中科院——首届北京高通量测序深度应用系统学习实操班

培训目标及特点：
培训立足于最新技术和工具，强调融会贯通，强调综合应用。
采用「互动式教学，讨论式授课，案例式学习」 的教学模式。
培训邀请的主讲老师均是有理论和实际研究经验的专家。
学员通过与专家直接交流，能够分享到顶尖学术机构的研究经验和实验设计思路。
学员通过集中专题学习后能够扩展思路，在研究技术方面领悟更多。

主要内容：
1. DNA 测序技术的进化
a)  第一代测序技术：Sanger 测序原理
)  第二代测序技术：Illumina，454, Ion Torrent 原理
c)  第三代测序技术：PacBio, Hellicos 原理
d)  第四代测序技术: Oxford NanoPore 原理
e)  其他技术 Hybridization based methods (NabSys) 

2. High throughput Sequencing for various biological problems （应用高通量测序技术解决各种生物学问题）
2.1 RNA Transcription （RNA 转录）
1. Chromatin Isolation by RNA Purification (ChIRP-Seq)
2.  Global Run-on Sequencing (GRO-Seq)
3. Ribosome Profiling Sequencing (Ribo-Seq)
4. RNA Immunoprecipitation Sequencing (RIP-Seq)
5. High-Throughput Sequencing of CLIP cDNA library (HITS-CLIP)
6. Crosslinking and Immunoprecipitation Sequencing (CLIP-Seq)
7. Photoactivatable Ribonucleoside–Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP)
8. Individual Nucleotide Resolution CLIP (iCLIP)
9. Native Elongating Transcript Sequencing (NET-Seq)
10. Targeted Purification of Polysomal mRNA (TRAP-Seq)
11. Crosslinking, Ligation, and Sequencing of Hybrids (CLASH-Seq)
12. Parallel Analysis of RNA Ends Sequencing (PARE-Seq)
13. Genome-Wide Mapping of Uncapped Transcripts (GMUCT)
14. Transcript Isoform Sequencing (TIF-Seq)15. Paired-End Analysis of TSSs (PEAT)

2.2. RNA Structure （RNA 结构解析）
1. Selective2』-Hydroxyl Acylation Analyzed by Primer Extension Sequencing (SHAPE-Seq)
2. Parallel Analysis of RNA Structure (PARS-Seq)
3. Fragmentation Sequencing (FRAG-Seq)
4. CXXC Affinity Purification Sequencing (CAP-Seq)
5. Alkaline Phosphatase, Calf Intestine-Tobacco Acid Pyrophosphatase Sequencing (CIP-TAP)
6. Inosine Chemical Erasing Sequencing (ICE)
7. m6A-Specific Methylated RNA Immunoprecipitation Sequencing (MeRIP-Seq)

2.3.  Low-Level RNA Detection, Digital RNA Sequencing （微量 RNA 检测，数字 RNA 测序）1. Whole-Transcript Amplification for Single Cells (Quartz-Seq)
2. Designed Primer–Based RNA Sequencing (DP-Seq)
3. Switch Mechanism at the 5』 End of RNA Templates (Smart-Seq)
4. Switch Mechanism at the 5』 End of RNA Templates Version 2 (Smart-Seq2)
5. Unique Molecular Identifiers (UMI)
6. Cell Expression by Linear Amplification Sequencing (CEL-Seq)
7. Single-Cell Tagged Reverse Transcription Sequencing (STRT-Seq)

2.4.  Low-Level DNA Detection（微量 DNA 检测）
1. Single-Molecule Molecular Inversion Probes (smMIP)
2. Multiple Displacement Amplification (MDA)
3. Multiple Annealing and Looping–Based Amplification Cycles (MALBAC)
4. Oligonucleotide-Selective Sequencing (OS-Seq)
5. Duplex Sequencing (Duplex-Seq)

