Rotor-Gene Q Pure Detection. High Resolution Melting. From Assay to Analysis. Nan Fang, Ph.D. Senior Scientist R&D QIAGEN. Sample & Assay Technologies

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1 Rotor-Gene Q Pure Detection High Resolution Melting From Assay to Analysis Nan Fang, Ph.D. Senior Scientist R&D QIAGEN

2 Overview.Agenda Introduction into HRM The principle Advantages Applications overview HRM in detail Analysis Dye Critical factors Reaction chemistry Instrument and software Cycling conditions Assay design Template Application data and summary The applications presented here are for research purposes. Not for diagnostic use.

The HRM principle Fluorescence 100 80 60 T m Melting Point 40 20 78 79

double-stranded PCR products based on the melting behavior Different

in real time using special intercalating dyes The fluorescence

3 The HRM principle Fluorescence T m Melting Point Temperature HRM characterizes double-stranded PCR products based on the melting behavior Different DNA sequences melt at different specific temperatures This is measured in real time using special intercalating dyes The fluorescence decreases during DNA dissociation The HRM software plots fluorescence decrease vs. temperature

4 Advantages of HRM Enables highly specific and accurate detection of genetic variations Allows further downstream analysis of amplicon (e.g. by sequencing) Less expensive than alternative methods Easy to use Fast Flexible Versatile

5 HRM applications SNP analysis Mutation detection and scanning Pathogen detection Methylation analysis STR and VNTR analysis Quantification of copy number variants and mosaicism

6 HRM An emerging technology HRM citations/year* Ririe, Rasmussen and Wittwer Product Differentiation by Analysis of DNA Melting Curves during the Polymerase Chain Reaction Anal. Biochem., 1997, vol *source: google scholar HRM is expected to become a standard technology for genotyping applications

7 Overview.Agenda Introduction into HRM The principle Advantages Applications overview HRM in detail Analysis Dye Critical factors Reaction chemistry Instrument and software Cycling conditions Assay design Template Application data and summary

8 HRM Analysis - Five steps from PCR to result Step 1: Amplification Was the amplification successful? Step 2: Melt curve analysis Check to verify amplification specificity Step 3: Normalisation Select suitable samples and analysis range Step 5: Autocalling genotypes unknowns will be either related to known genotypes or will be marked as variation Step 4: Difference plot Select the reference genotype

HRM and SNP genotyping Source: Wikipedia.SNP (= Single Nucleotide Polymorphism) Single nucleotide variation Can have major impact on how individuals respond to Disease Environmental factors (e.g. bacteria, viruses, chemicals) Drugs and other therapies SNP maps help to identify multiple genes associated with complex diseases (e.

9 HRM and SNP genotyping Source: Wikipedia.SNP (= Single Nucleotide Polymorphism) Single nucleotide variation Can have major impact on how individuals respond to Disease Environmental factors (e.g. bacteria, viruses, chemicals) Drugs and other therapies SNP maps help to identify multiple genes associated with complex diseases (e.g. cancer, diabetes, vascular disease) SNP Class* Base Change Typical T M Shift Abundance (in humans) I C/T and G/A Large>0.5 C 64% II C/A and G/T 20% III C/G 9% IV A/T Very Small <0.2 C 7% * Classification according to Venter et. al., 2002 Reliable SNP genotyping requires clear resolution of T M < 0.2 C

10 Traditional dye technology for melting analysis Non saturating intercalating dyes, e.g. SYBR Green. SYBR Green I is toxic to PCR, so low concentration is needed Unoccupied positions Some dye molecules relocate as melting begins and do not contribute to fluorescence decrease. Unsaturated binding may allow dye relocation during melts, making it less suitable for HRM SYBR Green I

11 Novel dye technology for melting analysis Saturating intercalating dyes, e.g. EvaGreen. Saturation dyes are much less toxic, so concentration used can be higher Dye saturation leaves no room for relocation events during melting. This reduces dye relocation events and improve melting resolution All positions occupied Saturating dyes like EvaGreen are required for high resolution melt analysis

12 Overview.Agenda Introduction into HRM The principle Advantages Applications overview HRM in detail Analysis Dye Critical factors Reaction chemistry Instrument and software Cycling conditions Assay design Template Application data and summary

13 The amplification step in HRM analysis Reaction chemistry Specific PCR products are vital for optimal results in HRM Classical melt analysis is recommended in HRM method development to monitor specificity of PCR amplification specific product unspecific products High quality PCR is imperative for good HRM results

Components of the Type-It and Epitect HRM kits

14 Components of the Type-It and Epitect HRM kits Reaction chemistry.enzyme: HotStarTaq Plus DNA Polymerase Activation within 5 minutes Unmatched specificity and sensitivity.buffer: Unique combination of K + and NH 4+ ions High specificity No optimization of PCR parameters necessary Dye: EvaGreen Saturating dye Distinct melting curves.q-solution Improves amplification of difficult loci.

