledge-based signatures. Therefore, we used the signatures obtained from the random-forest model. Our database provided the clinical characteristics of the AS signatures, including survival test, molecular subtype, and tumor microenvironment. The regulation by splicing factors was additionally investigated. Our database for developed signatures supported retrieval and visualization system.

Genetic risk variants for multiple sclerosis are linked to differences in alternative pre-mRNA splicing

BACKGROUND

Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system to which a genetic predisposition contributes. Over 200 genetic regions have been associated with increased disease risk, but the disease-causing variants and their functional impact at the molecular level are mostly poorly defined. We hypothesized that single-nucleotide polymorphisms (SNPs) have an impact on pre-mRNA splicing in MS.

METHODS

Our study focused on 10 bioinformatically prioritized SNP-gene pairs, in which the SNP has a high potential to alter alternative splicing events (ASEs). We tested for differential gene expression and differential alternative splicing in B cells from MS patients and healthy controls. We further examined the impact of the SNP genotypes on ASEs and on splice isoform expression levels. Novel genotype-dependent effects on splicing were verified with splicing reporter minigene assays.

RESULTS

We were able to confirm previously described findings regarding the relation of MS-associated SNPs with the ASEs of the pre-mRNAs from GSDMB and SP140. We also observed an increased IL7R exon 6 skipping when comparing relapsing and progressive MS patients to healthy subjects. Moreover, we found evidence that the MS risk alleles of the SNPs rs3851808 (EFCAB13), rs1131123 (HLA-C), rs10783847 (TSFM), and rs2014886 (TSFM) may contribute to a differential splicing pattern. Of particular interest is the genotype-dependent exon skipping of TSFM due to the SNP rs2014886. The minor allele T creates a donor splice site, resulting in the expression of the exon 3 and 4 of a short TSFM transcript isoform, whereas in the presence of the MS risk allele C, this donor site is absent, and thus the short transcript isoform is not expressed.

CONCLUSION

In summary, we found that genetic variants from MS risk loci affect pre-mRNA splicing. Our findings substantiate the role of ASEs with respect to the genetics of MS. Further studies on how disease-causing genetic variants may modify the interactions between splicing regulatory sequence elements and RNA-binding proteins can help to deepen our understanding of the genetic susceptibility to MS.

EventPointer 3.0: flexible and accurate splicing analysis that includes studying the differential usage of protein-domains

Alternative splicing (AS) plays a key role in cancer: all its hallmarks have been associated with different mechanisms of abnormal AS. The improvement of the human transcriptome annotation and the availability of fast and accurate software to estimate isoform concentrations has boosted the analysis of transcriptome profiling from RNA-seq. The statistical analysis of AS is a challenging problem not yet fully solved. We have included in EventPointer (EP), a Bioconductor package, a novel statistical method that can use the bootstrap of the pseudoaligners. We compared it with other state-of-the-art algorithms to analyze AS. Its performance is outstanding for shallow sequencing conditions. The statistical framework is very flexible since it is based on design and contrast matrices. EP now includes a convenient tool to find the primers to validate the discoveries using PCR. We also added a statistical module to study alteration in protein domain related to AS. Applying it to 9514 patients from TCGA and TARGET in 19 different tumor types resulted in two conclusions: i) aberrant alternative splicing alters the relative presence of Protein domains and, ii) the number of enriched domains is strongly correlated with the age of the patients.

Multi-omics research in sarcopenia: Current progress and future prospects

Sarcopenia is a systemic disease with progressive and generalized skeletal muscle dysfunction defined by age-related low muscle mass, high content of muscle slow fibers, and low muscle function. Muscle phenotypes and sarcopenia risk are heritable; however, the genetic architecture and molecular mechanisms underlying sarcopenia remain largely unclear. In recent years, significant progress has been made in determining susceptibility loci using genome-wide association studies. In addition, recent advances in omics techniques, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, offer new opportunities to identify novel targets to help us understand the pathophysiology of sarcopenia. However, each individual technology cannot capture the entire view of the biological complexity of this disorder, while integrative multi-omics analyses may be able to reveal new insights. Here, we review the latest findings of multi-omics studies for sarcopenia and provide an in-depth summary of our current understanding of sarcopenia pathogenesis. Leveraging multi-omics data could give us a holistic understanding of sarcopenia etiology that may lead to new clinical applications. This review offers guidance and recommendations for fundamental research, innovative perspectives, and preventative and therapeutic interventions for sarcopenia.

