这个专题叫Schedule for Single-cell RNA-seq workshop，那就把这个专题叫做【scRW】吧
第二课 Introduction to Single Cell RNA Sequencing
## <Introduction to Single Cell RNA Sequencing>
## 目录
## 1 Common applications of single cell RNA sequencing.
## 2 Overview of single cell RNA sequencing platforms.
## 3 Modified scRNA-seq workflows
## 4 Sample preparation and experimental design.
## 5 Effects of sample prep and sample type on analysis
Bulk vs Single Cell RNA Sequencing (scRNA-seq)
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Transcriptome Coverage (mRNA)
Transcriptome Coverage (mRNA) -
The World Between Bulk & scRNA-seq
The World Between Bulk & scRNA-seq
ps. throughput = the amount of material or items passing through a system or process.
1.Common Applications of scRNA-seq
More Cells or More Sequencing Reads?
2.Overview of single cell RNA sequencing platforms
2.1.1 Full Length Transcripts: SMART-seq (v3)
H Lim et al, Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR. J. Vis. Exp. (87), e51408, 2014 (doi:10.3791/51408)
M Hagemann-Jensen et al, Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3 bioRxiv 2019 (doi: https://doi.org/10.1101/817924)
2.1.2 Seq-Well: Honeycomb Biotechnologies
TM Gierahn et al, Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nat Methods. 2017 Apr;14(4):395-398. doi: 10.1038/nmeth.4179
2.1.3 Droplet scRNA-seq
2.1.4 inDrops Method Overview
A. M. Klein et al., Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells, Cell 2015 (doi: 10.1016/j.cell.2015.04.044)
R. Zilionis et al., Single-cell barcoding and sequencing using droplet microfluidics, Nature Protocols 2016 (doi: 10.1038/nprot.2016.154 )
2.2.1 scRNA-seq Library Structure (inDrops)
2.2.2 10x Genomics Method Overview
2.2.3 Doublets / Cell Density
2.2.4 Scrublet: Computational Identification of Doublets
S. Wolock et al. Scrublet: computational identification of cell doublets in single-cell transcriptomic data, bioRxiv 2018 (DOI: 10.1101/357368)
2.2.5 On the Horizon: Spatial Transcriptomics
Rodriques et al, Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.
Science. 2019 Mar 29;363(6434):1463-1467.
3.Modified scRNA-seq workflows
3.1 Transcript Specific Library Prep
3.2 CITE-seq / Cell Hashing
3.3 Cell Hashing / CITE-seq
3.4 Label-Free Multiplexing of Patient Samples
3.5 10x Capture Sequence / Feature Barcode
3.5.1 10x V(D)J Immune Profiling & 5’ gene expression
3.5.2 10x V(D)J Immune Profiling
3.6 TotalSeq
4.Sample preparation and experimental design
4.1 Single Cell Core Sample Repertoire
4.2 Key to Success: Sample Preparation
4.3 Sample Preparation
4.3.1 Sample Preparation: increasing cell viability
4.3.2 Sample Preparation: single cell suspension
4.4 Sample preparation protocol varies by cell-type
4.5 Enrichment Methods: pros & cons
4.6 Enrichment Methods: cell staining
4.7 Sample Preparation: cell numbers
- 液滴法的最小细胞数为10,000-25,000
-需要约50-100个具有独特转录组的细胞来鉴定种群群
-每ul 100-1000个细胞=每毫升100,000-1,000,000个细胞 - 通过血细胞计数器计数细胞–不要相信分类计数
-来自分选器的计数通常是实际细胞计数的½ - 尝试负选择以去除不需要的细胞
- 在更broader的标记上进行分类以增加细胞数
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对于不可避免的低密度样品
-将具有明显表达特征的细胞掺入样品中（没懂）
sample preparation
4.8 Sample Preparation: buffers
确保缓冲液不含钙，镁，EDTA或肝素（抑制RT-PCR）
4.9 Sample Preparation: viability checks 样品制备：可行性检查
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检查样品随时间的生存能力
-如果生存能力在短时间内降低，这将反映在转录数据中；
-线粒体读取计数很高。 -
检查单细胞悬液上清液中是否存在游离的浮动RNA（Ribogreen）
-在所有样品中产生背景噪音并使分析复杂化； -
台盼蓝trypan阳性的死细胞数量是和废掉的reads数量是呈正比的
-如果在封装时有30％的细胞死亡，那么最多将可以使用70％的测序数据。
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4.10 Sample Preparation: dead cell removal
- FACS out dead cells
-Will have all associated complications of FACS. - Miltenyi dead cell removal kit
-Magnetic beads used to remove dead cells & debris.
值得深思的问题
- 您要去除多少死细胞？
- 这对您正在研究的生物学意味着什么？
- 记录您的样品制备元数据！！！
4.11 Sample Preparation: cryopreservation
- 各种冷冻保存技术对样本（PBMC或细胞系）有几篇论文的相关报道。
- 冷冻保存成功与否取决于样品类型。
- 血液细胞和免疫细胞冷冻效果很好。
- 关键是补液后细胞的活力。
- 将Nuc-seq作为冷冻保存细胞的选项。
- 冷冻时组织的质量是下游数据质量的主要因素。
- 单细胞核心已将细胞冷冻在补充了5％DMSO的标准生长培养基中，效果最佳。
- 观察到解冻后原代细胞具有20％的细胞死亡。
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如果要冷冻组织以备后用，您可能需要考虑在BAM Banker冷冻保存剂中冷冻保存50 mg组织块。
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4.12 Sample Preparation: single nuclei RNA-seq
- 从目标样品中提取核。
- 去除死细胞/垂死细胞的转录噪音。
- 最常用于神经元样本。
- 适用于速冻临床样品。
- 多项研究表明核转录本占整个细胞转录本的很大一部分。
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由于内含子和非编码RNA的存在，分析更加困难。
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4.13 Best practices to obtain high quality sample
sample prep地址
-https://www.protocols.io/
-https://support.10xgenomics.com/single-cell-geneexpression/sample-prep
-https://community.10xgenomics.com/
5.Effects of sample prep and sample type on analysis
5.1 How Sample Prep Effects Data
5.2 Data Analysis: Quality Control (QC) metrics
5.2 关于scRNA-seq的最终想法
