Bruce Blumberg (blumberg@uci.edu) BioSci D145 Lecture #5 Bruce Blumberg (blumberg@uci.edu) 4103 Nat Sci 2 - office hours Tu, Th 3:30-5:00 (or by appointment) phone 824-8573 TA – Bassem Shoucri (bshoucri@uci.edu) 4351 Nat Sci 2, 824-6873, 3116 Office hours M 2-4 lectures will be posted on web pages after lecture http://blumberg.bio.uci.edu/biod145-w2015 http://blumberg-lab.bio.uci.edu/biod145-w2015 Last year’s midterm is now posted. It is useful to work through the problems to see what sort of questions I ask and how best to study. BioSci D145 lecture 1 page 1 ©copyright Bruce Blumberg 2010. All rights reserved

Human genome, mouse, rat, Drosophila, C. elegans “finished” Functional Genomics - Analysis of gene function on a whole genome basis Genome projects DNA sequencing Human genome, mouse, rat, Drosophila, C. elegans “finished” model organisms progressing rapidly Lots of new genes, but many lack known function Functional genomics Identification of gene functions associate functions with new genes coming from genome projects function of genes identified from characterizing diseases or mutants Identification of genes by their function discovery of new genes BioSci D145 lecture 6 page 2 ©copyright Bruce Blumberg 2010. All rights reserved

*Methods of profiling gene expression – large scale to whole genome What are the possibilities Array – micro or macro Sequence sampling SAGE – serial analysis of gene expression Massively parallel signature sequencing (RNA-seq, Illumina, 454) DNA microarray analysis was, until now totally dominant method Two basic flavors Spotted (spot DNA onto support) cDNA microarrays Oligonucleotide arrays Moderately expensive Synthesized (use photolithography to synthesize oligos onto silicon or other suitable support Affymetrix Gene Chips dominate VERY expensive Both are in wide use and suitable for whole genome analysis BioSci D145 lecture 6 page 3 ©copyright Bruce Blumberg 2010. All rights reserved

Source material is prepared cDNAs are PCR amplified OR Spotted arrays Source material is prepared cDNAs are PCR amplified OR Oligonucleotides synthesized Spotted onto treated glass slides RNA prepared from 2 sources Test and control Labeled probes prepared from RNAs Incorporate label directly Or incorporate modified NTP and label later Or chemically label mRNA directly Hybridize, wash, scan slide Express as ratio of one channel to other after processing BioSci D145 lecture 6 page 4 ©copyright Bruce Blumberg 2010. All rights reserved

Stanford type microarrayer DNA microarray types Stanford type microarrayer http://cmgm.stanford.edu/pbrown/mguide/index.html Printing method Reminiscent of fountain pen BioSci D145 lecture 6 page 5 ©copyright Bruce Blumberg 2010. All rights reserved

Amino-allyl labeled 1st strand cDNA Strategy to identify RAR target genes Agonist - TTNPB Antgonist - AGN193109 Harvest st 18 Poly A+ RNA Poly A+ RNA Amino-allyl labeled 1st strand cDNA Amino-allyl labeled 1st strand cDNA Alexa Fluor 555 (cy3) Alexa Fluor 647 (cy5) Alexa Fluor 555 (cy3) Alexa Fluor 647 (cy5) Probe microarrays upregulated downregulated BioSci D145 lecture 6 page 6 ©copyright Bruce Blumberg 2010. All rights reserved

Statistical analysis of output – VERY IMPORTANT! DNA microarray Statistical analysis of output – VERY IMPORTANT! Replicates are very important Preprocessing of data is needed To remove spurious signals BioSci D145 lecture 6 page 7 ©copyright Bruce Blumberg 2010. All rights reserved

Custom arrays possible and affordable DNA microarray Advantages Custom arrays possible and affordable Ratio of fluorescence is robust and reproducible Disadvantages Availability of chips Expense of production on your own Technical details in preparation BioSci D145 lecture 6 page 8 ©copyright Bruce Blumberg 2010. All rights reserved

High density arrays are synthesized directly on support Affymetrix GeneChips High density arrays are synthesized directly on support 4 masks required per cycle -> 100 masks per chip (25-mers) Pentium IV requires about 30 masks G.P. Li in Engineering directs a UCI facility that can make just about anything using photolithography BioSci D145 lecture 5 page 9 ©copyright Bruce Blumberg 2010. All rights reserved

Affymetrix GeneChips Streptavidin/phycoerythrin BioSci D145 lecture 5 page 10 ©copyright Bruce Blumberg 2010. All rights reserved