Insm1, Neurod1, and Pax6 promote murine pancreatic endocrine cell development through overlapping yet distinct RNA transcription and splicing programs

Insm1, Neurod1, and Pax6 are essential for the formation and function of pancreatic endocrine cells. Here, we report comparative immunohistochemical, transcriptomic, functional enrichment, and RNA splicing analyses of these genes using gene knock-out mice. Quantitative immunohistochemical analysis confirmed that elimination of each of these three factors variably impairs the proliferation, survival, and differentiation of endocrine cells. Transcriptomic analysis revealed that each factor contributes uniquely to the transcriptome although their effects were overlapping. Functional enrichment analysis revealed that genes downregulated by the elimination of Insm1, Neurod1, and Pax6 are commonly involved in mRNA metabolism, chromatin organization, secretion, and cell cycle regulation, and upregulated genes are associated with protein degradation, autophagy, and apoptotic process. Elimination of Insm1, Neurod1, and Pax6 impaired expression of many RNA-binding proteins thereby altering RNA splicing events, including for Syt14 and Snap25, two genes required for insulin secretion. All three factors are necessary for normal splicing of Syt14, and both Insm1 and Pax6 are necessary for the processing of Snap25. Collectively, these data provide new insights into how Insm1, Neurod1, and Pax6 contribute to the formation of functional pancreatic endocrine cells.

Principles and Practical Considerations for the Analysis of Disease-Associated Alternative Splicing Events Using the Gateway Cloning-Based Minigene Vectors pDESTsplice and pSpliceExpress

Splicing is an important RNA processing step. Genetic variations can alter the splicing process and thereby contribute to the development of various diseases. Alterations of the splicing pattern can be examined by gene expression analyses, by computational tools for predicting the effects of genetic variants on splicing, and by splicing reporter minigene assays for studying alternative splicing events under defined conditions. The minigene assay is based on transient transfection of cells with a vector containing a genomic region of interest cloned between two constitutive exons. Cloning can be accomplished by the use of restriction enzymes or by site-specific recombination using Gateway cloning. The vectors pDESTsplice and pSpliceExpress represent two minigene systems based on Gateway cloning, which are available through the Addgene plasmid repository. In this review, we describe the features of these two splicing reporter minigene systems. Moreover, we provide an overview of studies in which determinants of alternative splicing were investigated by using pDESTsplice or pSpliceExpress. The studies were reviewed with regard to the investigated splicing regulatory events and the experimental strategy to construct and perform a splicing reporter minigene assay. We further elaborate on how analyses on the regulation of RNA splicing offer promising prospects for gaining important insights into disease mechanisms.

Alternative Splicing Dynamics of the Hypothalamus-Pituitary-Ovary Axis During Pubertal Transition in Gilts

The timing of puberty in mammals marks the point at which reproduction becomes possible. Abnormalities in the timing of puberty may exert a series of negative effects on subsequent health outcomes. Alternative splicing (AS) has not only emerged as a significant factor in the transcription of genes but it is also reported to play a role in the timing of puberty. However, to date, the changes and dynamics of AS during the onset of puberty is extremely seldom explored. In the present study, we used gilts as a research model to investigated the dynamics of AS and differentially expressed AS (DEAS) events within the hypothalamus-pituitary-ovary (HPO) axis across pre-, in-, and post-puberty. We detected 3,390, 6,098, and 9,085 DEAS events in the hypothalamus, pituitary, and ovary when compared across pre-, in-, and post-pubertal stages, respectively. Within the entire HPO axis, we also identified 22,889, 22,857, and 21,055 DEAS events in the pre-, in-, and post-pubertal stages, respectively. Further analysis revealed that the differentially spliced genes (DSGs) associated with staged DEAS events were likely to be enriched in the oxytocin signaling pathway, thyroid hormone signaling pathway, GnRH signaling pathway, and oocyte meiosis signaling pathway. The DSGs associated with DEAS events across the entire HPO axis were enriched in endocytosis signaling pathway, the MAPK signaling pathway, and the Rap1 signaling pathway. Moreover. the ASs of TAC1, TACR3, CYP19A1, ESR1, ESRRA, and FSHR were likely to regulate the functions of the certain HPO tissues during the onset of puberty. Collectively, the AS dynamics and DEAS events were comprehensively profiled in hypothalamus, pituitary, and ovary across the pre-, in-, and post-pubertal stages in pigs. These findings may enhance our knowledge of how puberty is regulated by AS and shed new light on the molecular mechanisms underlying the timing of puberty in mammals.

