A robust and sensitive. for profiling of mirnas Life Sciences - Genomics. Stephanie Fulmer-Smentek. Group Manager. Agilent mirna profiling solution
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1 A robust and sensitive microarray system for profiling of mirnas Life Sciences - Genomics Stephanie Fulmer-Smentek RNA Applications R&D Group Manager
2 Overview microrna biology Agilent mirna platform - SurePrint technology - mirna protocol workflow - Probe and Array Design - Data Extraction and Quality Control Performance Data - Dynamic Range & sensitivity - Specificity - Data linearity - Reproducibility - Comparison to qrt-pcr Agilent mirna products
3 mirna Biology
4 micrornas (mirna) Long precursor (pri-mirna) Proteins Hairpin mirna precursor pre-mirna (~70nts) Proteins Mature mirna (~22nts, single-stranded) Proteins Combinatorial Regulation Key regulators of cell development ~22nts single-stranded RNAs Regulate mrna translation Found in animals, plants, & viruses ( total > 5000) >700 identified in humans (Sanger mirbase 10.0) 0) May regulate >30% of human genes Tissue-specific expression patterns Different cancers have distinct mirna expressions Diagnostic and prognostic potential being explored Proteins Translation inhibition No Protein Production Figures not drawn to scale
5 Challenges in mirna Profiling Small size High sequence homology Presence of larger RNAs with highly homologous sequences Expressed with large dynamic range Growing & changing database mirna Sequence #NT hsa-let-7a ugagguaguagguuguauaguu 22 hsa-let-7b ugagguaguagguugugugguu 22 hsa-let-7c ugagguaguagguuguaugguu 22 hsa-let-7d agagguaguagguugcauaguu hsa-let-7e ugagguaggagguuguauaguu hsa-let-7f ugagguaguagauuguauaguu 22 hsa-let-7g ugagguaguaguuuguacaguu hsa-let-7i l t ugagguaguaguuugugcuguu Sanger mirbase 10.0
6 Agilent s mirna platform
7 Agilent mirna Platform Highlights Low sample input ng Total RNA used for labeling NO small RNA isolation required Efficient, direct labeling method linked to specialized mirna probe design methods Simple protocol results in < 2 days High sequence and size specificity Multiplex format 8 arrays per slide Multiple probe sequences and probe replicates per mirna One-color analysis Enabled by Agilent SurePrint inkjet technology
8 Agilent SurePrint Inkjet Printing Benefits: Features are physically isolated from each other -- NO issue of light leaking Synthesis efficiency greater than 99.5% for 60-mer oligonucleotides: increased signal-tonoise because probe fidelity is critical ca for binding interactions Our feature size and printing technology allow us to have perfect registration from layer to layer (no blurry edges) Our feature size allows us to get sufficient pixels per feature after scanning to perform pixel level statistics that can eliminate outlier pixel populations and help estimate confidence in the measurement Back to Benchmarks Back to Performance
9 mirna Protocol workflow Total RNA (100ng) Time to results <2 days with minimal hands-on time Phosphatase treatment, 30 min, 37ºC Dephosphorylated RNA OH * OH OH Add DMSO Heat, ice Labeled RNA Desalted Labeled RNA * Assemble labeling reaction, 16ºC 2hr * OH Desalt with spin column Speed vac, ~1hr, 45ºC P P P C C P P Cy Cy Assemble hybridization mixture Heat, ice Hybridize 20 hours, 55ºC, 20RPM Wash, scan * Sample can be t d f t 80 o C if necessary mirna Profile stored frozen at -80 o C,
10 Probe Design Strategy Start design with full-length mirnaprobe sequence, attached to a stilt sequence. Utilize the C incorporated during labeling for additional G-C base pair on 3 end of mirna to increase stability Sequentially shorten target-probe base pairing from 5 end of mirna during preliminary Tm balancing by calculation. Incorporate hairpin structure on probes to increase size specificity and probe:target stability. Final Step: Select Tm-balanced probes for each mirna empirically using microarray data.
