mi rna part ii_2013

Sample & Assay Technologies

Advanced miRNA Expression Analysis :

From Experimental Design through Data Analysis

Jonathan Shaffer, Ph.D.

[email protected] Technologies, R&D Americas

The products described in this webinar are intended for molecular biology applications. These products are not intended for the diagnosis, prevention or treatment of disease.

Sample & Assay Technologies Three part webinar series

Webinar 2: Advanced miRNA Expression Analysis 2

miRNA and its role in human disease

Webinar 2 : Advanced microRNA expression analysis: From experimental design through data analysis

Speaker: Jonathan Shaffer, Ph.D.

Webinar 3 : Profiling miRNA expression in Cells, FFP E, and serum:On the road to biomarker development


Webinar 1 : Meeting the challenges of miRNA research :An introduction to microRNA biogenesis, function, a nd analysis


Sample & Assay Technologies Advanced miRNA Expression Analysis


Agenda

� Overview� miRNA Background� miRNA expression profiling using a miScript miRNA PCR Array

� How to calculate fold-change using the ∆∆CT method of relative quantification � Setting the Baseline and Threshold� Data analysis example 1: Basic Experiment� Using the free miScript miRNA PCR Array data analysis tools� Data analysis example 2: Serum miRNA Experiment

� Summary of QIAGEN’s miRNA detection portfolio� Current Promotion

Sample & Assay Technologies Canonical pathway of miRNA biogenesis


� Transcribed by RNA Polymerase II as a long primary transcript (pri-miRNAs), which may contain more than one miRNA.

� In the nucleus, pri-miRNAs are processed to hairpin-like pre-miRNAs by RNAse III-like enzyme Drosha.

� Pre-miRNAs are then exported to the cytosol by exportin 5.

� In the cytosol RNAse III-like Dicer processes these precursors to mature miRNAs.

� These miRNAs are incorporated in RISC.

� miRNAs with high homology to the target mRNA lead to mRNA cleavage.

� miRNAs with imperfect base pairing to the target mRNA lead to translational repression and/or mRNA degradation.

Sample & Assay Technologies Why quantify miRNAs?


� Virtually every publication includes characterization by quantification.

� Changes in miRNA can be correlated with gene expression changes in development, differentiation, signal transduction, infection, aging, and disease.

miRBase EntriesHighWire + PubMed Publications

Sample & Assay Technologies miRNA expression profiling applications


� Mechanisms of gene regulation

� Developmental biology

� Novel miRNA discovery

� Studying miRNA–mRNA and miRNA–protein interactions

� Integrative analyses of miRNAs in the context of gene regulatory networks

� Biomarkers

� Tissue-based miRNA biomarkers

� Tissues of unknown origin

� Circulating biomarkers

� Forensics

From Pritchard, C.C., et al, Nature Rev. Genet 2012, 13, 358-369

Sample & Assay Technologies miRNA quantification approaches


� Northern blotting

� Deep sequencing

� Microarrays

� Real-time PCR based approaches

Sample & Assay Technologies miRNA quantification by real-time PCR


� Real-time PCR quantification of miRNAs

� Has been the gold standard for gene quantification

� Is the method of choice to confirm next-generation sequencing and microarray results

� Simple and easy to carry out

� High sensitivity, specificity

� High throughput compatible, automatable

� Needs very low amounts of template

Sample & Assay Technologies miRNA expression profiling using real-time PCR


Key considerations

Scientific question� Well-defined and testable

Experimental sample set� Statistically meaningful number of replicates (biological replicates)

� A minimum of three replicates recommended� Additional replicates may enhance statistical power

� Inclusion of proper controls

Experimental testing platform� Simple, straightforward workflow� High sensitivity and specificity� When profiling expression: a variety of PCR arrays to meet your

experimental needs� Easy and simple data analysis tools� Customizable solutions� Availability of companion research tools

