The interplay between microRNA and alternative splicing of linear and circular RNAs in eleven plant species

2019 ◽  
Vol 35 (17) ◽  
pp. 3119-3126 ◽  
Author(s):  
Huiyuan Wang ◽  
Huihui Wang ◽  
Hangxiao Zhang ◽  
Sheng Liu ◽  
Yongsheng Wang ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Plant Species ◽  
Single Molecule ◽  
Mirna Target ◽  
Supplementary Information ◽  
Circular Rnas ◽  
Sequencing Data ◽  
Genomic Locus ◽  
Target Sites ◽  
Alternatively Spliced

Abstract Motivation MicroRNA (miRNA) and alternative splicing (AS)-mediated post-transcriptional regulation has been extensively studied in most eukaryotes. However, the interplay between AS and miRNAs has not been explored in plants. To our knowledge, the overall profile of miRNA target sites in circular RNAs (circRNA) generated by alternative back splicing has never been reported previously. To address the challenge, we identified miRNA target sites located in alternatively spliced regions of the linear and circular splice isoforms using the up-to-date single-molecule real-time (SMRT) isoform sequencing (Iso-Seq) and Illumina sequencing data in eleven plant species. Results In total, we identified 399 401 and 114 574 AS events from linear and circular RNAs, respectively. Among them, there were 64 781 and 41 146 miRNA target sites located in linear and circular AS region, respectively. In addition, we found 38 913 circRNAs to be overlapping with 45 648 AS events of its own parent isoforms, suggesting circRNA regulation of AS of linear RNAs by forming R-loop with the genomic locus. Here, we present a comprehensive database of miRNA targets in alternatively spliced linear and circRNAs (ASmiR) and a web server for deposition and identification of miRNA target sites located in the alternatively spliced region of linear and circular RNAs. This database is accompanied by an easy-to-use web query interface for meaningful downstream analysis. Plant research community can submit user-defined datasets to the web service to search AS regions harboring small RNA target sites. In conclusion, this study provides an unprecedented resource to understand regulatory relationships between miRNAs and AS in both gymnosperms and angiosperms. Availability and implementation The readily accessible database and web-based tools are available at http://forestry.fafu.edu.cn/bioinfor/db/ASmiR. Supplementary information Supplementary data are available at Bioinformatics online.

AStrap: identification of alternative splicing from transcript sequences without a reference genome

2018 ◽  
Vol 35 (15) ◽  
pp. 2654-2656 ◽  
Author(s):  
Guoli Ji ◽  
Wenbin Ye ◽  
Yaru Su ◽  
Moliang Chen ◽  
Guangzao Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Alternative Splicing ◽  
Single Molecule ◽  
Reference Genome ◽  
De Novo ◽  
Supplementary Information ◽  
Model Organisms ◽  
Sequencing Data ◽  
Extensive Evaluation ◽  
Reference Genomes

Abstract Summary Alternative splicing (AS) is a well-established mechanism for increasing transcriptome and proteome diversity, however, detecting AS events and distinguishing among AS types in organisms without available reference genomes remains challenging. We developed a de novo approach called AStrap for AS analysis without using a reference genome. AStrap identifies AS events by extensive pair-wise alignments of transcript sequences and predicts AS types by a machine-learning model integrating more than 500 assembled features. We evaluated AStrap using collected AS events from reference genomes of rice and human as well as single-molecule real-time sequencing data from Amborella trichopoda. Results show that AStrap can identify much more AS events with comparable or higher accuracy than the competing method. AStrap also possesses a unique feature of predicting AS types, which achieves an overall accuracy of ∼0.87 for different species. Extensive evaluation of AStrap using different parameters, sample sizes and machine-learning models on different species also demonstrates the robustness and flexibility of AStrap. AStrap could be a valuable addition to the community for the study of AS in non-model organisms with limited genetic resources. Availability and implementation AStrap is available for download at https://github.com/BMILAB/AStrap. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Quantifying full-length circular RNAs in cancer