15 Successful genotyping of class IV SNP Reaction chemistry Only optimized chemistry allows clear resolution of minute T M differences

Instrumentation prerequisites for HRM analysis Instrumentation Temperature Thermal variability from sample-to-sample must be minimal RGQ has an optimal

01 C Fluorescence Low noise from detector system High stability of excitation light and uniform illumination High intensity excitation tuned to the optimal

16 Instrumentation prerequisites for HRM analysis Instrumentation Temperature Thermal variability from sample-to-sample must be minimal RGQ has an optimal temperature uniformity of 0.01 C Fluorescence Low noise from detector system High stability of excitation light and uniform illumination High intensity excitation tuned to the optimal dye wavelength RGQ: low-noise photomultiplier & and high power HRM LED Combined prerequisites High data density i.e. high number of fluorescence data points per degree thermal transition RGQ with up to 50 points/ C (0.02 C resolution) Instrument precision is imperative for accurate HRM results

Instrument benchmarking by SNP differentiation Rotor-Gene with best performance of all cyclers Instrumentation Comparison of various block cyclers and the Rotor-Gene for HRM performance From Herrmann

17 Instrument benchmarking by SNP differentiation Rotor-Gene with best performance of all cyclers Instrumentation Comparison of various block cyclers and the Rotor-Gene for HRM performance From Herrmann et al; Clinical Chemistry 53, 2007; Block cycler with temp. uniformity: ± 0.4 C High fluorescence noise all traces intercalating no genotypes resolved Block cycler with temp. uniformity: ± 0.5 C several traces intercalating only one genotype resolved Block cycler with temp. uniformity: ± 0.2 C Two genotypes distinguished homozygous traces intercalating only two genotypes resolved Rotor-Gene HRM with temp. uniformity: ± 0.01 C all traces separated all 4 genotypes unambiguously resolved only real-time cycler resolving class IV SNP homozygous samples

18 Combined mode of cycler and chemistry Instrumentation & chemistry A: EpiTect HRM Kit and Rotor-Gene Q B: HRM Kit and Instrument from Supplier A II Confidence threshold: 95% Only the combination of optimal chemistry and instrumentation ensures reliable results

19 Maximum flexibility for analysis RGQ software methods fro HRM analysis Software qpcr modules Standard Curve Absolute Quantitation 2 Standard Curves Relative Quantitation C T Relative Quantitation Comparative Quantitation REST Allelic Discrimination Scatter Graph End-Point (+/-) Analysis Concentration Analysis Melt modules Melt Analysis Standard HRM Analysis ScreenClust HRM Analysis All melt modules can be used with HRM datasets Melt analysis Normalisation & Differentiation Preferably used during method development Standard HRM analysis Normalisation & Subtraction Genotyping via autocalling ScreenClust HRM analysis Normalisation plus statistical analysis Large & difficult datasets and screening applications Check and validate your data with more state-of-the art algorithms on the RGQ Find new HRM results with the unique analysis methods such as ScreenClust

20 Standard HRM data analysis workflow All Current Software Software Raw data Normalisation Difference plot 15 Line-of best fit Subtraction Normalised minus Hetero ,5 63,0 63,5 64,0 64,5 65,0 65,5 66,0 66,5 67,0 67,5 68,0 68,5 deg. Autocalling genotypes Rotor-Gene Q Operating Software

Data analysis Autocalling & confidence percentage Software Genotypes automatically called by comparing samples and controls in difference plot Confidence value (%) is calculated as integrity check

21 Data analysis Autocalling & confidence percentage Software Genotypes automatically called by comparing samples and controls in difference plot Confidence value (%) is calculated as integrity check for auto called results Samples below user-set confidence threshold will be marked as a variation (here: 95%) Difference plot Auto calling Results Variation (< 95%) 0 Normalised minus wt -5 Control (100%) ºC Rotor-Gene Q software conveniently identifies known genotypes or variations

22 Why is the standard HRM workflow often unsatisfactory Unmatched needs for HRM analysis Standard HRM software packages: Normalised minus TT 0-5 AA TT AT ºC plot and analyse only melt curve shape and position interpretation based on operator experience no standardisation manual intervention limits screening applications autocalling often fails for minute difference samples lack rigorous statistical interpretation of data sets limited confidence and comparability of results always need control samples for genotyping limits the number of unknowns in a run new polymorphisms often stay undetected

