AbstractBackgroundAlternative Splicing Research Articles

SIRTUIN 1 ISOFORMS DIFFERENTIALLY IMPACT MITOCHONDRIAL GENE EXPRESSION AND FUNCTION IN MUSCLE CELLS

Abstract Background Alternative splicing (AS) is a mechanism that generates multiple mRNA transcripts and protein isoforms from a single gene, thereby increasing transcriptomic and proteomic diversity. The spliced isoforms commonly lack one or more exons, which may have similar or even opposite functions. Alternatively spliced isoforms tend to increase during aging. The sirtuin-1 gene contains multiple exons and undergoes alternative splicing, which generates multiple isoforms. In this study, we assessed the impact of three sirtuin-1 isoforms on mitochondrial gene expression and function in muscle cells. Methods Three sirtuin-1 isoforms (V1, V2, V3) were subcloned into expression vectors. Muscle cell lines (H9C2 and C2C12) were transfected with sirtuin-1 isoforms, respectively. Microscopic images were obtained using a Nikon microscope. Gene expression was determined by quantitative RT-PCR and Western blotting. The mitochondrial function was determined with a Seahorse XFe96 Analyzer. Results and conclusions The sirtuin-1 V1 isoform significantly increased the oxygen consumption rate (OCR) and decreased glycolysis (ECAR) in muscle cells, while V2 and V3 isoforms had slight or no significant effect on OCR and ECAR. V1 isoform was localized in the nucleus, whereas V2 and V3 were localized in the cytoplasm. Sirtuin-1 isoforms differentially impacted mitochondrial complex genes, including NDUFS1, NDUFV1, NDUFV2, NDUFA5. Our data indicate that the domain loss changed sirtuin-1 isoform subcellular localization, differentially impacted mitochondrial gene expression, and affected mitochondrial function. The age-related change in the expression of sirtuin-1 isoforms could affect cardiac and skeletal muscle function in aging and senescence. Further exploration of the sirtuin-1 isoforms’ functions is warranted.

Development of a Prognostic Alternative Splicing Signature Associated With Tumor Microenvironment Immune Profiles in Lung Adenocarcinoma

BackgroundAlternative splicing (AS), a pivotal post-transcriptional process across more than 95% of human transcripts, is involved in transcript structural variations and protein complexity. Clinical implications of AS events and their interaction with tumor immunity were systematically analyzed in lung adenocarcinoma (LUAD).MethodsTranscriptome profiling as well as AS data of LUAD were retrospectively curated. Then, the network of the overall survival (OS)-relevant AS events with splicing factors was established. After screening OS-relevant AS events, a LASSO prognostic model was conducted and evaluated with ROC curves. A nomogram that integrated independent prognostic indicators was created. Immune response and immune cell infiltration were estimated with ESTIMATE, CIBERSORT, and ssGSEA algorithms. Drug sensitivity was inferred with pRRophetic package.ResultsIn total, 2415 OS-relevant AS events were identified across LUAD patients. The interaction network of splicing factors with OS-relevant AS events uncovered the underlying regulatory mechanisms of AS events in LUAD. Thereafter, a prognostic model containing 12 AS events was developed, which acted as a reliable and independent prognostic indicator following verification. A nomogram that constituted stage and risk score displayed great effectiveness in evaluating the survival likelihood. Moreover, the AS-based prognostic model was in relation to immune response and immune cell infiltration. Patients with a high-risk score displayed therapeutic superiority to cisplatin, erlotinib, gefitinib, and gemcitabine. Finally, three AS-relevant genes (CDKN2A, TTC39C, and PKIB) were identified as prognostic markers.ConclusionCollectively, our findings developed an AS event signature with powerful prognostic predictive efficacy in LUAD.