Sample & Assay Technologies miScript PCR System


Fully integrated, complete miRNA quantification sys tem

1. miScript II RT Kit� HiFlex Buffer: Unparalleled flexibility for quantification of

miRNA and mRNA from a single cDNA preparation� HiSpec Buffer: Unmatched specificity for mature

miRNA profiling

2. miScript miRNA PCR Arrays� miRNome� Pathway-focused

3. miScript PreAMP Kit� Optional step for small or precious samples� Full miRNome profiling from as little as 1 ng RNA

4. Assays� miScript Primer Assays� miScript Precursor Assays� QuantiTect Primer Assays

5. miScript SYBR Green PCR Kit� QuantiTect SYBR Green PCR Master Mix� Universal Primer

6. miScript miRNA PCR Array data analysis software � Straightforward, free data analysis

Sample & Assay Technologies miScript II RT Kit


A complete miRNA quantification solution

miScript II RT Kit

Biogenesis studies?Mature miRNA

quantification and profiling?

HiFlex Buffer HiSpec Buffer

Flexible detection of all RNA molecules

Patent-pending technology for the specific detection of mature miRNAs

Note: Only HiSpec Buffer is recommended for use with miScript miRNA PCR Arrays

Sample & Assay Technologies miScript II RT Kit


Reverse transcription using HiSpec Buffer

Sample & Assay Technologies miRNome miScript miRNA PCR Arrays


Leading coverage and validated assays

� Human� Mouse� Rat � Dog� Rhesus macaque

� 100% validated assays� Each assay is bench validated� Each array is quality controlled

� Leading miRNome coverage

� Customizable

� miRBase V17 and V18 assays are available!

� Contact us if you are interest in a different species!

miRNome Arrays Benefits of miRNome Arrays

Species Assays(miRBase V16)

Human 1066

Mouse 940

Rat 653

Dog 277

Rhesus macaque 469 (V18)

Sample & Assay Technologies Focused miScript miRNA PCR Arrays


Biologically relevant, intelligently designed

Focused Arrays

� miFinder� Cancer PathwayFinder� Brain Cancer � Breast Cancer� Ovarian Cancer� Liver miFinder – New!� Apoptosis� Cell Differentiation & Development� Immunopathology � Inflammatory Response & Autoimmunity� Diabetes � Neurological Development & Disease � T-Cell & B-Cell Activation� Prostate Cancer� Cardiovascular Disease� Serum & Plasma

� 100% validated assays� Each assay is bench validated� Each array is quality controlled

� Biological relevant and up-to-date

� Customizable

� Contact us if you are interest in a different species!

Benefits of Focused Arrays

Sample & Assay Technologies High Content (HC) miScript miRNA PCR Arrays


Targeted miRNome profiling

� miFinder 384HC

� Serum & Plasma 384HC

� Cancer PathwayFinder 384HC

� Liver miFinder 384HC – New!

Sample & Assay Technologies Anatomy of a miScript miRNA PCR Array


96-well Format: 84 miRNA + 12 controls

Cel-miR-39

miScript PCR Controls for Normalization

miRTC PPCSNORD61; SNORD68; SNORD72 SNORD95; SNORD96A; RNU6-2

RTControl

PCRControl

Spike in Control

84 miRNAs

� Cel-miR-39� Alternative data normalization using exogenously spiked Syn-cel-miR-39 miScript miRNA Mimic

� miScript PCR Controls� Data normalization using the ∆∆CT method of relative quantification

� miRNA reverse-transcription control (miRTC)� Assessment of reverse transcription performance

� Positive PCR control (PPC)� Assessment of PCR performance

Sample & Assay Technologies miScript PCR Controls


Stable expression and excellent amplification effic iencies

SNORD61

SNORD68

SNORD72

SNORD95

SNORD96A

RNU6-2

� Highly conserved across multiple species� Human, Mouse, Rat, Dog, Rhesus macaque

� Relatively stable expression in many tissues� Amplification efficiencies of these assays are 100%� Consistent performance in both HiSpec and HiFlex Buffers� Ideal normalizers for ∆∆CT method of relative quantification

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Brain Kidney Liver Lung Skeletal

