1. Master in Advanced Genetics
Single-Cell sequencing: limitations, applications and technical advances
Alex Subias Gusils
Subject: Genomics
Master in Advanced Genetics
7/01/2015

2. Introduction Single-cell sequencing Using the sc-seq we can:
Consist on analyzing the whole sequence information from
an individual cell using NGS
- The NGS techniques can help to improve it
Using the sc-seq we can:
Single-cell sequencing examines the sequence information from individual cells with optimized next generation sequencing technologies (NGS).
It is a perfect tool to obtain a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment.
A human cell consists of about 6 billion base pairs of DNA and 600 million bases of mRNA so it is too expensive and time-consuming to sequence by Sanger sequencing technique and the NGS techniques could help us in this field.
New biological results that relied on sequencing of whole or partial genomes or transcriptomes from single cells.
Researchers have typically taken top-down approaches, studying how things change in thousands or millions of cells and trying to infer what happened within each one but now thanks to the sc-seq we can monitor individual cells, offering an unprecedented view of cellular function and interactions with each other.
Sc-seq is a way to look at the diversity of cells at the individual cell level.
Trying to understand the function of an individual cell in the context of its microenvironment.
Studying cells at the single-cell level offers unique opportunities to dissect the interplay between intrinsic cellular processes and extrinsic stimuli such as the local environment in cell fate determination.
Sequence whole or partial genomes or transcriptomes from single cells
Study of the diversity of cells at the individual cell level
Obtain a higher resolution of cellular differences

3. Introduction Single-cell sequencing is a relatively recent technique:
Major developments and landmarks in human genetics and genomics
The first microorganism used for single-cell sequencing was a bacterium (nom del bacterium) l’any ...
In this table we can see the major developments and landmarks in human genetics and genomics, 1997 to date.
The unthinkable is now possible. Next-generation sequencing (NGS) has evolved rapidly, reducing costs and making cancer genome sequencing more routine. Traditional approaches requiring bulk DNA or RNA from multiple cells only provide global information on average states of cell populations without resolving genomic differences in heterogeneous tumors. But now, whole-genome amplification (WGA) and NGS advances enable analyses of single cells to detect variations in individual cancer cells and dissect tumor evolution. Thus, single-cell sequencing will improve oncology by detecting rare tumor cells early, monitoring circulating tumor cells (CTCs), measuring intra-/intertumor heterogeneity, guiding chemotherapy and controlling drug resistance – all aiding cancer diagnosis, prognosis and prediction and leading to individualized cancer therapy.
Naidoo N et al., 2001
The sc-seq needs time to achieve the objectives proposed at the beginning

4. Methods or There are two different methods:
Single-cell Genome Sequencing (scDNA-seq)
Single-cell RNA Sequencing (scRNA-seq)
The scDNA-seq protocol has five essential steps:
Cell isolation
DNA extraction
DNA amplification
Micromanipulation
Fluorescent-activated
cell sorting (FACS) or
Hi ha dos tipus de single-cell sequencing depeding on if we are working with the genome or with the RNA.
scDNAS: single-cell genome sequencing -> it is a technique that enables whole genome sequencing without requiring cell culture. The most popular method used for single-cell genome sequencing is Multiple Displacement Amplification.
Explicar en que consisteix el MDA!! The whole-genome amplification methods (WGA) used to obtain sufficient DNA to sequence are the multiple displacement amplification (MDA) which uses a strong strand displacing DNA polymerase to achieve a branching form of amplification. But it results in amplification biases, PCR or a combination of both.
Usually, we dissociate the tissue but on the other hand, we can micromanipulate but it is a laborious way to target a single cell.
Laser-capture
microdissection (LCM)
Analysis
Sequencing

5. Methods PAPER 2 There are two different methods:
Single-cell Genome Sequencing (scDNA-seq)
Single-cell RNA Sequencing (scRNA-seq)
- It provides the expression profile of individual cells analyzing their transcriptomes
- Identify rare cell types within a cell population
Analysis
The scheme of the protocol is the following:
This is the analysis of single-cell transcriptomes by rna-seq. Transcriptome: all the RNA of a cell.
The selected RNAs are converted into cDNAs which are more stable and can be relatively easily sequenced.
scRNA-seq: single-cell RNA sequencing -> provides the expression profile of individual cells. Through genes clustering analyses, rare cell types within a cell population can be identified.
Here we have a protocol to do a single cell RNA sequencing. The steps followed in the single-cell DNA sequencing are pràcticament the same.
In the current scRNA-seq protocols, RNA still needs to be converted to cDNA for sequencing.
So in this scheme we can see the different steps of this technique, which are:
Isolation of a single cells
RNA extraction
Reverse transcription
Amplification
Library generation
Sequencing
And the bioinformatic data analysis.
The common strategy used to capture the single-cell transcriptome relies on three major steps: RNA reverse transcription into first-strand cDNA, second-strand-synthesis and cDNA amplification and cDNA sequencing using NGS technologies.
Cell isolation
RNA extraction
cDNA synthesis
cDNA amplification
Sequencing

