Genetic analysis of individual genomes and single cells; Genome-wide association studies (GWAS)

Question 1

Whole-genome sequencing (WGS) has become relatively cheap, is quick and reliable for accurately sequencing individual genomes.
Personal genomics is increasingly utilised by clinicians and hospitals for

Answer 1

WGS and identification of genetic disorders like anorexia, Alzheimers and autism.

Question 2

Whole-genome sequencing (WGS) has led to

Answer 2

improved treatment of diseases, based on the individual genome

Question 3

Whole-genome sequencing (WGS)
Example: ARVD/C is a rare heart disease that leads to irregular electrical impulses that can be lethal.

Answer 3

Native Newfoundlanders have a very high incidence ARVD/C.
Through individual genome sequencing, a mutation in the AVRD5 gene has been identified as the cause of such cases of premature death (approximately 50% of males and 5% of females die by age 40, and 80% of males and 20% of females die by age 50).
Individuals carrying this mutation are now being implanted with internal cardiac defibrillators that can restart their hearts if electrical impulses stop or become irregular.

Question 4

Whole exome sequencing (WES) is similarly used in clinical settings identify genetic disorders and ultimately to the treatment of these.
Example: Nicholas Volmer

Answer 4

– intestinal fistulas.
>100 surgeries by age 3.
WES performed and a mutation in X-linked inhibitor of apoptosis (XIAP) gene identified.
Led doctors to perform a bone marrow transplant that saved his life.
1st kid whose life has been saved by sequencing!

Question 5

The NIH started the “Undiagnosed Diseases Network” with the goal to

Answer 5

use WGS and WES to diagnose rare and mysterious disease conditions of unknown genetic basis.

Question 6

“Undiagnosed Diseases Network”

Answer 6

Exome sequences from an individual with a clinical disorder are compared to exome sequences from healthy family members and reference sequences - to identify mutations that may be involved in the disease. The program has already diagnosed over 40 cases.

Question 7

It is now possible to sequence the genome from a single cell!

Answer 7

Single-cell sequencing (SCS)

Question 8

Single-cell sequencing (SCS)

Answer 8

involves isolating genomic DNA from a single cell, then subjected to whole-genome amplification (WGA) using PCR - to produce sufficient DNA to be sequenced.

Question 9

Amplification of the genome to produce enough DNA for sequencing without introducing errors remains a major challenge that researchers are working on so that SCS can become a more reliable and accurate technique for genetic testing.

Answer 9

WGA without introducing errors remains a major challenge – high-fidelity polymerases.

Question 10

SCS is valuable for analysing:

Answer 10

1. Somatic cell mutations,
   i.e. mutations that arise in somatic cells such as in a skin cancer, which are not heritable.
2. Germ-line mutations,
   i.e. heritable mutations that are transmitted to offspring via gametes.
3. Genetic variations from cell to cell,
   e.g. cancer cells from a tumor often show genetic diversity. Understanding variations in genetic diversity and gene expression by individual cells within a tumor could lead to better and more specific treatment options.

Question 11

Sequencing genomes from individual egg or sperm cells, especially for couples undergoing in vitro fertilisation, can identify

Answer 11

carrier conditions or specific germ-line mutations that could result in a genetic disorder in the offspring

Question 12

Single-cell sequencing (SCS)

Question 13

Now possible to isolate and sequence both DNA and RNA from single cells – the same cell!
Enables the

Answer 13

comparison of the genes present in a single cell and their relative expression levels for each transcript encoded by that cellular genome.

Question 14

Single-cell RNA sequencing (scRNA-seq)

Answer 14

scRNA-seq can be done non-destructively (Live-seq).
Use PCR to amplify genomic DNA (for sequencing).
mRNA is reverse transcribed into cDNA and cloned in a library and sequenced.

Question 15

scRNA-seq provides:

Answer 15

A quantitative transcriptome analysis in which the relative levels of RNA expressed in a cell can be determined.

