Browsing by Author "Liu, Chia-Yu"

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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
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Chiu, Chih-Min
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Lin, Feng-Mao
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Huang, Wei-Chih
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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.
Low-Complexity Detectors for Spatially-Modulated MIMO Systems
(2014)
Wu, Wen-Rong
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Lin, Chun-Tao
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Liu, Chia-Yu
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電信工程研究所
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Institute of Communications Engineering
Spatial modulation (SM) combined with spatial multiplexing is a newly developed transmission technique in multiple-input multiple-output (MIMO) systems. The resultant system, referred to as SM-MIMO, can use the maximum-likelihood (ML) detector jointly detecting the antenna index and symbol vector. As known, the ML detector can achieve optimum performance; however, its computational complexity may become prohibitively high when the dimension of MIMO system or symbol constellation is large. In this paper, we propose a new method to solve the problem. The main idea is to conduct a two-stage detection, antenna index and symbol. We develop a Gaussian approximation method such that the antenna-index can be first reliably detected. An enhanced method is also proposed so that the near-optimum performance can be obtained. Simulations show that our methods outperform existing methods while the detection complexity remains low.
Low-Complexity ML Detectors for Generalized Spatial Modulation Systems
(2015-11-01)
Lin, Chun-Tao
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Wu, Wen-Rong
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Liu, Chia-Yu
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傳播研究所
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Institute of Communication Studies
Spatial modulation (SM) combined with spatial multiplexing is a newly developed transmission scheme in multiple-input multiple-output (MIMO) systems. The resultant system, referred to as generalized SM (GSM), can use the maximum-likelihood (ML) detector jointly detecting the antenna-subset (AS) index and symbol vector. As known, the ML detector can achieve optimum performance; however, its computational complexity can be prohibitively high when the dimension of the GSM system is large. In this paper, we propose new methods to solve the problem. The main idea is to split the detection into two stages, one for the AS index and the other for the symbol vector. For the detection of the AS index, we develop two methods, referred to as Gaussian approximation and QR projection. Once the AS index is detected, conventional low-complexity ML detectors can be applied for the detection of the symbol vector. The diversity order for the proposed methods are further analyzed and an enhanced method is also proposed to achieve near-optimum performance. Finally, the proposed methods are extended to conduct soft detection of GSM systems. Simulations show that our methods significantly outperform existing ones while the detection complexity remains similar.
The aquatic animals' transcriptome resource for comparative functional analysis
(2018-05-09)
Chou, Chih-Hung
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Huang, Hsi-Yuan
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Huang, Wei-Chih
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Hsu, Sheng-Da
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Hsiao, Chung-Der
Background: Aquatic animals have great economic and ecological importance. Among them, non-model organisms have been studied regarding eco-toxicity, stress biology, and environmental adaptation. Due to recent advances in next-generation sequencing techniques, large amounts of RNA-seq data for aquatic animals are publicly available. However, currently there is no comprehensive resource exist for the analysis, unification, and integration of these datasets. This study utilizes computational approaches to build a new resource of transcriptomic maps for aquatic animals. This aquatic animal transcriptome map database dbATM provides de novo assembly of transcriptome, gene annotation and comparative analysis of more than twenty aquatic organisms without draft genome. Results: To improve the assembly quality, three computational tools (Trinity, Oases and SOAPdenovo-Trans) were employed to enhance individual transcriptome assembly, and CAP3 and CD-HIT-EST software were then used to merge these three assembled transcriptomes. In addition, functional annotation analysis provides valuable clues to gene characteristics, including full-length transcript coding regions, conserved domains, gene ontology and KEGG pathways. Furthermore, all aquatic animal genes are essential for comparative genomics tasks such as constructing homologous gene groups and blast databases and phylogenetic analysis. Conclusion: In conclusion, we establish a resource for non model organism aquatic animals, which is great economic and ecological importance and provide transcriptomic information including functional annotation and comparative transcriptome analysis.
Transcriptome sequencing based annotation and homologous evidence based scaffolding of Anguilla japonica draft genome
(2016-01-01)
Liu, Yu-Chen
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Hsu, Sheng-Da
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Chou, Chih-Hung
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Huang, Wei-Yun
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Chen, Yu-Hung
Background: Anguilla japonica (Japanese eel) is currently one of the most important research subjects in eastern Asia aquaculture. Enigmatic life cycle of the organism makes study of artificial reproduction extremely limited. Henceforth genomic and transcriptomic resources of eels are urgently needed to help solving the problems surrounding this organism across multiple fields. We hereby provide a reconstructed transcriptome from deep sequencing of juvenile (glass eels) whole body samples. The provided expressed sequence tags were used to annotate the currently available draft genome sequence. Homologous information derived from the annotation result was applied to improve the group of scaffolds into available linkage groups. Results: With the transcriptome sequence data combined with publicly available expressed sequence tags evidences, 18,121 genes were structurally and functionally annotated on the draft genome. Among them, 3,921 genes were located in the 19 linkage groups. 137 scaffolds covering 13 million bases were grouped into the linkage groups in additional to the original partial linkage groups, increasing the linkage group coverage from 13 to 14 %. Conclusions: This annotation provide information of the coding regions of the genes supported by transcriptome based evidence. The derived homologous evidences pave the way for phylogenetic analysis of important genetic traits and the improvement of the genome assembly.