Transcriptomics

Question 1

What is the term ‘omics’?

Answer 1

• Coined to describe the field of large-scale data-rich biology
• New technologies are becoming increasingly high throughput and are generating huge numbers (high
  resolution) of molecular measurements within a tissue or cell
• Data generated provide a snapshot of what is going on in a cell at a given time

Question 2

How are proteins made from DNA?

Answer 2

Transcription:
1) RNA polymerase binds to promoter regions of DNA. Initiates transcription of gene into pre-mRNA
2) Introns spliced and exons join together
3) mRNA undergoes polyadenylation, adding poly-A tail to 3’ end, protecting from degradation and aids in export from nucleus
4) Mature mRNA exits through nuclear pore into cytosol

Translation:
1) Ribosomes bind to mRNA, each tRNA has an anticodon that is complementary to the mRNA codon, ensuring the correct amino acid is added to the growing polypeptide chain
2) After synthesis, undergoes various post-translational modifications to become fully functional
3) Process continues until a terminator codon is reached, signalling the end of translation. The completed protein is then released to perform its functions within the cell

Question 3

What is transcriptomics?

Answer 3

Question 4

Transcriptomics Methods

Answer 4

Question 5

What is RNA Sequencing

Answer 5

Question 6

What are Illumina Systems

Answer 6

Question 7

Adv + Dis of Illumina Systems

Answer 7

Question 8

PacBio Systems

Answer 8

Question 9

Adv + Dis of PacBio Systems

Answer 9

Question 10

Oxford Nanopore

Answer 10

Question 11

Adv + Dis of Oxford Nanopore

Answer 11

Question 12

RNASeq Data Processing

Answer 12

• Are there any contaminants
• Are there reference genomes
• Low quality reads are filtered out to increase overall dataset quality

Question 13

RNASeq Data Alignment

Answer 13

RNAseq reads can be mapped to the transcriptome
- Need reliable gene models
- Can’t detect novel genes

RNAseq reads can be mapped to a reference genome
- RNAseq reads will contain regions covering an exon junction (where introns in the original DNA were spliced out) and these can be thousands of bp apart
- Junction reads need to be broken, or they will not be accurately mapped to the genome

Question 14

RNASeq Data Normalization

Answer 14

Question 15

Determining outliers, anomalies and noise

Answer 15

• When comparing different groups of samples, it’s ideal to have bigger inter-group variability than intra-group variability

PCA Plot
- can reduce a large dataset into 1 or 2 principal components which describe most of the variation

Pearson’s Coefficient
- measure the correlation (direction and strength) between two variables
-

Question 16

Differential Gene Expression

Answer 16

Question 17

Types of RNA Sequencing

Answer 17

• Spatial RNA Sequencing (spRNA-Seq)
• Single cell RNA Sequencing (scRNA-Seq)
• Bulk Sequencing

Question 18

What is bulk sequencing?

Answer 18

• Gene expression is averaged across
  a cell population, doesn’t consider spatial and temporal organisation of cells
• By averaging gene expression profiles, bulk RNA sequencing can sometimes obscure true signals
• RNA is more vulnerable to influence of micro/macro- environmental stimuli

Question 19

What is single cell sequencing?

Answer 19

• Treats individual cells as an individual sample
• ScRNA-seq may be beneficial for cells at different stages of the cell cycle or cells responding to different stimuli

Question 20

What is spatial sequencing?

Answer 20

Question 21

Impact of transcriptomics

Answer 21

Question 22

Challenges of transcriptomics

Answer 22

• Only reflects a ‘snapshot’ may not represent long term patterns
• doesn’t tell you about the various post-translational modification processes which also may alter the expression levels of the protein
• Non-coding RNAs (long non-coding RNAs, microRNAs, circularRNAs) are not measured. These can have significant impact on gene expression and regulation
• Epigenetic regulation is not measured (DNA methylation, histone modification). These also influence
  gene expression and regulation
• Careful consideration of
  experimental design needs to take place
• Transcriptomics alone can identify correlation, but not necessarily causation
• Large amounts of data are generated, and these can be complex for individuals to analyses and
  comprehend