SAPFIR: A webserver for the identification of alternative protein features

BackgroundAlternative splicing can increase the diversity of gene functions by generating multiple isoforms with different sequences and functions. However, the extent to which splicing events have functional consequences remains unclear and predicting the impact of splicing events on protein activity is limited to gene-specific analysis.ResultsTo accelerate the identification of functionally relevant alternative splicing events we created SAPFIR, a predictor of protein features associated with alternative splicing events. This webserver tool uses InterProScan to predict protein features such as functional domains, motifs and sites in the human and mouse genomes and link them to alternative splicing events. Alternative protein features are displayed as functions of the transcripts and splice sites. SAPFIR could be used to analyze proteins generated from a single gene or a group of genes and can directly identify alternative protein features in large sequence data sets. The accuracy and utility of SAPFIR was validated by its ability to rediscover previously validated alternative protein domains. In addition, our de novo analysis of public datasets using SAPFIR indicated that only a small portion of alternative protein domains was conserved between human and mouse, and that in human, genes involved in nervous system process, regulation of DNA-templated transcription and aging are more likely to produce isoforms missing functional domains due to alternative splicing.ConclusionOverall SAPFIR represents a new tool for the rapid identification of functional alternative splicing events and enables the identification of cellular functions affected by a defined splicing program. SAPFIR is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/sapfir/, a website implemented in Python, with all major browsers supported. The source code is available at https://github.com/DelongZHOU/SAPFIR.

Switched alternative splicing events as attractive features in lung squamous cell carcinoma

BackgroundAlternative splicing (AS) plays important roles in transcriptome and proteome diversity. Its dysregulation has a close affiliation with oncogenic processes. This study aimed to evaluate AS-based biomarkers by machine learning algorithms for lung squamous cell carcinoma (LUSC) patients.MethodThe Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database were utilized. After data composition balancing, Boruta feature selection and Spearman correlation analysis were used for differentially expressed AS events. Random forests and a nested fivefold cross-validation were applied for lymph node metastasis (LNM) classifier building. Random survival forest combined with Cox regression model was performed for a prognostic model, based on which a nomogram was developed. Functional enrichment analysis and Spearman correlation analysis were also conducted to explore underlying mechanisms. The expression of some switch-involved AS events along with parent genes was verified by qRT-PCR with 20 pairs of normal and LUSC tissues.ResultsWe found 16 pairs of splicing events from same parent genes which were strongly related to the splicing switch (intrapair correlation coefficient = − 1). Next, we built a reliable LNM classifier based on 13 AS events as well as a nice prognostic model, in which switched AS events behaved prominently. The qRT-PCR presented consistent results with previous bioinformatics analysis, and some AS events like ITIH5-10715-AT and QKI-78404-AT showed remarkable detection efficiency for LUSC.ConclusionAS events, especially switched ones from the same parent genes, could provide new insights into the molecular diagnosis and therapeutic drug design of LUSC.

A Prediction Model Using Alternative Splicing Events and the Immune Microenvironment Signature in Lung Adenocarcinoma

BackgroundAlternative splicing (AS) is a gene regulatory mechanism that drives protein diversity. Dysregulation of AS is thought to play an essential role in cancer initiation and development. This study aimed to construct a prognostic signature based on AS and explore the role in the tumor immune microenvironment (TIME) in lung adenocarcinoma.MethodsWe analyzed transcriptome profiling and clinical lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq. Prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan–Meier survival analyses, and proportional hazards model. The context of TIME in lung adenocarcinoma was also analyzed. Gene and protein expression data of Cyclin-Dependent Kinase Inhibitor 2A (CDKN2A) were obtained from ONCOMINE and Human Protein Atlas. Splicing factor (SF) regulatory networks were visualized.ResultsA total of 19,054 survival-related AS events in lung adenocarcinoma were screened in 1,323 genes. Exon skip (ES) and mutually exclusive exons (ME) exhibited the most and fewest AS events, respectively. Based on AS subtypes, eight AS prognostic signatures were constructed. Patients with high-risk scores were associated with poor overall survival. A nomogram with good validity in prognostic prediction was generated. AUCs of risk scores at 1, 2, and 3 years were 0.775, 0.736, and 0.759, respectively. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. Low-risk patients had a higher StromalScore, ImmuneScore, and ESTIMATEScore. AS-based risk score signature was positively associated with CD8+ T cells. CDKN2A was also found to be a prognostic factor in lung adenocarcinoma. Finally, potential functions of SFs were determined by regulatory networks.ConclusionTaken together, our findings show a clear association between AS and immune cell infiltration events and patient outcome, which could provide a basis for the identification of novel markers and therapeutic targets for lung adenocarcinoma. SF networks provide information of regulatory mechanisms.