Computing the Role of Alternative Splicing in Cancer

Most human genes undergo alternative splicing (AS), and dysregulation of alternative splicing contributes to tumor initiation and progression. Computational analysis of genomic and transcriptomic data enables the systematic characterization of alternative splicing and its functional role in cancer. In this review, we summarize the latest computational approaches to studying alternative splicing in cancer and the current limitations of the most popular tools in this field. Finally, we describe some of the current computational challenges in the characterization of the role of alternative splicing in cancer.

Prognostic Value and Potential Role of Alternative mRNA Splicing Events in Cervical Cancer

Background

Increasing evidence suggests that aberrant alternative splicing (AS) events are associated with progression of cancer. This study evaluated the prognostic value and clarify the role of AS events in cervical cancer (CC).

Methods

Based on RNA-seq AS event data and clinical information of CC patients in The Cancer Genome Atlas (TCGA) database, we sought to identify prognosis-related AS events in this setting. We selected several survival-associated AS events to construct a prognostic predictor for CC through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Moreover, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed on genes with prognosis-related AS events and constructed an AS-splicing factors (SFs) regulatory network.

Results

2770 AS events were significantly correlated with overall survival (OS). The area under the curve (AUC) values of receiver-operator characteristic curve (ROC) for the final prognostic predictor were 0.926, 0.946 and 0.902 at 3, 5, and 10 years, respectively. These values indicated efficiency in prognostic risk stratification for patients with CC. The final prognostic predictor was an independent predictor of OS (HR: 1.24; 95% CI: 1.020–1.504; P < 0.05). The AS-SFs correlation network may reveal an underlying regulatory mechanism of AS events.

Conclusion

AS events are essential participants in the prognosis of CC and hold great potentials for the prognostic stratification and development of treatment strategy.

Intron Retention as a Mode for RNA-Seq Data Analysis

Intron retention (IR) is an alternative splicing mode whereby introns, rather than being spliced out as usual, are retained in mature mRNAs. It was previously considered a consequence of mis-splicing and received very limited attention. Only recently has IR become of interest for transcriptomic data analysis owing to its recognized roles in gene expression regulation and associations with complex diseases. In this article, we first review the function of IR in regulating gene expression in a number of biological processes, such as neuron differentiation and activation of CD4⁺ T cells. Next, we briefly review its association with diseases, such as Alzheimer's disease and cancers. Then, we describe state-of-the-art methods for IR detection, including RNA-seq analysis tools IRFinder and iREAD, highlighting their underlying principles and discussing their advantages and limitations. Finally, we discuss the challenges for IR detection and potential ways in which IR detection methods could be improved.

Exon Definition Facilitates Reliable Control of Alternative Splicing in the RON Proto-Oncogene

Alternative splicing is a key step in eukaryotic gene expression that allows for the production of multiple transcript and protein isoforms from the same gene. Even though splicing is perturbed in many diseases, we currently lack insights into regulatory mechanisms promoting its precision and efficiency. We analyze high-throughput mutagenesis data obtained for an alternatively spliced exon in the proto-oncogene RON and determine the functional units that control this splicing event. Using mathematical modeling of distinct splicing mechanisms, we show that alternative splicing is based in RON on a so-called "exon definition" mechanism. Here, the recognition of the adjacent exons by the spliceosome is required for removal of an intron. We use our model to analyze the differences between the exon and intron definition scenarios and find that exon definition prevents the accumulation of deleterious, partially spliced retention products during alternative splicing regulation. Furthermore, it modularizes splicing control, as multiple regulatory inputs are integrated into a common net input, irrespective of the location and nature of the corresponding cis-regulatory elements in the pre-messenger RNA. Our analysis suggests that exon definition promotes robust and reliable splicing outcomes in RON splicing.