6. Considerations Isolation of single cells
We have some limitations in two of the steps of the protocols:
Isolation of single cells
There are different methods to obtain isolate cells and each one
has its advantages and disadvantages
- Laser-capture microdissection (LCM)
It is used to identify the cells of interest in an stained
section. We can cut it with a UV laser and then transfer
onto a membrane
Puc posar les limitacions d’un i de l’altre, dos o tres coses de cada un i ja està.
The minimal amount of starting materials from a single cell make degradation, sample loss and contamination exert pronunced effects on quality of sequencing data. Heavy amplification is often needed during sample preparation of single cell sequencing, resulting in errors and biases, which can lead to uneven coverage, noise and inaccurate quantification of sequencing data. It’s important to amplify a tiny amount of template to generate enough material to ensure adequate sequence coverage, accurate quantification and detection of sequence variation.
Genome and transcriptome sequencing require more starting material than what is found in an individual cell, it means thtat degradation, sample loss and contamination can have a pronunced effect on sequence quality and robustness. Because each cell contains such a tiny amount of genetic material, it must be copied or amplified, many times over, introducing noise into the system.
Isolation of single cell: the Laser-capture microdissection (LSM) can be used for collecting single cell but using this technique it is hard to capture a whole single cells without also collecting the materials fro neighboring cells. Other high-throughput methods for single cell isolation are the fluorescence-activated cell sorting (FACS) and microfluidics. Both are accurate, automatic and capable of isolating unbiased samples but both methods require detaching cells from their microenvironments first, maybe causing perturbation to the transcriptional profiles in RNA expression analysis. The FACS is the most commonly used method to isolate cells where fluorescent labeled antibodies are used to isolate cells of interest according to the targeted cell-surface markers.
Pel que fa al scRNA-seq: the number of cells to be analyzed -> due to the efficiency of reverse transcription and other noises introduced in the experiments, more cells are required for accurate expression analyses and cell type identification (at least 50 single cells need to be pooled in order to achieve a minimum CV value).
Les cells varien el seu transcriptoma segons els estimuls exteriors que reben i si alhora de separarles entre elles del teixit podem provocar que analitzem un transcriptoma que no es el que era abans de la manipulacio, per aixo es tant important tot el metode de cell isolation.
Is hard to capture a whole single cell without also collecting
the materials from neighbouring cells
Saliba AE et al., 2014

7. Considerations - Micromanipulation using a patch pipette
It is useful to isolate cells from culture or liquid
samples such as saliva or blood
It is laborious and time-consuming
Navin N et al., 2011
- Fluorescent-activated cell sorting (FACS)
The most commonly used method. We use fluorescent
labeled antibodies to isolate cells of interest according
to the targeted cell-surface markers
We need antibodies that target specific proteins and
that’s not always possible to obtain
Saliba AE et al., 2014

8. Considerations Genome or cDNA amplification
Genome and transcriptome sequencing require more starting material than what is found
in an individual cell so heavy amplification is often needed
This huge amplification could result in degradation, sample loss and contamination and it
can have an effect on sequence quality and robustness
DNA
Amplified DNA

