New Approach for Detection of Normal Alternative Splicing Events and Aberrant Spliceogenic Transcripts with Long-Range PCR and Deep RNA Sequencing.
Ontology highlight
ABSTRACT:
SUBMITTER: Dragos VS
PROVIDER: S-EPMC8389194 | biostudies-literature | 2021 Jul
REPOSITORIES: biostudies-literature
Publications
New Approach for Detection of Normal Alternative Splicing Events and Aberrant Spliceogenic Transcripts with Long-Range PCR and Deep RNA Sequencing.
Dragoš Vita Šetrajčič VŠ Stegel Vida V Blatnik Ana A Klančar Gašper G Krajc Mateja M Novaković Srdjan S
Biology 20210723 8
RNA sequencing is a promising technique for detecting normal and aberrant RNA isoforms. Here, we present a new single-gene, straightforward 1-day hands-on protocol for detection of splicing alterations with deep RNA sequencing from blood. We have validated our method's accuracy by detecting previously published normal splicing isoforms of <i>STK11</i> gene. Additionally, the same technique was used to provide the first comprehensive catalogue of naturally occurring alternative splicing events of ...[more]
Similar Datasets
Project description:Alternative splicing (AS), as an effective and universal mechanism of transcriptional regulation, is involved in the development and progression of cancer. Therefore, systematic analysis of alternative splicing in pancreatic adenocarcinoma (PAAD) is warranted. The corresponding clinical information of the RNA-Seq data and PAAD cohort was downloaded from the TCGA data portal. Then, a java application, SpliceSeq, was used to evaluate the RNA splicing pattern and calculate the splicing percentage index (PSI). Differentially expressed AS events (DEAS) were identified based on PSI values between PAAD cancer samples and normal samples of adjacent tissues. Kaplan-Meier and Cox regression analyses were used to assess the association between DEAS and patient clinical characteristics. Unsupervised cluster analysis used to reveal four clusters with different survival patterns. At the same time, GEO and TCGA combined with GTEx to verify the differential expression of AS gene and splicing factor. After rigorous filtering, a total of 45,313 AS events were identified, 1,546 of which were differentially expressed AS events. Nineteen DEAS were found to be associated with OS with a five-year overall survival rate of 0.946. And the subtype clusters results indicate that there are differences in the nature of individual AS that affect clinical outcomes. Results also identified 15 splicing factors associated with the prognosis of PAAD. And the splicing factors ESRP1 and RBM5 played an important role in the PAAD-associated AS events. The PAAD-associated AS events, splicing networks, and clusters identified in this study are valuable for deciphering the underlying mechanisms of AS in PAAD and may facilitate the establishment of therapeutic goals for further validation.
| S-EPMC8100795 | biostudies-literature
Project description:Retroviral vectors integrate in genes and regulatory elements and may cause transcriptional deregulation of gene expression in target cells. Integration into transcribed genes also has the potential to deregulate gene expression at the posttranscriptional level by interfering with splicing and polyadenylation of primary transcripts. To examine the impact of retroviral vector integration on transcript splicing, we transduced primary human cells or cultured cells with HIV-derived vectors carrying a reporter gene or a human ?-globin gene under the control of a reduced-size locus-control region (LCR). Cells were randomly cloned and integration sites were determined in individual clones. We identified aberrantly spliced, chimeric transcripts in more than half of the targeted genes in all cell types. Chimeric transcripts were generated through the use of constitutive and cryptic splice sites in the HIV 5? long terminal repeat and gag gene as well as in the ?-globin gene and LCR. Compared with constitutively spliced transcripts, most aberrant transcripts accumulated at a low level, at least in part as a consequence of nonsense-mediated mRNA degradation. A limited set of cryptic splice sites caused the majority of aberrant splicing events, providing a strategy for recoding lentiviral vector backbones and transgenes to reduce their potential posttranscriptional genotoxicity.
| S-EPMC3347495 | biostudies-literature
Project description:Myotonic dystrophy type 2 (DM2) is a genetic, autosomal dominant disease due to expansion of tetraplet (CCTG) repetitions in the first intron of the ZNF9/CNBP gene. DM2 is a multisystemic disorder affecting the skeletal muscle, the heart, the eye and the endocrine system. According to the proposed pathological mechanism, the expanded tetraplets have an RNA toxic effect, disrupting the splicing of many mRNAs. Thus, the identification of aberrantly spliced transcripts is instrumental for our understanding of the molecular mechanisms underpinning the disease. The aim of this study was the identification of new aberrant alternative splicing events in DM2 patients. By genome wide analysis of 10 DM2 patients and 10 controls (CTR), we identified 273 alternative spliced exons in 218 genes. While many aberrant splicing events were already identified in the past, most were new. A subset of these events was validated by qPCR assays in 19 DM2 and 15 CTR subjects. To gain insight into the molecular pathways involving the identified aberrantly spliced genes, we performed a bioinformatics analysis with Ingenuity system. This analysis indicated a deregulation of development, cell survival, metabolism, calcium signaling and contractility. In conclusion, our genome wide analysis provided a database of aberrant splicing events in the skeletal muscle of DM2 patients. The affected genes are involved in numerous pathways and networks important for muscle physio-pathology, suggesting that the identified variants may contribute to DM2 pathogenesis.
