• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.669-671
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• 2014

High Throughput Sequencing (HTS) 기술의 발달로 인해 시퀀싱 비용이 감소함에 따라 다양한 분야에서 이를 활용한 융합 연구가 활발하게 진행되고 있다. HTS 기술에서 가장 중요한 부분은 수백만개의 short read 들을 표준유전체 (reference genome)에 정렬시키는 것인데 RNA 시퀀싱 (RNA-Seq) 의 경우 RNA splicing 으로 인해 일반적인 aligner 로 처리가 불가능하다. 복잡한 RNA-Seq 정렬 문제를 해결하기 위해 그동안 다양한 알고리즘들이 제안되어 왔다. 본 논문에서는 RNA-seq 정렬분야에서 잘 알려진 알고리즘들과 최신 알고리즘들을 살펴봄으로써 RNA-seq 정렬 알고리즘의 동향을 살펴보고자 한다.

• Journal of Sensor Science and Technology
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• v.21 no.5
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• pp.359-366
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• 2012

Nanopore DNA sequencing is an emerging and promising technique that can potentially realize the goal of a low-cost and high-throughput method for analyzing human genome. Especially, solid-state nanopores have relatively high mechanical stability, simple surface modification, and facile fabrication process without the need for labeling or amplification of PCR (polymerized chain reaction) in DNA sequencing. For these advantages of solid-sate nanopores, the use of solid-state nanopores has been extensively considered for developing a next generation DNA sequencing technology. Solid-state nanopore sequencing technique can determine and count charged molecules such as single-stranded DNA, double-stranded DNA, or RNA when they are driven to pass through a membrane nanopore between two electrolytes of cis-trans chambers with applied bias voltage by measuring the ionic current which varies due to the existence of the charged particles in the nanopore. Recently, many researchers have suggested that nanopore-based sensors can be competitive with other third-generation DNA sequencing technologies, and may be able to rapidly and reliably sequence the human genome for under $1,000.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.5-5
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• 2018

Ginseng (Panax ginseng C.A. Meyer), one of the most widely used medicinal plants in traditional oriental medicine, is used for the treatment of various diseases. It has been classified according to its cultivation environment, such as field cultivated ginseng (FCG) and mountain cultivated ginseng (MCG). However, little is known about differences in gene expression in ginseng roots between field cultivated and mountain cultivated ginseng. In order to investigate the whole transcriptome landscape of ginseng, we employed High-Throughput sequencing technologies using the Illumina HiSeqTM2500 system, and generated a large amount of sequenced transcriptome from ginseng roots. Approximately 77 million and 87 million high-quality reads were produced in the FCG and MCG roots transcriptome analyses, respectively, and we obtained 256,032 assembled unigenes with an average length of 1,171 bp by de novo assembly methods. Functional annotations of the unigenes were performed using sequence similarity comparisons against the following databases: the non-redundant nucleotide database, the InterPro domains database, the Gene Ontology Consortium database, and the Kyoto Encyclopedia of Genes and Genomes pathway database. A total of 4,207 unigenes were assigned to specific metabolic pathways, and all of the known enzymes involved in starch and sucrose metabolism pathways were also identified in the KEGG library. This study indicated that alpha-glucan phosphorylase 1, putative pectinesterase/pectinesterase inhibitor 17, beta-amylase, and alpha-glucan phosphorylase isozyme H might be important factors involved in starch and sucrose metabolism between FCG and MCG in different environments.

• Journal of Microbiology and Biotechnology
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• v.27 no.2
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• pp.321-334
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• 2017

