• Genomics & Informatics
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• v.20 no.1
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• pp.2.1-2.11
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• 2022

The method of single-cell RNA sequencing has been rapidly developed, and numerous experiments have been conducted over the past decade. Their results allow us to recognize various subpopulations and rare cell states in tissues, tumors, and immune systems that are previously unidentified, and guide us to understand fundamental biological processes that determine cell identity based on single-cell gene expression profiles. However, it is still challenging to understand the principle of comprehensive gene regulation that determines the cell fate only with transcriptome, a consequential output of the gene expression program. To elucidate the mechanisms related to the origin and maintenance of comprehensive single-cell transcriptome, we require a corresponding single-cell epigenome, which is a differentiated information of each cell with an identical genome. This review deals with the current development of single-cell epigenomic library construction methods, including multi-omics tools with crucial factors and additional requirements in the future focusing on DNA methylation, chromatin accessibility, and histone post-translational modifications. The study of cellular differentiation and the disease occurrence at a single-cell level has taken the first step with single-cell transcriptome and is now taking the next step with single-cell epigenome.

• Genomics & Informatics
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• v.10 no.1
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• pp.1-8
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• 2012

Recently, the technologies of DNA sequence variation and gene expression profiling have been used widely as approaches in the expertise of genome biology and genetics. The application to genome study has been particularly developed with the introduction of the nextgeneration DNA sequencer (NGS) Roche/454 and Illumina/ Solexa systems, along with bioinformation analysis technologies of whole-genome $de$ $novo$ assembly, expression profiling, DNA variation discovery, and genotyping. Both massive whole-genome shotgun paired-end sequencing and mate paired-end sequencing data are important steps for constructing $de$ $novo$ assembly of novel genome sequencing data. It is necessary to have DNA sequence information from a multiplatform NGS with at least $2{\times}$ and $30{\times}$ depth sequence of genome coverage using Roche/454 and Illumina/Solexa, respectively, for effective an way of de novo assembly. Massive shortlength reading data from the Illumina/Solexa system is enough to discover DNA variation, resulting in reducing the cost of DNA sequencing. Whole-genome expression profile data are useful to approach genome system biology with quantification of expressed RNAs from a wholegenome transcriptome, depending on the tissue samples. The hybrid mRNA sequences from Rohce/454 and Illumina/Solexa are more powerful to find novel genes through $de$ $novo$ assembly in any whole-genome sequenced species. The $20{\times}$ and $50{\times}$ coverage of the estimated transcriptome sequences using Roche/454 and Illumina/Solexa, respectively, is effective to create novel expressed reference sequences. However, only an average $30{\times}$ coverage of a transcriptome with short read sequences of Illumina/Solexa is enough to check expression quantification, compared to the reference expressed sequence tag sequence.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.73-73
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• 2019

Angelica gigas Nakai (Korean danggui), a member of the Umbelliferae family, is a Korean traditional medicinal plant whose roots have been used for treating gynecological diseases. Transcriptomics is the study of the transcriptome, which is the complete set of RNA transcripts that are produced by the genome, using high-throughput methods, such as microarray analysis. In this study, transcriptome analysis of A.gigas Nakai was carried out. Transcriptome sequencing and assembly was carried out by using Illumina Hiseq 2500, Velvet and Oases. A total of 109,591,555 clean reads of A. gigas Nakai was obtained after trimming adaptors. The obtained reads were assembled with an average length of 1,154 bp, a maximum length of 13,166 bp, a minimum length of 200 pb, and N50 of 1,635 bp. Functional annotation and classification was performed using NCBI NR, InterprotScan, KOG, KEGG and GO. Candidate genes for phenylpropanoid biosynthesis were obtanied from A.gigas transcriptome and the genes and its proteins were confirmed through the NCBI homology BLAST searches, revealing high identity with other othologous genes and proteins from various plants pecies. In RNA sequencing analysis using an Illumina Next-Seq2500 sequencer, we identified a total 94,930 transcripts and annotated 71,281 transcripts, which provide basic information for further research in A.gigas Nakai. Our transcriptome data reveal that several differentially expressed genes related to flower color in A.gigas Nakai. The results of this research provide comprehensive information on the A.gigas Nakai genome and enhance our understanding of the flower color related gene pathways in this plant.