Each gene is represented by a series of oligonucleotide pairs Affymetrix GeneChips Each gene is represented by a series of oligonucleotide pairs One perfect match One with a single mismatch Only hybridization to perfect match but not mismatch is considered to be real Gene is considered “detected” if > ½ of oligo pairs are positive Number of pairs depends on organism and how well characterized array behavior is Human uses 8 pairs Xenopus uses 16 pairs BioSci D145 lecture 5 page 11 ©copyright Bruce Blumberg 2010. All rights reserved

Result is in single color Affymetrix GeneChips Result is in single color Always need two chips – control and experimental for each condition Also need replicates for each condition For diverse biological samples (e.g., humans) 10 replicates required! For less diverse samples (cell lines) probably 5 replicates needed Advantages Commercially available Standardized Disadvantages About $1000 to buy, probe and process each chip (at UCI)! About $700 elsewhere May not be available for your organism of interest No ability to compare probes directly on the same chip Must rely on technology BioSci D145 lecture 5 page 12 ©copyright Bruce Blumberg 2010. All rights reserved

Identifying genes expressed in one condition vs. another DNA microarrays What are they good for? Identifying genes expressed in one condition vs. another One tissue vs. another (heart vs liver) Tissue vs. tumor (liver vs. hepatocarcinoma) In response to a treatment (e.g., RA) In response to disease (e.g., after viral infection) Building expression profiles Tissues Cancers Developmental stages Expressed genes Identifying organisms in food Array can identify which animals are present in a mix http://www.dnavision.com/files/FOODIDBrosh%20En.pdf BioSci D145 lecture 5 page 13 ©copyright Bruce Blumberg 2010. All rights reserved

What are they good for? (contd) DNA microarrays What are they good for? (contd) Response of animal to drugs or chemicals Toxicogenomics Pharmacogenomics Diagnostics SNP analysis to identify disease loci Specific testing for known diseases BioSci D145 lecture 5 page 14 ©copyright Bruce Blumberg 2010. All rights reserved

Signal intensity (or signal/noise) Improved dyes, label uniformly DNA microarrays What are the limitations of microarray technology? What sorts of factors might confound the experiment? Signal intensity (or signal/noise) Improved dyes, label uniformly Biological variation (samples are inherently different) Sufficient # of replicates is key keep individuals separate Not all mRNAs will be present at sufficient levels to detect Amplification, but beware of bias Good statistical analysis is required Bayesian statistics are best (Pierre Baldi is local expert) calculating the probability of a new event on the basis of earlier probability estimates which have been derived from empiric data i.e., don’t assume random distribution in datasets, calculate probability based on real data Bayesian approach great for small number of replicates, converges on t-test at high number of replicates http://cybert.microarray.ics.uci.edu/ BioSci D145 lecture 5 page 15 ©copyright Bruce Blumberg 2010. All rights reserved

Where/when are they expressed? Known genes (e.g. from genome projects) Functional Genomics - The challenge: Many new genes of unknown function Where/when are they expressed? Known genes (e.g. from genome projects) Gene chips (Affymetrix) Microarrays (Oligo, cDNA, protein) Novel genes Differential display Expression profiling SAGE and related approaches What do they interact with? Biochemical methods Yeast two, three hybrid screening Phage display Expression cloning Proteomics 2 dimensional gel electrophoresis Mass spectrometry Protein microarrays BioSci D145 lecture 5 page 16 ©copyright Bruce Blumberg 2010. All rights reserved

