Transcript ppt
Microarrays and the shadows in Plato's cave Matthias E. Futschik Institute for Theoretical Biology Humboldt-University, Berlin, Germany Overview General Introduction Introduction to microarray techniques: Plato and the cave: What can we learn from Greek philosophy? The statement of the problem: Where do we start & where do we want to go? Microarray data analysis: The way out of the cave and the challenges that we are meeting. Experimental background Types of microarrays Microarray platforms Image processing and data storage Design of experiments Reference design Factorial design Yeast cDNA microarray Plato’s Cave AND now, I said, let me show in a figure how far our nature is enlightened or unenlightened: Behold! Human beings living in a underground den, which has a mouth open towards the light and reaching all along the den; here they have been from their childhood, and have their leg and necks chained so that they cannot move, and can only see before them, being prevented by the chains from turning round their heads.Above and behind them a fire is blazing at a distance, and between the fire and the prisoners there is a raised way; and you will see, if you look, a low wall built along the way, like the screen which marionette players have in front of them, over which they show the puppets…. To them, I said, the truth would be literally nothing but the shadows of the images… And now look again, and see what will naturally follow if the prisoners are released and disabused of their error. At first, when any of them is liberated and compelled suddenly to stand up and turn his neck round and walk and look towards the light, he will suffer sharp pains; the glare will distress him, and he will be unable to see the realities of which in his former state he had seen the shadows; and then conceive some one saying to him, that what he saw before was an illusion, but that now, when he is approaching nearer to being and his eye is turned towards more real existence, he has a clearer vision,… Plato’s Cave And suppose once more, that he is reluctantly dragged up a steep and rugged ascent, and held fast until he's forced into the presence of the sun himself, is he not likely to be pained and irritated? When he approaches the light his eyes will be dazzled, and he will not be able to see anything at all of what are now called realities… He will require to grow accustomed to the sight of the upper world. Imagine once more, I said, such an one coming suddenly out of the sun to be replaced in his old situation; would he not be certain to have his eyes full of darkness? And if there were a contest, and he had to compete in measuring the shadows with the prisoners who had never moved out of the den, while his sight was still weak, and before his eyes had become steady (and the time which would be needed to acquire this new habit of sight might be very considerable) would he not be ridiculous? Men would say of him that up he went and down he came without his eyes; and that it was better not even to think of ascending; and if any one tried to loose another and lead him up to the light, let them only catch the offender, and they would put him to death. The Fire: Genetic networks The Problem Complex regulation of gene expression The Sun: New drug discovery by knowledge discovery The Shadow: Microarrays Thousands of simultaneously measured gene activities Methodology 1. 2. 3. 4. 5. 6. 7. From Image to Numbers: Image-Analysis Well begun is half done: Design of experiments Cleaning up: Preprocessing and Normalisation Go fishing: Significance of Differences in Gene Expression Data Who is with whom: Clustering of samples and genes Gattica becomes alive: Classification and Disease Profiling The whole picture: An integrative approach What are microarrays? Microarrays consist of localised spots of oligonucleotides or cDNA attached on glass surface or nylon filter Different production: Spotted microarrays Photolithographicly synthesised microarrays (Affymetrix) Different read-outs: Two-channel (or two-colour) microarrays One-channel (or one-colour) microarrays Applications: Clustering of genes: Co-expression and co-regulation go together enabling functional annotation Clustering of time series Classification of tissue samples and marker gene identification Clustering of arrays: finding new disease subclasses Reconstruction of gene networks (Reverse engineering) Typical cDNA microarray experiment Microarray technology I Two-colour microarray (cDNA and spotted oligonucleotide microarrays) Probes are PCR products based on a chosen cDNA library or synthesized oligonucleotides (length 50-70) optimized for specifity and binding properties >> probe design Probes are mechanically spotted. To control variation of amount of printed cDNA/oligos and spot morphology, reference RNA sample is included. Thus, ratios are considered as basic units for analysing gene expression. Absolute intensities should be interpreted with care. Array production - Galbraith lab Affymetrix GeneChip technology Production by photolitography Hybridisation process and biotin labelíng; Fragmentation aims to destroy higher order structures of cRNA Microarray technologies II One-colour microarrays (Affymetrix GeneChips) Measurement of hybridisation of target RNA to sets of 25oligonucleotides (probes). Probes are paired: Perfect match (PM) and mis-match (MM). PM are complementary to the gene sequence of interest. MM include a single nucleotide changed in the middle position of the oligonucleotide. MM serve for controlling of experimental variation and non-specific cross-hybridisation. Thus, MMs constitute internal references (on the probe site). Average (PM-MM) delivers measure for gene expression. However, different methods to calculates summary indices exist (e.g. MAS,dchip, RMA...) From Images to Numbers Impurities, overlapping spots Donut-shaped spots, Inhomogeneous intensities Local Background Spatial bias Image Analysis 1. Localisation of spots: locate centres after (manual) adjustment of grid 2. Segmentation: classification of pixels either as signal or background. Different procedures to define background. 