11 Array Design Human mirna Microarray, v1.0: Content from Sanger mirbase release 9.1 Probes for 470 human and 64 human viral mirnas Each mirna has 2 different probe sequences, each replicated multiple times on the microarray: at least 20 features/mirna Eight identical, separately hybridizable, arrays per slide Where possible*, probes have been empirically Tm balanced. Multiple probe sequences and replicates allow for robust mirna level data summarization * When mirna has been present in tested samples
12 Human mirna microarray
13 Scanning and Data Extraction -XDR Automated t extended d Dynamic Range Scanning Automatically scans twice, with high sensitivity and low sensitivity High Low Feature Extraction Automatically combines 2 scan data and generates each array s QC report and text output 8 sets of text outputs and QC Reports
14 Feature Extraction Data Processing 2 text files Regular Data.txt File Feature Finding Cookie Cutter Pixel Rejection Outlier flagging Background Subtraction intensity abundance gnumpix gmeansig gmediansig gpixsdev gbgnumpix gbgmeansig gbgmediansig gbgpixsdev gissaturated gisfeatnonunifol gisbgnonunifol gisfeatpopnol gisbgpopnol gbgsubsignal GeneView Data.txt File: simplified format 5 columns gene level l summary Total Gene Signal Calculation
15 Calculation of mirna TotalGeneSignal in Feature Extraction Multiple probe sequences/mirna Multiple replicates/probe sequence Probe A Probe B X Outlier Step 1 Reject Outlier Features Step 2 Average non-outlier feature replicates/probe sequence Step 3 Multiply that average by the total # pixels representing that sequence and multiply by weight Step 4 Sum TotalProbeSignals for all probes for each mirna [( )/9] *10*(#pixels/feature)*W=TotalProbeSignal (Probe A) [( )/8] *10*(#pixels/feature)*W=TotalProbeSignal (Probe B) TotalProbeSignal (Probe A)+TotalProbeSignal (Probe B)=TotalGeneSignal Note: The weight factor scales the total signals back to a similar scale as intensity values, to better fit with downstream analysis
16 Metrics and tools for assessment of mirna profiling data quality 2 methods for in-process quality control of mirna microarray experiments: QC report generated with each microarray run QC metric chart, plots key mirna specific metrics across all microarrays in a given Feature Extraction run QC metrics can be customized by the user using the free QC metric tool
17 Sample Microarray QC Report Header Grid Placement Outlier Statistics Outlier Distribution Net Signal Statistics Histogram of Background Subtracted Signal
18 Intra-array Reproducibility Signal Spatial Distribution mirna specific QC Metrics
19 QC Run Chart mirna specific metrics presented for an entire feature extraction run
20 Performance Data
21 Linear Dynamic Range of mirna measurements ignal Equal-molar synthetic mirnas were labeled and hybridized at amol to 1 fmol /mirna per microarray. TotalGeneS fmol = 1000 amol 1 amol = 1000 zmol RNA Amount (zmol)
22 Specificity of hybridization 40hr Hyb Before Empirical Tm-balancing: (Wang, Ach, & Curry, RNA, 13, 1-9) mirna mirna mirna mirna mirna mirna mirna mirna 7a 7b 7c 7d 7e 7f 7g 7i Probes 7a Probes 7b Hyb Probes 7c Probes 7d Probes 7e Probes 7f Probes 7g Probes 7i After Empirical Tm-balancing: (unpublished) 40hr Hyb mirna mirna mirna mirna mirna mirna mirna mirna 7a 7b 7c 7d 7e 7f 7g 7i Probes 7a Probes 7b Probes 7c Probes 7d Probes 7e Probes 7f Probes 7g Probes 7i
23 Effect of Hybridization Time on Specificity Empirically i Tm-balanced Probes: (unpublished) 40hr Hyb mirna mirna mirna mirna mirna mirna mirna mirna 7a 7b 7c 7d 7e 7f 7g 7i Probes 7a Probes 7b Probes 7c Probes 7d Probes 7e Probes 7f Probes 7g Probes 7i mirna mirna mirna mirna mirna mirna mirna mirna 7a 7b 7c 7d 7e 7f 7g 7i Probes 7a Probes 7b Probes 7c y Probes 7d Probes 7e Probes 7f Probes 7g Probes 7i hr Hyb
24 Complex sample titration study Brain and Placenta total RNA samples, pure and in two different mixtures (25:75 and 75:25) Each sample was processed in 4 replicates using standard conditions, by 4 different users TotalGeneSignals for the mirnas were loaded into GeneSpring GX for analysis No per-chip normalization was applied Signal response as a function of %Brain sample was analyzed for selected mirnas.
