Single- cell RNA sequencing methodologies and ESCG pla:orm. Karolina Wallenborg October 2, 2017

Transcription

1 Single- cell RNA sequencing methodologies and ESCG pla:orm Karolina Wallenborg October 2, 2017

2 From Wikipedia

3 Short history of scrna- seq 10XGenomics BioRad/Illumina BD Resolve Adapted from: Kolodziejczyk A et al, Molecular Cell, 2015

4 ApplicaTons for scrna- sequencing Heterogeneity analysis Cell type identficaton Lineage tracing, cellular states in differentaton and development Monoallelic gene expression, splicing pazerns Zeisel A, et al, Science 2015

5 Single- cell isolaton or capture MulT- Sample Nano- Dispenser Micro- well chip Cytoplasmic aspiraton Adapted from: Kolodziejczyk A et al, Molecular Cell, 2015

6 Reverse transcripton and amplificaton Adapted from: Kolodziejczyk A et al, Molecular Cell, 2015 Poly(T) primer Single cell contain ~10 pg total RNA 1-5% is mrna 10-20% of the transcripts get reverse transcribed

7 Current scrna- sequencing protocols Adapted from Poulin JF et al, Nature Neuroscience, 2016

8 Single- cell RNA- sequencing protocols - Which method suits you? Full- length Whole transcript informaton Gene expression quantficaton Isoform, SNP and mutatons Tag- based methods (5 or 3 ) EsTmate of transcript abundance Early multplexing Combined with molecular countng Retain DNA strand informaton

9 ESCG pla:orm Started in 2015 Sten Linnarsson (STRT- seq, STRT/C1), Rickard Sandberg (Smart- seq2) High throughput single- cell RNA- sequencing 280,000 single cells sequenced 77 projects Number of projects per cell type Oligodendrocytes Breast Cancer Cells Brain cells Ependymal cells Cardiomyocytes Neurons KeraTnocytes GBM cells Neural Crest Cells Innate Lymphoid Cells Blastema Cells ES Cells Immune Cells CAFs Endothelial Cells Pericytes SpermaTds Fibroblasts Pancreas cells Mesenchymal Cells Smooth muscle Cells CLL tumor Cells Epithelial Cells Bone marrow Cells Kidney Cells Microglia Thymic Cells Macrophages Liver Astrocytes Endothelial Cells Leukemia Cells IPS Cells Cancer Cell line Tongue Cells

10 How do you get started? User meetng Project discussion Feasibility Tissue, cells Project size Time line Choice of method Data output Number of cells to be analyzed LocaTon, cell delivery BioinformaTcs Early contact How many cells must I analyze? NaTonal BioinformaTcs Infrastructure Sweden (NBIS) Data delivery User fees And how deep must I sequence?

11 Single cell submission guidelines OpTmize your cell isolaton protocol Limit Tme of isolaton Be gentle Single cell suspension criteria High viability (>80%) No cell clumps or debris Cell strain and wash FACS facility Cell viability stain Visit us Single cell suspension quality control

12 Smart- seq2 at ESCG 384 well plates IsolaTon: FACS Input: cells/nuclei Full- length Sequencing: 50bp single- read ERCC spike- ins Two different dilutons Flexible delivery

13 STRT- seq- 2i: dual- index 5 single- cell RNA- sequencing Adapted from: Hochgerner H, et al, BioRxiv, 2017 IsolaTon: FACS/dispensing Input: Cells/nuclei Scale: 9600 cells (~2500 cells) Sequencing: 5 - tag (50 bp single read) Up to 8 samples in parallel No size limitaton UMI:s

14 10X Genomics - Drop- seq technology IsolaTon: Droplets Input: Cells/nuclei Scale: ,000 x 8 Sequencing: 3 - tag (HiSeq2500/NovaSeq) Up to 8 samples in parallel Validated up to 30μm (channels 50μm) UMI, cell barcode, sample barcode CellRanger, Loupe, R- package

15 Comparing our services Full- length Quan?ta?ve Smart- seq2 STRT- Wafergen 10xGenomics Format Eppendorf Twin- tek Microwell chip Chromium microfluidics chip Cell number 384 9,600 (~2,500) 8 x ,000 Input FACS- sorted cells Suspension Suspension Transcript coverage Features Flexible delivery Isoforms, SNPs, mutatons Nuclei ERCC spike- ins Full- length 5 3 LimiTng diluton/ FACS Cell selecton Unbiased 8 samples parallel Nuclei High throughput 8 samples parallel Nuclei Sample pooling

16 Data delivery Sequencing at NGI, HiSeq2500, NovaSeq Analysis pipelines for mouse and human In- house: STRT, smart- seq2 Cell ranger: 10xGenomics UPPMAX, BioinformaTcs compute and storage Users apply individually for projects Annotated gene expression data, QC- files, Fastq BioinformaTcs Done by user Support from BILS and WABI CollaboraTons

17 User fees Smart- seq2 384 well plate ValidaTon Smart- seq2 library Sequencing (50 bp, single- read STRT- Wafergen 9600 wells chip (~2,500 cells) ValidaTon STRT library (dual index) Sequencing (50 bp single- read) 10XGenomics 1 sample (~3,000 cells) ValidaTon Illumina library Sequencing (paired- end, dual index) ~40,000 SEK ~50,000 SEK ~42,000 SEK Costs include: Reagents, consumables, instrument depreciaton, instrument service, personnel. Overhead is not included.

18 ESCG StaTsTcs Pig, 1 Monkey, 2 Hydra, 1 Zebrafish, 1 Newt, 2 10X Genomics, Smart- seq2, Human, 33 Mouse, 37 STRT- C1 (Fluidigm), 6729 STRT- seq- 2i (Wafergen), LICR SU Lund InternaTonal UU KI, Huddinge KI, Solna

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20 What lays ahead? Emerging techniques Single nuclei RNA- sequencing Single cell ATAC- seq Transcriptome + Epigenome Transcriptome + Proteome CRISPR- Cas9 + Transcriptome split- pooling scrna- seq ValidaTon Small molecule FISH Human Cell Atlas

21 The STRT/C1 method AAAAAAAA mrna C1-P1-T31 TTTTTTTTT PvuI site biotin RT & template switching C1-P1-TSO UMI rgrgrg AAAAAAAA C C C TTTTTTTTT cdna amplification C1-P1-PCR GGG AAAAAAAA CCC TTTTTTTTT C1-P1-PCR Tagmentation GGG CCC AAAAAAAA TTTTTTTTT Illumina P2 GGG CCC Cell barcode AAAAAAAA TTTTTTTTT Streptavidin bead separation - pooling - PvuI restriction GGG CCC AAAAAAAA TTTTTTTTT Sequencing GGG CCC Read 2 Modified from: Picelli (2016), RNA Biology, July 21: 1-14 Read 1

22 The Smart-seq2 method AAAAAAAA mrna NVTTTTTTTTT SMARTdT30VN +G --> LNA-modified G RT & template switching TSO-LNA rgrg+g AAAAAAAA C C C NVTTTTTTTTT cdna amplification ISPCR GGG CCC AAAAAAAA NVTTTTTTTTT ISPCR Tagmentation & library preparation GGG CCC AAAAAAAA NVTTTTTTTTT i5 index Illumina P5 Illumina P7 i7 index Sequencing Read 1 Modified from: Picelli (2016), RNA Biology, July 21: 1-14 Read 2