Human Disease Research by Applying Next-Generation Sequencing and NanoString Technology

다국어 초록 (Multilingual Abstract)

(Chapter 1 Abstract)
Molecules and Cells. 42(1): 87-95 (SCI), 2019
Wonseok Shin participated as the first author.
Novel Discovery of LINE-1 in a Korean Individual by a Target Enrichment Method

Wonseok Shin
Department of Nanobiomedical Science
General Graduate School of Dankook University

Advisor: Professor. Kyudong Han, Ph. D.

Long interspersed element-1 (LINE-1 or L1) is an autonomous retrotransposon, which is capable of inserting into a new region of genome. Previous studies have reported that these elements lead to genomic variations and altered functions by affecting gene expression and genetic networks. Mounting evidence strongly indicates that genetic diseases or various cancers can occur as a result of retrotransposition events that involve L1s. Therefore, the development of methodologies to study the structural variations and interpersonal insertion polymorphisms by L1 element-associated changes in an individual genome is invaluable. In this study, we applied a systematic approach to identify human-specific L1s (i.e., L1Hs) through the bioinformatics analysis of high-throughput next-generation sequencing data. We identified 525 candidates that could be inferred to carry non-reference L1Hs in a Korean individual genome (KPGP9). Among them, we randomly selected 40 candidates and validated that approximately 92.5% of non-reference L1Hs were inserted into a KPGP9 genome. In addition, unlike conventional methods, our relatively simple and expedited approach was highly reproducible in confirming the L1 insertions. Taken together, our findings strongly support that the identification of non-reference L1Hs by our novel target enrichment method demonstrates its future application to genomic variation studies on the risk of cancer and genetic disorders.
 
(Chapter 2 Abstract)

Application of NanoString Technologies in Angioimmunoblastic T-cell lymphoma

Wonseok Shin
Department of Nanobiomedical Science
General Graduate School of Dankook University

Advisor: Professor. Kyudong Han, Ph. D.

Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive disease. Most cancer diagnoses are determined by anatomical histology. Therefore, many samples are stored in FFPE blocks for H&E staining. However, RNAs extracted from the FFPE block have a high level of fragmentation, making it difficult to perform accurate DEG analysis using RNA sequencing. To overcome fragmented RNAs drawback in NGS application, we applied the NanoString nCounter® technique of hybridization method that can be used for DEG analysis without PCR amplification. We characterized the gene expression profiling of AITLs though transcriptome analysis based on the nCounter® PanCancer IO 360™ Panel and NanoString platform. To perform the analysis of differential expression gene (DEGs) profiles in AITLs, we compared the NanoString data from eight AITL patients with a healthy control donor. Ninety-one genes were up-regulated and six genes were down-regulated in AITLs compared to control. The GO analysis of 97-DEGs revealed that they were closely related to cytokine, MAPK cascade, leukocyte differentiation, and immune response, suggesting that this affect the immune system. In addition, KEGG analysis revealed that AITL DEGs were found to be highly involved in cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway. We believe that comprehensive multiplex studies, along with Nanostring analysis, may be helpful to understand the molecular mechanisms of AITL, including mutations, gene expression, and protein expression studies. 

(Chapter 3 Abstract)
Genes & Genomics. 41(10): 1233-1240 (SCIE), 2019
Wonseok Shin participated as the corresponding author.
Comparison of Library Construction Kits for mRNA Sequencing in the Illumina Platform

Wonseok Shin
Department of Nanobiomedical Science
General Graduate School of Dankook University

Advisor: Professor. Kyudong Han, Ph. D.

The emergence of next-generation sequencing (NGS) technologies has made a tremendous contribution to the deciphering and significance of transcriptome analysis in biological fields. Since the advent of NGS technology in 2007, Illumina, Inc. has provided one of the most widely used sequencing platforms for NGS analysis. Although reagents and protocols provided by Illumina are adequately performed in transcriptome sequencing, recently, alternative reagents and protocols which are relatively cost effective are accessible. However, the kits derived from various manufacturers have advantages and disadvantages when researchers carry out the transcriptome library construction. We compared them using a variety of protocols to produce Illumina-compatible libraries based on transcriptome. Three different mRNA sequencing kits were selected for this study: TruSeq® RNA Sample Preparation V2 (Illumina, Inc., USA), Universal Plus mRNA-Seq (NuGEN, Ltd., UK), and NEBNext® Ultra™ Directional RNA Library Prep Kit for Illumina® (New England BioLabs, Ltd., USA). We compared them focusing on cost, experimental time, and data output. The quality and quantity of sequencing data obtained through the NGS technique were strongly influenced by the type of the sequencing library kits. It suggests that for transcriptome studies, researchers should select a suitable library construction kit according to the goal and resources of experiments. The present work will help researchers to choose the right sequencing library construction kit for transcriptome analyses.

목차 (Table of Contents)

• Contents
• Abstract (Chapter 1)···············································································i
• Abstract (Chapter 2)·············································································iii
• Abstract (Chapter 3)··············································································v
• Contents···························································································vii
• List of Figures·····················································································xi
• List of Tables·····················································································xiii
• Chapter 1. Novel discovery of LINE-1 in a Korean individual by a target enrichment method·······························································································1
• 1.1. Introduction···················································································2
• 1.2. Materials and Methods······································································5
• 1.2.1. Probe design·················································································5
• 1.2.2. Library construction······································································6
• 1.2.3. Next-generation sequencing····························································10
• 1.2.4. Data analyses··············································································11
• 1.2.5. Validation of non-reference L1Hs insertions········································14
• 1.3. Results and Discussion·····································································16
• 1.3.1. Description of the L1Hs-targeted enrichment method····························16
• 1.3.2. Identification of non-reference L1Hs insertions····································24
• 1.3.3. Characterization of non-reference L1Hs insertions································58
• 1.3.4. Validation of non-reference L1Hs insertions and identification of false positives····························································································81
• 1.4. Conclusion···················································································88
• 1.5. References····················································································89
• Chapter 2. Application of NanoString technologies in angioimmunoblastic T-cell lymphoma·························································································95
• 2.1. Introduction·················································································96
• 2.2. Materials and Methods····································································98
• 2.2.1. Sample collection and Clinical information·········································98
• 2.2.2. Total RNA extraction from FFPE samples and NanoString nCounter Assay·99
• 2.2.3. Normalization and Statistics··························································100
• 2.2.4. Data analysis·············································································101
• 2.3. Results·······················································································102
• 2.3.1. Application of Nanostring system from AITL FFPE blocks·····················102
• 2.3.2. Differential expression genes profiling of AITLs using NanoString system output·····························································································105
• 2.3.3. Gene Ontology and KEGG pathway analysis of AITL···························126
• 2.4. Discussion ··················································································154
• 2.5. References··················································································157
• Chapter 3. Comparison of library construction kits for mRNA sequencing in the Illumina platform··············································································162
• 3.1. Introduction················································································163
• 3.2. Materials and Methods···································································166
• 3.2.1. Isolation of total RNA from the tissue···············································166
• 3.2.2. RNA-based library construction·····················································167
• 3.2.3. NGS and Data analysis·································································170
• 3.3. Results and Discussion···································································172
• 3.3.1. Experimental design and components of RNA-seq kit···························172
• 3.3.2. Comparison of experimental protocols·············································178
• 3.3.3. Analysis of RNA-seq data······························································179
• 3.4. Conclusion··················································································188
• 3.5. References··················································································190
• VITA······························································································194
• Research Ethics Education Certificate·····················································200