Muscle

Testis Thymus

Mean C

T

Tissue Expression

Amplification Efficiencies

Primer Hsa Mmu Rno Cfa Mml

SNORD61 103 99 95 99 101

SNORD68 101 100 93 97 99

SNORD72 94 100 93 91 97

SNORD95 102 103 98 100 106

SNORD96A 102 95 95 92 104

RNU6-2 98 98 95 99 103

Sample & Assay Technologies miScript miRNA PCR Arrays

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Formats built to fit your cycler AND your experimen t

96-well 384-well

384-well (4 x 96) Rotor-Disc 100

Webinar 2: Advanced miRNA Expression Analysis

Sample & Assay Technologies miScript miRNA PCR Arrays


Compatible with a wide range of instruments

� 96-Well: 7000, 7300, 7500, 7700, 7900HT, ViiA 7� FAST 96-Well: 7500, 7900HT, Step One Plus, ViiA 7� FAST 384-Well: 7900HT, ViiA 7

� Mastercycler ep realplex 2/2S/4/4S

� Mx3000p, Mx3005p, Mx4000p

� iCycler, MyiQ, MyiQ2, iQ5, CFX96, CFX384� Opticon, Opticon 2, Chromo 4

� LightCycler 480

� TP-800

RotorGene Q



QIAGEN PCR Array Service Core

miScript miRNA PCR Arrays

� Total RNA Isolation: miRNeasy Kits

� Reverse Transcription: miScript II RT Kit

� qPCR: miScript miRNA PCR Arrays

� Data analysis included!

Send your samples and receive results!



Rapid Workflow = Robust, Reproducible Performance

miScript miRNA PCR Arrays

y = 1.0075x + 0.2891

R2 = 0.989

15

20

25

30

15 20 25 30

Mean CT: Biological Replicate 1

Mean C

T: Biological Replicate 2

1st Time Array User

� Total HeLa S3 (miRNeasy)� Pellet 1: Frozen June 2010� Pellet 2: Frozen April 2011

� HiSpec Buffered cDNA� miScript real-time PCR

� miFinder miScript miRNA PCR Array

� 1 hour� HiSpec Buffer

� 2 minutes

� 2 hours

� 15 minutes



Real-time PCR data analysis

(1) Schmittgen TD, Livak KJ.(2008):Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc.;3(6):1101-8

(2) Livak, KJ, and Schmittgen, TD.(2001): Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2-∆∆CT Method METHODS 25, 402–408

(3) www.Gene-Quantification.info

CT = 23.8

� Absolute quantification� Absolute input copies, based on a standard curve

� Relative quantification� Comparative CT method: also known as the 2-∆∆CT method� Selection of internal control� Selection of calibrator (e.g. untreated control or normal

sample)� Assumes that the PCR efficiency of the target gene is

similar to the internal control gene (and that the efficiency of the PCR is close to 100%)

� Fold change = 2-∆∆CT

– ∆CT = CTGene - CT

Normalizer

– ∆∆CT = ∆CT (sample 2) – ∆CT (sample 1) where sample 1 is the control sample and sample 2 is the experimental sample



Data analysis workflow

Steps 1 & 2:Set Baseline and Threshold to determine C T values

Step 3:Export C T values

Step 4:Analyze data using ∆∆CT method of relative quantification



Set Baseline and Threshold to determine C T values

Steps 1 & 2

� Baseline� Definition: Noise level in early cycles where there is no detectable increase in

fluorescence due to PCR products.� How to Set:

– Observe amplification plot using the “Linear View”– Determine the earliest visible amplification– Set the baseline from cycle 2 to 2 cycles before the earliest visible amplification– Note: The number of cycles used to calculate the baseline can be changed and should be

reduced if high template amounts are used




Steps 1 & 2

� Threshold� Purpose: Used to determine the CT (threshold cycle) value. The point at which

the amplification curve intersects with the threshold line is called the CT.� How to Set:

– Observe amplification plot using the “Log View”– Place the threshold in the lower half of the log-linear range of the amplification plot, above

the background signal– Note: Never set the threshold in the plateau phase



Applied Biosystems ® 7900HT

Setting the Baseline and Threshold

Threshold: 0.2

� Baseline: From cycle 2 (or 3) to 2 cycles before the earliest visible amplification.� Threshold: Place in the lower half of the log-linear range of the amplification plot,

above the background signal.

