Bioinformatics 11: Gene expression and regulation

Question 1

What is the transcriptome and what does it include?

Answer 1

The transcriptional output of a genome

includes ribosomal RNA, messenger RNA, transfer RNA and regulatory RNAs

Translation of the transcriptome generates the proteome

Question 2

What is gene expression data and how is it obtained?

Answer 2

Expression data refers to RNA:

• distribution
• abundance

Obtained through various experimental means, usually Reverse Transcription

Question 3

Traditional molecular biological techniques for gene-by-gene analysis?

Answer 3

Northern Blotting
In situ hybridisation
RT-PCR (Reverse transcription- PCR)

Question 4

Describe the process of northern blotting

Answer 4

Northern blotting: involves extracting RNA and comparing transcript abundance from different samples

• RNA separated by size via electrophoresis + blotted onto membrane
• Specific genes detected by hybridisation of radio-labelled RNA or DNA probe and developed on film
• Known expressed gene (e.g. Beta-actin) used as loading control
• Relative quantitation -> Comparison to loading control

Question 5

Describe process of in-situ hybridisation

Answer 5

in-situ hybridisation: allows detection directly in tissues

• Sections (thin slices) or permeabilised tissues enable probe access
• Multiplexing possible via fluorescence detection (antibody amplification) -> FISH (Qualitative)

Question 6

What are expressed-sequence tags (ESTs)?

Answer 6

Expressed sequence tag = short sub-sequence of a cDNA sequence. Represent a portion of an expressed gene

ESTs may be used to identify gene transcripts, useful in gene sequence determination

Question 7

What is the purpose of Unigene?

Answer 7

Unigene collates EST data

• all-by-all sequence comparisons that identify overlapping ESTs

ESTs organised into clusters - each represent one unique expressed human gene

Allows comparing of gene expression via Digital Differential Display

Question 8

What is Digitial Differential DIsplay (DDD) and what is it used for?

Answer 8

DDD compares the presentation of Unigene clusters in multiple cDNA / EST libraries

Allows for analysis of significant differences in gene expression

Particularly useful in disease vs ‘normal’ comparison

Question 9

Pros and cons of EST analysis

Answer 9

Pros
- All genes analysed including
novel transcript variants
- Fast and CHeap
- EST clones available to community (I.M.A.G.E Consortium)

Cons

• Random sequencing strategy - only useful for high abundance transcripts
• some Data quality poor
• genomic contamination of cDNA can occur
• stats tools have low sensitivity, can only detect large differences in expression

Question 10

What is the purpose of ‘Serial analysis of gene expression’ (SAGE)?

Answer 10

Technique developed to further quantify ESTs
- increases efficiency of EST profiling

cDNA is synthesised from mRNA , cut into short (10-17bp) fragments with enzymes and concatenated (joined together)

Each molecule is included in concatamer at a rate proportional to abundance

Qualitative (presence/absence) and quantitative (count of tags) data

Question 11

What database collates SAGE data?

Answer 11

SAGEgenie

Question 12

What is a microarray? How is gene expression visualised using them?

Answer 12

Patches (features) of DNA molecules on a glass/silicon support

Gene expression visualised via hybridisation of fluorescently labelled cDNA/mRNA
- data collected by fluorescence microscopy scanning

Question 13

2 main types of micro array and their differences?

Answer 13

Spotted array

• small ‘spots’ regions (cDNA) of varying intensities of fluorescence represent levels of gene expression
• (low density, ~ 7000 spots per 2cm^2)

In situ synthesised DNA array

• features (oligonucleotide arrays) -> synthesis by photolithography, one nucleotide per spot
• (high density, ~250,000 features per 2cm^2)

Question 14

Problems with microarray data - how do scientists make sense of it?

Answer 14

Problems
Large amounts of information, few samples, many genes (sparse data)
+ changes in gene expression is correlated

Solution
- Cluster genes / samples by expression patterns, interactions, regulation etc. across samples/genes e.g. using Volcano plots to visualise data

Question 15

Volcano plots show what?

Answer 15

Volcano plots identify genes with particular fold change and levels of statistical significance

Question 16

Which major database collates data on gene expression? What data does it accept?

Answer 16

Gene expression omnibus (GEO)
-contains info from SAGEgenie and Unigene

Only accepts MIAME compliant data