2021 ◽  
Author(s):  
Ken Hung-On Yu ◽  
Christina Huan Shi ◽  
Bo Wang ◽  
Savio Ho-Chit Chow ◽  
Grace Tin-Yun Chung ◽  
...  
Keyword(s):  
Experimental Data ◽  
Alternative Splicing ◽  
Nasopharyngeal Carcinoma ◽  
Computational Efficiency ◽  
Full Length ◽  
Circular Rnas ◽  
Sequencing Data ◽  
Response Elements ◽  
Different Types ◽  
Alternatively Spliced

AbstractCircular RNAs (circRNAs) are abundantly expressed in cancer. Their resistance to exonucleases enables them to have potentially stable interactions with different types of biomolecules. Alternative splicing can create different circRNA isoforms that have different sequences and unequal interaction potentials. The study of circRNA function thus requires knowledge of complete circRNA sequences. Here we describe psirc, a method that can identify full-length circRNA isoforms and quantify their expression levels from RNA sequencing data. We confirm the effectiveness and computational efficiency of psirc using both simulated and actual experimental data. Applying psirc on transcriptome profiles from nasopharyngeal carcinoma and normal nasopharynx samples, we discover and validate circRNA isoforms differentially expressed between the two groups. Compared to the assumed circular isoforms derived from linear transcript annotations, some of the alternatively spliced circular isoforms have 100 times higher expression and contain substantially fewer microRNA response elements, demonstrating the importance of quantifying full-length circRNA isoforms.

scholarly journals Quantifying full-length circular RNAs in cancer

2021 ◽  
pp. gr.275348.121
Author(s):  
Ken Hung-On Yu ◽  
Christina Huan Shi ◽  
Bo Wang ◽  
Savio Ho-Chit Chow ◽  
Grace Tin-Yun Chung ◽  
...  
Keyword(s):  
Experimental Data ◽  
Alternative Splicing ◽  
Nasopharyngeal Carcinoma ◽  
Computational Efficiency ◽  
Full Length ◽  
Circular Rnas ◽  
Sequencing Data ◽  
Response Elements ◽  
Different Types ◽  
Alternatively Spliced

Circular RNAs (circRNAs) are abundantly expressed in cancer. Their resistance to exonucleases enables them to have potentially stable interactions with different types of biomolecules. Alternative splicing can create different circRNA isoforms that have different sequences and unequal interaction potentials. The study of circRNA function thus requires knowledge of complete circRNA sequences. Here we describe psirc, a method that can identify full-length circRNA isoforms and quantify their expression levels from RNA sequencing data. We confirm the effectiveness and computational efficiency of psirc using both simulated and actual experimental data. Applying psirc on transcriptome profiles from nasopharyngeal carcinoma and normal nasopharynx samples, we discover and validate circRNA isoforms differentially expressed between the two groups. Compared to the assumed circular isoforms derived from linear transcript annotations, some of the alternatively spliced circular isoforms have 100 times higher expression and contain substantially fewer microRNA response elements, demonstrating the importance of quantifying full-length circRNA isoforms.

scholarly journals circtools—a one-stop software solution for circular RNA research

2018 ◽  
Vol 35 (13) ◽  
pp. 2326-2328 ◽  
Author(s):  
Tobias Jakobi ◽  
Alexey Uvarovskii ◽  
Christoph Dieterich
Keyword(s):  
High Throughput Sequencing ◽  
Circular Rna ◽  
Statistical Testing ◽  
Supplementary Information ◽  
Circular Rnas ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Multi Stage ◽  
Sequence Reconstruction ◽  
One Stop

