• Journal of Ginseng Research
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• 제38권4호
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• pp.278-288
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• 2014

Background: Panax ginseng Meyer is a traditional medicinal plant famous for its strong therapeutic effects and serves as an important herbal medicine. To understand and manipulate genes involved in secondary metabolic pathways including ginsenosides, transcriptome profiling of P. ginseng is essential. Methods: RNA-seq analysis of adventitious roots of two P. ginseng cultivars, Chunpoong (CP) and Cheongsun (CS), was performed using the Illumina HiSeq platform. After transcripts were assembled, expression profiling was performed. Results: Assemblies were generated from ~85 million and ~77 million high-quality reads from CP and CS cultivars, respectively. A total of 35,527 and 27,716 transcripts were obtained from the CP and CS assemblies, respectively. Annotation of the transcriptomes showed that approximately 90% of the transcripts had significant matches in public databases.We identified several candidate genes involved in ginsenoside biosynthesis. In addition, a large number of transcripts (17%) with different gene ontology designations were uniquely detected in adventitious roots compared to normal ginseng roots. Conclusion: This study will provide a comprehensive insight into the transcriptome of ginseng adventitious roots, and a way for successful transcriptome analysis and profiling of resource plants with less genomic information. The transcriptome profiling data generated in this study are available in our newly created adventitious root transcriptome database (http://im-crop.snu.ac.kr/transdb/index.php) for public use.

• BMB Reports
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• 제48권7호
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• pp.388-394
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• 2015

The brain is an organ that consists of various cell types. As our knowledge of the structure and function of the brain progresses, cell type-specific research is gaining importance. Together with advances in sequencing technology and bioinformatics, cell type-specific transcriptome studies are providing important insights into brain cell function. In this review, we discuss 3 different cell type-specific transcriptome analyses i.e., Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP)/RiboTag, and single cell RNA-Seq, that are widely used in the field of neuroscience. [BMB Reports 2015; 48(7): 388-394]

• Childhood Kidney Diseases
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• 제15권1호
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• pp.38-48
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• 2011

목 적: 국소성 분절성 사구체 경화증(Focal segmental glomerulosclerosis, 이하 FSGS)은 소아신부전의 원인 중 가장 흔한 사구체 질환이다. 일차성 FSGS의 병인은 아직 알려져 있지 않으므로, 저자들은 FSGS의 동물 모델을 대상으로 cDNA 마이크로어레이를 이용한 유전자 발현 양상 분석을 통하여 유전자 발현 수준에서의 FSGS의 질환의 특성을 밝히고자 하였다. 방 법: 사람의 일차성 FSGS와 유사한 질병경과를 보이는 동물모델인 FGS/kist 생쥐의 신피질 조직을 대조군 생쥐(FGS/kist 생쥐의 조상 strain인 RFM/kist 생쥐)와 AB 1700 mouse chip을 이용한 마이크로어레이 실험으로 비교하였다. 결 과: FGS 질병특이 유전자가 62개 추출되었다. 이들은 세포주기/사멸, 면역반응과 지질 대사/혈관 질환과 관련된 유전자들로써, 유전자간 network의 중심유전자가 면역반응(TNF, IL-6/4, IFNg)과 세포사멸 조절 유전자(TP 53), 그리고 지질대사의 중요 유전자인 PPARG이었다. 결 론: 이 연구에서 저자들은 자발적인 FSGS의 임상경과를 보이는 FGS/Kist 생쥐의 신장조직의 유전자 발현의 분석을 통하여 신장세포사멸과 면역반응에 뒤따르는 기질 섬유화, 그리고 지질 대사의 이상과 조기 혈관 질환이 FSGS의 병태생리에 기여할 것임을 다시 확인할 수 있었다. 추가적인 연구가 계속된다면 global transcriptome profiling 기법으로 병인 탐색 및 치료방법 개발 에 의미 있는 결과를 도출할 수 있을 것이다.

• BMB Reports
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• 제55권3호
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• pp.113-124
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• 2022

Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2003년도 생물공학의 동향(XIII)
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• pp.601-602
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• 2003

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.246-246
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• 2022

• 한국작물학회:학술대회논문집
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• 한국작물학회 2023년도 춘계학술대회
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• pp.132-132
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• 2023

• 한국약용작물학회:학술대회논문집
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• 한국약용작물학회 2012년도 심포지엄 및 춘계학술발표회
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• pp.341-342
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• 2012

• Genomics & Informatics
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• 제17권1호
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• pp.8.1-8.10
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• 2019

Alveolar type II cells constitute a small fraction of the total lung cell mass. However, they play an important role in many cellular processes including trans-differentiation into type I cells as well as repair of lung injury in response to toxic chemicals and respiratory pathogens. Transcription factors are the regulatory proteins dynamically modulating DNA structure and gene expression. Transcription factor profiling in microarray datasets revealed that several members of AP1, ATF, $NF-{\kappa}B$, and C/EBP families involved in diverse responses were expressed in mouse lung type II cells. A transcriptional factor signature consisting of Cebpa, Srebf1, Stat3, Klf5, and Elf3 was identified in lung type II cells, Sox9+ pluripotent lung stem cells as well as in mouse lung development. Identification of the transcription factor profile in mouse lung type II cells will serve as a useful resource and facilitate the integrated analysis of signal transduction pathways and specific gene targets in a variety of physiological conditions.

• Genomics & Informatics
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• 제10권1호
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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.