Baseline: 3 to 15



QIAGEN Rotor-Gene ® Q

Setting the Baseline and Threshold

Baseline Threshold: 0.02

Always select “Dynamic Tube”

Potentially select “Slope Correct” and/or “Ignore First”



Use the Second Derivative Maximum analysis method

miScript miRNA PCR Arrays on Roche ® LightCycler ® 480

Select Second Derivative Maximumanalysis method

Obtain C T Values



Step 3: Export C T values

� One 5 µM FFPE section used per FFPE isolation� Each isolation is from a different section� On average, each isolation provided enough total RNA for:

– Two full human miRNome profiles– Ten pathway-focused PCR arrays

� RT: 125 ng total RNA, HiSpec Buffer� qPCR: Human miFinder miScript miRNA PCR Array (0.5 ng cDNA per well)

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1 7 13 19 25 31 37 43 49 55 61 67 73

CT Value

FFPE Isolation 1

FFPE Isolation 2

FFPE Isolation 34

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12

16

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28

32

36

40

1 7 13 19 25 31 37 43 49 55 61 67 73

CT Value

FFPE Isolation 1

FFPE Isolation 2

FFPE Isolation 3

Normal Lung Lung Tumor



∆∆CT method of relative quantification

Step 4: Analyze data

Normal (N) Lung Total RNA Lung Tumor (T) total RNA

N cDNA (Iso. 1) N cDNA (Iso. 2) N cDNA (Iso. 3) T cDNA (Iso. 1) T cDNA (Iso. 2) T cDNA (Iso. 3)

Exported C T values Exported C T valuesCalculate ∆CTfor each miRNAon each array

∆CT = CTmiRNA – AVG CT

SN1/2/3/4/5/6 ∆CT = CTmiRNA – AVG CT

SN1/2/3/4/5/6

� Tip for choosing an appropriate snoRNA/snRNA control s for normalization� Make sure that the selected controls are not influenced by the experimental conditions




Step 4: Analyze data (cont.)

Normal (N) Lung Lung Tumor (T)Calculate ∆CT

for each miRNAon each array

∆CT ∆CT∆CT ∆CT∆CT ∆CT

Calculate ∆∆CT for each miRNA

between groups(T – N)

∆∆CT = Avg. ∆CT (T) – Avg. ∆CT (N)

Calculate fold-change for each miRNA (T vs. N)

2-(∆∆CT)

Calculate Average ∆CT for each miRNAwithin group (N or T)

∆CT + ∆CT + ∆CT

3

∆CT + ∆CT + ∆CT

3



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-10

-6

-2

2

6

10

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Log2 Fold-Regulation (Tumor vs. Norm

al)

Fold-Regulation: Tumor vs. Normal

� Significant differences exist between the mature miRNA expression levels of the two tissue types


Step 4: Analyze data (cont.)



Incorporating the free miScript miRNA PCR Array Data Analysis Software

miScript’s straightforward, data analysis workflow

Steps 1 & 2:Set Baseline and Threshold to determine C T values

Step 3:Export C T values

Step 4:Access the free data analysis tools at

http://pcrdataanalysis.sabiosciences.com/mirna

Step 5 & on:Automatic data using ∆∆CT method of relative quantification




Steps 1 & 2

� Baseline� Definition: Noise level in early cycles where there is no detectable increase in

fluorescence due to PCR products.� How to Set:

– Observe amplification plot using the “Linear View”– Determine the earliest visible amplification– Set the baseline from cycle 2 to 2 cycles before the earliest visible amplification– Note: The number of cycles used to calculate the baseline can be changed and should be

reduced if high template amounts are used

� Threshold� Purpose: Used to determine the CT (threshold cycle) value. The point at which

the amplification curve intersects with the threshold line is called the CT.� How to Set:

– Observe amplification plot using the “Log View”– Place the threshold in the lower half of the log-linear range of the amplification plot, above

the background signal– Note: Never set the threshold in the plateau phase

� Important: Ensure that baseline and threshold settings are the same across all PCR runs in the same analysis to allow comparison of results.