Abstract Motivation Circular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, are not polyadenylated and have been shown to be highly specific for cell type and developmental stage. CircRNA detection starts from high-throughput sequencing data and is a multi-stage bioinformatics process yielding sets of potential circRNA candidates that require further analyses. While a number of tools for the prediction process already exist, publicly available analysis tools for further characterization are rare. Our work provides researchers with a harmonized workflow that covers different stages of in silico circRNA analyses, from prediction to first functional insights. Results Here, we present circtools, a modular, Python-based framework for computational circRNA analyses. The software includes modules for circRNA detection, internal sequence reconstruction, quality checking, statistical testing, screening for enrichment of RBP binding sites, differential exon RNase R resistance and circRNA-specific primer design. circtools supports researchers with visualization options and data export into commonly used formats. Availability and implementation circtools is available via https://github.com/dieterich-lab/circtools and http://circ.tools under GPLv3.0. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Biogenesis mechanisms of circular RNA can be categorized through feature extraction of a machine learning model

2019 ◽  
Vol 35 (23) ◽  
pp. 4867-4870
Author(s):  
Chengyu Liu ◽  
Yu-Chen Liu ◽  
Hsien-Da Huang ◽  
Wei Wang
Keyword(s):  
Feature Extraction ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Cpg Island ◽  
Cpg Islands ◽  
Circular Rna ◽  
Training Data ◽  
Supplementary Information ◽  
Circular Rnas ◽  
Genomic Locus

Abstract Motivation In recent years, multiple circular RNAs (circRNA) biogenesis mechanisms have been discovered. Although each reported mechanism has been experimentally verified in different circRNAs, no single biogenesis mechanism has been proposed that can universally explain the biogenesis of all tens of thousands of discovered circRNAs. Under the hypothesis that human circRNAs can be categorized according to different biogenesis mechanisms, we designed a contextual regression model trained to predict the formation of circular RNA from a random genomic locus on human genome, with potential biogenesis factors of circular RNA as the features of the training data. Results After achieving high prediction accuracy, we found through the feature extraction technique that the examined human circRNAs can be categorized into seven subgroups, according to the presence of the following sequence features: RNA editing sites, simple repeat sequences, self-chains, RNA binding protein binding sites and CpG islands within the flanking regions of the circular RNA back-spliced junction sites. These results support all of the previously reported biogenesis mechanisms of circRNA and solidify the idea that multiple biogenesis mechanisms co-exist for different subset of human circRNAs. Furthermore, we uncover a potential new links between circRNA biogenesis and flanking CpG island. We have also identified RNA binding proteins putatively correlated with circRNA biogenesis. Availability and implementation Scripts and tutorial are available at http://wanglab.ucsd.edu/star/circRNA. This program is under GNU General Public License v3.0. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Global Survey of the Full-Length Cabbage Transcriptome (Brassica oleracea Var. capitata L.) Reveals Key Alternative Splicing Events Involved in Growth and Disease Response

2021 ◽  
Vol 22 (19) ◽  
pp. 10443
Author(s):  
Yong Wang ◽  
Jialei Ji ◽  
Long Tong ◽  
Zhiyuan Fang ◽  
Limei Yang ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Brassica Oleracea ◽  
Single Molecule ◽  
Alternative Polyadenylation ◽  
Full Length ◽  
Genomic Research ◽  
Accurate Information ◽  
Sequencing Data ◽  
Specific Expression ◽  
Global Survey

Cabbage (Brassica oleracea L. var. capitata L.) is an important vegetable crop cultivated around the world. Previous studies of cabbage gene transcripts were primarily based on next-generation sequencing (NGS) technology which cannot provide accurate information concerning transcript assembly and structure analysis. To overcome these issues and analyze the whole cabbage transcriptome at the isoform level, PacBio RS II Single-Molecule Real-Time (SMRT) sequencing technology was used for a global survey of the full-length transcriptomes of five cabbage tissue types (root, stem, leaf, flower, and silique). A total of 77,048 isoforms, capturing 18,183 annotated genes, were discovered from the sequencing data generated through SMRT. The patterns of both alternative splicing (AS) and alternative polyadenylation (APA) were comprehensively analyzed. In total, we detected 13,468 genes which had isoforms containing APA sites and 8978 genes which underwent AS events. Moreover, 5272 long non-coding RNAs (lncRNAs) were discovered, and most exhibited tissue-specific expression. In total, 3147 transcription factors (TFs) were detected and 10 significant gene co-expression network modules were identified. In addition, we found that Fusarium wilt, black rot and clubroot infection significantly influenced AS in resistant cabbage. In summary, this study provides abundant cabbage isoform transcriptome data, which promotes reannotation of the cabbage genome, deepens our understanding of their post-transcriptional regulation mechanisms, and can be used for future functional genomic research.

