Browsing by Author "Chen, Ting-Wen"

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Characterization of Copy Number Variations in Oral Cavity Squamous Cell Carcinoma Reveals a Novel Role for MLLT3 in Cell Invasiveness
(1970-01-01)
Wang, Chun-, I
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Kao, Huang-Kai
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Chen, Ting-Wen
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Huang, Yenlin
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Cheng, Hsing-Wen
Background DNA copy number variations (CNVs) are a hallmark of cancer, and the current study aimed to demonstrate the profile of the CNVs for oral cavity squamous cell carcinoma (OSCC) and elucidate the clinicopathological associations and molecular mechanisms of a potential marker derived from CNVs, mixed-lineage leukemia translocated to chromosome 3 protein (MLLT3), in OSCC carcinogenesis. Materials and Methods CNVs in 37 OSCC tissue specimens were analyzed using a high-resolution microarray, the OncoScan array. Gene expression was analyzed by real-time polymerase chain reaction in 127 OSCC and normal tissue samples. Cell function assays included cell cycle, migration, invasion and chromatin immunoprecipitation assays. Results We found a novel copy number amplified region, chromosome 9p, encompassing MLLT3 via the comparison of our data set with six other OSCC genome-wide CNV data sets. MLLT3 overexpression was associated with poorer overall survival in patients with OSCC (p = .048). MLLT3 knockdown reduced cell migration and invasion. The reduced invasion ability in MLLT3-knockdown cells was rescued with double knockdown of MLLT3 and CBP/p300-interacting transactivator with ED rich carboxy-terminal domain 4 (CITED4; 21.0% vs. 61.5%). Knockdown of MLLT3 impaired disruptor of telomeric silencing-1-like (Dot1L)-associated hypermethylation in the promoter of the tumor suppressor, CITED4 (p < .001), and hence dysregulated HIF-1 alpha-mediated genes (TWIST, MMP1, MMP2, VIM, and CDH1) in OSCC cells. Conclusion We identified unique CNVs in tumors of Taiwanese patients with OSCC. Notably, MLLT3 overexpression is related to the poorer prognosis of patients with OSCC and is required for Dot1L-mediated transcriptional repression of CITED4, leading to dysregulation of HIF-1 alpha-mediated genes. Implications for Practice This article reports unique copy number variations in oral cavity squamous cell carcinoma (OSCC) tumors of Taiwanese patients. Notably, MLLT3 overexpression is related to the poorer prognosis of patients with OSCC and is required for Dot1L-mediated transcriptional repression of CITED4, leading to dysregulation of HIF-1 alpha-mediated genes.
ChIPseek, a web-based analysis tool for ChIP data
(2014-06-30)
Chen, Ting-Wen
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Li, Hsin-Pai
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Lee, Chi-Ching
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Gan, Ruei-Chi
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Huang, Po-Jung
Background: Chromatin is a dynamic but highly regulated structure. DNA-binding proteins such as transcription factors, epigenetic and chromatin modifiers are responsible for regulating specific gene expression pattern and may result in different phenotypes. To reveal the identity of the proteins associated with the specific region on DNA, chromatin immunoprecipitation (ChIP) is the most widely used technique. ChIP assay followed by next generation sequencing (ChIP-seq) or microarray (ChIP-chip) is often used to study patterns of protein-binding profiles in different cell types and in cancer samples on a genome-wide scale. However, only a limited number of bioinformatics tools are available for ChIP datasets analysis. Results: We present ChIPseek, a web-based tool for ChIP data analysis providing summary statistics in graphs and offering several commonly demanded analyses. ChIPseek can provide statistical summary of the dataset including histogram of peak length distribution, histogram of distances to the nearest transcription start site (TSS), and pie chart (or bar chart) of genomic locations for users to have a comprehensive view on the dataset for further analysis. For examining the potential functions of peaks, ChIPseek provides peak annotation, visualization of peak genomic location, motif identification, sequence extraction, and comparison between datasets. Beyond that, ChIPseek also offers users the flexibility to filter peaks and re-analyze the filtered subset of peaks. ChIPseek supports 20 different genome assemblies for 12 model organisms including human, mouse, rat, worm, fly, frog, zebrafish, chicken, yeast, fission yeast, Arabidopsis, and rice. We use demo datasets to demonstrate the usage and intuitive user interface of ChIPseek. Conclusions: ChIPseek provides a user friendly interface for biologists to analyze large scale ChIP data without requiring any programing skills. All the results and figures produced by ChIPseek can be downloaded for further analysis. The analysis tools built into ChIPseek, especially the ones for selecting and examine a subset of peaks from ChIP data, provides invaluable helps for exploring the high through-put data from either ChIP-seq or ChIP-chip.