23 Real-life performance test How many genotypes do you see? 100 Fluorescence-Normalized HRM Plot 90 Rotor-Gene Operating Software Normalised Fluorescence unpublished customer field test data ºC

24 Real-life performance test How many genotypes do you see? 40 Difference Plot 1st possibility 35 Rotor-Gene Operating Software Normalised minus 7/ unpublished customer field test data ºC

25 Real-life performance test How many genotypes do you see? Difference Plot 2nd possibility 5 Rotor-Gene Operating Software Normalised minus 7/ unpublished customer field test data ºC

26 Real-life performance test How many genotypes do you see? Difference Plot 3rd possibility 10 Rotor-Gene Operating Software Normalised minus 9.3/ unpublished customer field test data ºC

27 Real-life performance test How many genotypes do you see? ScreenClust HRM Cluster Plot Rotor-Gene ScreenClust HRM Software Only ScreenClust HRM Software accurately separates all genotypes Standardized process to retrieve the correct result unpublished customer field test data

28 Rotor-Gene ScreenClust HRM Software How does it work Software.Uses innovative statistical methods Analyzes the differences between all samples within one HRM run Groups all samples according to the alleles into clusters Displays the clusters graphically M1 M7 M3 M4 M5 WT M6.Advantages: Superior auto calling of genotypes Automatic detection of new mutations Provides statistical values for maximum confidence in the results Minimized efforts and highly standardized processes Orthogonal approach e.g. for validation purposes

Line-of best fit Differentiation Averaging Subtraction Autocalling

29 Advanced Statistical Data Analysis Workflow Rotor-Gene ScreenClust HRM Software ONLY Software Raw data Normalisation Residual plot Line-of best fit Differentiation Averaging Subtraction Autocalling genotypes Clustering Principal component analysis supervised unsupervised

ScreenClust HRM Workflow Clustering Software The human eyes can easily see clusters but the software must decide on facts using algorithms to define which sample belongs to which cluster Two modes:

30 ScreenClust HRM Workflow Clustering Software The human eyes can easily see clusters but the software must decide on facts using algorithms to define which sample belongs to which cluster Two modes: unsupervised and supervised clustering Unsupervised: groups are unknown or not all of the controls are available sample is assigned to cluster 1, or cluster 2 or... allows hypothesis free analysis method of choice to detect new genetic polymorphism Supervised: groups are known and controls are available for each group sample is assigned to wild type or mutant or heterozygous group... allows autocalling based on several control samples method of choice for genotyping

Current paper for ScreenClust HRM qpcr special edition in METHODS Software METHODS Volume 50, Issue 4, Pages S10-S14 (April 2010) allows to get a deeper

31 Current paper for ScreenClust HRM qpcr special edition in METHODS Software METHODS Volume 50, Issue 4, Pages S10-S14 (April 2010) allows to get a deeper insight in the methods and workflows incldues supplemental on-line material with formulas and description of the algorithms gives some application examples

32 Software: a critical success factor ScreenClust example for a difficult SNP genotyping data set Software wild type heterozygote mutant QIAGEN products used Type-it HRM PCR Kit Rotor-Gene 5plex HRM ScreenClust HRM Software.A/T Class IV SNP minute differences between homozygote alleles (< 0.1 C) impossible to resolve genotypes in a normalized melt plot with Rotor-Gene Q operating Software.ScreenClust HRM provides unambiguous detection clear automated clustering of all genotypes exploits the full resolving power of RGQ instrument and type-it HRM chemistry

33 HRM analysis melting of amplicon at 72 C Cycling 72 C? UB = 100% unmethylated, bisulfite converted human DNA MB = 100% methylated, bisulfite converted human DNA Target: CpG island of the MLH1 gene melting of amplicons at 72 C results in partial dye release already during the extension step amplification plots display lower plateaus and therefore seem to indicate lower product yields

34 Modified HRM cycling protocol Cycling 3-step cycling with extension at 72 C 3-step cycling with extension at 68 C Ensure that cycling conditions allow amplification of all genotypes

35 Guidelines for assay design, cycling and analysis.assay design Design assays with PCR product lengths of bp For SNP analysis, use of PCR products of bp is recommended The melting temperature of primers used for PCR with subsequent HRM analysis should be at least 56 C Design assays with a single melting domain ( Follow cycling guidelines as recommended in the Type-It and EpiTect HRM manual, respectively. Initially determine the melting point for each new HRM PCR product. Run HRM analysis to span a temperature range from C. For time savings, perform subsequent HRM analyses from 5 C below the lowest T M of all expected PCR products to 5 C above the highest T M of all PCR products..analysis Check that the PCR result contains only specific product Exclude samples showing primer dimers or nonspecific products from analysis