| S-EPMC3983107 | biostudies-literature
Project description:The killer-cell Ig-like receptors (KIR) form a multigene entity involved in modulating immune responses through interactions with MHC class I molecules. The complexity of the KIR cluster is reflected by, for instance, abundant levels of allelic polymorphism, gene copy number variation, and stochastic expression profiles. The current transcriptome study involving human and macaque families demonstrates that KIR family members are also subjected to differential levels of alternative splicing, and this seems to be gene dependent. Alternative splicing may result in the partial or complete skipping of exons, or the partial inclusion of introns, as documented at the transcription level. This post-transcriptional process can generate multiple isoforms from a single KIR gene, which diversifies the characteristics of the encoded proteins. For example, alternative splicing could modify ligand interactions, cellular localization, signaling properties, and the number of extracellular domains of the receptor. In humans, we observed abundant splicing for KIR2DL4, and to a lesser extent in the lineage III KIR genes. All experimentally documented splice events are substantiated by in silico splicing strength predictions. To a similar extent, alternative splicing is observed in rhesus macaques, a species that shares a close evolutionary relationship with humans. Splicing profiles of Mamu-KIR1D and Mamu-KIR2DL04 displayed a great diversity, whereas Mamu-KIR3DL20 (lineage V) is consistently spliced to generate a homolog of human KIR2DL5 (lineage I). The latter case represents an example of convergent evolution. Although just a single KIR splice event is shared between humans and macaques, the splicing mechanisms are similar, and the predicted consequences are comparable. In conclusion, alternative splicing adds an additional layer of complexity to the KIR gene system in primates, and results in a wide structural and functional variety of KIR receptors and its isoforms, which may play a role in health and disease.
| S-EPMC6288254 | biostudies-literature
Project description:Splicing misregulation, such as the inclusion of previously unknown cryptic exons, is implicated in numerous diseases. Recent methods have increased accurate and efficient detection of such splicing alterations occurring in disease phenotypes. However, the quantification and differential analyses of non-canonical splicing alterations remains focused at a splice event level, thus preventing a complete view of the effects on the downstream transcriptomic landscape. Here, we present a novel and integrated pipeline, SpliCeAT, that (1) detects and quantifies differential non-canonical splicing events from short-read bulk RNA-seq data, (2) augments the canonical transcriptome with novel transcripts containing these non-canonical splicing events, and (3) performs transcript-level differential analysis to identify and quantify aberrant cryptic exon-containing transcripts based on this augmented transcriptome. Using TDP-43, an ALS/FTD-associated RNA-binding protein as an example, we identified and catalogued aberrant splicing events in embryonic mouse brains. The accuracy of our integrated pipeline was further confirmed and validated with long-read isoform sequencing. Furthermore, by comparing neuronal TDP-43 knockouts in mice with a publicly available human dataset with TDP-43 pathology, we identified and validated 4 common genes, namely, Kalrn/KALRN, Poldip3/POLDIP3, Rnf144a/RNF144A, and Unc13a/UNC13A, with cryptic exons. In summary, our integrated pipeline, novel splice events are identified, incorporated and quantified at the transcript level, thereby enabling more complete transcriptome profiling of well-annotated genomes in in the case of pathological splicing misregulation.
2025-02-02 | GSE288457 | GEO
Project description:Different strategies of ovarian stimulation are widely used in IVF to retrieve mature metaphase II (MII) oocytes for fertilization. On average, approximately 70% of recovered oocytes are mature, while personalized administration of hCG and/or GnRH agonist trigger and in vitro maturation (IVM) management can further improve the maturation rate. However, even under such conditions, a complete absence of oocyte maturation is still observed sporadically. The probable causes for such maturation-deficient (MD) oocytes - which arrest abnormally at metaphase I (MI) stage - are still under investigation. In the present study, using single-cell transcriptomic RNA sequencing (RNA-seq) and differential expression analysis, we showed that gene expression profiles were aberrant, and alternative splicing (AS) patterns were changed in MD oocytes when compared with normally mature (MN) oocytes. Gene ontology (GO) enrichment demonstrated that the differently expressed genes (DEGs) were mostly correlated with pre-mRNA splicing, RNA transportation, RNA processing, and mRNA regulation. Subsequently, analysis of AS events revealed that genes with altered AS patterns were primarily associated with metabolism and cell cycle. With these findings, we have demonstrated aberrant gene expression in complete maturation-deficient oocytes, and we propose that alterations in post-transcriptional regulation constitute a potential underlying mechanism governing oocyte maturation.