2.5.  DNA Methylation（DNA 甲基化）
1. Bisulfite Sequencing (BS-Seq)2. Post-Bisulfite Adapter Tagging (PBAT)
3. Tagmentation-Based Whole Genome Bisulfite Sequencing (T-WGBS)
4. Oxidative Bisulfite Sequencing (oxBS-Seq)
5. Tet-Assisted Bisulfite Sequencing (TAB-Seq)
6. Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq)
7. Methylation-Capture (MethylCap)
8. Methyl-Binding-Domain–Capture (MBDCap)
9. Reduced-Representation Bisulfite Sequencing (RRBS-Seq)

2.6.  DNA-Protein Interactions（DNA 和蛋白质互作）
1. DNase l Hypersensitive Sites Sequencing (DNase-Seq)
2. MNase-Assisted Isolation of Nucleosomes Sequencing (MAINE-Seq)3. Chromatin Immunoprecipitation Sequencing (ChIP-Seq)
4. Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE-Seq)
5. Assay for Transposase-Accessible Chromatin Sequencing (ATAC-Seq)
6. Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET)
7. Chromatin Conformation Capture (Hi-C/3C-Seq)
8. Circular Chromatin Conformation Capture (4-C or 4C-Seq)9. Chromatin Conformation Capture Carbon Copy (5-C)

2.7.  Sequence Rearrangements（序列重排）
1. Retrotransposon Capture Sequencing (RC-Seq)
2. Transposon Sequencing (Tn-Seq)3. Translocation-Capture Sequencing (TC-Seq) 
3. Data analysis （part 1）：data pre-processing（数据分析第一部分，数据前处理）3.1 evaluation of data quality 
数据质量评估 Data format，fasta，fastq，quality value，gff
33.2 Data cleanup 数据清洗 Quality filter, trimmer, clipper
4. Data analysis （part 2）：reference free analyses，（数据分析第二部分，无参转录组分析）4.1 Trinity de novo transcriptome assembly
4.2 Analysis of Differential Expressed Gene （DEGs）
4.3 Abundance estimation using RSEM
4.4 Differential expression analysis using EdgeR
4.5 Explore the results (cummerbund)
4.6 MA plot, Volcano plot, False Discovery Rate (FDR)
4.7 hierarchical two-way clustering, pairwise sample-distance, gene expression profiles.
5 Data analysis 
（part 3）：reference based analyses，（数据分析第三部分，有参转录组分析）
5.1 Mapping reads to the reference (tophat)
5.2 Assemble mapped reads (cufflinks)
5.3 Merge sample-specific assemblies (cuffmerge)
5.4 Analysis of Differentially Expressed Gene （DEGs）
5.5 Identify DEGs (cuffdiff)5.6 Explore the results (cummerbund)6 Data analysis 

（part 4）：from gene list to gene function，（数据分析第四部分，基因功能注释）
6.1 File format for annotation information: GFF3
6.2 Annotation
6.3 Homology search (BLAST+/SwissProt/Uniref90)
6.4 Protein domain identification (HMMER/PFAM)
6.5 Protein signal peptide and transmembrane domain prediction (singalP/tmHMM)
6.6 Comparing to currently curated annotation databases (EMBL Uniprot eggnog/GO)6.7 Enrichment analysis using DAVID
6.8 Gene name batch viewer6.9 Gene functional classification
6.10 Functional annotation chart
6.11 Functional annotation clusteringLab
（上机实验）
Lab1: Connection to cloudlab using PuttyLab
2: File transfer between cloudlab and local computer using filezillaLab
3: Linux commandsLab
4: Reads quality evaluation: fastqcLab
5a: Reads quality control: fastx tool kitLab
5b: Processing the mapping file: samtoolLab
6: Reference free analysis: Tuxedo packageLab
7: Reference based analysis: Trinity packageLab
8: Annotation: TrinnotateLab9: Enrichment analysis using DAVID 
参会费用：每人￥3900 元（含报名费、培训费、资料费、证书相关费用），食宿可统一安排，费用自理。 

主讲专家：中国科学院基因组研究所
中国医学科学院药用植物研究所 

联系人：张爱国 老师咨询电话：136 8311 1214
需要详细的红头通知文件，可电话咨询张老师。

编辑： 会议君    来源：丁香园