Genome-Wide Analyses of Prognostic and Therapeutic Alternative Splicing Signatures in Bladder Urothelial Carcinoma.

BackgroundAlternative splicing (AS) is an indispensable post-transcriptional modification applied during the maturation of mRNA, and AS defects have been associated with many cancers. This study was designed to thoroughly analyze AS events in bladder urothelial carcinoma (BLCA) at the genome-wide level.MethodsWe adopted a gap analysis to screen for significant differential AS events (DASEs) associated with BLCA. DASEs with prognostic value for OS and the disease-free interval (DFI) were identified by Cox analysis. In addition, a differential AS network and AS clusters were identified using unsupervised cluster analysis. We examined differences in the sensitivity to chemotherapy and immunotherapy between BLCA patients with high and low overall survival (OS) risk.ResultsAn extensive number of DASEs (296) were found to be clinically relevant in BLCA. A prognosis model was established based prognostic value of OS and DFI. CUGBP elav-like family member 2 (CELF2) was identified as a hub splicing factor for AS networks. We also identified AS clusters associated with OS using unsupervised cluster analysis, and we predicted that the effects of cisplatin and gemcitabine chemotherapy would be different between high- and low-risk groups based on OS prognosis.ConclusionWe completed a comprehensive analysis of AS events in BLCA at the genome-wide level. The present findings revealed that DASEs and splicing factors tended to impact BLCA patient survival and sensitivity to chemotherapy drugs, which may provide novel prospects for BLCA therapies.

Identification of novel alternative splicing biomarkers for breast cancer with LC/MS/MS and RNA-Seq

BackgroundAlternative splicing isoforms have been reported as a new and robust class of diagnostic biomarkers. Over 95% of human genes are estimated to be alternatively spliced as a powerful means of producing functionally diverse proteins from a single gene. The emergence of next-generation sequencing technologies, especially RNA-seq, provides novel insights into large-scale detection and analysis of alternative splicing at the transcriptional level. Advances in Proteomic Technologies such as liquid chromatography coupled tandem mass spectrometry (LC–MS/MS), have shown tremendous power for the parallel characterization of large amount of proteins in biological samples. Although poor correspondence has been generally found from previous qualitative comparative analysis between proteomics and microarray data, significantly higher degrees of correlation have been observed at the level of exon. Combining protein and RNA data by searching LC–MS/MS data against a customized protein database from RNA-Seq may produce a subset of alternatively spliced protein isoform candidates that have higher confidence.ResultsWe developed a bioinformatics workflow to discover alternative splicing biomarkers from LC–MS/MS using RNA-Seq. First, we retrieved high confident, novel alternative splicing biomarkers from the breast cancer RNA-Seq database. Then, we translated these sequences into in silico Isoform Junction Peptides, and created a customized alternative splicing database for MS searching. Lastly, we ran the Open Mass spectrometry Search Algorithm against the customized alternative splicing database with breast cancer plasma proteome. Twenty six alternative splicing biomarker peptides with one single intron event and one exon skipping event were identified. Further interpretation of biological pathways with our Integrated Pathway Analysis Database showed that these 26 peptides are associated with Cancer, Signaling, Metabolism, Regulation, Immune System and Hemostasis pathways, which are consistent with the 256 alternative splicing biomarkers from the RNA-Seq.ConclusionsThis paper presents a bioinformatics workflow for using RNA-seq data to discover novel alternative splicing biomarkers from the breast cancer proteome. As a complement to synthetic alternative splicing database technique for alternative splicing identification, this method combines the advantages of two platforms: mass spectrometry and next generation sequencing and can help identify potentially highly sample-specific alternative splicing isoform biomarkers at early-stage of cancer.

