Chapter !9 - Microarrays and Transcriptomics Code : KSI0018
<Index of Chpater 9>
Introduction
Microarrays provide the link between the static genome and the dynamic proteome. We use microarrays
(1) To analyse the mRNAs in a cell, to reavel the expression patterns of proteins.
(2) To detect genomic DNA sequences to reveal absent or mutated genes.
The transcriptome of a cell is the set of RNA molecules it contains. The proteome is its proteins .
We infer protein expression patterns from measuements of the relative amounts of the corresponding mRNAs. Hybridization in an accurate and sensitive sequence is present
<The basic innovation of microarrays is parallel processing>
1. One-to-one . To detect whether one oligonucleotide has a particular known sequence, test whether it can hybridize to the oligonucleotide with the complementar sequence.
2. Many to one. To detect the presence or absence of a query oligonucleotide in a mixture, spread the mixture out and test component of the mixture for binding to the oligonucleotide complementary to the query. This is a nothern or Southern blot.
3. Many to many. To detect the presence or absence of many oligonucleotides in a mixture, synthesize a set of oligonucleotides, one complemantary to each sequence of the query list and test each component of the mixture for binding to each memeber of the set of complementary oligonucleotides.
The immobilized material on the chip is the probe. THe sample tested is the target.
Microarrays are also need to screen for mutations and polymorphisms. Microarrays containing many sequence variants of a single gene can detect differences from a standard reference sequence.
Different types of chip support different investigation
Expression chip / mismatched oligonucleotide / probe pair/ genomic hybridization / Mutation or polymorphism microarray analysis / protein microarrays / tissue microarrays.
-Applications of DNA microarrays
>Investigating cellular states and processes
> COmparision of related species
> Diagnosis of genetic disease
> Genetic warning signs
> Preciese diagnosis of disease
> Drug selection
> Determination of gene function
> Target selection for drug design
Analysis of microarrary data
Two general approaches to the analysis of a gene expression matrix involve
1. Comparisons focused on the genes. i.e. Comparing distrivbutions of expression patterns of different genes by comparing rows in the expression matrix.
2. Comparisons focused on samples. Comparing expression profiles of different samples by comparing columns of the expression matrix.
Gene vectors/ sample vectors
Depending on the origin of the samples, what is already known about them and what we want to learn data anaylsis can proceed in different directions .
1. Known characteristics.
2. Pre-assign
Reduction of dimensionality.
> Processing the data from a microarray experiment produces a gene expression table, or matrix. The rows index the genes and the columns index the samples. We can either focus on the genes, and ask. How do patterns of epxpression of different genes very among the different samples? Or we can focus on the samples, and ask. How do the samples differ in teir gene expression pattterns?
Expression patterns in different physiological states
-The diauxic shift in Saccharomyces cerevisiae
-Sleep in rats and fruit flies
> Oxygen is essential for aeroic life, yet its reduced forms include some of the most toxic substances with which cells must cope.
> The diauxic shift in yeast is the transition from fermetantative metabolism when the yeast runs out of glucose in the medium. THe shift is effected by a retooling in which the expression patterns of relavant genes are altered.
>If the physiology of sleep is not well understood, the molecular biology of sleep is even more obscure. Measurements of changes in gene expression during sleep and wakefulness give clues as to what distinguishes the states, at the molecular level.
Expression pattern changes in development
-Variation of expression patterns during the life cycle of Drosophila melanogaster
-Different life stages make different demands on different genes
Measurement of expression pattrns at different stages reveal which batteries of genes are active in development. Particularly strikng, in Drosophila, is the alternation of time-of - onset of the expression patterns of some genes. embryo and pupa show similarites and larva and adult.
-Flower formation in roses.
Expression patterns in learning and memory : Long-term potentiation
-Conserved clusters of co-expressing genes
Evolutionary changes in expression patterns
- Learning must be regarded as a specialized form of development
> The design of the experiments presents a number of difficulties,. however,
There is a high background of variation in expression pattern among different individuals of any species and among different tissues within any individual.
Use of a microarray containing oligomer sequences derived from human genes to measure mRNA levels in chimpanzee tissue underestimates the expression levels in the chimpanzee because of less effective hybridization resulting from sequence changes.
Applications of microarrays in medicine
-Development of antibiotic resistance in bacteria
> Development of vancomycin resistance - a chronology
> Microorganisms also develop resistance by evolving enztmes that destroy an antibiotic or pump it out of cells.
Genes upregulated with increased vancomycin resistance are associated with the followings
1. Purine biosynthesis, which is a large componento f the change in expression.
2. Cell envelope synthesis, remodeling , and degradation
3. Proteins involved in transport and binding of amino acids, peptides and amines, and nucleic acid components
4. Synthesis of staphyloxanthin, an orange carotenoid that gives S. aureus its golden colour.
Genes Dounrefulated with increased vancomycin resistance are associated with
1. Energy metabolism
2. Cell envelope biosynthesis.
3. Proteins involved in transport and binding of carbohydrates, organic alcohols and acids.
4. Salvage of nucleic acid components
5. Regulatory functions
6. tetracyclin resistance
-Childhood leukaemias
> Expression profiling can
1. permit precise diagnosis of the subtype of the disease
2. Predict the likely course of the disease.
3. Guide choice of therapy.
Whole trranscriptome shotgun sequencing : RNA-seq
> Methods for expression profiling include microarrays and whole transcriptome shotgun sequencing. or RNA-seq.
Both methods are in widespreasd use at present.
By asking in detail what one wants from the results, one can ake an intelligent choice between them for any particular experiment on any particular system.
