Single Cell RNA Sequencing

(Applications & Methods)

Presented by:

Bushra Arif (11)

Farah Arooj (4)

Institute of Biochemistry and Biotechnology

University of Punjab

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Contents

Introduction of scRNA sequencing

Why we use single cell

Methods of isolating single cell

Methods of scRNA seq

Data Analysis

Applications

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Introduction

• Genetically identical cells show variations

• Transcriptome: an essential piece of cell identity

• Reveal the state of a cell

• Mammalian cells contain 105–106 mRNA molecules

• Population studies averages the cells transcriptome

• Inappropriate for rare population studies

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Why Single cell study?

Single-cell studies reveal

• Relationship between intrinsic cellular processes

and extrinsic stimuli

• Hidden variation in gene expression

• Unknown species or regulatory processes of

biotechnological or medical relevance

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History

• Norman N. Iscove done work on exponential amplification

of cDNAs by PCR

• James Eberwine done linear amplification of cDNA by T-

RNA polymerase-based in vitro transcription

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Method of the year; 2013

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Single Cell RNA Sequencing Process

By Huang et al., 2014

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Florescence-activated cell sorting

(FACS) 33%

Micromanipulation17%

Laser capture microdissection

17%

Optical tweezers6%

Single cell isolation methods

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Florescent Activated Cell Sorting(FACS)

• Technique for purification of cell and subcellular

populations

• High purity of the sorted population

• Sort as many as 300,000 cells per minute

• Machine can be set to ignore droplets containing dead

cells

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Limitations

• Require large starting material

• Not well suited for the isolation of extremely rare

cells

• Needs antibodies to target specific proteins

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Micromanipulation

• Microscope assisted manual cell picking tool

• Targeted isolation of single cell

• Select a specific cell through microscope observation

• Aspirate the cell by micropipette suction

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Limitations

• Manual process confines the overall throughput

• Low microliter samples can’t be manipulated

• Not possible to visually control accurate transfer of

the single cell

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Optical tweezers

• Optical tweezers use focused laser beam to trap,

manipulate and position micron sized objects.

Limitation:

• Optical set-up can damage

the cells

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Laser capture microdissection (LCM)

• Advanced technique to isolate cells from solid tissue

samples

• Microscopically visualize target cell or compartment

• Mark the section to be cut on the display

• Cut the tissue and isolate cells

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LCM

c c c

Methods of single cell RNA sequencing

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Basic steps

Cell lysis

Reverse transcription

Second strand synthesis

Library preparation

Sequencing

Data analysis

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Cell lysis and mRNA isolation

• Eukaryotic cells are lysed in hypotonic buffer containing a

detergent e.g. guanidine thiocyanate and Nonidet P-40

• Using oligo-dT coated magnetic beads that will remove proteins,

metabolites, and the cell debris, from the mRNAs

• The lysate buffer then washed away isolating mRNAs with poly(A)

tails

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Reverse transcription

• Total RNA is isolated which contain all types of RNA.

• To Capture only the mRNA, specific oligo dT primers are used

• Reverse transcriptase of MMLV having the low RNase H

activity, increased thermo stability and produces RNA-DNA

hybrid molecules with an average length of 1.5–2 kb.

• Superscript III

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2nd strand Synthesis and Amplification

PCR based amplification(Homopolymer tailing OR Template switching)

In vitro transcription

Rolling circle amplification

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Methods

Tang et al. STRT

SMART-Seq CEL-Seq

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Tang et al.• Published in 2009

• Total RNA is isolated and fragmented.

• Converted to cDNA by using an oligodT primer with a specific anchor

sequence.

• The second strand is synthesized using a poly T primer with another

anchor sequence.

• PCR amplified from primers against the two anchor sequences.

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Drawback• Premature termination of RT reduces transcript coverage

at the 5’ end

• Introduction of a polyA tail in addition to its own poly A

sequence at the 3’ end of the input RNA causes a loss of

strand information in the resulting double-stranded

cDNA.

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Single cell tagged reverse transcription (STRT)

•Based on template switching

•Done to pool different cell RNAs

•5’ end of cDNA are tagged with unique barcodes

•Barcode is 4-5 bp random sequence or restriction site

•Biotin is introduced at both the 3’ and 5’ ends via the use of

biotinylated primers.

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• Binding to streptavidin beads,

enzymatic cleavage leads to

the selection of only the 5’

fragments for library

construction.

•Subsequent sequencing and

analysis shows 5’ read bias

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Drawback of template switching is:

• Lower sensitivity compared to homopolymer tailing which

may due to an imperfect efficiency of RT M-MuLV to add

3’cytosines

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Cell expression by linear amplification and sequencing (CEL-seq.)

• Highly multiplexed

• Based on in vitro transcription of mRNA to amplify only the 3’ end RNA

only

• OligodT primer containing the 5’ Illumina adaptor, a cell barcode, and a

T7promoter.

• cDNA samples are amplified by IVT from the T7 promoter

• RNA fragmentation & Illumina adaptor is ligated at 3’ end

• RNA is reverse transcribed, library is prepared then sequencing

• The first read recovers the barcode, whereas the second identifies the

mRNA transcript.

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SMART-Seq

• Switch mechanism at 5’ end of RNA template

• Based on template switching mechanism

• Generate full transcript coverage.

• Anchor a 5’ universal seq. and 3’ Cs along with Locked nucleic

acid by RT

• cDNA is amplified and tagmentation is used to construct

libraries

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Data Analysis

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Quality check • Software is fastaqc which checks for Presence and abundance of contaminating sequences. Average read length GC content• Bad quality reads (score <20) are trimmed using

trimmomatric.

Good quality Poor quality

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Data alignment

• Bowtie or TopHat

• Align large sets of short DNA sequence reads to large

genomes

• Softwares are splice aware and considers the genomic intron-

exon structure by splitting unmapped reads and aligning the

read fragments independently

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Data Assembly

• Can be done by

Reference based assembly (Cufflinks)

De novo assembly (Without any ref. using Trinity

• Generates a large number of reads that are mapped to contigs

which are then clustered to genes using Corset.

• Cuffmerge is used for final assembly

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De novo assembly

• Assemble the reads into unique transcript sequences

• Clusters related contigs that into coresponding portions of

alternatively spliced transcripts

• Constructs a de Bruijn graph for each cluster of related contigs

showing the overlapping between variants.

• Finally it reconstructs full-length, linear transcripts by integrating the

individual de Bruijn graphs with the original reads and paired ends.

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Differential gene expression

• Statitsical difference between the set of genes of two populations

or conditions.

• Cuffdiff2 count the number of sequence reads in a window as

FPKM (fragments per kilobase of transcript per million mapped read)

• Moving window along the seq. generates an expression profile in

the form of scores.

• Score normalization help in determining DGE

• Long and highly expressed genes have more reads

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When samples of yeast species were grown into two different medias. Some genes are over expressed in one of sample.

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Applications of single cell RNA sequencing

Allele specific expression • Different expression patterns of

cells

• Some genes are expressed high

in some while low in other.

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• Determine the different cell stages, lineages and their

signaling pathways.

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Study disease

•Non-invasive way to monitor the progress of

human disease

•Monitor rare or precious biological sample

•Knockout or knockdown gene studies

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Stem cell and embryonic differentiation

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• SNP discovery(only in exonic region)

• Genomic medicine

• Epigenetics & Cell lineage hierarchy

• Combined approaches

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Thank you