Process surveillance within agricultural biogas plants (BGPs) was concurrently studied by high-throughput 16S rRNA gene amplicon sequencing and an optimized quantitative microscopic fingerprinting (QMF) technique. In contrast to 16S rRNA gene amplicons, digitalized microscopy is a rapid and cost-effective method that facilitates enumeration and morphological differentiation of the most significant groups of methanogens regarding their shape and characteristic autofluorescent factor 420. Moreover, the fluorescence signal mirrors cell vitality. In this study, four different BGPs were investigated. The results indicated stable process performance in the mesophilic BGPs and in the thermophilic reactor. Bacterial subcommunity characterization revealed significant differences between the four BGPs. Most remarkably, the genera Defluviitoga and Halocella dominated the thermophilic bacterial subcommunity, whereas members of another taxon, Syntrophaceticus, were found to be abundant in the mesophilic BGP. The domain Archaea was dominated by the genus Methanoculleus in all four BGPs, followed by Methanosaeta in BGP1 and BGP3. In contrast, Methanothermobacter members were highly abundant in the thermophilic BGP4. Furthermore, a high consistency between the sequencing approach and the QMF method was shown, especially for the thermophilic BGP. The differences elucidated that using this biphasic approach for mesophilic BGPs provided novel insights regarding disaggregated single cells of Methanosarcina and Methanosaeta species. Both dominated the archaeal subcommunity and replaced coccoid Methanoculleus members belonging to the same group of Methanomicrobiales that have been frequently observed in similar BGPs. This work demonstrates that combining QMF and 16S rRNA gene amplicon sequencing is a complementary strategy to describe archaeal community structures within biogas processes.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.9
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• pp.1345-1352
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• 2016

The hindgut of horses is an anaerobic fermentative chamber for a complex and dynamic microbial population, which plays a critical role in health and energy requirements. Research on the gut microbiota of Mongolian horses has not been reported until now as far as we know. Mongolian horse is a major local breed in China. We performed high-throughput sequencing of the 16S rRNA genes V4 hypervariable regions from gut fecal material to characterize the gut microbiota of Mongolian horses and compare them to the microbiota in Thoroughbred horses. Fourteen Mongolian and 19 Thoroughbred horses were used in the study. A total of 593,678 sequence reads were obtained from 33 samples analyzed, which were found to belong to 16 phyla and 75 genera. The bacterial community compositions were similar for the two breeds. Firmicutes (56% in Mongolian horses and 53% in Thoroughbred horses) and Bacteroidetes (33% and 32% respectively) were the most abundant and predominant phyla followed by Spirochaete, Verrucomicrobia, Proteobacteria, and Fibrobacteres. Of these 16 phyla, five (Synergistetes, Planctomycetes, Proteobacteria, TM7, and Chloroflexi) were significantly different (p<0.05) between the two breeds. At the genus level, Treponema was the most abundant genus (43% in Mongolian horses vs 29% in Thoroughbred horses), followed by Ruminococcus, Roseburia, Pseudobutyrivibrio, and Anaeroplasma, which were detected in higher distribution proportion in Mongolian horses than in Thoroughbred horses. In contrast, Oscillibacter, Fibrobacter, Methanocorpusculum, and Succinivibrio levels were lower in Mongolian horses. Among 75 genera, 30 genera were significantly different (p<0.05) between the two breeds. We found that the environment was one of very important factors that influenced horse gut microbiota. These findings provide novel information about the gut microbiota of Mongolian horses and a foundation for future investigations of gut bacterial factors that may influence the development and progression of gastrointestinal disease in horses.

• International Journal of Oral Biology
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• v.45 no.3
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• pp.77-83
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• 2020

In the oral cavity, complex microbial community is shaped by various host and environmental factors. Extensive literature describing the oral microbiome in the context of oral health and disease is available. Advances in DNA sequencing technologies and data analysis have drastically improved the analysis of the oral microbiome. For microbiome study, bacterial 16S ribosomal RNA gene amplification and sequencing is often employed owing to the cost-effective and fast nature of the method. In this review, practical considerations for performing a microbiome study, including experimental design, molecular analysis technology, and general data analysis, will be discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.11
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• pp.1715-1724
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• 2019