Evaluation and Application of the Strand-Specific Protocol for Next-Generation Sequencing
(2015-01-01)
Tsai, Kuo-Wang
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Chang, Bill
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Pan, Cheng-Tsung
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Lin, Wei-Chen
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Chen, Ting-Wen
Next-generation sequencing (NGS) has become a powerful sequencing tool, applied in a wide range of biological studies. However, the traditional sample preparation protocol for NGS is non-strand-specific (NSS), leading to biased estimates of expression for transcripts overlapped at the antisense strand. Strand-specific (SS) protocols have recently been developed. In this study, we prepared the same RNA sample by using the SS and NSS protocols, followed by sequencing with Illumina HiSeq platform. Using real-time quantitative PCR as a standard, we first proved that the SS protocol more precisely estimates gene expressions compared with the NSS protocol, particularly for those overlapped at the antisense strand. In addition, we also showed that the sequence reads from the SS protocol are comparable with those from conventional NSS protocols in many aspects. Finally, we also mapped a fraction of sequence reads back to the antisense strand of the known genes, originally without annotated genes located. Using sequence assembly and PCR validation, we succeeded in identifying and characterizing the novel antisense genes. Our results show that the SS protocol performs more accurately than the traditional NSS protocol and can be applied in future studies.
FastAnnotator- an efficient transcript annotation web tool
(2012-12-13)
Chen, Ting-Wen
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Gan, Ruei-Chi Richie
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Wu, Timothy H.
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Huang, Po-Jung
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Lee, Cheng-Yang
Background: Recent developments in high-throughput sequencing (HTS) technologies have made it feasible to sequence the complete transcriptomes of non-model organisms or metatranscriptomes from environmental samples. The challenge after generating hundreds of millions of sequences is to annotate these transcripts and classify the transcripts based on their putative functions. Because many biological scientists lack the knowledge to install Linux-based software packages or maintain databases used for transcript annotation, we developed an automatic annotation tool with an easy-to-use interface. Methods: To elucidate the potential functions of gene transcripts, we integrated well-established annotation tools: Blast2GO, PRIAM and RPS BLAST in a web-based service, FastAnnotator, which can assign Gene Ontology (GO) terms, Enzyme Commission numbers (EC numbers) and functional domains to query sequences. Results: Using six transcriptome sequence datasets as examples, we demonstrated the ability of FastAnnotator to assign functional annotations. FastAnnotator annotated 88.1% and 81.3% of the transcripts from the well-studied organisms Caenorhabditis elegans and Streptococcus parasanguinis, respectively. Furthermore, FastAnnotator annotated 62.9%, 20.4%, 53.1% and 42.0% of the sequences from the transcriptomes of sweet potato, clam, amoeba, and Trichomonas vaginalis, respectively, which lack reference genomes. We demonstrated that FastAnnotator can complete the annotation process in a reasonable amount of time and is suitable for the annotation of transcriptomes from model organisms or organisms for which annotated reference genomes are not avaiable. Conclusions: The sequencing process no longer represents the bottleneck in the study of genomics, and automatic annotation tools have become invaluable as the annotation procedure has become the limiting step. We present FastAnnotator, which was an automated annotation web tool designed to efficiently annotate sequences with their gene functions, enzyme functions or domains. FastAnnotator is useful in transcriptome studies and especially for those focusing on non-model organisms or metatranscriptomes. FastAnnotator does not require local installation and is freely available at http://fastannotator.cgu.edu.tw.
