Browsing by Author "Shrestha, Sirjana"

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A computational approach for identifying microRNA-target interactions using high-throughput CLIP and PAR-CLIP sequencing
(2013-01-21)
Chou, Chih-Hung
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Lin, Feng-Mao
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Chou, Min-Te
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Hsu, Sheng-Da
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Chang, Tzu-Hao
Background: MicroRNAs (miRNAs) play a critical role in down-regulating gene expression. By coupling with Argonaute family proteins, miRNAs bind to target sites on mRNAs and employ translational repression. A large amount of miRNA-target interactions (MTIs) have been identified by the crosslinking and immunoprecipitation (CLIP) and the photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) along with the next-generation sequencing (NGS). PAR-CLIP shows high efficiency of RNA co-immunoprecipitation, but it also lead to T to C conversion in miRNA-RNA-protein crosslinking regions. This artificial error obviously reduces the mappability of reads. However, a specific tool to analyze CLIP and PAR-CLIP data that takes T to C conversion into account is still in need. Results: We herein propose the first CLIP and PAR-CLIP sequencing analysis platform specifically for miRNA target analysis, namely miRTarCLIP. From scratch, it automatically removes adaptor sequences from raw reads, filters low quality reads, reverts C to T, aligns reads to 3'UTRs, scans for read clusters, identifies high confidence miRNA target sites, and provides annotations from external databases. With multi-threading techniques and our novel C to T reversion procedure, miRTarCLIP greatly reduces the running time comparing to conventional approaches. In addition, miRTarCLIP serves with a web-based interface to provide better user experiences in browsing and searching targets of interested miRNAs. To demonstrate the superior functionality of miRTarCLIP, we applied miRTarCLIP to two public available CLIP and PAR-CLIP sequencing datasets. miRTarCLIP not only shows comparable results to that of other existing tools in a much faster speed, but also reveals interesting features among these putative target sites. Specifically, we used miRTarCLIP to disclose that T to C conversion within position 1-7 and that within position 8-14 of miRNA target sites are significantly different (p value = 0.02), and even more significant when focusing on sites targeted by top 102 highly expressed miRNAs only (p value = 0.01). These results comply with previous findings and further suggest that combining miRNA expression and PAR-CLIP data can improve accuracy of the miRNA target prediction. Conclusion: To sum up, we devised a systematic approach for mining miRNA-target sites from CLIP-seq and PAR-CLIP sequencing data, and integrated the workflow with a graphical web-based browser, which provides a user friendly interface and detailed annotations of MTIs. We also showed through real-life examples that miRTarCLIP is a powerful tool for understanding miRNAs. Our integrated tool can be accessed online freely at http://miRTarCLIP.mbc.nctu.edu.tw.
A systematic review of microRNA expression profiling studies in human gastric cancer
(2014-08-01)
Shrestha, Sirjana
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Hsu, Sheng-Da
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Huang, Wei-Yun
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Huang, Hsi-Yuan
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Chen, WenLiang
Gastric cancer (GC) is the second leading cause of global cancer mortality. Most GC patients are diagnosed with advanced-stage disease and show extremely poor prognosis. All of the GC research has a common interest to search for the specific and sensitive biomarkers for early diagnosis of GC. Number of microRNAs play important role in GC. We carried out a systematic review of published miRNA profiling studies that compared the miRNA expression profiles between GC tissues and paired noncancerous gastric tissue. A vote-counting strategy was followed with the collection of information like total number of studies reporting differential expression of miRNA, total number of tissue samples used in the studies, direction of differential expression and fold change. A total of 352 differentially expressed microRNAs were reported in the 14 microRNA expression profiling studies that compared GC tissues with normal tissues with 120 microRNAs reported at least in two studies. In the group of consistently reported microRNAs, miR-21 was reported upregulated in 10 studies followed by miR-25, miR-92, and miR-223 upregulated in eight studies. MiR-375 and miR-148a were found downregulated in six and five studies, respectively, followed by miR-638 in four studies. MiR-107 and miR-103 were reported in nine and eight studies, respectively, but their expression were inconsistent. From this study, the most consistently reported upregulated microRNA was found to be miR-21. This systematic review study of human GC microRNA expression profiling studies would provide information on microRNAs with potential role as the biomarkers in gastric cancer.