Dynamic Alternative Splicing During Mouse Preimplantation Embryo Development

The mechanism of alternative pre-mRNA splicing (AS) during preimplantation development is largely unknown. In order to capture the dynamic changes of AS occurring during embryogenesis, we carried out bioinformatics analysis based on scRNA-seq data over the time-course preimplantation development in mouse. We detected numerous previously-unreported differentially expressed genes at specific developmental stages and investigated the nature of AS at both minor and major zygotic genome activation (ZGA). The AS and differential AS atlas over preimplantation development were established. The differentially alternatively spliced genes (DASGs) are likely to be key splicing factors (SFs) during preimplantation development. We also demonstrated that there is a regulatory cascade of AS events in which some key SFs are regulated by differentially AS of their own gene transcripts. Moreover, 212 isoform switches (ISs) during preimplantation development were detected, which may be critical for decoding the mechanism of early embryogenesis. Importantly, we uncovered that zygotic AS activation (ZASA) is in conformity with ZGA and revealed that AS is coupled with transcription during preimplantation development. Our results may provide a deeper insight into the regulation of early embryogenesis.

Identification of neoantigens derived from alternative splicing and RNA modification

The acquisition of somatic mutations is the most common event in cancer. Neoantigens expressed from genes with mutations acquired during carcinogenesis can be tumor-specific. Since the immune system recognizes tumor-specific peptides, they are potential targets for personalized neoantigen-based immunotherapy. However, the discovery of druggable neoantigens remains challenging, suggesting that a deeper understanding of the mechanism of neoantigen generation and better strategies to identify them will be required to realize the promise of neoantigen-based immunotherapy. Alternative splicing and RNA editing events are emerging mechanisms leading to neoantigen production. In this review, we outline recent work involving the large-scale screening of neoantigens produced by alternative splicing and RNA editing. We also describe strategies to predict and validate neoantigens from RNA sequencing data.

Integration of CLIP experiments of RNA-binding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data

BACKGROUND

Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein.

RESULTS

In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four CLIP databases: POSTAR2, CLIPdb, DoRiNA and StarBase. The analysis of these experiments shows the strong coherence between the binding sites of RBPs of similar families. Augmenting this information with expression changes, we are able to correctly predict the splicing factors that regulate splicing in two gold-standard experiments in which specific splicing factors are knocked-down.

CONCLUSIONS

The methodology presented in this study allows the prediction of active splicing factors in either cancer or any other condition by only using the information of transcript expression. This approach opens a wide range of possible studies to understand the splicing regulation of different conditions. A tutorial with the source code and databases is available at https://gitlab.com/fcarazo.m/sfprediction .

In vivo measurements reveal a single 5'-intron is sufficient to increase protein expression level in Caenorhabditis elegans

Introns can increase gene expression levels using a variety of mechanisms collectively referred to as Intron Mediated Enhancement (IME). IME has been measured in cell culture and plant models by quantifying expression of intronless and intron-bearing reporter genes in vitro. We developed hardware and software to implement microfluidic chip-based gene expression quantification in vivo. We altered position, number and sequence of introns in reporter genes controlled by the hsp-90 promoter. Consistent with plant and mammalian studies, we determined a single, natural or synthetic, 5'-intron is sufficient for the full IME effect conferred by three synthetic introns, while a 3'-intron is not. We found coding sequence can affect IME; the same three synthetic introns that increase mcherry protein concentration by approximately 50%, increase mEGFP by 80%. We determined IME effect size is not greatly affected by the stronger vit-2 promoter. Our microfluidic imaging approach should facilitate screens for factors affecting IME and other intron-dependent processes.

Alternative splicing of P2RX7 pre-messenger RNA in health and diseases: Myth or reality?

Alternative splicing (AS) tremendously increases the use of genetic information by generating protein isoforms that differ in protein-protein interactions, catalytic activity and/or subcellular localization. This review is not dedicated to AS in general, but rather we focus our attention on AS of P2RX7 pre-mRNA. Whereas P2RX7 mRNA is expressed by virtually all eukaryotic mammalian cells, the expression of this channel receptor is restrained to certain cells. When expressed at the cell membrane, P2RX7 controls downstream events including release of inflammatory molecules, phagocytosis, cell proliferation and death and metabolic events. Therefore, P2RX7 is an important actor of health and diseases. In this review, we summarize the general mechanisms leading to AS. Further, we recapitulate our current knowledge concerning the functional regions in P2RX7, identified at the genetic or exonic levels, and how AS may affect the expression of these regions. Finally, the potential of P2RX7 splice variants to control the fate of cancer cells is discussed.