Full-length-transcriptomic analysis in mice and human heart using Single-Molecule Real-time Sequencing (SMRT) identified 15 novel isoforms and a novel promoter region of PGC1-alpha

Abstract Background Alternative splicing is a process by which exons within a pre-mRNA are joined or skipped, resulting in isoforms being encoded by a single gene. Alternative Splicing affecting transcription factors may have substantial impact on cellular dynamics. The PPARG Coactivator 1 Alpha (PGC1-α), is a major modulator in energy metabolism. Data from murine skeletal muscle revealed distinctive isoform patterns giving rise to different phenotypes, i.e. mitogenesis and hypertrophy. Here, we aimed to establish a complete dataset of isoforms in murine and human heart applying single-molecule real-time (SMRT)-sequencing as novel approach to identify transcripts without need for assembly, resulting in true full-length sequences. Moreover, we aimed to unravel functional relevance of the various isoforms during experimental ischemia reperfusion (I/R). Methods RNA-Isolation was performed in murine (C57Bl/6J) or human heart tissue (obtained during LVAD-surgery), followed by library preparation and SMRT-Sequencing. Bioinformatic analysis was done using a modified IsoSeq3-Pipeline and OS-tools. Identification of PGC1-α isoforms was fulfilled by similarity search against exonic sequences within the full-length, non-concatemere (FLNC) reads. Isoforms with Open-Reading-Frame (ORF) were manually curated and validated by PCR and Sanger-Sequencing. I/R was induced by ligature of the LAD for 45 min in mice on standard chow as well as on high-fat-high-sucrose diet. Area At Risk (AAR) and remote tissue were collected three and 16 days after I/R or sham-surgery (n=4 per time point). Promotor patterns were analyzed by qPCR. Results Deciphering the full-length transcriptome of murine and human heart resulted in ∼60000 Isoforms with 99% accuracy on mRNA-sequence. Focusing on murine PGC1-α-isoforms we discovered and verified 15 novel transcripts generated by hitherto unknown splicing events. Additionally, we identified a novel Exon 1 originating between the known promoters followed by a valid ORF, suggesting the discovery of a novel promoter. Remarkably, we found a homologous novel Exon1 in human heart, suggesting conservation of the postulated promoter. In I/R the AAR exhibited a significant lower expression of established and novel promoters compared to remote under standard chow 3d post I/R. 16d post I/R, the difference between AAR & Remote equalized in standard chow while remaining under High-Fat-Diet. Conclusion Applying SMRT-technique, we generated the first time a complete full-length-transcriptome of the murine and human heart, identifying 15 novel potentially coding transcripts of PGC1-α and a novel exon 1. These transcripts are differentially regulated in experimental I/R in AAR and remote myocardium, suggesting transcriptional regulation and alternative splicing modulating PGC1-α function in heart. Differences between standard chow and high fat diet suggest impact of impaired glucose metabolism on regulatory processes after myocardial infarction. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Collaborative Research Centre 1116 (German Research Foundation)

Dynamic nanopore long-read sequencing analysis of HIV-1 splicing events during the early steps of infection

BackgroundAlternative splicing is a key step in Human Immunodeficiency Virus type 1 (HIV-1) replication that is tightly regulated both temporally and spatially. More than 50 different transcripts can be generated from a single HIV-1 unspliced pre-messenger RNA (pre-mRNA) and a balanced proportion of unspliced and spliced transcripts is critical for the production of infectious virions. Understanding the mechanisms involved in the regulation of viral RNA is therefore of potential therapeutic interest. However, monitoring the regulation of alternative splicing events at a transcriptome-wide level during cell infection is challenging. Here we used the long-read cDNA sequencing developed by Oxford Nanopore Technologies (ONT) to explore in a quantitative manner the complexity of the HIV-1 transcriptome regulation in infected primary CD4+ T cells.ResultsONT reads mapping to the viral genome proved sufficiently long to span all possible splice junctions, even distant ones, and to be assigned to a total of 150 exon combinations. Fifty-three viral RNA isoforms, including 14 new ones were further considered for quantification. Relative levels of viral RNAs determined by ONT sequencing showed a high degree of reproducibility, compared favourably to those produced in previous reports and highly correlated with quantitative PCR (qPCR) data. To get further insights into alternative splicing regulation, we then compiled quantifications of splice site (SS) usage and transcript levels to build “splice trees”, a quantitative representation of the cascade of events leading to the different viral isoforms. This approach allowed visualizing the complete rewiring of SS usages upon perturbation of SS D2 and its impact on viral isoform levels. Furthermore, we produced the first dynamic picture of the cascade of events occurring between 12 and 24 h of viral infection. In particular, our data highlighted the importance of non-coding exons in viral RNA transcriptome regulation.ConclusionONT sequencing is a convenient and reliable strategy that enabled us to grasp the dynamic of the early splicing events modulating the viral RNA landscape in HIV-1 infected cells.