Integrated MicroRNA-mRNA Analysis Reveals miR-204 Inhibits Cell Proliferation in Gastric Cancer by Targeting CKS1B, CXCL1 and GPRC5A
(2018-01-01)
Shrestha, Sirjana
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Yang, Chi-Dung
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Hong, Hsiao-Chin
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Chou, Chih-Hung
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Tai, Chun-San
Gastric cancer (GC) is the second most frequent cause of cancer-related deaths worldwide. MicroRNAs are single-stranded RNA molecules of 21-23 nucleotides that regulate target gene expression through specific base-pairing interactions between miRNA and untranslated regions of targeted mRNAs. In this study, we generated a multistep approach for the integrated analysis of miRNA and mRNA expression. First, both miRNA and mRNA expression profiling datasets in gastric cancer from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) identified 79 and 1042 differentially expressed miRNAs and mRNAs, respectively, in gastric cancer. Second, inverse correlations between miRNA and mRNA expression levels identified 3206 miRNA-mRNA pairs combined with 79 dysregulated miRNAs and their 774 target mRNAs predicted by three prediction tools, miRanda, PITA, and RNAhybrid. Additionally, miR-204, which was found to be down-regulated in gastric cancer, was ectopically over-expressed in the AGS gastric cancer cell line and all down-regulated targets were identified by RNA sequencing (RNA-seq) analysis. Over-expression of miR-204 reduced the gastric cancer cell proliferation and suppressed the expression of three targets which were validated by qRT-PCR and luciferase assays. For the first time, we identified that CKS1B, CXCL1, and GPRC5A are putative targets of miR-204 and elucidated that miR-204 acted as potential tumor suppressor and, therefore, are useful as a promising therapeutic target for gastric cancer.
Large-Scale Functional Analysis of CRP-Mediated Feed-Forward Loops
(2018-08-01)
Yang, Chi-Dung
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Huang, Hsi-Yuan
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Shrestha, Sirjana
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Chen, Yen-Hua
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Huang, Hsien-Da
Feed-forward loops (FFLs) represent an important and basic network motif to understand specific biological functions. Cyclic-AMP (cAMP) receptor protein (CRP), a transcription factor (TF), mediates catabolite repression and regulates more than 400 genes in response to changes in intracellular concentrations of cAMP in Escherichia coli. CRP participates in some FFLs, such as araBAD and araFGH operons and adapts to fluctuating environmental nutrients, thereby enhancing the survivability of E. coli. Although computational simulations have been conducted to explore the potential functionality of FFLs, a comprehensive study on the functions of all structural types on the basis of in vivo data is lacking. Moreover, the regulatory role of CRP-mediated FFLs (CRP-FFLs) remains obscure. We identified 393 CRP-FFLs in E. coli using EcoCyc and RegulonDB. Dose-response genomic microarray of E. coli revealed dynamic gene expression of each target gene of CRP-FFLs in response to a range of cAMP dosages. All eight types of FFLs were present in CRP regulon with various expression patterns of each CRP-FFL, which were further divided into five functional groups. The microarray and reported regulatory relationships identified 202 CRP-FFLs that were directly regulated by CRP in these eight types of FFLs. Interestingly, 34% (147/432) of genes were directly regulated by CRP and CRP-regulated TFs, which indicates that these CRP-regulated genes were also regulated by other CRP-regulated TFs responding to environmental signals through CRP-FFLs. Furthermore, we applied gene ontology annotation to reveal the biological functions of CRP-FFLs.
miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database
(2016-01-04)
Chou, Chih-Hung
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Chang, Nai-Wen
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Shrestha, Sirjana
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Hsu, Sheng-Da
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Lin, Yu-Ling
MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.
miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database
(2020-01-08)
Huang, Hsi-Yuan
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Lin, Yang-Chi-Dung
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Li, Jing
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Huang, Kai-Yao
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Shrestha, Sirjana
MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18-25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA-target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA-target interaction databases.
miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions
(2014-01-01)
Hsu, Sheng-Da
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Tseng, Yu-Ting
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Shrestha, Sirjana
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Lin, Yu-Ling
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Khaleel, Anas
MicroRNAs (miRNAs) are small non-coding RNA molecules capable of negatively regulating gene expression to control many cellular mechanisms. The miRTarBase database (http://mirtarbase.mbc.nctu.edu.tw/) provides the most current and comprehensive information of experimentally validated miRNA-target interactions. The database was launched in 2010 with data sources for >100 published studies in the identification of miRNA targets, molecular networks of miRNA targets and systems biology, and the current release (2013, version 4) includes significant expansions and enhancements over the initial release (2010, version 1). This article reports the current status of and recent improvements to the database, including (i) a 14-fold increase to miRNA-target interaction entries, (ii) a miRNA-target network, (iii) expression profile of miRNA and its target gene, (iv) miRNA target-associated diseases and (v) additional utilities including an upgrade reminder and an error reporting/user feedback system.