Objective: As laying hens become aged, laying performance and egg quality are generally impaired. One of the practical methods to rejuvenate production and egg quality of aged laying hens with decreasing productivity is a forced molting. However, the changes in intestinal microbiota after forced molting of aged hens are not clearly known. The aim of the present study was to analyze the changes in excreta bacterial communities after forced molting of aged laying hens. Methods: A total of one hundred 66-wk-old Hy-Line Brown laying hens were induced to molt by a 2-d water removal and an 11-d fasting until egg production completely ceased. The excreta samples of 16 hens with similar body weight were collected before and immediately after molting. Excreta bacterial communities were analyzed by high-throughput sequencing of bacterial 16S rRNA genes. Results: Bacteroidetes, Firmicutes, and Proteobacteria were the three major bacterial phyla in pre-molting and immediate post-molting hens, accounting for more than 98.0%. Lactobacillus genus had relatively high abundance in both group, but decreased by molting (62.3% in premolting and 24.9% in post-molting hens). Moreover, pathogenic bacteria such as Enterococcus cecorum and Escherichia coli were more abundant in immediate post-molting hens than in pre-molting hens. Forced molting influenced the alpha diversity, with higher Chao1 (p = 0.012), phylogenetic diversity whole tree (p = 0.014), observed operational taxonomic unit indices (p = 0.006), and Simpson indices (p<0.001), which indicated that forced molting increased excreta bacterial richness of aged laying hens. Conclusion: This study improves the current knowledge of bacterial community alterations in the excreta by forced molting in aged laying hens, which can provide increasing opportunity to develop novel dietary and management skills for improving the gastrointestinal health of aged laying hens after molting.

• Korean Journal of Poultry Science
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• v.44 no.3
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• pp.199-209
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• 2017

Mitogen-activated protein kinase (MAPK) signaling pathways play a key role in innate immunity, inflammation, cell proliferation, cell differentiation, and cell death. The main objective of this study was to investigate the expression level of candidate MAPK pathway genes in the intestinal mucosal layer of two genetically disparate chicken lines (Marek's disease-resistant line 6.3 and Marek's disease-susceptible line 7.2) induced with necrotic enteritis (NE). Using high-throughput RNA sequencing, we investigated 178 MAPK signaling pathway related genes that were significantly and differentially expressed between the intestinal mucosal layers of the NE-afflicted and control chickens. In total, 15 MAPK pathway genes were further measured by quantitative real-time PCR(qRT-PCR) and the results were consistent with the RNA-sequencing data. All 178 identified genes were annotated through Gene Ontology and mapped onto the KEGG chicken MAPK signaling pathway. Several key genes of the MAPK pathway, ERK1/2, JNK1-3, p38 MAPK, MAP2K1-4, $NF-{\kappa}B1/2$, c-Fos, AP-1, Jun-D, and Jun, were differentially expressed in the two chicken lines. Therefore, we believe that RNA sequencing and qRT-PCR analysis provide resourceful information for future studies on MAPK signaling of genetically disparate chicken lines in response to pathogens.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.47-53
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• 2017

In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.

• Animal Bioscience
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• v.35 no.8
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• pp.1162-1173
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• 2022

Objective: This study aimed to investigate the fermentation profiles, bacterial community and predicted metabolic characteristics of Sudangrass (Sorghum sudanense Stapf.) during ensiling. Methods: First-cutting Sudangrass was harvested at the vegetative stage and ensiled in laboratory-scale silos (1 L capacity). Triplicate silos were sampled after 1, 3, 7, 15, 30, and 60 days of ensiling, respectively. The bacterial communities on day 3 and 60 were assessed through high-throughput sequencing technology, and 16S rRNA-gene predicted functional profiles were analyzed according to the Kyoto encyclopedia of genes and genomes using Tax4Fun. Results: The Sudangrass silages showed good fermentation quality, indicated by higher lactic acid contents, and lower pH, butyric acid and ammonia nitrogen contents. The dominant genus Lactococcus on day 3 was replaced by Lactobacillus on day 60. The metabolism of amino acid, energy, cofactors and vitamins was restricted, and metabolism of nucleotide and carbohydrate was promoted after ensiling. The 1-phosphofructokinase and pyruvate kinase of bacterial community seemed to play important roles in stimulating the lactic acid fermentation, and the promotion of arginine deiminase could help lactic acid bacteria to tolerate the acidic environment. Conclusion: High-throughput sequencing technology combined with 16S rRNA gene-predicted functional analyses revealed the differences during the early and late stages of Sudangrass ensiling not only for distinct bacterial community but also for specific functional metabolites. The results could provide a comprehensive insight into bacterial community and metabolic characteristics to further improve the silage quality.