36 Effect of template purity on HRM Template.Typical Contaminants NaCl KOAc EDTA ETOH Isopropanol Na Citrate Phenol

37 Template purity effect of contaminants NaCl Template Effect of NaCl on T M T M [ C] None 10mM 50mM 100mM Concentration [mm] Salts increase the T M of PCR amplicons

38 Conclusions and recommendations Template.Conclusions Differences in final reaction compositions result in different melting behaviour and lead to wrong genotype classification.recommendations Use identical method for DNA isolation for all samples Use identical batch of reagents for DNA isolation, including resuspension / elution buffer for all samples Be careful to avoid contamínant carryover in your sample

39 Overview.Agenda Introduction into HRM The principle Advantages Applications overview HRM in detail Analysis Dye Critical factors Reaction chemistry Instrument and software Cycling conditions Assay design Template Application data and summary

40 Application example: SNP genotyping Detection of point mutations in the human KRAS gene QIAGEN products used Type-it HRM PCR Kit Rotor-Gene 5plex HRM Standard HRM analysis module Assay source: Do et al.: High resolution melting analysis for rapid and sensitive EGFR and KRAS mutation detection in formalin fixed paraffin embedded Biopsies BMC Cancer 2008, 8:142 Analysis of point mutations in the human KRAS gene

41 Application example: Mutation scanning Successful scanning of insertions/deletions in EGFR exon 19 M7 M4 M1 M3 M5 M4 WT M6 M6 M4 QIAGEN products used Type-it HRM PCR Kit Rotor-Gene 5plex HRM ScreenClust HRM Software M7 M5 M1 M3 M7 M3 M6 M5 WT M1 WT Assay source: Do et al.: High resolution melting analysis for rapid and sensitive EGFR and KRAS mutation detection in formalin fixed paraffin embedded Biopsies BMC Cancer 2008, 8:142 Supervised analysis of various gene mutations normalized melt plot with almost identical curve shape making genotyping very challenging 7 genotypes (6 mutations and wild type) called successfully by ScreenClust HRM 3 cluster plots here as the first 3 principal components were required for discrimination

42 Application example: Methylation analysis Various ratios of methylated and unmethylated DNA-APC QIAGEN products used EpiTect Bisulfite Kit EpiTect HRM PCR Kit Rotor-Gene 5plex HRM Standard HRM analysis module Analysis of a CpG island from the promoter region of the APC gene (adenomatosis polyposis coli) Mixtures of methylated and unmethylated DNA as template Clear resolution of similar methylation degrees down to 5% sensitivity

43 Application Example: Allelic ratio analysis QIAGEN products used RGQ 5plex HRM ScreenClust HRM.Four allelic ratios of the factor V Leiden (G1691A) polymorphism difficult to resolve allelic ratios down to 2.5% minimal melt curve shape differences for 2.5%, 5% and 10% mutations.rotor-gene Q plus ScreenClust HRM analysis provides unambiguous resolution of all allelic ratios also in unsupervised mode Sensitivity < 2.5% allelic ratios often needed for somatic mutation research

44 Application Example: Pathogen typing with HRM Bacteria species typing for veterinary diagnostics Classification of Mycoplasma Synoviae strains with HRM from N. Jeffrey et al Microbiology : QIAGEN products used: RLT lysis buffer Qiaex II matrix RW1 Buffer QIAquick PCR Rotor-Gene Q 5plex HRM Mycoplasma synoviae is an economically important pathogen of poultry worldwide Causing respiratory infection and synovitis HRM analyses allows detection and identification of all M. synoviae strains Rapid and effective analysis for outbreaks situations (single test in less than 2 h)

45 Summary HRM is a powerful emerging technique to investigate genetic differences offering Throughput & speed Cost effectiveness & convenience Broad application range Outstanding performance in HRM analysis requires: Reliable template purity Highly specific HRM PCR kits with saturating dye qpcr and HRM instrument with superior temperature uniformity Powerful software packages for any kind of data analysis

Powerful analysis software packages Easy and reliable data acquisition and interpretation A variety of different algorithms for

46 The complete solution for HRM analysis gdna preparation from any sample type Manual or automated for any throughput Highly specific HRM PCR kits Mandatory for good HRM results Most precise real-time cycler on the market Prerequisite for accurate HRM analysis Powerful analysis software packages Easy and reliable data acquisition and interpretation A variety of different algorithms for full flexibility Cluster 1 Cluster 2 Cluster Reliable results by dedicated solutions for an entire HRM workflow

47 Questions and Answers

For outstanding performance in real-time PCR

Rotor-Gene Q For outstanding performance in real-time PCR Outstanding thermal and optical performance due to rotary format An unmatched optical range spanning UV to infrared wavelengths State-of-the art