Novel Role for miR-1290 in Host Species Specificity of Influenza A Virus
(2019-09-06)
Huang, Sheng-Yu
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Huang, Chih-Heng
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Chen, Chi-Jene
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Chen, Ting-Wen
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Lin, Chun-Yuan
The role of microRNA (miRNA) in influenza A virus (IAV) host species specificity is not well understood as yet. Here, we show that a host miRNA, miR-1290, is induced through the extracellular signal-regulated kinase (ERK) pathway upon IAV infection and is associated with increased viral titers in human cells and ferret animal models. miR-1290 was observed to target and reduce expression of the host vimentin gene. Vimentin binds with the PB2 subunit of influenza A virus ribonucleoprotein (vRNP), and knockdown of vimentin expression significantly increased vRNP nuclear retention and viral polymerase activity. Interestingly, miR-1290 was not detected in either chicken cells or mouse animal models, and the 3' UTR of the chicken vimentin gene contains no binding site for miR-1290. These findings point to a host species-specific mechanism by which IAV upregulates miR-1290 to disrupt vimentin expression and retain vRNP in the nucleus, thereby enhancing viral polymerase activity and viral replication.
PARRoT - a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms
(2016-12-22)
Gan, Ruei-Chi
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Chen, Ting-Wen
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Wu, Timothy H.
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Huang, Po-Jung
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Lee, Chi-Ching
Background: Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Results: Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. Conclusions: In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw.
PARRoT - a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms
(2016-12-22)
Gan, Ruei-Chi
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Chen, Ting-Wen
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Wu, Timothy H.
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Huang, Po-Jung
;
Lee, Chi-Ching
Background: Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Results: Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. Conclusions: In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw.
TACCO, a Database Connecting Transcriptome Alterations, Pathway Alterations and Clinical Outcomes in Cancers
(2019-03-07)
Chou, Po-Hao
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Liao, Wei-Chao
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Tsai, Kuo-Wang
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Chen, Ku-Chung
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Yu, Jau-Song
Because of innumerable cancer sequencing projects, abundant transcriptome expression profiles together with survival data are available from the same patients. Although some expression signatures for prognosis or pathologic staging have been identified from these data, systematically discovering such kind of expression signatures remains a challenge. To address this, we developed TACCO (Transcriptome Alterations in CanCer Omnibus), a database for identifying differentially expressed genes and altered pathways in cancer. TACCO also reveals miRNA cooperative regulations and supports construction of models for prognosis. The resulting signatures have great potential for patient stratification and treatment decision-making in future clinical applications. TACCO is freely available at http://tacco.life.nctu.edu.tw/.
Tigecycline-non-susceptible hypervirulent Klebsiella pneumoniae strains in Taiwan
(2020-02-01)
Cheng, Yi-Hsiang
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Huang, Tzu-Wen
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Juan, Chih-Han
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Chou, Sheng-Hua
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Tseng, Yao-Yi
Objectives Emergent antimicrobial-resistant hypervirulent Klebsiella pneumoniae (hvKp) is an important public health issue. We aimed to investigate resistance mechanisms and hypervirulent traits among tigecycline-non-susceptible (TNS) K. pneumoniae clinical strains, focusing on one hvKp strain with in vivo evolution of tigecycline resistance. Methods TNS K. pneumoniae strains causing invasive diseases in a medical centre in Taiwan between July 2015 and April 2018 were collected. Resistance mechanisms were determined and hvKp strains were defined as rmpA/rmpA2-carrying strains. Isogenic strains with and without tigecycline resistance were subjected to WGS and in vivo virulence testing. Further, site-directed mutagenesis was used to confirm the resistance mechanism. Results In total, 31 TNS K. pneumoniae strains were isolated, including six hypervirulent strains. Tigecycline resistance mechanisms were mostly caused by overexpression of AcrAB and OqxAB together with up-regulation of RamA or RarA, respectively. One TNS hypervirulent strain (KP1692; MIC=6mg/L) derived from its tigecycline-susceptible counterpart (KP1677; MIC=0.75mg/L) showed acrAB overexpression. WGS revealed four genetic variations between KP1677 and KP1692. In addition, using site-directed mutagenesis, we confirmed that a 1bp insertion in the ramA upstream region (RamR-binding site), leading to ramA and acrAB overexpression in KP1692, was responsible for tigecycline resistance. The in vivo virulence experiment showed that the TNS hvKp strain KP1692 still retained its high virulence compared with KP1677. Conclusions hvKp strains accounted for 19.4% among TNS strains. We identified alterations in the ramA upstream region as a mechanism of in vivo tigecycline resistance development in an hvKp strain.