• Journal of Genetic Medicine
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• v.20 no.2
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• pp.31-38
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• 2023

Rare diseases, even though defined as fewer than 20,000 in South Korea, with over 8,000 rare Mendelian disorders having been identified, they collectively impact 6-8% of the global population. Many of the rare diseases pose significant challenges to patients, patients' families, and the healthcare system. The diagnostic journey for rare disease patients is often lengthy and arduous, hampered by the genetic diversity and phenotypic complexity of these conditions. With the advent of next-generation sequencing technology and clinical implementation of exome sequencing (ES) and genome sequencing (GS), the diagnostic rate for rare diseases is 25-50% depending on the disease category. It is also allowing more rapid new gene-disease association discovery and equipping us to practice precision medicine by offering tailored medical management plans, early intervention, family planning options. However, a substantial number of patients remain undiagnosed, and it could be due to several factors. Some may not have genetic disorders. Some may have disease-causing variants that are not detectable or interpretable by ES and GS. It's also possible that some patient might have a disease-causing variant in a gene that hasn't yet been linked to a disease. For patients who remain undiagnosed, reanalysis of existing data has shown promises in providing new molecular diagnoses achieved by new gene-disease associations, new variant discovery, and variant reclassification, leading to a 5-10% increase in the diagnostic rate. More advanced approach such as long-read sequencing, transcriptome sequencing and integration of multi-omics data may provide potential values in uncovering elusive genetic causes.

• Genomics & Informatics
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• v.11 no.2
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• pp.76-82
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• 2013

Over the past decade or so, dramatic developments in our ability to experimentally determine the content and function of genomes have taken place. In particular, next-generation sequencing technologies are now inspiring a new understanding of bacterial transcriptomes on a global scale. In bacterial cells, whole-transcriptome studies have not received attention, owing to the general view that bacterial genomes are simple. However, several recent RNA sequencing results are revealing unexpected levels of complexity in bacterial transcriptomes, indicating that the transcribed regions of genomes are much larger and complex than previously anticipated. In particular, these data show a wide array of small RNAs, antisense RNAs, and alternative transcripts. Here, we review how current transcriptomics are now revolutionizing our understanding of the complexity and regulation of bacterial transcriptomes.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.169-169
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• 2019

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.7
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• pp.1062-1071
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• 2018

The misuse of anabolic hormones or illegal drugs is a ubiquitous problem in animal husbandry and in food safety. The ban on growth promotants in food producing animals in the European Union is well controlled. However, application regimens that are difficult to detect persist, including newly designed anabolic drugs and complex hormone cocktails. Therefore identification of molecular endogenous biomarkers which are based on the physiological response after the illicit treatment has become a focus of detection methods. The analysis of the 'transcriptome' has been shown to have promise to discover the misuse of anabolic drugs, by indirect detection of their pharmacological action in organs or selected tissues. Various studies have measured gene expression changes after illegal drug or hormone application. So-called transcriptomic biomarkers were quantified at the mRNA and/or microRNA level by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) technology or by more modern 'omics' and high throughput technologies including RNA-sequencing (RNA-Seq). With the addition of advanced bioinformatical approaches such as hierarchical clustering analysis or dynamic principal components analysis, a valid 'biomarker signature' can be established to discriminate between treated and untreated individuals. It has been shown in numerous animal and cell culture studies, that identification of treated animals is possible via our transcriptional biomarker approach. The high throughput sequencing approach is also capable of discovering new biomarker candidates and, in combination with quantitative RT-qPCR, validation and confirmation of biomarkers has been possible. These results from animal production and food safety studies demonstrate that analysis of the transcriptome has high potential as a new screening method using transcriptional 'biomarker signatures' based on the physiological response triggered by illegal substances.