9. Applications Studies of heterogeneous samples
- We can identify different cell types in scarce samples in disease like cancer
Identify differences between healthy and diseased tissues
Cell identity
Navin N et al., 2011
- The single-cell transcriptome profiling can identify biologically relevant differences in cells,
even when cells may not be distinguishable by cell morphology
Here I review the most recent developments in genome wide profiling single-cells:
The publication of Nature continued: Single-cell genome and transcriptome sequencing methods are generating a fresh wave of biological insights into development, cancer and neuroscience.
Aquí també hauriem de dir les aplicacions primers dels single-cell genome sequencing i despres les del scRNA-seq no??
Every cell is unique, it occupies an exclusive position in space, carries distinct errors in its copied genome and is subject to programmed and induced changes in gene expression. The sc-seq methods offer a way to dissect this heterogeneity.
With the single-cell sequencing technique we can make studies of heterogeneous samples, rare cell types, cell lineage relationships, phonetypes associated with mosaicism or variability, analyses of microbes that cannot be cultured and disease evolution.
It can be used in metagenomics studies and when sequencing the first time from novel species. Enables research into various areas such as microbial genetics, ecology and infectious diseases.
! Data obtained from microorganisms might establish processes for culturing in the future.
Microbiomes are the major targets of single-cell genomics due to its difficulty for culturing, to identify microbiomes’ identities and its genomes. When the data will be assembled in the near future, several functions of theses microorganisms might be discovered and might provide pros and cons regarding human health.
Cancer sequencing is also an emerging application of single-cell genome sequencing. Cancer scDNAseq is particularly useful for examining the depth of complexity and compound mutations present in amplified therapeutic targets such as receptor tyrosine kinase genes (EGFR).
scDNA-seq: can reveal mutations and structural changes in the genomes of cancer cells, which tend to have high mutation rates. This information can be used to describe the clonal structure and to trace the evolution and spread of the disease.
These approaches are also revealing a surprising level of mosaicism in somatic tissues such as the brain.
scRNA-seq: differences between cells can be greater yet at the RNA level. The single-cell transcriptome profiling can identify biologically relevant differenes in cells, even when cells may not be distinguishable by marker genes or cell morphology.
The number of circulating tumor cells (CTC) in peripheral blood of cancer patients has been shown to correlate to prognosis. However, it is challenging to enumerate and characterize the isolated CTCs as they are often contamined with a large number of leukocytes and erythrocytes. scRNA-seq could be applied to differenciate cancer cells from normal blood cells and obtain the expression profiles of tumor cells at the same time.
It can also be used to analyze rare cells types in early human embryo and adult stem cells, both of which exist transiently and difficult to be characterized with current technologies. The CTCs levels would provide an indication of cancer activity in a patient and also provide genetic information that could direct therapy over the course of treatment.
Microbial genetics
- The data obtained from microorganisms might establish processes for
culturing in the future

10. Applications Cancer prognosis
- The number of CTCs in peripheral blood of cancer patients has been shown to correlate to prognosis
- Using the scRNA-seq we can differentiate CTCs from normal blood cells
Study of somatic mutations
We can discover and screen somatic mutations that play an important
role in the origin and progression of diseases such as aging, immunity,
cancer, neurodegenerative disorders and others
Medical applications for example: profiling of rare tumor cells in scarce clinical samples, isolation and profiling of circulating tumor cells in the blood and identification and profiling of rare chemoresistant cells before and after adjuvant therapy.
Early detection of rare tumors, monitoring of circulating tumor cells (CTCs), measuring intratumor heterogeneity and guilding chemotherapy.
Single-cell genomic methods have tha capacity to resolve complex mixtures of cells in tumors.
DNA sequencing has the potential to identify structural changes and in addition to copy number and we know that there are classes of genomic copy number profiles have shown strong correlation with patient survival.
Sc-seq can also provide a higher sensitivity for detecting rare chemoresistant clones in primary tumors.
Navin N et al., 2011
Disease evolution
- The scDNA-seq can reveal mutations and structural changes in the genome of cancer cells
- This information can be used to describe their clonal structure and to trace the evolution and
spread of the disease (metastasis)

11. Future
LESS AMPLIFICATION
MORE CELLS
MORE TYPE OF DATA - - -

12. Conclusions
The single-cell sequencing is a new technique that needs time to obtain important
results
There has been considerable recent progress in analyzing single-cell genomes and
mRNA transcriptomes
Improvements in the basic technology as well as in data analysis and interpretation
will be important for obtaining the precision of measurement needed to understand
the role of a cell

13. References
Eberwine J, Sul J-Y, Bartfai T, Kim J (2014). ‘The promise of single-cell sequencing’, Nature Methods
Lovett M (2013). ‘The applications of single-cell genomics’. Human Molecular Genetics
Macaulay IC, Voet T (2014). ‘Single cell genomics: advances and future perspectives’. PLoS Genetics
Naidoo N, Pawitan Y, Soong R, Cooper DN, Ku CS (2011). ‘Human genetics and genomics a decade after
the release of the draft sequence of the human genome’. Human Genomics
Navin N, Hicks J (2011) . ‘Future medical applications of singles-cell sequencing in cancer’.
Genome Medicine
Navin N, Kendall J, Troge J, Andrews P et al. (2011). ‘Tumour evolution inferred by
single-cell sequencing’, Nature
Nawy T. (2013). ‘Single-cell sequencing’. Nature Methods 
Saliba AE, Westermann AJ, Gorski SA, Vogel J (2014). ‘Single-cell RNA-seq: advances and future challenges’.
Nucleic Acids Research