TranscriptAchilles: a genome-wide platform to predict isoform biomarkers of gene essentiality in cancer

BACKGROUND

Aberrant alternative splicing plays a key role in cancer development. In recent years, alternative splicing has been used as a prognosis biomarker, a therapy response biomarker, and even as a therapeutic target. Next-generation RNA sequencing has an unprecedented potential to measure the transcriptome. However, due to the complexity of dealing with isoforms, the scientific community has not sufficiently exploited this valuable resource in precision medicine.

FINDINGS

We present TranscriptAchilles, the first large-scale tool to predict transcript biomarkers associated with gene essentiality in cancer. This application integrates 412 loss-of-function RNA interference screens of >17,000 genes, together with their corresponding whole-transcriptome expression profiling. Using this tool, we have studied which are the cancer subtypes for which alternative splicing plays a significant role to state gene essentiality. In addition, we include a case study of renal cell carcinoma that shows the biological soundness of the results. The databases, the source code, and a guide to build the platform within a Docker container are available at GitLab. The application is also available online.

CONCLUSIONS

TranscriptAchilles provides a user-friendly web interface to identify transcript or gene biomarkers of gene essentiality, which could be used as a starting point for a drug development project. This approach opens a wide range of translational applications in cancer.

Maximizing the Utility of Cancer Transcriptomic Data

Transcriptomic profiling has been applied to large numbers of cancer samples, by large-scale consortia, including The Cancer Genome Atlas, International Cancer Genome Consortium, and Cancer Cell Line Encyclopedia. Advances in mining cancer transcriptomic data enable us to understand the endless complexity of the cancer transcriptome and thereby to discover new biomarkers and therapeutic targets. In this paper, we review computational resources for deep mining of transcriptomic data to identify, quantify, and determine the functional effects and clinical utility of transcriptomic events, including noncoding RNAs, post-transcriptional regulation, exogenous RNAs, and transcribed genetic variants. These approaches can be applied to other complex diseases, thereby greatly leveraging the impact of this work.

Comparison of RNA-seq and microarray platforms for splice event detection using a cross-platform algorithm

Background

RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem.

We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments.

Results

As might be expected, RNA-seq appears superior in cases where the technologies disagree and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads.

Conclusions

Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5082-2) contains supplementary material, which is available to authorized users.

Systematic Analysis of Survival-Associated Alternative Splicing Signatures in Gastrointestinal Pan-Adenocarcinomas

BACKGROUND

Gastrointestinal pan-adenocarcinomas, which mainly include adenocarcinomas of the esophagus, stomach, colon, and rectum, place a heavy burden on society owing to their poor prognoses. Since aberrant alternative splicing (AS) are starting to be considered as efficacious signatures for tumor prognosis predicting and therapeutic targets, systematic analysis of AS events is urgent.

METHODS

Prognosis-related AS events were selected by using univariate COX regression analysis. Gene functional enrichment analysis revealed the pathways enriched by prognosis-related AS. Then, prognostic signatures based on AS events were developed for prognosis prediction. Potential mechanism to regulate splicing events by splicing factors was analyzed via Pearson correlation and regulatory networks were constructed.

FINDINGS

A total of 967, 918, 674, and 406 AS events were identified as prognosis-related AS events in esophagus, stomach, colon, and rectum adenocarcinomas, respectively. Survival-associated AS events were distinguishing in the four subtypes of adenocarcinoma. Furthermore, computational algorithm results indicated that perturbation of ribosome and ubiquitin-mediated proteolysis pathways were the potential molecular mechanisms corresponding to inferior prognoses. Most notably, several prognostic signatures based on AS events displayed moderate performance in prognosis predicting. The area under curve values of the time-dependent receiver operating characteristic were 0.961, 0.871, 0.870, and 0.890 in esophagus, stomach, colon, and rectum adenocarcinomas. Survival-associated splicing factors were submitted to construct the AS regulatory network, which could be an underlying mechanism of AS events.

INTERPRETATION

AS may could be ideal indiactors in the prognosis of gastrointestinal pan-adenocarcinomas. Exploring interesting splicing regulatory networks is conducive to solve the puzzles of AS.