Single’cell)RNA)sequencing) methodologies)and)ESCG)plaorm) · Modified from: Picelli (2016), RNA...
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Singlecell RNA sequencing methodologies and ESCG pla:orm Karolina Wallenborg October 2, 2017
Transcript of Single’cell)RNA)sequencing) methodologies)and)ESCG)plaorm) · Modified from: Picelli (2016), RNA...
Single-‐cell RNA sequencing methodologies and ESCG pla:orm
Karolina Wallenborg October 2, 2017
From Wikipedia
Short history of scRNA-‐seq
Adapted from: Kolodziejczyk A et al, Molecular Cell, 2015
10XGenomics BioRad/Illumina BD Resolve
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
Single-‐cell isolaTon or capture
Adapted from: Kolodziejczyk A et al, Molecular Cell, 2015
MulT-‐Sample Nano-‐Dispenser
Micro-‐well chip
Cytoplasmic aspiraTon
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
Current scRNA-‐sequencing protocols
Adapted from Poulin JF et al, Nature Neuroscience, 2016
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
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
0 2 4 6 8 10 12
Oligod
endrocytes
Breast Cancer C
ells
Brain cells
Epen
dymal cells
Cardiomyocytes
Neu
rons
KeraTn
ocytes
GBM cells
Neu
ral Crest Cells
Innate Lym
phoid Ce
lls
Blastema Ce
lls
ES Cells
Immun
e Ce
lls
CAFs
Endo
thelial Cells
Pericytes
SpermaT
ds
Fibrob
lasts
Pancreas cells
Mesen
chym
al Cells
Smoo
th m
uscle Ce
lls
CLL tumor Cells
Epith
elial Cells
Bone
marrow Cells
Kidn
ey Cells
Microglia
Thym
ic Cells
Macroph
ages
Liver
Astrocytes
Endo
thelial Cells
Leukem
ia Cells
IPS Ce
lls
Cancer Cell line
Tongue
Cells
Number of projects per cell type
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 • NaTonal BioinformaTcs Infrastructure Sweden (NBIS)
– Data delivery – User fees
How many cells must I analyze?
And how deep must I sequence ?
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
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
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
10X Genomics -‐Drop-‐seq technology
• IsolaTon: Droplets • Input: Cells/nuclei • Scale: 500-‐10,000 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
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 500-‐10,000
Input FACS-‐sorted cells Suspension Suspension
Transcript coverage Full-‐length 5’ 3’
Features • Flexible delivery • Isoforms, SNPs,
mutaTons • Nuclei • ERCC spike-‐ins
• LimiTng diluTon/FACS
• Cell selecTon • Unbiased • 8 samples parallel • Nuclei
• High throughput • 8 samples parallel • Nuclei • Sample pooling
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
User fees
Smart-‐seq2
384 well plate
STRT-‐Wafergen
9600 wells chip (~2,500 cells)
10XGenomics
1 sample (~3,000 cells)
• ValidaTon • Smart-‐seq2
library • Sequencing • (50 bp, single-‐
read
• ValidaTon • STRT library (dual
index) • Sequencing (50 bp
single-‐read)
• 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.
ESCG StaTsTcs
Smart-‐seq2, 95500
STRT-‐C1 (Fluidigm),
6729 STRT-‐seq-‐2i (Wafergen),
21282
10X Genomics, 158500
Mouse , 37 Human, 33
Newt, 2
Pig, 1 Monkey, 2 Hydra, 1 Zebrafish,
1
KI, Solna KI, Huddinge
UU
SU Lund
LICR InternaTonal
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
Modified from: Picelli (2016), RNA Biology, July 21: 1-14
The STRT/C1 method
mRNA
RT & template switching
C1-P1-T31AAAAAAAA
TTTTTTTTT
AAAAAAAArGrGrGC C C
C1-P1-TSO
cDNA amplification
C1-P1-PCR
PvuI site
TTTTTTTTT
UMI
AAAAAAAAGGGCCC TTTTTTTTT
C1-P1-PCR
Tagmentation
GGGCCC
AAAAAAAA TTTTTTTTT
GGGCCC
AAAAAAAA TTTTTTTTT
Cell barcode
Illumina P2
biotin
Streptavidin bead separation - pooling - PvuI restriction
GGGCCC
AAAAAAAA TTTTTTTTT
Sequencing
GGGCCC
Read 2 Read 1
Modified from: Picelli (2016), RNA Biology, July 21: 1-14
The Smart-seq2 method
mRNA
RT & template switching
SMARTdT30VN
AAAAAAAANVTTTTTTTTT
AAAAAAAANVTTTTTTTTT
rGrG+GC C C
TSO-LNA
cDNA amplification
NVTTTTTTTTTGGGCCC
AAAAAAAA
ISPCR
ISPCR
Tagmentation & library preparation
NVTTTTTTTTTGGGCCC
AAAAAAAA
i5 index
i7 index
Illumina P7
Illumina P5
Sequencing
Read 1 Read 2
+G --> LNA-modified G