Alternative Splicing for Mechanical Resilience: The Softening Effect of Filamin’s Hinge

2007 ◽  
Author(s):  
Dennis E. Discher ◽  
Colin Johnson
Keyword(s):  
Alternative Splicing ◽  
Protein Structure ◽  
Molecular Mechanics ◽  
Single Molecule ◽  
Rate Dependence ◽  
Random Coil ◽  
Thermal Unfolding ◽  
Softening Effect ◽  
Alternatively Spliced ◽  
Structural Methods

Alternative splicing within proteins is common but not well understood in its influence on protein structure and stability. Filamins are ubiquitous actin-crosslinking proteins with two dozen Immunolgobulin (Ig) repeats and one alternatively-spliced ‘hinge’ that has been hypothesized to add flexibility. The hinge is also predicted to perturb folding. The molecular mechanics of filamins are probed here by AFM-forced extension, with a particular focus on the ∼30 aa hinge between repeats R15 and R16. After re-examining full-length filamin to clarify the single molecule limit for AFM experiments on long chains, short concatemers of (R15-R16)m and (R15-hinge-R16)m were studied by both AFM and solution structural methods. AFM shows that the hinged isoform extends and unfolds at smaller forces (60 pN) than the hinge-less form (80 pN), implying that the alternative splicing introduces a random coil that softens both adjacent domains. Circular Dichroism confirms that the hinge is a random coil, and thermal unfolding in solution suggests a weak destabilization by the hinge. Together with the rate-dependence of forced extension in AFM, the results reveal added resilience as the unfolding transition shifts to longer lengths upon insertion of the alternatively spliced hinge.

scholarly journals Bivartect: accurate and memory-saving breakpoint detection by direct read comparison

2020 ◽  
Vol 36 (9) ◽  
pp. 2725-2730
Author(s):  
Keisuke Shimmura ◽  
Yuki Kato ◽  
Yukio Kawahara
Keyword(s):  
Genome Editing ◽  
High Throughput Sequencing ◽  
Variant Calling ◽  
Simulated Data ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Node ◽  
Single Nucleotide ◽  
Target Sites

Abstract Motivation Genetic variant calling with high-throughput sequencing data has been recognized as a useful tool for better understanding of disease mechanism and detection of potential off-target sites in genome editing. Since most of the variant calling algorithms rely on initial mapping onto a reference genome and tend to predict many variant candidates, variant calling remains challenging in terms of predicting variants with low false positives. Results Here we present Bivartect, a simple yet versatile variant caller based on direct comparison of short sequence reads between normal and mutated samples. Bivartect can detect not only single nucleotide variants but also insertions/deletions, inversions and their complexes. Bivartect achieves high predictive performance with an elaborate memory-saving mechanism, which allows Bivartect to run on a computer with a single node for analyzing small omics data. Tests with simulated benchmark and real genome-editing data indicate that Bivartect was comparable to state-of-the-art variant callers in positive predictive value for detection of single nucleotide variants, even though it yielded a substantially small number of candidates. These results suggest that Bivartect, a reference-free approach, will contribute to the identification of germline mutations as well as off-target sites introduced during genome editing with high accuracy. Availability and implementation Bivartect is implemented in C++ and available along with in silico simulated data at https://github.com/ykat0/bivartect. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Position-wise binding preference is important for miRNA target site prediction

2020 ◽  
Vol 36 (12) ◽  
pp. 3680-3686
Author(s):  
Amlan Talukder ◽  
Xiaoman Li ◽  
Haiyan Hu
Keyword(s):  
Dynamic Programming ◽  
Markov Model ◽  
Mirna Target ◽  
Dynamic Programming Algorithm ◽  
Target Prediction ◽  
Target Site ◽  
Mirna Target Site ◽  
Supplementary Information ◽  
Target Sites ◽  
Target Binding