Export C T values and access free analysis tools

Steps 3 & 4

� Export CT values according to the manual supplied with the real-time PCR instrument

� Access the free miScript miRNA PCR Array Data Analysis Tools� Website: http://sabiosciences.com/mirnaArrayDataAnalysis.php

– Web-based

– Excel-based



miScript miRNA PCR Array Data Analysis Tools

Step 5: Automatic data analysis

� Web-based software� No installation needed� Tailored for each array

� Raw CT values to fold-change results� Using ∆∆CT Method

� Multiple Analysis Formats� Scatter Plot� Volcano Plot� Multi-Group Plot� Clustergram

Downloadable Excel analysis templates are also avai lable



Step 5A

miScript miRNA PCR Array Data Analysis

Website dedicated for array data analysis� http://pcrdataanalysis.sabiosciences.com/mirna

Upload Readout Tab� This tab includes:

� Uploading instructions� Data normalization instructions� Instructions that walk you through the data analysis

(right side of ‘Upload Readout’ Tab – not shown on this image)

� You can also Take a Test Run or Play Movie Guide for help with using the software

� What should you do at this page?1. Choose array catalog number from ‘Catalog

Number’ dropdown menu2. Upload exported CT values from computer3. Click Upload

1. Choose Catalog Number

2. Upload exported C T values

3. Click Upload



Step 5B


Readout Tab �� Basic Setup

� This tab includes:� All miRNAs and controls found on

chosen array� Column where Normalization RNA

(control gene) can be selected� All CT data uploaded to software

� What should you do at this page?1. Click boxes next to desired ‘Control

Genes’ (miScript PCR Controls are pre-selected)

2. Designate columns of CT values as Control, Group 1, Group 2, etc.

3. Click ‘Update All Changes’

1. Choose ‘Control Genes’

2. Designate C T values column groups

3. Click Update All Changes



Step 5C


Readout Tab �� View Housekeeping Genes, Data Overview, & Data QC

� View Housekeeping Genes Tab� Selected ‘Control Genes’ can be

visualized and method of normalization can be chosen

� Data Overview Tab� This tab provides an overview of all

∆∆CT calculations performed by the software

� Data QC Tab� This tab provides an overview of QC

data associated with the miRTC(reverse transcription control) and PPC (positive PCR control)

Readout Tab �� View Housekeeping Genes

Readout Tab �� Data QC

Choose ‘Normalized By’



Step 5D


Analysis Result Tab: this tab provides an overview of all ∆∆CT related calculations and provides a guide for you regarding the trust that you should place in your data (see red arrow)

Comments on data quality



Step 5E


Scatter Plot, Volcano Plot, Clustergram, and Multigroup Plot Tabs: When clicked, these tabs provide various statistical outputs that will open as new windows. The scatter plot is included as an example.

Scatter Plot



Step 5F


Export Data Tab: When clicked, results calculated by the miScript miRNA PCR Array Data Analysis software can be exported to Microsoft Excel.