• BMB Reports
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• v.43 no.10
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• pp.704-709
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• 2010

The Swedish mutation (K595N/M596L) of amyloid precursor protein (APP-swe) has been known to increase abnormal cleavage of cellular APP by Beta-secretase (BACE), which causes tau protein hyperphosphorylation and early-onset Alzheimer's disease (AD). Here, we analyzed the effect of APP-swe in global gene expression using deep transcriptome sequencing technique. We found 283 genes were down-regulated and 348 genes were up-regulated in APP-swe expressing H4-swe cells compared to H4 wild-type cells from a total of approximately 74 million reads of 38 base pairs from each transcriptome. Two independent mechanisms such as kinase and phosphatase signaling cascades leading hyperphosphorylation of tau protein were regulated by the expression of APP-swe. Expressions of catalytic subunit as well as several regulatory subunits of protein phosphatases 2A were decreased. In contrast, expressions of tau-phosphorylating glycogen synthase kinase $3\beta$(GSK-3$\beta$), cyclin dependent kinase 5 (CDK5), and cAMP-dependent protein kinase A (PKA) catalytic subunit were increased. Moreover, the expression of AD-related Aquaporin 1 and presenilin 2 expression was regulated by APP-swe. Taken together, we propose that the expression of APP-swe modulates global gene expression directed to AD pathogenesis.

• Genes and Genomics
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• v.40 no.12
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• pp.1287-1300
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• 2018

Hydrogen sulfide ($H_2S$), a small bioactive gas, has been proved functioning in plant growth and development as well as alleviation of abiotic stresses, which including promoting seed germination, accelerating embryonic root growth, regulating flower senescence, inducing stomatal closure, and defending drought, heat, heavy metals and osmotic stresses etc. However, the molecular functioning mechanism of $H_2S$ was still unclear. The primary objective of this research was to analyze the transcriptional differences and functional genes involved in the $H_2S$ responses. In details, 4-week-old plantlets in tissue culture of grapevine (Vitis vinifera L.) cultivar 'Zuoyouhong' were sprayed with 0.1 mM NaHS for 12 h, and then transcriptome sequencing and qRT-PCR analysis were used to study the transcriptional differences and functional genes involved in the $H_2S$ responses. Our results indicated that 650 genes were differentially expressed after $H_2S$ treatment, in which 224 genes were up-regulated and 426 genes were down-regulated. The GO enrichment analysis and KEGG enrichment analysis results indicated that the up-regulated genes after $H_2S$ treatment focused on carbon metabolism, biosynthesis of amino acids, and glycolysis/gluconeogenesis, and the down-regulated genes were mainly in metabolic pathways, biosynthesis of secondary metabolites, and plant hormone signal transduction. Analyzing the transcription factor coding genes in details, it was indicated that 10 AP2/EREBPs, 5 NACs, 3 WRKYs, 3 MYBs, and 2 bHLHs etc. transcription factor coding genes were up-regulated, while 4 MYBs, 3 OFPs, 3 bHLHs, 2 AP2/EREBPs, 2 HBs etc. transcription factor coding genes were down-regulated. Taken together, $H_2S$ increased the productions in secondary metabolites and a variety of defensive compounds to improve plant development and abiotic resistance, and extend fruits postharvest shelf life by regulating the expression of AP2/EREBPs, WRKYs, MYBs, CABs, GRIP22, FERRITINs, TPSs, UGTs, and GHs etc.

• Journal of Animal Science and Technology
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• v.64 no.6
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• pp.1144-1172
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• 2022

Salmonella enterica serovar Typhimurium isolate HJL777 is a virulent bacterial strain in pigs. The high rate of salmonella infection are at high risk of non-typhoidal salmonella gastroenteritis development. Salmonellosis is most common in young pigs. We investigated changes in gut microbiota and biological function in piglets infected with salmonella via analysis of rectal fecal metagenome and intestinal transcriptome using 16S rRNA and RNA sequencing. We identified a decrease in Bacteroides and increase in harmful bacteria such as Spirochaetes and Proteobacteria by microbial community analysis. We predicted that reduction of Bacteroides by salmonella infection causes proliferation of salmonella and harmful bacteria that can cause an intestinal inflammatory response. Functional profiling of microbial communities in piglets with salmonella infection showed increasing lipid metabolism associated with proliferation of harmful bacteria and inflammatory responses. Transcriptome analysis identified 31 differentially expressed genes. Using gene ontology and Innate Immune Database analysis, we identified that BGN, DCN, ZFPM2 and BPI genes were involved in extracellular and immune mechanisms, specifically salmonella adhesion to host cells and inflammatory responses during infection. We confirmed alterations in gut microbiota and biological function during salmonella infection in piglets. Our findings will help prevent disease and improve productivity in the swine industry.