25 Selection of genes for titration test Select mirna s significantly different (P<0.01) between 100% Brain and 75%Brain:25% Placenta (no fold change cut-off)
26 Linearity of Signal Response Up-regulated in Brain Down-regulated in Brain
27 Confirmation of small fold changes across the titration range hsa-mir-9*; FC=088for FC= %Brain/100% Brain ain) mple/bra o (selected sam Ratio
28 Reproducibility- Intra-user Intra-slide Inter-slide
29 Reproducibility- Inter-user
30 Comparison of mirna Microarray Results to qrt-pcr Array (log 2 (Mean Tota al Gene Sig gnal) 12 mir-15a y = x R = qpcr (Mean Ct) (log 2 (Mean Total Gen ne Signal) Array mir-34a y = x R = qpcr (Mean Ct) Tissues = Placenta, Brain, Breast, Liver, Heart, Testes, Ovary, Thymus, Skeletal Muscle
31 Comparison of mirna Microarray Results to qrt-pcr, cont. )qrt Array (log 2 (Mean To otal Gene Signal) hsa-mir-155 y = x R = qpcr (Mean Ct) Array (log 2 (Mea an Total Ge ene Signal) hsa-mir-296 y = x R = qpcr (Mean Ct) Tissues = Placenta, Brain, Breast, Liver, Heart, Testes, Ovary, Thymus, Skeletal Muscle
32 Microarray Correlation to qrt-pcr for 38 mirna tested More * *Three mirnas had poor correlations: hsa-mir-494: sequence change from Sanger 9.1 to 10.0 hsa-mir-631: Low signals for both methods hsa-mir-296: (now hsa-mir-296-5p), next slide
33 Titration of hsa-mirna-296 suggests consistent probe performance Tot talgenesig gnal Equal-molar synthetic mirnas were labeled and hybridized at amol to 1 fmol /mirna per microarray fmol = 1000 amol 1 amol = 1000 zmol RNA Amount (zmol)
34 Differential Expression Comparison between mirna microarrays and qrt-pcr Placenta/Testes Skeletal Muscle/Breast Arrays (Log 2 (Pla acenta/tes tes)) 4 0 Ar rrays (Log 2(SkM/Brea 2 ast)) -4-2 Y = x R = qpcr (Mean deltact, Placenta-Testes) 2 0 Y = x R = qpcr (Mean deltact, SkM-Breast) Log2 expression ratios of the 38 mirnas in two different tissue pairs were determined for both qpcr and array measurements. Results are shown here are for placenta/testes and skeletal muscle/breast ratios.
35 Summary of performance data Five orders of magnitude of linear dynamic range Detection of mirnas in amounts as low as 10 zmol (~6000 molecules) Highly specific hybridization with low levels of crosshybridization with as few as one mismatch Accurate and consistent detection of small fold changes Reproducible data across multiple users Good correlation with RT-PCR
36 mirna products from Agilent Technologies Microarray Platform: -Human mirna microarray kit (version 1.0) -mirna labeling reagent and hybridization kit Coming soon: Mouse, Rat and updated Human microarray kits 2100 Bioanalyzer: Total RNA Assays (for RNA integrity) -RNA 6000 Nano Kit -RNA 6000 Pico Kit Small RNA Kit (for analysis of small RNAs) Stratagene s e qpcr: -High-Specificity mirna QRT-PCR Detection Kit -mirna Specific Forward Primers
37 For more information Technical Background: Wang, Ach, & Curry, RNA, 13, 1-9 (2007). Product Information:
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