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Arrays against time Transcriptomics ‘101’ Wuhan 2011 CCC
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WT Mutant Over expressed Other species Transcription assay: Northerns Extract target RNA YFG Label probe + hybridise Next gene quantitate
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Slow (Time consuming) Hard (Technically challenging) 捡了芝麻丢了西瓜 Problems with Northerns:
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Systems biology networks - We want to look at lots of transcripts:
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AtRegNet (gene regulation network) Aracyc +other metabolomics data Arabidopsis gene network (Ma et al. Genome Research 2007) Arabidopsis
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Merged Network Proteins (red) Metabolites (blue) & Genes (green) 19392 nodes and 72715 edges 捡了芝麻丢了西瓜
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WT Mutant Over expressed Other species Northerns – a few genes at a time. Extract target RNA YFG Label probe + hybridise Next gene quantitate Again and again and….
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Sequencing ESTs (Déjà vu?) Differential display (random 5’ primers + fixed polyA primers) Mass transcript profiling: Transcriptomics Microarrays
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Probe preparation Acquire or Generate probes ‘All the genes you want’ Label cDNA from sample 1 RNA …and sample 2 RNA Target preparation Extract RNA from your Control AND your Experimental plant Spot
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Identify ‘spots’ remove background produce ‘red/green’ ratios Link ratio to relative abundance. Link spot to gene. Link genes to each other. Hybridise & Scan
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Arrays How do you make them ?
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Arrayers
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Pins Pin type: blunt, ring, quill, coated….. Breaking: bending, sticking Consistency of spots: ‘coffee-cup’, splash, drip Contamination: carry-over, dust, hairs, crystals. Etc etc….
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Slides Cracking Splitting Exfoliating Fluorescing Coatings - Hydrophobic, hydrophilic, correctly aged poly- lysine (a bit of an art) Home-made vs bought (cost of internal vs external quality control. Scan before coating, scan after coating, scan after arraying, scan after hyb-ing all part of QC Etc…etc...
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The finished spotted array Before processing, we have a LOT of spots
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After processing, we have a LOT of objective data Example Hybridisation
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What biological questions can you answer with arrays ?
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5 hormone response gene family members In different experiments 3. Root vs shoot hyb1. +hormone vs ctrl hyb2. Normal vs mutant hyb microarray Sorting out gene families
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The original choice was: Mass amplifications of cDNAs identified by partial sequence (ESTs) What goes on the slide ?
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However ….. Duplication in genomes is a real problem Human Plant Yeast
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Gene families: (# of members as a proportion of the genome) Apart from wholesale duplication Unique2345>5 35%12.5%7%4.4%3.6%37.4% Conservation between genes: 37% of genes are highly conserved (TBLASTX E<10 -30 ) 10% more are partially conserved (TBLASTX E<10 -5 )
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Gene of interest ESTs have inherent problems Example EST sequence 1 Homologous EST sequence 2 Dissimilar EST sequence 3 On the slide 1 2 3 Labelled target may hybridise similarly to each
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Better solutions: GSTs (gene specific tags) Oligo arrays Affymetrix genechips RNA seq???
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Selection of Expression Probes Probes Sequence Perfect Match Mismatch Chip 5’5’ 3’3’
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Affymetrix Wafer and Chip Format 1.28cm 5 - 50 µm Millions of identical oligonucleotide probes per feature 49 - 400 chips/wafer up to ~ 3,000,000 features/chip
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Probe cells of an Affymetrix GeneChip contain millions of identical 25-mers 25-mer
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Photolithographic Synthesis Lamp Mask Chip
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Synthesis of Ordered Oligonucleotide Arrays One nucleotide at a time. here
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Procedures for Target Preparation RNA AAAA RNA Quality control
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Procedures for Target Preparation cDNA Wash & Stain Scan Hybridise (16 hours) RNA AAAA BBBB Biotin-labeled transcripts Fragment (heat, Mg 2+ ) Fragmented cRNA B B B B IVT (Biotin-UTP Biotin-CTP)
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GeneChip ® Expression Analysis Hybridization and Staining Array cRNA Target Hybridized Array Ab detection
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Affymetrix software derives the intensity for each probe from the 75% quantile of the pixel values in each box.
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The intensities of the multiple probes within a probeset are combined into ONE measure of expression Expression Measure
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Chips need to be normalised against each other. Each chip is a different colour in this graph They are not co-incident for intensities To compare they need to be comparable
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RMA uses normalisation at the probe level Chip 1 Chip 2 Chip 3 1 2 3 4 5 1 2 3 5 7 2 3 4 5 9 Order by ranks PA PB PC PD PE Chip 1 Chip 2 Chip 3 1 2 4 3 5 7 2 5 3 1 5 3 4 2 9 Average the intensities at each rank Chip 1 Chip 2 Chip 3 1.33 2.33 3.33 4.66 7 PA PB PC PD PE Chip 1 Chip 2 Chip 3 1.33 2.33 4.66 3.33 7 7 2.33 4.66 3.33 1.33 4.66 2.33 3.33 1.33 7 Reorder by probe
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R / BioConductor training AffylmGUI training Xspecies analysis training Normalisation, filtering and annotation.CDF, filtering, stats and annotation RMA Normalisation
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Sequencing: current / next gen / future Sequencing is likely to complement arrays in the future
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Standard (Sanger) sequencing Template Primer PrimerPrimer PrimerPrimer Random ddNTP termination. Label can be added to the: Primer ddNTP –or- Incorporated dNTPs
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454 sequencing (images by Roche) Sample Input and Fragmentation: Genomic DNA or BACs are fractionated into small, 300- to 800-basepair fragments Library Preparation: Short adaptors (A and B) - specific for both the 3' and 5' ends - are added to each single stranded fragment. One Fragment = One Bead: Each fragment of the single-stranded DNA library is immobilized individually onto beads in a water-in-oil mixture. emPCR (Emulsion PCR) Amplification: Each unique fragment is amplified in parallel to several million per bead. One Bead = One Read: The clonally amplified fragments are loaded onto a PicoTiterPlate device for sequencing. Only one bead per well. Auto fluidics flows individual nucleotides in a fixed order across the hundreds of thousands of wells containing one bead. Addition of a nucleotide results in a chemiluminescent signal.
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Solexa sequencing I Series of images taken from www.illumina.com
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Solexa sequencing II
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Solexa sequencing III
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But the future may be even faster…… http://www.pacificbiosciences.com/aboutus/video-gallery Note: Direct link may be disallowed by the server. – try direct paste into a browser and click the SMRT Biology Overview in the video-gallery archive
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Rubber sequencing
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