Similar to gene-expression microarray analysis, but does not need prior sequence information – more comprehensive.

Question 16

Sequencing DNA and RNA from the same cell type typically requires the use of PCR to amplify genomic DNA (to sequence DNA). The mRNA, is reverse transcribed into cDNA and then subsequently incorporated into a library and sequenced. scRNA-seq also then provides

Answer 16

1. a quantitative transcriptome analysis in which the relative levels of RNA expressed in a cell can be determined
2. quantitative data about RNA expression, similar to gene-expression microarray analysis. However, scRNA-seq reveals all transcripts expressed in a cell, unlike microarrays where transcripts identification is limited by the probes present on the array.

Question 17

Many disease treatments are designed to target cells, such as those in a tumor, as if all cells are homogeneous in genotype and phenotype. In fact, often such cells are quite heterogeneous genetically. scRNA-seq is now being applied to reveal the heterogeneity of cell types in tumors and other conditions, to then help plan better treatment approaches based on genetics of the cell types and their relative abundance.

Question 18

Single-cell RNA sequencing (scRNA-seq)
Example:

Answer 18

Innate lymphoid cells (ILCs) in the bone marrow can differentiate into a variety of different immune cell types.

Question 19

Innate lymphoid cells (ILCs) in the bone marrow can differentiate into a variety of different immune cell types.

Answer 19

Play important roles in immunity and the regulation of inflammation, thus are important cellular targets for immunotherapy.

Question 20

Dataplot of 325 ILCs from mouse marrow cells - groups ILCs into similar clusters based on shared gene-expression patterns. Each dot represents an individual cell, plotted against its expression levels for all genes analyzed by RNA-seq.

Answer 20

scRNA-seq of mouse bone marrow progenitor cells enabled identification of different subsets of ILCs by their RNA-expression patterns. Such analysis reveals similarities in gene expression but significant differences in the transcriptomes of ILCs that, by phenotype, might appear to be the same. For example, in the figure, note how the RNA-seq profiles of RNAs expressed by cells in cluster C10 are very different than the profiles of RNAs expressed by cells in cluster C3.

Question 21

Heatmap – displays RNA expression levels for selected genes in cell clusters. Columns represent scRNA-seq for each of the 325 cells, and each row shows the expression level heat map for a specific gene. b-actin mRNA is control (bottom row).

Question 22

Genome-Wide Association Studies (GWAS)
From thousands of cells to thousands of individuals!

Answer 22

Microarray-based genomic analysis and WGS led to a powerful strategy called genome-wide association studies (GWAS) - to analyze populations of people for disease genes.

Question 23

Genome-Wide Association Studies (GWAS)

Answer 23

Genomes from several hundred to thousand of unrelated individuals with a particular disease are analysed and compared to genomes of healthy individuals, with the goal is to identify genetic variations that may confer risk of developing the disease.

Question 24

Most GWAS use

Answer 24

SNP microarrays that can probe on the order of 500,000 SNPs to evaluate results from different individuals.

Question 25

Also use WGS to look for

Answer 25

specific gene differences, evaluate CNVs, or search for changes in the epigenome, such as methylation patterns in order to potentially associate these with the disease.

Question 26

Analysis of GWAS results requires statistical analysis to

Answer 26

predict the relative potential impact (association or risk) of a particular genetic variation on development of a disease phenotype

Question 27

In GWAS a scatterplot representation, called a ___________, is used to display data with a large number of data points.

Answer 27

Manhattan plot

Question 28

Shown here is a Manhattan plot from a GWAS for Type 2 diabetes. The study revealed 386,371 genetic markers, clustered by chromosome number (x-axis). Markers above the black line (y-axis) appeared to be significantly associated with the disease.
These genes can therefore be causally linked to the potential of individuals carrying mutations (e.g. SNPs) to be at a higher predisposition to contract Type 2 diabetes.