How to do successful gene expression analysis - Siena 20100625

accelerating your analysis How to do successful gene expression analysis Jan Hellemans, PhD

introduction accelerating your analysis qPCR: reference technology for nucleic acid quantification sensitivity and specificity wide dynamic range speed relative low cost conceptual and practical simplicity easy to perform ≠ easy to do it right many steps involved all need to be right

introduction accelerating your analysis RNA quality RT and PCR Choice of Choice of assessment primer design RT chemistry cDNA synthesis Sample extraction strategy Sample selection and handling Assay validation Data Data reporting analysis

prepare – cycle - report accelerating your analysis

prepare accelerating your analysis experiment design • power analysis • sample vs gene maximization • run layout samples • preparation • quality control • pre amplification assays • design • in silico validation • empirical validation reference gene • selection • validation

power analysis accelerating your analysis determination of the number of data points needed to reach statistical significance for a given difference variability 14,00 12,00 technical constraints 10,00 critical t-value confidence interval (CI) 8,00 3 (~ critical t-value t*) 6,00 CI = SEM x t* 4,00 2,00 0,00 2 3 4 5 10 20 100 number of datapoints

power analysis accelerating your analysis determination of the number of data points needed to reach statistical significance for a given difference variability technical constraints confidence interval (CI) 3 Mann-Whitney test: nA + nB 8 Wilcoxon test: 6 pairs http://www.cs.uiowa.edu/~rlenth/Power/

sample versus gene maximization accelerating your analysis how to set-up an experiment with 3 genes of interest (GOI) & 3 reference genes (REF) 11 samples (S) & 1 no template control (NTC) gene maximization sample maximization REF1 REF2 REF3 GOI1 GOI2 GOI3 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 NTC S1 REF1 S2 S3 REF2 S4 S5 REF3 S6 S7 GOI1 NTC REF1 REF2 REF3 GOI1 GOI2 GOI3 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 NTC S1 GOI2 S2 S3 GOI3 S8 S9 S10 S11 NTC

sample versus gene maximization accelerating your analysis sample maximization – to be preferred no increase in variation due to absence of inter-run variation suitable for retrospective studies and controlled experiments gene maximization introduces (under-estimated) inter-run variation applicable for prospective studies or large studies in which the number of samples do not fit in the run anymore inter-run variation can be measured and corrected for using inter-run calibrators (IRC) through a procedure called inter-run calibration

preparation accelerating your analysis cDNA synthesis most variable step in the workflow (> RT replicates) different performance of the enzymes linearity and yield are important DNase treament retropseudogenes (15%) and single exon genes (5%) on column vs. in solution verify absence of DNA qPCR for genomic DNA target on RNA as input

quality control – RNA integrity value accelerating your analysis Evaluate integrity of 18S and 28S rRNA Agilent Bioanalyzer Bio-Rad Experion Caliper GX Qiagen QIAxcel Shimadzu MultiNA

quality control – 5’-3’ ratio accelerating your analysis universally expressed low abundant reference anchored oligo(dT) reverse transcription 5’ 3’ AAAAAA Cq 5’ Thermic degradation Cq 3’ 9 8 7 6 5'-3' delta Ct 5 4 3 2 1 0 109 109* 109** 275 275* 275** 539 539* 539** s am ple s  increasing delta-Cq values upon artificial RNA degradation

quality control – SPUD assay for inhibition accelerating your analysis spiking of synthetic sequence lacking homology with any known human sequence into RNA SPUD SPUD SPUD SPUD SPUD + + + + + H2O heparin RNA1 RNA2 RNA3 ------------RT-qPCR--------- Cq 22 Cq 27 Cq 22 Cq 25 Cq 22 ΔCq > 1: presence of inhibitors

pre-amplification accelerating your analysis methods WT-Ovation (NuGEN) limited cycle PCR (PreAmp - Applied Biosystems) preservation of differential expression (fold changes) before (B) and after (A) sample pre-amplification (G1S1)B/(G1S2) B = (G1S1) A/(G1S2) A G1B/G2B < > G1A/G2A gene G, sample S, before B, after A

http://www.rtprimerdb.org accelerating your analysis

assay design guidelines accelerating your analysis location sequence repeats, protein domains splice variants intron spanning vs intra exonic short amplicons: 80-150bp SNPs primers dTm < 2°C identical Tm for all assays maximum 2 GC in last 5 nucleotides use software to design assays Primer3(Plus), BeaconDesigner, RTprimerDB

in silico validation accelerating your analysis do thorough in silico assay evaluation BLAST/BiSearch specificity analysis mfold secondary structure SNP analysis of primer annealing regions splice variant specificity streamline in silico analyses with RTprimerDB pipeline

empirical assay validation accelerating your analysis specificity size analysis (only once) agarose or polyacrylamide gel capillary electrophoresis melting curves (SYBR, repeated) [sequence / restriction digest] amplification efficiency standard curve range & number dilution points representative sample [single curve efficiency algorithms] for absolute quantification linear range and limit of detection

single reference gene accelerating your analysis quantitative RT-PCR analysis of 10 reference genes (belonging to different functional and abundance classes) on 85 samples from 13 different human tissues 4 3 ACTB HMBS 2 HPRT1 TBP 1 UBC 0 A B C D E F G