Serum Sample analysis using the miScript PCR System


44

Workflow: Serum & plasma miRNA expression profiling

1. Collect whole blood and separate serum or plasma

2. Recommended starting amount of serum or plasma: 100–200 µl� Note: If starting with 50 µl (or less) of serum or plasma, incorporate preamplification

3. Isolate RNA: miRNeasy Serum/Plasma Kit + miRNeasy Serum/Plasma Spike-in Control

4. Reverse transcription: Perform miScript II RT reaction (using HiSpec Buffer)� Per intended 384-well plate , reverse transcribe 1.5 µl RNA eluate (1/10th prep)

5. (Optional) Preamplification: If the starting amount of serum or plasma is 50 µl (or less), perform preamplification using the miScript PreAMP PCR Kit

6. Real-time PCR: Profile miRNA expression using chosen miScript miRNA PCR Array� Array recommendations:

– miRNome miScript miRNA PCR Array– Serum & Plasma 384HC miScript miRNA PCR Array– Serum & Plasma miScript miRNA PCR Array



45

Biomarker discovery workflow


Concept

Phase I (determined expressed miRNAs):Pooled sample profiling,

Maximal Assays (miRNome or 384HC)

Phase II (determine differentially expressed miRNAs ):Individual profiling of samples (that went into poo ls),

Only Expressed miRNAs (< 384-well plate)

Phase III (statistical power):Individual profiling of all samples in study,

Differentially Expressed miRNAs from Phase II (multi ple samples per 384-well plate)



Serum & Plasma Samples

Special data analysis case

Serum or plasma total RNA samples: The snoRNA/snRNA panel of targets does not exhibit robust expression and therefore should not be selected as Normalization Controls.

Control Serum Sample 1 Serum Sample 2 Serum Sample 3

SNORD61 36.3 34.3 35.8

SNORD68 34.6 35.0 35.3

SNORD72 35.0 35.0 35.0

SNORD95 31.1 39.3 33.5

SNORD96A 33.6 34.5 35.4

RNU6-2 37.9 39.1 35.0

Typical CT Values for miScript PCR Controls in Serum Samples

� Step 1: Calibrate samples using cel-miR-39 CT mean� Step 2: Normalize serum or plasma sample data

� Option 1: Normalize CT values to CT mean of all commonly expressed miRNAs� Option 2: Normalize CT values to CT mean of invariant miRNAs

Sample & Assay Technologies Anatomy of a miScript miRNA PCR Array


96-well Format: 84 miRNA + 12 controls

Cel-miR-39

miScript PCR Controls for Normalization

miRTC PPCSNORD61; SNORD68; SNORD72 SNORD95; SNORD96A; RNU6-2

RTControl

PCRControl

Spike in Control

84 miRNAs

� Cel-miR-39� Alternative data normalization using exogenously spiked Syn-cel-miR-39 miScript miRNA Mimic

� miScript PCR Controls� Data normalization using the ∆∆CT method of relative quantification

� miRNA reverse-transcription control (miRTC)� Assessment of reverse transcription performance

� Positive PCR control (PPC)� Assessment of PCR performance



Calibrate samples using cel-miR-39 C T mean

Serum or plasma sample data normalization

� Uncalibrated

Assay Sample 1 Sample 2

hsa-miR-16 16.0 19.0

hsa-miR-21 20.0 24.0

hsa-miR-192 23.0 26.0

hsa-miR-103 23.0 23.0

hsa-miR-25 22.0 25.0

cel-miR-39 18.0 21.0

� Compared to sample 1, all assays in sample 2 appear to have delayed CT values� Compared to sample 1, cel-miR-39 in sample 2 also has a delayed CT value� Conclusion: calibrate samples (cel-miR-39 CT values indicate a differential recovery)

� Calibrated (Sample 1 C T values +3)

Assay Sample 1 Sample 2

hsa-miR-16 19.0 19.0

hsa-miR-21 23.0 24.0

hsa-miR-192 26.0 26.0

hsa-miR-103 26.0 23.0

hsa-miR-25 25.0 25.0

cel-miR-39 21.0 21.0



Option 1: C T values normalized to C T mean of expressed miRNAs


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-4

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4

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12

Fold-Regulation

� Calculate the C T mean for commonly expressed miRNAs� Those miRNAs with C T values < 30 (or 32, or 35) in all assessed samples