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
(2018-01-04)
Chou, Chih-Hung
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Shrestha, Sirjana
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Yang, Chi-Dung
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Chang, Nai-Wen
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Lin, Yu-Ling
MicroRNAs (miRNAs) are small non-coding RNAs of similar to 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased similar to 1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
Pilot Study to Establish a Novel Five-Gene Biomarker Panel for Predicting Lymph Node Metastasis in Patients With Early Stage Endometrial Cancer
(2020-01-21)
Huang, Chia-Yen
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Liao, Kuang-Wen
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Chou, Chih-Hung
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Shrestha, Sirjana
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Yang, Chi-Dung
Introduction: In the United States and Europe, endometrial endometrioid carcinoma (EEC) is the most prevalent gynecologic malignancy. Lymph node metastasis (LNM) is the key determinant of the prognosis and treatment of EEC. A biomarker that predicts LNM in patients with EEC would be beneficial, enabling individualized treatment. Current preoperative assessment of LNM in EEC is not sufficiently accurate to predict LNM and prevent overtreatment. This pilot study established a biomarker signature for the prediction of LNM in early stage EEC. Methods: We performed RNA sequencing in 24 clinically early stage (T1) EEC tumors (lymph nodes positive and negative in 6 and 18, respectively) from Cathay General Hospital and analyzed the RNA sequencing data of 289 patients with EEC from The Cancer Genome Atlas (lymph node positive and negative in 33 and 256, respectively). We analyzed clinical data including tumor grade, depth of tumor invasion, and age to construct a sequencing-based prediction model using machine learning. For validation, we used another independent cohort of early stage EEC samples (n = 72) and performed quantitative real-time polymerase chain reaction (qRT-PCR). Finally, a PCR-based prediction model and risk score formula were established. Results: Eight genes (ASRGL1, ESR1, EYA2, MSX1, RHEX, SCGB2A1, SOX17, and STX18) plus one clinical parameter (depth of myometrial invasion) were identified for use in a sequencing-based prediction model. After qRT-PCR validation, five genes (ASRGL1, RHEX, SCGB2A1, SOX17, and STX18) were identified as predictive biomarkers. Receiver operating characteristic curve analysis revealed that these five genes can predict LNM. Combined use of these five genes resulted in higher diagnostic accuracy than use of any single gene, with an area under the curve of 0.898, sensitivity of 88.9%, and specificity of 84.1%. The accuracy, negative, and positive predictive values were 84.7, 98.1, and 44.4%, respectively. Conclusion: We developed a five-gene biomarker panel associated with LNM in early stage EEC. These five genes may represent novel targets for further mechanistic study. Our results, after corroboration by a prospective study, may have useful clinical implications and prevent unnecessary elective lymph node dissection while not adversely affecting the outcome of treatment for early stage EEC.
SVAD: A genetic database curates non-ischemic sudden cardiac death-associated variants
(2020-08-19)
Huang, Wei-Chih
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Huang, Hsin-Tzu
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Chen, Po-Yuan
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Wang, Wei-Chi
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Ko, Tai-Ming
Sudden cardiac death (SCD) is an important cause of mortality worldwide. It accounts for approximately half of all deaths from cardiovascular disease. While coronary artery disease and acute myocardial infarction account for the majority of SCD in the elderly population, inherited cardiac diseases (inherited CDs) comprise a substantial proportion of younger SCD victims with a significant genetic component. Currently, the use of next-generation sequencing enables the rapid analysis to investigate relationships between genetic variants and inherited CDs causing SCD. Genetic contribution to risk has been considered an alternate predictor of SCD. In the past years, large numbers of SCD susceptibility variants were reported, but these results are scattered in numerous publications. Here, we present the SCD-associated Variants Annotation Database (SVAD) to facilitate the interpretation of variants and to meet the needs of data integration. SVAD contains data from a broad screening of scientific literature. It was constructed to provide a comprehensive collection of genetic variants along with integrated information regarding their effects. At present, SVAD has accumulated 2,292 entries within 1,239 variants by manually surveying pertinent literature, and approximately one-third of the collected variants are pathogenic/likely-pathogenic following the ACMG guidelines. To the best of our knowledge, SVAD is the most comprehensive database that can provide integrated information on the associated variants in various types of inherited CDs. SVAD represents a valuable source of variant information based on scientific literature and benefits clinicians and researchers, and it is now available on.