• BMB Reports
• /
• v.52 no.9
• /
• pp.540-547
• /
• 2019

Immune repertoire is a collection of enormously diverse adaptive immune cells within an individual. As the repertoire shapes and represents immunological conditions, identification of clones and characterization of diversity are critical for understanding how to protect ourselves against various illness such as infectious diseases and cancers. Over the past several years, fast growing technologies for high throughput sequencing have facilitated rapid advancement of repertoire research, enabling us to observe the diversity of repertoire at an unprecedented level. Here, we focus on B cell receptor (BCR) repertoire and review approaches to B cell isolation and sequencing library construction. These experiments should be carefully designed according to BCR regions to be interrogated, such as heavy chain full length, complementarity determining regions, and isotypes. We also highlight preprocessing steps to remove sequencing and PCR errors with unique molecular index and bioinformatics techniques. Due to the nature of massive sequence variation in BCR, caution is warranted when interpreting repertoire diversity from error-prone sequencing data. Furthermore, we provide a summary of statistical frameworks and bioinformatics tools for clonal evolution and diversity. Finally, we discuss limitations of current BCR-seq technologies and future perspectives on advances in repertoire sequencing.

• Journal of Life Science
• /
• v.31 no.4
• /
• pp.410-417
• /
• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• The Plant Pathology Journal
• /
• v.36 no.5
• /
• pp.468-475
• /
• 2020

Malva vein clearing virus (MVCV) is a member of the Potyvirus species, and has a negative impact on the aesthetic development of Alcea rosea. It was first reported in Germany in 1957, but its complete genome sequence data are still scarce. In the present work, A. rosea leaves with vein-clearing and mosaic symptoms were sampled and analyzed with small RNA deep sequencing. By denovo assembly the raw sequences of virus-derived small interfering RNAs (vsiRs) and whole genome amplification of malva vein cleaning virus SX strain (MVCV-SX) by specific primers targeting identified contig gaps, the full-length genome sequences (9,645 nucleotides) of MVCV-SX were characterized, constituting of an open reading frame that is long enough to encode 3,096 amino acids. Phylogenetic analysis showed that MVCV-SX was clustered with euphorbia ringspot virus and yam mosaic virus. Further analyses of the vsiR profiles revealed that the most abundant MVCV-vsiRs were between 21 and 22 nucleotides in length and a strong bias was found for "A" and "U" at the 5′-terminal residue. The results of polarity assessment indicated that the amount of sense strand was almost equal to that of the antisense strand in MVCV-vsiRs, and the main hot-spot region in MVCV-SX genome was found at cylindrical inclusion. In conclusion, our findings could provide new insights into the RNA silencing-mediated host defence mechanism in A. rosea infected with MVCV-SX, and offer a basis for the prevention and treatment of this virus disease.

• Genomics & Informatics
• /
• v.19 no.1
• /
• pp.2.1-2.10
• /
• 2021

BRAF inhibitors (e.g., vemurafenib) are widely used to treat metastatic melanoma with the BRAF V600E mutation. The initial response is often dramatic, but treatment resistance leads to disease progression in the majority of cases. Although secondary mutations in the mitogen-activated protein kinase signaling pathway are known to be responsible for this phenomenon, the molecular mechanisms governing acquired resistance are not known in more than half of patients. Here we report a genome- and transcriptome-wide study investigating the molecular mechanisms of acquired resistance to BRAF inhibitors. A microfluidic chip with a concentration gradient of vemurafenib was utilized to rapidly obtain therapy-resistant clones from two melanoma cell lines with the BRAF V600E mutation (A375 and SK-MEL-28). Exome and transcriptome data were produced from 13 resistant clones and analyzed to identify secondary mutations and gene expression changes. Various mechanisms, including phenotype switching and metabolic reprogramming, have been determined to contribute to resistance development differently for each clone. The roles of microphthalmia-associated transcription factor, the master transcription factor in melanocyte differentiation/dedifferentiation, were highlighted in terms of phenotype switching. Our study provides an omics-based comprehensive overview of the molecular mechanisms governing acquired resistance to BRAF inhibitor therapy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.3
• /
• pp.551-569
• /
• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.