VIP DB - A viral protein domain usage and distribution database
(2012-09-01)
Chen, Ting-Wen
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Gan, Richie Ruei-Chi
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Wu, Timothy H.
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Lin, Wen-Chang
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Tang, Petrus
During the viral infection and replication processes, viral proteins are highly regulated and may interact with host proteins. However, the functions and interaction partners of many viral proteins have yet to be explored. Here, we compiled a Viral Protein domain DataBase (VIP DB) to associate viral proteins with putative functions and interaction partners. We systematically assign domains and infer the functions of proteins and their protein interaction partners from their domain annotations. A total of 2,322 unique domains that were identified from 2,404 viruses are used as a starting point to correlate GO classification, KEGG metabolic pathway annotation and domain-domain interactions. Of the unique domains, 42.7% have GO records, 39.6% have at least one domain-domain interaction record and 26.3% can also be found in either mammals or plants. This database provides a resource to help virologists identify potential roles for viral protein. All of the information is available at http://vipdb.cgu.edu.tw. (C) 2012 Elsevier Inc. All rights reserved.
Whole Genome DNA Methylation Analysis of Active Pulmonary Tuberculosis Disease Identifies Novel Epigenotypes: PARP9/miR-505/RASGRP4/GNG12 Gene Methylation and Clinical Phenotypes
(2020-05-01)
Chen, Yung-Che
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Hsiao, Chang-Chun
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Chen, Ting-Wen
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Wu, Chao-Chien
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Chao, Tung-Ying
We hypothesized that DNA methylation patterns may contribute to the development of active pulmonary tuberculosis (TB). Illumina's DNA methylation 450 K assay was used to identify differentially methylated loci (DML) in a discovery cohort of 12 active pulmonary TB patients and 6 healthy subjects (HS). DNA methylation levels were validated in an independent cohort of 64 TB patients and 24 HS. Microarray analysis identified 1028 DMLs in TB patients versus HS, and 3747 DMLs in TB patients after versus before anti-TB treatment, while autophagy was the most enriched signaling pathway. In the validation cohort, PARP9 and miR505 genes were hypomethylated in the TB patients versus HS, while RASGRP4 and GNG12 genes were hypermethylated, with the former two further hypomethylated in those with delayed sputum conversion, systemic symptoms, or far advanced lesions. MRPS18B and RPTOR genes were hypomethylated in TB patients with pleural involvement. RASGRP4 gene hypermethylation and RPTOR gene down-regulation were associated with high mycobacterial burden. TB patients with WIPI2/GNG12 hypermethylation or MRPS18B/FOXO3 hypomethylation had lower one-year survival. In vitro ESAT6 and CFP10 stimuli of THP-1 cells resulted in DNA de-methylation changes of the PARP9, RASGRP4, WIPI2, and FOXO3 genes. In conclusions, aberrant DNA methylation over the PARP9/miR505/RASGRP4/GNG12 genes may contribute to the development of active pulmonary TB disease and its clinical phenotypes, while aberrant DNA methylation over the WIPI2/GNG12/MARPS18B/FOXO3 genes may constitute a determinant of long-term outcomes.