Big data-based identification and in situ application of single nucleotide polymorphism markers for geographical origin in aquatic organisms = 수산 생물의 원산지 판별을 위한 빅데이터 기반 SNP 마커의 발굴 및 현장 적용

목차 (Table of Contents)

• Chapter I. General introduction 1
• 1. Importance of geographic origin identification in aquatic organisms 1
• 2. NGS analysis for Big Data research 5
• 3. SNP analysis 7
• 4. Purpose of this study 8
• 5. References 10
• Chapter II. Development of SNP markers for geographical origin identification to differentiate Korean and Chinese Scapharca subcrenata 14
• 1. Abstract 14
• 2. Introduction 16
• 3. Materials and Methods 20
• 3.1. Sample collection 20
• 3.2. Genomic DNA extraction 21
• 3.3. GBS analysis 21
• 3.4. Identification of candidate SNP markers by bioinformatics analysis 24
• 3.5. PCR and genotype analysis 26
• 3.6. SYBR Green qPCR 29
• 3.7. Determination of threshold Ct values using a gaussian mixture model 31
• 3.8. Verification of the efficiency and limit of detection of the designed qPCR primers using SYBR Green qPCR 31
• 3.9. qPCR with SYBR Green staining and undiluted DNA 32
• 4. Results 35
• 4.1. GBS Library 35
• 4.2. Genetic differentiation in S. subcrenata populations from Korea and China 40
• 4.3. Identification of candidate SNP marker using statistical analysis 42
• 4.4. SNP marker selection 48
• 4.5. Training step 52
• 4.6. Verification of the accuracy of origin country determination by the SNP marker via validation test 55
• 4.7. Application of verified SNP markers 57
• 4.8. Identification of S. subcrenata country of origin using ΔCt values from SYBR Green and TaqMan qPCR analysis based on SNP genotypes 59
• 4.9. Specificity and detection efficiency of SNP marker 63
• 5. Discussion 65
• 6. References 72
• Chapter III. Development of SNP markers for geographical origin identification to differentiate Korean and Chinese Octopus minor 77
• 1. Abstract 77
• 2. Introduction 79
• 3. Materials and Methods 82
• 3.1. Sample collection 82
• 3.2. Genomic DNA extraction 83
• 3.3. GBS analysis 83
• 3.4. Identification of candidate SNP markers by bioinformatics analysis 86
• 3.5. PCR and genotype analysis 88
• 3.6. SYBR Green qPCR 91
• 3.7. Determination of threshold Ct value using a gaussian mixture model. 93
• 3.8. Verification of the efficiency and LOD of the designed qPCR primers using SYBR Green qPCR 93
• 3.9. qPCR with TaqMan probes and undiluted DNA 96
• 4. Results 97
• 4.1. GBS Library 97
• 4.2. Genetic differentiation in O. minor populations from Korea and China 102
• 4.3. Identification of candidate SNP marker using statistical analysis 104
• 4.4. SNP marker selection 110
• 4.5. Training step 113
• 4.6. Verification of the accuracy of origin country determination by the SNP marker via validation test 116
• 4.7. Application of verified SNP markers 118
• 4.8. Identification of O. minor country of origin using ΔCt values from SYBR Green 120
• 4.9. Specificity and detection efficiency of SNP marker 124
• 5. Discussion 126
• 6. References 132
• Chapter IV. Development of SNP markers for geographical origin identification to differentiate Korean and Russian Chionoecetes opilio 136
• 1. Abstract 136
• 2. Introduction 138
• 3. Materials and Methods 142
• 3.1. Sample collection. 142
• 3.2. Genomic DNA extraction 143
• 3.3. GBS analysis 143
• 3.4. Identification of candidate SNP markers by bioinformatics analysis 146
• 3.5. PCR and genotype analysis. 148
• 3.6. SYBR Green qPCR. 151
• 3.7. Determination of threshold Ct value using a gaussian mixture model 153
• 3.8. Verification of the efficiency and limit of detection of the designed qPCR primers using SYBR Green qPCR 153
• 3.9. qPCR with SYBR Green staining and undiluted DNA 154
• 4. Results 156
• 4.1. GBS Library 156
• 4.2. Genetic differentiation in C. opilio populations from Korea and Russia 161
• 4.3. Identification of candidate SNP marker using statistical analysis 163
• 4.4. SNP marker selection 169
• 4.5. Training step 173
• 4.6. Verification of the accuracy of origin country determination by the SNP marker via validation test 178
• 4.7. Application of verified SNP markers 180
• 4.8. Identification of C. opilio country of origin using ΔCt values from SYBR Green . 182
• 4.9. Specificity and detection efficiency of SNP marker 185
• 5. Discussion 187
• 6. References 193
• Chapter V. Development of SNP markers for geographical origin identification to differentiate Korean and Japanese Pagrus major 197
• 1. Abstract 197
• 2. Introduction 199
• 3. Materials and Methods 202
• 3.1. Sample collection. 202
• 3.2. Genomic DNA extraction 203
• 3.3. GBS analysis 203
• 3.4. Identification of candidate SNP markers by bioinformatics analysis 206
• 3.5. PCR and genotype analysis. 208
• 3.6. SYBR Green qPCR. 210
• 3.7. Determination of threshold Ct value using a gaussian mixture model 212
• 3.8. Verification of the efficiency and LOD of the designed qPCR primers using SYBR Green qPCR 212
• 3.9. qPCR with SYBR Green staining and undiluted DNA 213
• 4. Results 214
• 4.1. GBS Library 214
• 4.2. Genetic differentiation in P. major populations from Korea and Japan 219
• 4.3. Identification of candidate SNP marker using statistical analysis 221
• 4.4. SNP marker selection 227
• 4.5. Training step 231
• 4.6. Verification of the accuracy of origin country determination by the SNP marker via validation test 235
• 4.7. Application of verified SNP markers 237
• 4.8. Identification of P. major country of origin using ΔCt values from SYBR Green . 239
• 4.9. Specificity and detection efficiency of SNP marker 242
• 5. Discussion 244
• 6. References 249
• 국문 요약 254