Methods of profiling gene expression (small number of genes) How to evaluate gene expression? Old, low-throughput - prepare RNA sample and perform Northern blot – immobilize RNA on filter, probe Quantitative WHY? Nuclease protection quantitative In situ hybridization Not quantitative – enzymatic reaction Newer, high throughput methods RT-PCR Can be quantitative Quantitative real time RT-PCR Or prepare protein samples and evaluate proteins Western blot - detect protein of interest with specific antibody. ELISA – enzyme linked immunosorbent assay quantitative RIA – radioimmunoassay - quantitative Probe is in excess BioSci D145 lecture 5 page 17 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - size and splicing Quantitation of mRNA levels possible methods Northern analysis nuclease protection RT-PCR measure steady state mRNA levels (production/degradation) mRNA size determination – Northern blot only way good RNA size markers = accurate sizing which to use, poly A+ or total RNA? A+ much more sensitive (50-100x) what about mRNAs with no or short tails? total RNA much simpler gel limitations – 20 μg/lane is practical limit what is a key factor in sizing mRNAs? Appropriate size standards larger and smaller than target BioSci D145 lecture 5 page 18 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) Nuclease protection assays approach hybridize a single-stranded (SS) probe (DNA or RNA) to RNA sample probe must be larger than protected region digest remaining single stranded regions electrophorese on denaturing polyacrylamide gel advantages less sensitive to slightly degraded mRNA absolutely quantitative can tolerate large amounts of RNA (100+ μg) allows detection of rare transcripts but gives high background multiple simultaneous detection disadvantages more tedious than Northern no blot to reuse multiple simultaneous detection hard to optimize BioSci D145 lecture 5 page 19 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR - reverse transcriptase mediated PCR approach reverse transcribe mRNA -> cDNA amplify with specific primers quantitate flavors relative quantitation – compare to invariant gene absolute quantitation by comparison to synthetic reference competitive PCR various fluorescent dye mediated methods advantages very fast and simple works with tiny amounts of material limitations RT efficiency differs by mRNAs Must be in linear amplification range Errors increase exponentially with amplification BioSci D145 lecture 5 page 20 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR reverse transcriptase mediated PCR relative concentration determination perform multiplex reaction using two primer sets 1 for reference, 1 experimental advantages no fancy equipment required disadvantages careful attention to linear region for both primer sets often must add one set during reaction companies claim to have products that eliminate this need more than 2 primer sets are not reliable BioSci D145 lecture 5 page 21 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR (contd) absolute concentration determination real time PCR Taqman, molecular beacons Fluorescent methods that allow direct quantitation of PCR product approach special oligonucleotide that has a fluor and a quenching group on it. When whole, no fluorescence perform PCR reaction, if primer anneals, Taq polymerase removes the reporter group which can now fluoresce BioSci D145 lecture 5 page 22 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR (contd) absolute concentration determination - Taqman, etc Fluorescence detected continuously in real time advantages can be detected in real time with proper instrument no difficulties with linearity multiplexing of probes possible (limited by available dyes) very good for clinical diagnostics disadvantages requires instrument varies from expensive to extremely expensive Not of equal quality need to make custom oligos - can be expensive must know something about relative abundance of mRNAs before setting up reactions careful optimization required for best results primer concentrations target concentrations BioSci D145 lecture 5 page 23 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR (contd) absolute concentration determination – Sybr Green Alternative real time RT-PCR utilizes a single dye approach Extend a single template Detect ds DNA with a specific dye BioSci D145 lecture 5 page 24 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR (contd) absolute concentration determination – Sybr green Plot lift off time Generate standard curve BioSci D145 lecture 5 page 25 ©copyright Bruce Blumberg 2010. All rights reserved

Analysis of mRNA - quantitation (contd) RT-PCR Sybr Green (contd) Advantages No special primers needed Single dye, simple Fast, robust and quantitative Good for routine use Disadvantages Need instrument Single dye, can’t multiplex Problems with multiple fragments Melting curves required Absolute quantitation requires std curve BioSci D145 lecture 5 page 26 ©copyright Bruce Blumberg 2010. All rights reserved

Other methods of transcriptome analysis - parallel Microarray was once the dominant method Direct RNA sequencing methods are rapidly displacing microarrays SAGE (serial analysis of gene expression) Nanostring is modern implementation Short sequences RNAseq Directly sequence large numbers of RNAs Longer sequences SAGE Relies on generating many very short sequences and matching these to the genome 10 bp = short SAGE 17 bp = “long” SAGE BioSci D145 lecture 5 page 27 ©copyright Bruce Blumberg 2010. All rights reserved

Other methods of transcriptome analysis - parallel SAGE (continued) What is the obvious shortcoming of this method? Sequences may not be unique and could have difficulty mapping to the genome BioSci D145 lecture 5 page 28 ©copyright Bruce Blumberg 2010. All rights reserved

Other methods of transcriptome analysis - parallel RNA seq – Ali Mortazavi is local expert Use of massively parallel sequencing allows precise quantitation of transcript Also allows discovery of rare splice forms Discovery of unexpected transcripts Main problem is in mapping sequence calls to genome Sequencing has 1-2% errors which can make mapping to genome fail or induce “in silico cross-hybridization” Mapping to incorrect genomic location BioSci D145 lecture 5 page 29 ©copyright Bruce Blumberg 2010. All rights reserved

Assumes you know all the transcripts Microarray vs. RNAseq Microarray Assumes you know all the transcripts Any sequence you did not know was expressed will not be there. except whole genome tiling arrays – Kapranov paper Detection limit issues Signal-noise ratio Well validated , expression analysis can be quantitative RNAseq No assumption re transcripts but need genome sequence Can discover novel sequences or new splice forms not yet characterized Detection limits are not a problem – can detect small # Getting better, expression analysis can be quantitative Still have issues mapping sequences to genome Should improve over time BioSci D145 lecture 5 page 30 ©copyright Bruce Blumberg 2010. All rights reserved