| S-EPMC7513853 | biostudies-literature
Project description:BackgroundNon-alcoholic fatty liver disease (NAFLD) is one of most common diseases in the world. Recently, alternative splicing (AS) has been reported to play a key role in NAFLD processes in mammals. Ducks can quickly form fatty liver similar to human NAFLD after overfeeding and restore to normal liver in a short time, suggesting that ducks are an excellent model to unravel molecular mechanisms of lipid metabolism for NAFLD. However, how alternative splicing events (ASEs) affect the fatty liver process in ducks is still unclear.ResultsHere we identify 126,277 unique transcripts in liver tissue from an overfed duck (77,237 total transcripts) and its sibling control (69,618 total transcripts). We combined these full-length transcripts with Illumina RNA-seq data from five pairs of overfed ducks and control individuals. Full-length transcript sequencing provided us with structural information of transcripts and Illumina RNA-seq data reveals the expressional profile of each transcript. We found, among these unique transcripts, 30,618 were lncRNAs and 1,744 transcripts including 155 lncRNAs and 1,589 coding transcripts showed significantly differential expression in liver tissues between overfed ducks and control individuals. We also detected 27,317 ASEs and 142 of them showed significant relative abundance changes in ducks under different feeding conditions. Full-length transcript profiles together with Illumina RNA-seq data demonstrated that 10 genes involving in lipid metabolism had ASEs with significantly differential abundance in normally fed (control) and overfed ducks. Among these genes, protein products of five genes (CYP4F22, BTN, GSTA2, ADH5, and DHRS2 genes) were changed by ASEs.ConclusionsThis study presents an example of how to identify ASEs related to important biological processes, such as fatty liver formation, using full-length transcripts alongside Illumina RNA-seq data. Based on these data, we screened out ASEs of lipid-metabolism related genes which might respond to overfeeding. Our future ability to explore the function of genes showing AS differences between overfed ducks and their sibling controls, using genetic manipulations and co-evolutionary studies, will certainly extend our knowledge of genes related to the non-pathogenic fatty liver process.
| S-EPMC9976415 | biostudies-literature
Project description:The application of steatotic liver graft has been increased significantly due to the severe donor shortage and prevalence of non-alcoholic fatty liver disease. However, steatotic donor livers are vulnerable to acute phase inflammatory injury, which may result in cancer recurrence. Alternative splicing events (ASEs) are critical for diverse transcriptional variants in hepatocellular carcinoma (HCC). Here, we aimed to depict the landscape of ASEs, as well as to identify the differential ASEs in steatotic liver graft and their association with tumor recurrence after transplantation. The overall portrait of intragraft transcripts and ASEs were elucidated through RNA sequencing with the liver graft biopsies from patients and rat transplant models. Various differential ASEs were identified in steatotic liver grafts. CYP2E1, ADH1A, CYP2C8, ADH1C, and HGD, as corresponding genes to the common pathways involved differential ASEs in human and rats, were significantly associated with HCC patients' survival. The differential ASEs related RNA-binding proteins (RBPs) were enriched in metabolic pathways. The altered immune cell distribution, particularly macrophages and neutrophils, were perturbated by differential ASEs. The cancer hallmarks were enriched in steatotic liver grafts and closely associated with differential ASEs. Our work identified the differential ASE network with metabolic RBPs, immune cell distribution, and cancer hallmarks in steatotic liver grafts. We verified the link between steatotic liver graft injury and tumor recurrence at post-transcriptional level, offered new evidence to explore metabolism and immune responses, and provided the potential prognostic and therapeutic markers for tumor recurrence.
| S-EPMC10179559 | biostudies-literature
Project description:Alternative splicing (AS) is a closely regulated process that allows a single gene to encode multiple protein isoforms, thereby contributing to the diversity of the proteome. Dysregulation of the splicing process has been found to be associated with many inherited diseases. However, among the pathogenic AS events, there are numerous "passenger" events whose inclusion or exclusion does not lead to significant changes with respect to protein function. In this study, we evaluate the secondary and tertiary structural features of proteins associated with disease-causing and neutral AS events, and show that several structural features are strongly associated with the pathological impact of exon inclusion. We further develop a machine-learning-based computational model, ExonImpact, for prioritizing and evaluating the functional consequences of hitherto uncharacterized AS events. We evaluated our model using several strategies including cross-validation, and data from the Gene-Tissue Expression (GTEx) and ClinVar databases. ExonImpact is freely available at http://watson.compbio.iupui.edu/ExonImpact.
| S-EPMC5390777 | biostudies-literature
Project description:MotivationAdvancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The first involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence. To date, these models have utilized only expression data. In this work, we address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors.ResultsWe perform a detailed comparison of two previous modeling approaches, Bayesian and Deep Neural networks, dissecting the confounding effects of datasets and target functions. We then develop a new target function for AS prediction in exon skipping events and show it significantly improves model accuracy. Next, we develop a modeling framework that leverages transfer learning to incorporate CLIP-Seq, knockdown and over expression experiments, which are inherently noisy and suffer from missing values. Using several datasets involving key splice factors in mouse brain, muscle and heart we demonstrate both the prediction improvements and biological insights offered by our new models. Overall, the framework we propose offers a scalable integrative solution to improve splicing code modeling as vast amounts of relevant genomic data become available.Availability and implementationCode and data available at: majiq.biociphers.org/jha_et_al_2017/.Contactyosephb@upenn.edu.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5870723 | biostudies-literature