L12 Microarrays PDF

L12 Microarrays Learning outcomes: This lecture will review how the complexity information increases as the flow of the Central Dogma proceeds from gene regulation to protein interactions. The architecture of protein coding mRNAs will be summarised. The concepts and molecu...

L12 Microarrays Learning outcomes: This lecture will review how the complexity information increases as the flow of the Central Dogma proceeds from gene regulation to protein interactions. The architecture of protein coding mRNAs will be summarised. The concepts and molecular biology processes underpinning large-scale genome wide DNA microarrays will be covered. An example of a workflow to determine genome-wide differential gene expression in a biological system will be outlined. The need for controls and statistical analysis will be discussed. After this lecture students should have a clear idea of the molecular logic governing DNA arrays and how they can be used to make meaningful insights into the process of large-scale gene regulation in a biological system. Central dogma and microarray summary Central dogma: DNA (genome) -> RNA (transcriptome) -> Protein (proteome). Genome: The genome consists of all an organism’s genes and additional DNA sequences important for regulation of gene expression Transcriptome: The transcriptome is the complete set of transcripts (or transcribed genes) present in a particular tissue or cell at a particular time point. All cells will have the same genome, but the transcriptome is dynamic and will be different in every cell depending on the tissue function. You can identify the active transcriptome using microarrays. It is a measure of transcriptomics. Microarray: Tool to simultaneously measure the gene expression level of thousands of genes. o Microarrays measure the genes that are actively being expressed in the tissue, i.e. the mRNA that is present. o Microarrays rely on the biological principle of complementary hybridisation. Probes are complementary to the known mRNA sequences of the genes of interest. Therefore, you must know the target DNA sequence. Molecular biology processes underpinning genome wide DNA microarrays Microarrays are a collection of small probes which can detect the presence of complementary mRNA in a large population of mRNAs.  The sequence of entire genomes gives us access to thousands [potentially all] mRNA sequences, but you MUST know the gene sequence first. Microarray process Probes synthesised for all known and predicted mRNAs and are generally 25-70 nucleotides long. They are immobilised on a solid surface e.g. silicon. Thousands of probes produced on a silicon base = GeneChip. mRNA from test sample converted to cDNA using reverse transcriptase and labelled with a fluorescent probe. Labelled cDNA is applied to the array and allowed to bind to the spotted cDNAs or oligonucleotides. The location of fluorescent spots on microarray can rapidly identify the genes expressed in the test sample. Each location at the chip will have many copies of the same strand. Shining a laser at the GeneChip array causes tagged DNA fragments that hybridised to glow. Level of fluorescence detected by a chip reader. The location and brightness of the fluorescent spots on the microarray identify the genes expressed in the test sample and their level of expression In a gene chip feature, the level of fluorescence is the sum of hybridisation across the entire region. The output of the scanner is the gene name and a relative expression value. Types of microarray platforms: Multiple synthesised short oligonucleotides [25mers] on silicon (Affymetrix) single channel fluorescent label between 11 and 20 probe per target gene up to 40,000 gene targets/single chip Densely packed chip means more genes can be assessed but the oligos must be shorter, therefore there is a risk of oligonucleotides cross-hybridising to the wrong sequence. o Therefore, each given gene is represented by 11 different probes scattered across the chip and expression of the gene is derived from an average of reading from the 11 different probes, so there are less likely to be inaccurate readings. Spotted cDNA or long oligos [70mers] on glass slide home grown or commercial. two channel: simultaneous co-hybridisation of two samples two colour fluorescence Microarray workflow and the need for controls and statistical analysis Small probes mean there is a risk of DNA from more than one gene binding if it happens to have the same sequence.  To minimise the effect of ‘noise’ the probe sets for a single gene are randomised across the GeneChip The intensity and location of the probe features is read by a scanner The readings are assimilated into expression values for every single gene Useful applications Example experiments: Use microarray to identify regionally expressed genes. Identify genes that are coregulated o Aim to identify genes expressed at different stages of cell cycle, isolate mRNA from G1, S, G2, M o Find expression levels of every gene at each timepoint. Comparative microarray o Label different samples different colours and compare expression levels. o Can also be compared graphically:  o Plot level of expression of each gene in two samples. If the two samples are the same, each gene has the same expression level, and the data will have a narrow spread. o If the genes are expressed differently, there will be a wider spread of data Summary of usage Microarray Transcriptomics Microarrays consist of probes for all of the known genes to date [~35,000] Microarrays have probes specific for some, but not all, splice variants Microarrays can detect thousands of genes at one time Using mRNA from different tissue or cells, microarray studies can distinguish genes that are expressed differently Computational methods can predict what genes might be in the same pathway, i.e. which genes are co-regulated  Microarray results are very sensitive to error, large numbers are being analysed therefore errors can occur, sophisticated statistics needed to analyse the data to check for significance Not all cellular processes are controlled by transcription e.g. protein modification