• BMB Reports
• /
• v.55 no.9
• /
• pp.465-471
• /
• 2022

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of large-scale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment.

• BMB Reports
• /
• v.49 no.12
• /
• pp.653-654
• /
• 2016

The human reference genome, maintained by the Genome Reference Consortium, is conceivably the most complete genome assembly ever, since its first construction. It has continually been improved by incorporating corrections made to the previous assemblies, thanks to various technological advances. Many currently-ongoing population sequencing projects have been based on this reference genome, heightening hopes of the development of useful medical applications of genomic information, thanks to the recent maturation of high-throughput sequencing technologies. However, just one reference genome does not fit all the populations across the globe, because of the large diversity in genomic structures and technical limitations inherent to short read sequencing methods. The recent success in de novo construction of the highly contiguous Asian diploid genome AK1, by combining single molecule technologies with routine sequencing data without resorting to traditional clone-by-clone sequencing and physical mapping, reveals the nature of genomic structure variation by detecting thousands of novel structural variations and by finally filling in some of the prior gaps which had persistently remained in the current human reference genome. Now it is expected that the AK1 genome, soon to be paired with more upcoming de novo assembled genomes, will provide a chance to explore what it is really like to use ancestry-specific reference genomes instead of hg19/hg38 for population genomics. This is a major step towards the furthering of genetically-based precision medicine.

• Genomics & Informatics
• /
• v.17 no.1
• /
• pp.3.1-3.4
• /
• 2019

Intratumor heterogeneity within a single tumor mass is one of the hallmarks of malignancy and has been reported in various tumor types. The molecular characterization of intratumor heterogeneity in breast cancer is a significant challenge for effective treatment. Using single-cell RNA sequencing (RNA-seq) data from a public resource, an ERBB pathway activated triple-negative cell population was identified. The differential expression of three subtyping marker genes (ERBB2, ESR1, and PGR) was not changed in the bulk RNA-seq data, but the single-cell transcriptomes showed intratumor heterogeneity. This result shows that ERBB signaling is activated using an indirect route and that the molecular subtype is changed on a single-cell level. Our data propose a different view on breast cancer subtypes, clarifying much confusion in this field and contributing to precision medicine.

• Journal of Genetic Medicine
• /
• v.20 no.2
• /
• pp.46-51
• /
• 2023

Exonic copy number variation (CNV), involving deletions and duplications at the gene's exon level, presents challenges in detection due to their variable impact on gene function. The study delves into the complexities of identifying large CNVs and investigates less familiar but recurrent exonic CNVs, notably enriched in East Asian populations. Examining specific cases like DRC1, STX16, LAMA2, and CFTR highlights the clinical implications and prevalence of exonic CNVs in diverse populations. The review addresses diagnostic challenges, particularly for single exon alterations, advocating for a strategic, multi-method approach. Diagnostic methods, including multiplex ligation-dependent probe amplification, droplet digital PCR, and CNV screening using next-generation sequencing data, are discussed, with whole genome sequencing emerging as a powerful tool. The study underscores the crucial role of ethnic considerations in understanding specific CNV prevalence and ongoing efforts to unravel subtle variations. The ultimate goal is to advance rare disease diagnosis and treatment through ethnically-specific therapeutic interventions.

• Genomics & Informatics
• /
• v.16 no.3
• /
• pp.71-74
• /
• 2018

Because castration-resistant prostate cancer (CRPC) does not respond to androgen deprivation therapy and has a very poor prognosis, it is critical to identify a prognostic indicator for predicting high-risk patients who will develop CRPC. Here, we report a dataset of whole genomes from four pairs of primary prostate cancer (PC) and CRPC samples. The analysis of the paired PC and CRPC samples in the whole-genome data showed that the average number of somatic mutations per patients was 7,927 in CRPC tissues compared with primary PC tissues (range, 1,691 to 21,705). Our whole-genome sequencing data of primary PC and CRPC may be useful for understanding the genomic changes and molecular mechanisms that occur during the progression from PC to CRPC.