Systematic profiling of alternative splicing in Helicobacter pylori-negative gastric cancer and their clinical significance

BackgroundAlternative splicing (AS) may cause structural and functional variations in the protein to promote the proliferation of tumor cells. However, there is no comprehensive analysis of the clinical significance of AS in Helicobacter pylori-negative gastric cancer (HP− GC).MethodsThe clinical, gene expression profile data and AS events of 138 HP− GC patients were obtained from the database named the cancer genome atlas. Differently expressed AS (DEAS) events were determined by a comparison of the PSI values between HP− GC samples and adjacent normal samples. Unsupervised clustering analysis, proportional regression and Kaplan–Meier analysis were used to explore the association between clinical data and immune features and to establish two nomograms about the prognosis of HP− GC. Finally, splicing networks were constructed using Cytoscape.ResultsA total of 48141 AS events and 1041 DEAS events were found in HP− GC. Various functions and pathways of DEAS events parent genes were enriched, such as cell-substrate junction, cell leading edge, focal adhension, and AMPK signaling. Seven overall survival (OS)-related and seven disease-free survival (DFS)-related AS events were used to construct the prognostic signatures. Based on the independent prognostic factors, two nomograms were established and showed excellent performance. Then, splicing regulatory networks among the correlations suggested that splicing factors were significantly associated with prognostic DEASs. Finally, the unsupervised clustering analysis revealed that DEAS-based clusters were associated with clinical characteristics, tumor microenvironment, tumor mutation burden, and immune features.ConclusionSeven OS-related and seven DFS-related AS events have been found to be correlated with the prognosis of HP− GC and can be used as prognostic factors to establish an effective nomogram.

A single mutation in the ACTR8 gene associated with lineage-specific expression in primates

BackgroundAlternative splicing (AS) generates various transcripts from a single gene and thus plays a significant role in transcriptomic diversity and proteomic complexity. Alu elements are primate-specific transposable elements (TEs) and can provide a donor or acceptor site for AS. In a study on TE-mediated AS, we recently identified a novel AluSz6-exonized ACTR8 transcript of the crab-eating monkey (Macaca fascicularis). In the present study, we sought to determine the molecular mechanism of AluSz6 exonization of the ACTR8 gene and investigate its evolutionary and functional consequences in the crab-eating monkey.ResultsWe performed RT-PCR and genomic PCR to analyze AluSz6 exonization in the ACTR8 gene and the expression of the AluSz6-exonized transcript in nine primate samples, including prosimians, New world monkeys, Old world monkeys, and hominoids. AluSz6 integration was estimated to have occurred before the divergence of simians and prosimians. The Alu-exonized transcript obtained by AS was lineage-specific and expressed only in Old world monkeys and apes, and humans. This lineage-specific expression was caused by a single G duplication in AluSz6, which provides a new canonical 5′ splicing site. We further identified other alternative transcripts that were unaffected by the AluSz6 insertion. Finally, we observed that the alternative transcripts were transcribed into new isoforms with C-terminus deletion, and in silico analysis showed that these isoforms do not have a destructive function.ConclusionsThe single G duplication in the TE sequence is the source of TE exonization and AS, and this mutation may suffer a different fate of ACTR8 gene expression during primate evolution.

