single cell multi-omics technologies and … of...single-cell g&t-seq (voet group) erccs a a a a...

Single Cell Multi-Omics Technologies and

Applications

Lia Chappell

Wellcome Sanger Institute, Cambridge, UK

LC5@sanger.ac.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: LC5@sanger.ac.uk

“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