ANTIGEN PRESENTATION T – CELL RECOGNITION T – CELL ACTIVATION T – CELL EFFECTOR FUNCTIONS
Single Cell Multi-Omics Technologies and … of...Single-cell G&T-seq (Voet group) ERCCs A A A A A A...
Transcript of Single Cell Multi-Omics Technologies and … of...Single-cell G&T-seq (Voet group) ERCCs A A A A A A...
Single Cell Multi-Omics Technologies and
Applications
Lia Chappell
Wellcome Sanger Institute, Cambridge, UK
Twitter: @LiaVLChappell
Shameless advertisement! ☺
Andy Russell
(Sanger)
Thierry Voet
(KU Leuven + Sanger)
Also Twitter! (#SingleCell and more)
Generating a suspension
of single cells(Really important!)
Tissue dissociation:
• Human Cell Atlas (HCA) https://www.humancellatlas.org/
• Protocols.io
https://www.protocols.io/groups/hca
• 10x Genomics website
• BioRxiv
Cell preservation:
• Methanol (rehydrate with PBS
or SSC, Chen et al. 2018)
• DSP (a reversible crosslinker, Attar et al. 2018)
• RNAlater (a commercial salt solution)
• RNA Assist (a commercial product: like honey!)
• Freeze down (like cell culture)
• BioRxiv good source for latest “tricks”
What layers can you capture from single cells?
(Mostly with sequencing)
Layers in single cells
RNA
DNA
Protein
(From Illumina)
RNA
ATAC-seq for open chromatin
sc gDNA: problems
True
False negative
False positive
sc gDNA: choose SNPs or CNVs(SNPs) (CNVs)
Bisulfite sequencing for DNA methylation
Convert unmethylated
C → U
Methylated C
G&T-seq as an example of a Multi-Omics method
Single-cell G&T-seq (Voet group)
ERCCs
A A A A A
A
ERCC
T T T T T
Low-elution magnet
gDNA well
mRNA well
BeadsCell lysate
In plate format,
automated on
robotic platforms
Nature Protocols. 2016 Nov;11(11):2081-103.
Nature Methods. 2015 Jun;12(6):519-22.
Relationship between RNA and DNA maintained by copying plate layout for
both layers
RNA DNA
Genotyping + Phenotyping at single-cell resolution
genotype
phenotype
SNVs SVs CNVs
Coding SNVs Fusion transcripts Gene dosage
&
RNA
DNA
Single-cell G&T-seq
Nature Protocols. 2016 Nov;11(11):2081-103.
Nature Methods. 2015 Jun;12(6):519-22.
Genotype-phenotype correlation at single cell level
DNA
Genotype-phenotype correlation at single cell level
scG&T-seqscRNA-seq scG&T-seq
• The relative contribution of
embryonic cells to tissues/organs;
• The ‘noise’ in early embryonic
development between individuals;
• Developmental and cellular
architectures of organs:
➢ clonal structures
➢ amount of stem cells contributing to
functional units
➢ differentiation trajectories available to
given adult stem cell populations;
• Nature and role of somatic
mutation in phenotypic variation,
aging and disease
• Cell lineage perturbed in diseased
tissues/organs
One human, multiple genomes
… as a means to study cellular architectures of human organs
scNMT-seq as another example
of a Multi-Omics method
scNMT-seq: three layers(from two plates)
Relationship between RNA and Epigenome maintained by copying plate
layout for both layers
RNA
Epigenome
(Accessibility and methylation)
Other plate-based Multi-Omics methods
Multiple ways of doing this…
Alternatives to plate-based
Multi-Omics methods
CITE-seq/REAP-seq/AB-seq→same barcode for 2 libraries
Combinatorial indexing→ Fixed cells only!
Fig. 1 sci-CAR workflow.
Junyue Cao et al. Science 2018;361:1380-1385
Published by AAAS
Another dimension: spatial
Slide-seq→ each bead barcode has
known spatial location
Slide-seq
Slide-seq
Beyond plate format…
Single cell RNA-seq: plate format
Single cell RNA-seq: plate format
A trend for increasing scale…
A trend for increasing scale…
Valentine Svensson, Roser Vento-Tormo, Sarah A Teichmann
Another way: droplets
Barcoded beads…
Barcoded beads Sequencing reads
Drop-seq (Macosko et al. 2015)
“Barnyard” plots (Drop-seq)
(Macosko et al. 2015)
Drop-seq
A
B
C
D
InDrop
10X “black box”
Nanowells: e.g. Seq-Well
Beads fit into wells…
Same beads as Drop-seq…
Barcoded beads Sequencing reads
Capture mRNA on beads
Master mold: reverse of wells
Wafer
(replaceable)
Glass slide
Hole in
Hole out
ç
Master mold: reverse of wells
Holes in Holes out
Plasma oven: neat chemistry!
MIT plasma oven
Sanger plasma oven
Sanger plasma oven
Surface chemistry
Workflow for sample loading…
Count and
aliquot
beads
Prep cell
suspension
(up to 10k)
Cells and
beads
loaded
onto array
mRNA
bound to
beads
“Smart-
seq2”
sized
cDNA pool
3’ end
scRNA-
seq library
Load
beads
onto array
Day 0 Day 1 Day 2
Beads on microwell array
HEK/3T3 cells→ maths fail! (10 fold excess!)
Mouse cells: right number!
Seq-Well: at least as good as Drop-seq
From Seq-Well paper (Gierahn et al. 2017)
Thanks for listening!Twitter: @LiaVLChappell
Email: [email protected]
“Tracing early mammalian
lineage decisions by single
cell genomics”
(“Gastulation project”)
• Wolf Reik
• Sarah Teichmann
• Bertie Gottgens
• Thierry Voet
• John Marioni
• Shankar Srinivas
• Jennifer Nichols
• Ben Simons
“The Homunculus in our
Thymus: A Cellular
Genomics Approach”
(“Thymus project”)
• Georg Hollander
• Chris Ponting
• John Marioni
• Chris Schofield
• Jon Chapman
• Thierry Voet
• Stephen Sansom
Team 176
(Voet group at Sanger)
• Thierry Voet
• Andy Russell
• Lauren Deighton
• Raheleh Rahbari
• Sebastian Grossmann
• Sabine Eckert
• Charlotte King
• Jannat Ijaz