• ALGAE
• /
• v.28 no.1
• /
• pp.31-43
• /
• 2013

This review provides a comprehensive summary of the PCR primers and profiles currently in use in our laboratory for red algal DNA barcoding and phylogenetic research. While work focuses on florideophyte taxa, many of the markers have been applied successfully to the Bangiales, as well as other lineages previously assigned to the Bangiophyceae sensu lato. All of the primers currently in use with their respective amplification profiles and strategies are provided, which can include full fragment, overlapping fragments and what might best be called "informed overlapping fragments", i.e., a fragment for a marker is amplified and sequenced for a taxon and those sequence data are then used to identify the best primers to amplify the remaining fragment(s) for that marker. We extend this strategy for the more variable markers with sequence from the external PCR primers used to "inform" the selection of internal sequencing primers. This summary will hopefully serve as a useful resource to systematists in the red algal community.

• Molecules and Cells
• /
• v.45 no.5
• /
• pp.343-352
• /
• 2022

The advent of the assay for transposase-accessible chromatin using sequencing (ATAC-seq) has shown great potential as a leading method for analyzing the genome-wide profiling of chromatin accessibility. A comprehensive reference to the ATAC-seq dataset for disease progression is important for understanding the regulatory specificity caused by genetic or epigenetic changes. In this study, we present a genome-wide chromatin accessibility profile of 44 liver samples spanning the full histological spectrum of nonalcoholic fatty liver disease (NAFLD). We analyzed the ATAC-seq signal enrichment, fragment size distribution, and correlation coefficients according to the histological severity of NAFLD (healthy control vs steatosis vs fibrotic nonalcoholic steatohepatitis), demonstrating the high quality of the dataset. Consequently, 112,303 merged regions (genomic regions containing one or multiple overlapping peak regions) were identified. Additionally, we found differentially accessible regions (DARs) and performed transcription factor binding motif enrichment analysis and de novo motif analysis to determine new biomarker candidates. These data revealed the gene-regulatory interactions and noncoding factors that can affect NAFLD progression. In summary, our study provides a valuable resource for the human epigenome by applying an advanced approach to facilitate diagnosis and treatment by understanding the non-coding genome of NAFLD.

• Molecules and Cells
• /
• v.40 no.10
• /
• pp.737-751
• /
• 2017

Histone-modifying enzymes are key players in the field of cellular differentiation. Here, we used GSK-J4 to profile important target genes that are responsible for neural differentiation. Embryoid bodies were treated with retinoic acid ($10{\mu}M$) to induce neural differentiation in the presence or absence of GSK-J4. To profile GSKJ4-target genes, we performed RNA sequencing for both normal and demethylase-inhibited cells. A total of 47 and 58 genes were up- and down-regulated, respectively, after GSK-J4 exposure at a log2-fold-change cut-off value of 1.2 (p-value < 0.05). Functional annotations of all of the differentially expressed genes revealed that a significant number of genes were associated with the suppression of cellular proliferation, cell cycle progression and induction of cell death. We also identified an enrichment of potent motifs in selected genes that were differentially expressed. Additionally, we listed upstream transcriptional regulators of all of the differentially expressed genes. Our data indicate that GSK-J4 affects cellular biology by inhibiting cellular proliferation through cell cycle suppression and induction of cell death. These findings will expand the current understanding of the biology of histone-modifying enzymes, thereby promoting further investigations to elucidate the underlying mechanisms.

• Korean Journal of Medicinal Crop Science
• /
• v.25 no.6
• /
• pp.411-417
• /
• 2017

Background: Adenophora triphylla var. japonica (Regel) H. Hara shows vegetative growth with radical leaves during the first year and shows reproductive growth with cauline leaves and bolting during the second year. In addition, the shape of the plant varies within the same species. For this reason, there are limitations to classifying the species by visual examination. However, there is not sufficient genetic information or molecular tools to analyze the genetic diversity of the plant. Methods and Results: Approximately 34.59 Gbp of raw data containing 342,487,502 reads was obtained from next generation sequencing (NGS) and these reads were assembled into 357,211 scaffolds. A total of 84,106 simple sequence repeat (SSR) regions were identified and 14,133 primer sets were designed. From the designed primer sets, 95 were randomly selected and were applied to the genomic DNA which was extracted from five plants and pooled. Thirty-nine primer sets showing more than two bands were finally selected as SSR markers, and were used for the genetic relationship analysis. Conclusions: The 39 novel SSR markers developed in this study could be used for the genetic diversity analysis, variety identification, new variety development and molecular breeding of A. triphylla.

• Genomics & Informatics
• /
• v.15 no.1
• /
• pp.51-53
• /
• 2017

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.