CuAS: a database of annotated transcripts generated by alternative splicing in cucumbers

BackgroundAlternative splicing (AS) plays a critical regulatory role in modulating transcriptome and proteome diversity. In particular, it increases the functional diversity of proteins. Recent genome-wide analysis of AS using RNA-Seq has revealed that AS is highly pervasive in plants. Furthermore, it has been suggested that most AS events are subject to tissue-specific regulation.DescriptionTo reveal the functional characteristics induced by AS and tissue-specific splicing events, a database for exploring these characteristics is needed, especially in plants. To address these goals, we constructed a database of annotated transcripts generated by alternative splicing in cucumbers (CuAS: http://cmb.bnu.edu.cn/alt_iso/index.php) that integrates genomic annotations, isoform-level functions, isoform-level features, and tissue-specific AS events among multiple tissues. CuAS supports a retrieval system that identifies unique IDs (gene ID, isoform ID, UniProt ID, and gene name), chromosomal positions, and gene families, and a browser for visualization of each gene.ConclusionWe believe that CuAS could be helpful for revealing the novel functional characteristics induced by AS and tissue-specific AS events in cucumbers. CuAS is freely available at http://cmb.bnu.edu.cn/alt_iso/index.php.

DTA-SiST: de novo transcriptome assembly by using simplified suffix trees

BackgroundAlternative splicing allows the pre-mRNAs of a gene to be spliced into various mRNAs, which greatly increases the diversity of proteins. High-throughput sequencing of mRNAs has revolutionized our ability for transcripts reconstruction. However, the massive size of short reads makes de novo transcripts assembly an algorithmic challenge.ResultsWe develop a novel radical framework, called DTA-SiST, for de novo transcriptome assembly based on suffix trees. DTA-SiST first extends contigs by reads that have the longest overlaps with the contigs’ terminuses. These reads can be found in linear time of the lengths of the reads through a well-designed suffix tree structure. Then, DTA-SiST constructs splicing graphs based on contigs for each gene locus. Finally, DTA-SiST proposes two strategies to extract transcript-representing paths: a depth-first enumeration strategy and a hybrid strategy based on length and coverage. We implemented the above two strategies and compared them with the state-of-the-art de novo assemblers on both simulated and real datasets. Experimental results showed that the depth-first enumeration strategy performs always better with recall and also better with precision for smaller datasets while the hybrid strategy leads with precision for big datasets.ConclusionsDTA-SiST performs more competitive than the other compared de novo assemblers especially with precision measure, due to the read-based contig extension strategy and the elegant transcripts extraction rules.

Differential isoform expression and alternative splicing in sex determination in mice

BackgroundAlternative splicing (AS) may play an important role in gonadal sex determination (GSD) in mammals. The present study was designed to identify differentially expressed isoforms and AS modifications accompanying GSD in mice.ResultsUsing deep RNA-sequencing, we performed a transcriptional analysis of XX and XY gonads during sex determination on embryonic days 11 (E11) and 12 (E12). Analysis of differentially expressed genes (DEG) identified hundreds of genes related to GSD and early sex differentiation that may represent good candidates for sex reversal. Expression at time point E11 in males was significantly enriched in RNA splicing and mRNA processing Gene Ontology terms. Differentially expressed isoform analysis identified hundreds of specific isoforms related to GSD, many of which showed no differences in the DEG analysis. Hundreds of AS events were identified as modified at E11 and E12. Female E11 gonads featured sex-biased upregulation of intron retention (in genes related to regulation of transcription, protein phosphorylation, protein transport and mRNA splicing) and exon skipping (in genes related to chromatin repression) suggesting AS as a post-transcription mechanism that controls sex determination of the bipotential fetal gonad.ConclusionOur data suggests an important role of splicing regulatory mechanisms for sex determination in mice.

BCL2L12: a multiply spliced gene with independent prognostic significance in breast cancer.