• Journal of Information Processing Systems
• /
• v.13 no.6
• /
• pp.1527-1543
• /
• 2017

MiRNA is a biological short sequence, which plays a crucial role in almost all important biological process. MiRNA patterns are common sequence segments of multiple mature miRNA sequences, and they are of significance in identifying miRNAs due to the functional implication in miRNA patterns. In the proposed approach, the primary miRNA patterns are produced from sequence alignment, and they are then cut into short segment miRNA patterns. From the segment miRNA patterns, the candidate miRNA patterns are selected based on estimated probability, and from which, the potential miRNA patterns are further selected according to the classification performance between authentic and artificial miRNA sequences. Three parameters are suggested that bi-nucleotides are employed to compute the estimated probability of segment miRNA patterns, and top 1% segment miRNA patterns of length four in the order of estimated probabilities are selected as potential miRNA patterns.

• Journal of Microbiology and Biotechnology
• /
• v.28 no.6
• /
• pp.976-986
• /
• 2018

Knowledge about the gut bacterial communities associated with insects is essential to understand their roles in the physiology of the host. In the present study, the gut bacterial communities of a laboratory-reared insecticide-susceptible (IS), and a field-collected insecticide-resistant (IR) population of a major rice pest, the brown planthopper Nilaparvata lugens, were evaluated. The deep-sequencing analysis of the V3 hypervariable region of the 16S rRNA gene was performed using Illumina and the sequence data were processed using QIIME. The toxicological bioassays showed that compared with the IS population, IR population exhibited 7.9-, 6.7-, 14.8-, and 18.7-fold resistance to acephate, imidacloprid, thiamethoxam, and buprofezin, respectively. The analysis of the alpha diversity indicated a higher bacterial diversity and richness associated with the IR population. The dominant phylum in the IS population was Proteobacteria (99.86%), whereas the IR population consisted of Firmicutes (46.06%), followed by Bacteroidetes (30.8%) and Proteobacteria (15.49%). Morganella, Weissella, and Enterococcus were among the genera shared between the two populations and might form the core bacteria associated with N. lugens. The taxonomic-to-phenotypic mapping revealed the presence of ammonia oxidizers, nitrogen fixers, sulfur oxidizers and reducers, xylan degraders, and aromatic hydrocarbon degraders in the metagenome of N. lugens. Interestingly, the IR population was found to be enriched with bacteria involved in detoxification functions. The results obtained in this study provide a basis for future studies elucidating the roles of the gut bacteria in the insecticide resistance-associated symbiotic relationship and on the design of novel strategies for the management of N. lugens.

• Clinical and Experimental Reproductive Medicine
• /
• v.49 no.4
• /
• pp.225-238
• /
• 2022

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

• Korean Journal of Radiology
• /
• v.21 no.4
• /
• pp.505-508
• /
• 2020

The epidemic of 2019 novel coronavirus, later named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still gradually spreading worldwide. The nucleic acid test or genetic sequencing serves as the gold standard method for confirmation of infection, yet several recent studies have reported false-negative results of real-time reverse-transcriptase polymerase chain reaction (rRT-PCR). Here, we report two representative false-negative cases and discuss the supplementary role of clinical data with rRT-PCR, including laboratory examination results and computed tomography features. Coinfection with SARS-COV-2 and other viruses has been discussed as well.

• The Plant Pathology Journal
• /
• v.29 no.3
• /
• pp.223-233
• /
• 2013

Rice stripe virus (RSV) is one of the most destructive viruses of rice, and greatly reduces rice production in China, Japan, and Korea, where mostly japonica cultivars of rice are grown. RSV is transmitted by the small brown plant-hopper (SBPH) in a persistent and circulative-propagative manner. Several methods have been developed for detection of RSV, which is composed of four single-stranded RNAs that encode seven proteins. Genome sequence data and comparative phylogenetic analysis have been used to identify the origin and diversity of RSV isolates. Several rice varieties resistant to RSV have been selected and QTL analysis and fine mapping have been intensively performed to map RSV resistance loci or genes. RSV genes have been used to generate several genetically modified transgenic rice plants with RSV resistance. Recently, genome-wide transcriptome analyses and deep sequencing have been used to identify mRNAs and small RNAs involved in RSV infection; several rice host factors that interact with RSV proteins have also been identified. In this article, we review the current statues of RSV research and propose integrated approaches for the study of interactions among RSV, rice, and the SBPH.