Abstract Motivation It is a fundamental task to identify microRNAs (miRNAs) targets and accurately locate their target sites. Genome-scale experiments for miRNA target site detection are still costly. The prediction accuracies of existing computational algorithms and tools are often not up to the expectation due to a large number of false positives. One major obstacle to achieve a higher accuracy is the lack of knowledge of the target binding features of miRNAs. The published high-throughput experimental data provide an opportunity to analyze position-wise preference of miRNAs in terms of target binding, which can be an important feature in miRNA target prediction algorithms. Results We developed a Markov model to characterize position-wise pairing patterns of miRNA–target interactions. We further integrated this model as a scoring method and developed a dynamic programming (DP) algorithm, MDPS (Markov model-scored Dynamic Programming algorithm for miRNA target site Selection) that can screen putative target sites of miRNA-target binding. The MDPS algorithm thus can take into account both the dependency of neighboring pairing positions and the global pairing information. Based on the trained Markov models from both miRNA-specific and general datasets, we discovered that the position-wise binding information specific to a given miRNA would benefit its target prediction. We also found that miRNAs maintain region-wise similarity in their target binding patterns. Combining MDPS with existing methods significantly improves their precision while only slightly reduces their recall. Therefore, position-wise pairing patterns have the promise to improve target prediction if incorporated into existing software tools. Availability and implementation The source code and tool to calculate MDPS score is available at http://hulab.ucf.edu/research/projects/MDPS/index.html. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SRPK1/2 and PP1α exert opposite functions by modulating SRSF1-guided MKNK2 alternative splicing in colon adenocarcinoma

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Hongda Liu ◽  
Zheng Gong ◽  
Kangshuai Li ◽  
Qun Zhang ◽  
Zekuan Xu ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Colon Adenocarcinoma ◽  
Mapk Signaling ◽  
Splicing Factor ◽  
Tumor Proliferation ◽  
Sequencing Data ◽  
Alternatively Spliced ◽  
Xenograft Models ◽  
Splicing Isoforms ◽  
Splicing Factor 1

Abstract Background The Mnk2 kinase, encoded by MKNK2 gene, plays critical roles in MAPK signaling and was involved in oncogenesis. Human MKNK2 pre-mRNA can be alternatively spliced into two splicing isoforms, the MKNK2a and MKNK2b, thus yielding Mnk2a and Mnk2b proteins with different domains. The involvement of Mnk2 alternative splicing in colon cancer has been implicated based on RNA-sequencing data from TCGA database. This study aimed at investigating the upstream modulators and clinical relevance of Mnk2 alternative splicing in colon adenocarcinoma (CAC). Methods PCR, western blotting and immunohistochemistry (IHC) were performed to assess the expression of Mnk2 and upstream proteins in CAC. The function of Mnk2 and its regulators were demonstrated in different CAC cell lines as well as in xenograft models. Two independent cohorts of CAC patients were used to reveal the clinical significance of MKNK2 alternative splicing. Results Comparing with adjacent nontumorous tissue, CAC specimen showed a decreased MKNK2a level and an increased MKNK2b level, which were correlated with KRAS mutation and tumor size. The SRSF1 (serine/arginine-rich splicing factor 1) was further confirmed to be the major splicing factor targeting MKNK2 in CAC cells. Higher expression of SRPK1/2 or decreased activity of PP1α were responsible for enhancing SRSF1 phosphorylation and nucleus translocation, subsequently resulted in a switch of MKNK2 alternative splicing. Conclusions Our data showed that phosphorylation and subcellular localization of SRSF1 were balanced by SRPK1/2 and PP1α in CAC cells. High nucleus SRSF1 promoted MKNK2 splicing into MKNK2b instead of MNK2a, consequently enhanced tumor proliferation.

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