Option 2: C T values normalized to C T mean of invariant miRNAs


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-4

0

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Fold-Regulation

Commonly Expressed miRNAs

hsa-let-7a hsa-miR-92a

hsa-let-7c hsa-miR-93

hsa-miR-21 hsa-miR-103a

hsa-miR-22 hsa-miR-126

hsa-miR-23a hsa-miR-145

hsa-miR-24 hsa-miR-146a

hsa-miR-25 hsa-miR-191

hsa-miR-26a hsa-miR-222

hsa-miR-26b hsa-miR-423-5p

� Calculate the C T mean for invariant miRNAs� Choose at least 4 to 6 miRNAs that exhibit little C T variation



Comparison of normalization methods


Option 1:Commonly Expressed miRNAs

(miRNome, 384HC)

Option 2:Invariant Panel of miRNAs

(small panel screening)

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Fold-Regulation

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Fold-Regulation

� Note 1: In this example, fold-regulation looks highly similar, irrespective of the chosen normalization method. This is correct, as your results should be independent of the chosen normalization method.

� Note 2: For small panel screening, do not use a CT mean of all miRNAs, as this array is biased (miRNA assays included on this array are not random)



miRNA expression profiling


1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

1.E+01

1.E

-05

1.E

-04

1.E

-03

1.E

-02

1.E

-01

1.E

+0

0

1.E

+0

1

2-∆CT

: Normal Serum2-∆CT: Breast Cancer Serum

miR-34a

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26

30

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miRNA

CT Value

Serum Isolation 1

Serum Isolation 2

Serum Isolation 3

Normal Serum 2 -∆CT: Breast Cancer vs. Normal

� Workflow� 200 µl serum � 50 µl total RNA � 5 µl total RNA, HiSpec Buffer � one-half of cDNA used for 96-well

miFinder miScript miRNA PCR Array

� High reproducibility can be achieved using the miRNeasy Supplementary Protocol � Each isolation was from a different normal serum donor

� Significant differences exist between the mature miRNA expression levels of the two tissue types

� ± 2-fold [red lines] used as a cutoff for significance

Sample & Assay Technologies Where can I find miScript miRNA PCR Arrays?


www.sabiosciences.com/mirna_pcr_array.php

� miRNA Overview

� miScript PCR System

� miScript miRNA PCR Arrays

� Products for functional studies

� miRNA purification options

Sample & Assay Technologies Where can I find miScript Primer Assays?


www.qiagen.com/GeneGlobe

Sample & Assay Technologies QIAGEN’s miRNA portfolio

55

Your miRNA workflow, from sample to results!

miRNeasy Mini Kit, miRNeasy Micro Kit miScript II RT K it and PreAMP Kit HiPerFect Transfection Reagent

miRNeasy 96 Kit miScript SYBR Green PCR Kit Attractene Transfection R eagent

miRNeasy FFPE Kit miScript miRNA PCR Arrays miScript miRNA Mimics

miRNeasy Serum/Plasma Kit miScript miRNA Data Analysi s Tool miScript miRNA Inhibitors

PAXgene Tissue miRNA Kit miScript Primer Assay Custom miScript miRNA Mimics

PAXgene Blood miRNA Kit miScript Precursor Assay miSc ript Target Protector

Supplementary protocol for miRNA from Plasma and Serum

miScript PCR Starter KitmiScript miRNA Inhibitor 96 and 384 Plates and Sets

Pro

filin

g

QIAcube QIAgility Rotor-Gene Q


QIAGEN Service Core

FunctionalizationIsolationQuantification and profiling

Sample & Assay Technologies Upcoming webinars


Experimental Setup and miRNA Profiling webinars

Webinar 3: Profiling miRNA expression: on the road to biomarker development

Date: April 24, 2013, 9:30 am EDT


Sample & Assay Technologies Thank you for attending

57

http://www.sabiosciences.com/promotion/miscriptdemo.php

Technical Support Contact Information

� Monday through Friday

� 8:00AM to 6:00PM EST

� Direct Phone: 888-503-3187

� E-Mail: [email protected]



Thank you for attending today’s webinar!

Jonathan Shaffer, Ph.D.

[email protected] Technologies, R&D Americas

Questions?

mi rna part ii_2013

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