Background Alternative splicing is a key process in carcinogenesis and, from a clinical aspect, holds great promises, as alternatively spliced variants have emerged as an untapped source of diagnostic and prognostic markers. Our aim was to assess the prognostic value of three recently recognized splice variants of the apoptosis-related gene, BCL2L12, in breast cancer (BC). Methods Total RNA was extracted from breast samples (150 BC and 80 tumor-adjacent normal tissues) and, following cDNA synthesis, a variant-specific qPCR was performed for the expressional quantification of BCL2L12 v.1, v.2 and v.4 transcript variants. Extensive statistical analysis, including bootstrap resampling and internal validation, was conducted in order to evaluate the associations of v.1, v.2 and v.4 expression with patients' clinopathological and survival data. Results All examined BCL2L12 variants were significantly upregulated in BC specimens compared to their non-cancerous counterpart (v.1, p<0.001; v.2, p=0.009; v.4, p=0.004). Increased BCL2L12 v.4 mRNA expression was associated with markers of unfavorable prognosis namely, advanced tumor grade (p=0.002), ER- (p=0.015)/PR- (p<0.001) negativity, Ki-67-positivity (p=0.007) and high NPI (Nottingham prognostic index) score (p=0.033). Moreover, v.4 was significantly overexpressed in women with triple negative BC (TNBC) and HER2-positive tumors compared to those harboring luminal tumors (p<0.001). Survival analysis disclosed that BCL2L12 v.2 overexpression, as a continuous variable ([HR]=0.45, 95% CI=0.17-0.82, p=0.010), is a strong and independent marker of favorable prognosis for BC patients. Interestingly, v.2 retains its prognostic value in patients with Grade II/III ([HR]=0.21, 95% CI=0.05-0.57, p=0.006) or HER2-positive/TNBC tumors ([HR]=0.25, 95% CI=0.05-0.74, p=0.042). Conclusions BCL2L12 v.1, v.2, v.4 are aberrantly expressed in BC. Their expressional analysis by cost-effective molecular methods could provide a novel molecular tool for BC management.

Characterization of kinase gene expression and splicing profile in prostate cancer with RNA-Seq data

BackgroundAlternative splicing is a ubiquitous post-transcriptional regulation mechanism in most eukaryotic genes. Aberrant splicing isoforms and abnormal isoform ratios can contribute to cancer development. Kinase genes are key regulators of multiple cellular processes. Many kinases are found to be oncogenic and have been intensively investigated in the study of cancer and drugs. RNA-Seq provides a powerful technology for genome-wide study of alternative splicing in cancer besides the conventional gene expression profiling. But this potential has not been fully demonstrated yet.MethodsWe characterized the transcriptome profile of prostate cancer using RNA-Seq data from viewpoints of both differential expression and differential splicing, with an emphasis on kinase genes and their splicing variations. We built a pipeline to conduct differential expression and differential splicing analysis, followed by functional enrichment analysis. We performed kinase domain analysis to identify the functionally important candidate kinase gene in prostate cancer, and calculated the expression levels of isoforms to explore the function of isoform switching of kinase genes in prostate cancer.ResultsWe identified distinct gene groups from differential expression and splicing analyses, which suggested that alternative splicing adds another level to gene expression regulation. Enriched GO terms of differentially expressed and spliced kinase genes were found to play different roles in regulation of cellular metabolism. Function analysis on differentially spliced kinase genes showed that differentially spliced exons of these genes are significantly enriched in protein kinase domains. Among them, we found that gene CDK5 has isoform switching between prostate cancer and benign tissues, which may affect cancer development by changing androgen receptor (AR) phosphorylation. The observation was validated in another RNA-Seq dataset of prostate cancer cell lines.ConclusionsOur work characterized the expression and splicing profiles of kinase genes in prostate cancer and proposed a hypothetical model on isoform switching of CDK5 and AR phosphorylation in prostate cancer. These findings bring new understanding to the role of alternatively spliced kinases in prostate cancer and also demonstrate the use of RNA-Seq data in studying alternative splicing in cancer.