Single versus multiple reference genes accelerating your analysis single reference gene errors related to the use of a single reference gene: > 3 fold in 25% of the cases > 6 fold in 10% of the cases multiple reference genes developed a robust algorithm for assessment of expression stability of candidate reference genes proposed the geometric mean of at least 3 reference genes for accurate and reliable normalisation geNorm analysis in pilot study Vandesompele et al. Genome Biol. 2002 Jun 18;3(7):RESEARCH0034.

geNorm accelerating your analysis validation insensitive to outliers reduce most of the variation statistically more significant results accurate assessment of small expression differences de facto standard for reference gene validation 2 400 citations of the geNorm technology ~12 000 geNorm software downloads in 112 countries

genormPLUS accelerating your analysis

cycle accelerating your analysis cycle • instrument • chemistry • controls

instrument accelerating your analysis fast PCR fast ramping ≠ fast qPCR experiment 96-well vs 384-well 384-well system is slightly more expensive 384-well plates harder to pipet (multichannel pipets or pipetting robot) 384-well run gives 4x more data in same time 384-well plates require smaller volumes plate homogeneity test

chemistry accelerating your analysis choose probes for multiplexing genotyping absolute sensitivity (detection past cycle 40) (e.g. clinical-diagnostic setting, GMO detection) choose SYBR Green I for all other applications low cost seeing what you do

controls accelerating your analysis melting curve unique melt peak for all samples? replicates delta-Cq < 0.5 cycles? controls negative control really blank delta-Cq samples/NTC > 5? positive controls with expected Cq? amplification plot shape (kinetic outlier detection)

report accelerating your analysis relative quantification • efficiency correction • multiple reference gene normalization • inter-run calibration • error propagation bio statistical analysis • biological replicates • log transform data • selection of statistical test reporting guidelines • RDML • MIQE

calculation methods accelerating your analysis Cq RQ NRQ CNRQ Inter-run calibration Normalization Cq RQtoi NRQsoi RQ E NRQ CNRQ n n n RQref i n NRQirci i i Hellemans et al. Genome Biol. 2007;8(2):R19.

data processing – relative quantification accelerating your analysis

qbasePLUS accelerating your analysis

quality control accelerating your analysis PCR replicates ∆Cq < 0.5 cycles no template control no signal (no Cq value) Cq (NTC) > Cq (samples) + 5 reference gene stability M < 0.5 M < 1 for heterogeneous samples CV < 25% CV < 50% for heterogeneous samples normalization factors no unexpected high variation

replicates accelerating your analysis technical vs biological replicates repeated measures vs. replication PCR replicates (pipetting error & Poisson’s law) RT replicates repeated RNA extraction from same sample repeated cell cultures / patient sampling true biological replicates (from different subjects) no statistics on repeated measures type of replicates dictates conclusions that can be drawn

statistical tests accelerating your analysis relative quantities are not normally distributed log transformation makes them more symmetrical relevant tests in the field of relative quantification comparison of 2 unpaired groups t test Mann-Whitney randomization test comparison of 2 paired groups ratio t test (paired t test on log values) Wilcoxon rank sum test correlation analysis Pearson Spearman linear regression correct for multiple testing

MIQE accelerating your analysis http://www.rdml.org/miqe Bustin et al. Clin Chem. 2009 Apr;55(4):611-22. authors improve quality of qPCR experiments reliable and unequivocal interpretation of results reviewers and editors assess technical merit full disclosure of reagents and analysis methods consumers of published research published results easier to reproduce

MIQE checklist for authors, reviewers and editors accelerating your analysis experimental design sample nucleic acid extraction reverse transcription target information oligonucleotides qPCR protocol qPCR validation data analysis E – essential D – desirable

RDML accelerating your analysis http://www.rdml.org Lefever et al. Nucleic Acids Res. 2009 Apr;37(7):2065-9.

acknowledgements accelerating your analysis Jo Vandesompele Stefaan Derveaux http://www.biogazelle.com - Jan.Hellemans@biogazelle.com

How to do successful gene expression analysis - Siena 20100625

by Biogazelle on Jul 06, 2010

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