3. Signal extraction: for each spot of the array, calculates signal intensity pairs, background and quality measures. Data acquisition Scans of slides are usually stored in 16-bit TIFF files. Thus, scanned intensities vary between 0 and 216. Scanning of separate channels can adjusted by selection of laser power and gain of photo-multiplier. Common aim: balancing of channels. Common problems: avoiding of saturation of high intensity spots while increasing signal to noise ratios. Data acquisition Image processing software produces a variety of measures: Spot intensities, local background, spot morphology measures. Software vary in computational approaches of image segmentation and read-out. Open issues: local background correction derivation of ratios for spot intensities flagging of spots, multiple scanning procedures Design of experiment Two channel microarrays incorporate a reference sample. Choice of reference determines follow-up analysis. A1 A2 All samples are co-hybridised with common reference sample R Reference design: ● Advantage: Robust and scalable. Length of path of direct comparison equals 2. ● Disadvantage: Half of the measurements are made on reference sample which is commonly of little or no interest ● A3 Alternative Designs: Dye-swap design: each comparison includes dye-swap to distinguish dye effects from differential expression (important for direct labelling method) ● A1 Loop-design: No reference sample is involved. Increase of efficiency is, however, accompanied with a decrease of robustness. A2 ● Latin-square design: classical design to separate effects of different experimental factors ● A3 Comparison of designs: Yang and Speed, Nature genetics reviews, 2002 Define before experiment what differences (contrasts) should be determined to make best use out of (usually) limited number of arrays Sources of variation in gene expression measurements using microarrays ● ● ● Microarray platform Manufacturing or spotting process ● Manufacturing batch ● Amplification by PCR and purification ● Amount of cDNA spotted, morphology of spot and binding of cDNA to substrate mRNA extraction and preparation ● Protocol of mRNA extraction and amplification ● Labelling of mRNA Sources of variation in gene expression measurements using microarrays II ● ● ● Hybridisation ● Hybridisation conditions such as temperature, humidity, hyb-buffer Scanning ● scanner ● scanning intensity and PMT settings Imaging ● software ● flagging, background correction,... Design of experiment Important issues for DOE: Technical replicates assess variability induced by experimental procedures. ● ● Biological replicates (assess generality of results). Number of replicates depends on desired sensitivity and sensibility of measurements and research goal. ● Randomisation to avoid confounding of experimental factors. Blocking to reduce number of experimental factors. ● Design of experiment ● Control spots assess reproducibility within and between array, background intensity, cross-hybridisation and/or sensitivity of measurement ● can consists of empty spots or hybridisation-buffer, genomic DNA, foreign DNA, house-holding genes ● Foreign (non-cross-hybridising) cDNA can be 'spiked in'. Use of dilution series can assess sensitivity of detecting differential expression by 'ratio controls'. ● Validation of results: by other experimental techniques (e.g. Northern, RT-PCR) ● by comparison with independent experiments. ● Data storage Microarrays experiments produce large amounts of data: data storage and accessibility are of major importance for the follow-up analysis. Not only signal values have to be stored but also: TIFF images and imaging read-out ● Gene annotation ● Experimental protocol ● Information about samples ● Results of pre-processing, normalization and further analysis ● In fact, data of the whole experiment has to be stored, and its internal structure i.e. which sample was extracted by what methods was hybridised on which batch of slides by whom and when? Type of storage Flat file: for small-scale experiments and one-off analysis. Example NCBI - GenBank ● ● Database: necessary for large scale experiments. Microarray DBs typically relational, SQL-based models. Their internal relational structure should reflect the experiment structure. These types of databases will become essiential tools for post-genomic analysis. Data storage II Sharing microarray data: • NCBI • EBI • Stanford • Journals ie Nature Standardization of information by MGED: ● MIAME (minimal information about a microarray experiment) ● MAGE-ML based on XML for data exchange Take-home messages for today • Remember: Microarrays are shadows of genetic networks • Watch out for experimental variation •The complexity of microarray experiments should be reflected in the structure used for data storage • For soccer tonight: Go, Italy, go!