Browsing by Author "Wu, Wei-Yun"

Now showing 1 - 4 of 4

A new method for post Genome-Wide Association Study (GWAS) analysis of colorectal cancer in Taiwan
(2013-04-10)
Wang, Hwei-Ming
;
Chang, Tzu-Hao
;
Lin, Feng-Mao
;
Chao, Te-Hsin
;
Huang, Wei-Chih
Recently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development. (c) 2012 Elsevier B.V. All rights reserved.
Bacterial Communities in Semen from Men of Infertile Couples: Metagenomic Sequencing Reveals Relationships of Seminal Microbiota to Semen Quality
(2014-10-23)
Weng, Shun-Long
;
Chiu, Chih-Min
;
Lin, Feng-Mao
;
Huang, Wei-Chih
;
Liang, Chao
Some previous studies have identified bacteria in semen as being a potential factor in male infertility. However, only few types of bacteria were taken into consideration while using PCR-based or culturing methods. Here we present an analysis approach using next-generation sequencing technology and bioinformatics analysis to investigate the associations between bacterial communities and semen quality. Ninety-six semen samples collected were examined for bacterial communities, measuring seven clinical criteria for semen quality (semen volume, sperm concentration, motility, Kruger\'s strict morphology, antisperm antibody (IgA), Atypical, and leukocytes). Computer-assisted semen analysis (CASA) was also performed. Results showed that the most abundant genera among all samples were Lactobacillus (19.9%), Pseudomonas (9.85%), Prevotella (8.51%) and Gardnerella (4.21%). The proportion of Lactobacillus and Gardnerella was significantly higher in the normal samples, while that of Prevotella was significantly higher in the low quality samples. Unsupervised clustering analysis demonstrated that the seminal bacterial communities were clustered into three main groups: Lactobacillus, Pseudomonas, and Prevotella predominant group. Remarkably, most normal samples (80.6%) were clustered in Lactobacillus predominant group. The analysis results showed seminal bacteria community types were highly associated with semen health. Lactobacillus might not only be a potential probiotic for semen quality maintenance, but also might be helpful in countering the negative influence of Prevotella and Pseudomonas. In this study, we investigated whole seminal bacterial communities and provided the most comprehensive analysis of the association between bacterial community and semen quality. The study significantly contributes to the current understanding of the etiology of male fertility.
Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing
(2013)
Chiu, Chih-Min
;
Lin, Feng-Mao
;
Chang, Tzu-Hao
;
Huang, Wei-Chih
;
Liang, Chao
The human body plays host to a vast array of bacteria which are harmful or beneficial. Next generation sequencing technology have increased its accuracy in identifying bacteria. This work develops a novel platform for rapidly detecting probiotics and pathogens based on sequencing results of 16S rRNA. A database that recorded the species of probiotics and pathogens from literature was constructed, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. A bacteria disease risk model for seven diseases was constructed based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species for clinical microbiology applications. Detecting how probiotics and pathogens inhabit humans and affect their health significantly contributes to develop a diagnosis and treatment method.
miRTarBase: a database curates experimentally validated microRNA-target interactions
(2011-01-01)
Hsu, Sheng-Da
;
Lin, Feng-Mao
;
Wu, Wei-Yun
;
Liang, Chao
;
Huang, Wei-Chih
MicroRNAs (miRNAs), i.e. small non-coding RNA molecules (similar to 22 nt), can bind to one or more target sites on a gene transcript to negatively regulate protein expression, subsequently controlling many cellular mechanisms. A current and curated collection of miRNA-target interactions (MTIs) with experimental support is essential to thoroughly elucidating miRNA functions under different conditions and in different species. As a database, miRTarBase has accumulated more than 3500 MTIs by manually surveying pertinent literature after data mining of the text systematically to filter research articles related to functional studies of miRNAs. Generally, the collected MTIs are validated experimentally by reporter assays, western blot, or microarray experiments with overexpression or knockdown of miRNAs. miRTarBase curates 3576 experimentally verified MTIs between 657 miRNAs and 2297 target genes among 17 species. miRTarBase contains the largest amount of validated MTIs by comparing with other similar, previously developed databases. The MTIs collected in the miRTarBase can also provide a large amount of positive samples to develop computational methods capable of identifying miRNA-target interactions. miRTarBase is now available on http://miRTarBase.mbc.nctu.edu.tw/, and is updated frequently by continuously surveying research articles.