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods

BackgroundAlternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints.ResultsConsidering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method.ConclusionsIn the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

Manananggal - a novel viewer for alternative splicing events

BackgroundAlternative splicing is an important cellular mechanism that can be analyzed by RNA sequencing. However, identification of splicing events in an automated fashion is error-prone. Thus, further validation is required to select reliable instances of alternative splicing events (ASEs). There are only few tools specifically designed for interactive inspection of ASEs and available visualization approaches can be significantly improved.ResultsHere, we present Manananggal, an application specifically designed for the identification of splicing events in next generation sequencing data. Manananggal includes a web application for visual inspection and a command line tool that allows for ASE detection. We compare the sashimi plots available in the IGV Viewer, the DEXSeq splicing plots and SpliceSeq to the Manananggal interface and discuss the advantages and drawbacks of these tools. We show that sashimi plots (such as those used by the IGV Viewer and SpliceSeq) offer a practical solution for simple ASEs, but also indicate short-comings for highly complex genes.ConclusionManananggal is an interactive web application that offers functions specifically tailored to the identification of alternative splicing events that other tools are lacking. The ability to select a subset of isoforms allows an easier interpretation of complex alternative splicing events. In contrast to SpliceSeq and the DEXSeq splicing plot, Manananggal does not obscure the gene structure by showing full transcript models that makes it easier to determine which isoforms are expressed and which are not.

UlfasQTL: an ultra-fast method of composite splicing QTL analysis

BackgroundAlternative splicing plays important roles in many regulatory processes and diseases in human. Many genetic variants contribute to phenotypic differences in gene expression and splicing that determine variations in human traits. Detecting genetic variants that affect splicing phenotypes is essential for understanding the functional impact of genetic variations on alternative splicing. For many situations, the key phenotype is the relative splicing ratios of alternative isoforms rather than the expression values of individual isoforms. Splicing quantitative trait loci (sQTL) analysis methods have been proposed for detecting associations of genetic variants with the vectors of isoform splicing ratios of genes. We call this task as composite sQTL analysis. Existing methods are computationally intensive and cannot scale up for whole genome analysis.ResultsWe developed an ultra-fast method named ulfasQTL for this task based on a previous method sQTLseekeR. It transforms tests of splicing ratios of multiple genes to a matrix form for efficient computation, and therefore can be applied for sQTL analysis at whole-genome scales at the speed thousands times faster than the existing method. We tested ulfasQTL on the data from the GEUVADIS project and compared it with an existing method.ConclusionsulfasQTL is a very efficient tool for composite splicing QTL analysis and can be applied on whole-genome analysis with acceptable time.

The developing xylem transcriptome and genome-wide analysis of alternative splicing in Populus trichocarpa(black cottonwood) populations

BackgroundAlternative splicing (AS) of genes is an efficient means of generating variation in protein structure and function. AS variation has been observed between tissues, cell types, and different treatments in non-woody plants such as Arabidopsis thaliana (Arabidopsis) and rice. However, little is known about AS patterns in wood-forming tissues and how much AS variation exists within plant populations.ResultsHere we used high-throughput RNA sequencing to analyze the Populus trichocarpa (P. trichocarpa) xylem transcriptome in 20 individuals from different populations across much of its range in western North America. Deep transcriptome sequencing and mapping of reads to the P. trichocarpa reference genome identified a suite of xylem-expressed genes common to all accessions. Our analysis suggests that at least 36% of the xylem-expressed genes in P. trichocarpa are alternatively spliced. Extensive AS was observed in cell-wall biosynthesis related genes such as glycosyl transferases and C2H2 transcription factors. 27902 AS events were documented and most of these events were not conserved across individuals. Differences in isoform-specific read densities indicated that 7% and 13% of AS events showed significant differences between individuals within geographically separated southern and northern populations, a level that is in general agreement with AS variation in human populations.ConclusionsThis genome-wide analysis of alternative splicing reveals high levels of AS in P. trichocarpa and extensive inter-individual AS variation. We provide the most comprehensive analysis of AS in P. trichocarpa to date, which will serve as a valuable resource for the plant community to study transcriptome complexity and AS regulation during wood formation.