The following is a comprehensive strategy for qPCR that works and is practically, mathematically and statistically accurate. It conforms to the MIQE guidelines, which should be reported in all qPCR experiments (Bustin et al, 2009). Recommendations on primer Tm, statistical outputs and graphical representations etc may differ from previous work or practices.

The following assumes work in prokaryotes with no splicing.

Primer Design

Design primers to your target(s) and at least two reference genes.

Reference genes:

- You will need to find multiple reference genes to normalize expression to.

- These need to be stable across all the conditions (control and experimental) and this needs to be empirically determined by your own testing (see later).

- Candidate genes might come from:

o Previous publications

o Previous experience

o Microarray compendiums; variance in expression can be determined for individual genes from thousands of samples across multiple conditions (e.g. Faith et al, 2009 Nucleic Acids Research, 2008, Vol. 36).

Design process:

- Go to http://www.idtdna.com/primerquest/home/index, enter your sequence and select ‘two primers, intercalating dye’.

- Click on ‘customize your assay’. Up the optimal Tm to 63 and the minimum Tm to 60.

- Increase the optimal amplicon length to 120bp.

- Click ‘get assays’ and find a primer pair that closely matches the above conditions and for which both the primer Tms are equal. Click ‘view assay details’. Hovering over the primer sequence will give you options to check secondary structure and BLAST for off target transcripts. Do this.

- Order your favorite primer pair.

RNA preparation

Prepare RNA as detailed elsewhere on the Wiki, ensuring that you include on column DNase digestion. NOTE: column digestion of DNA is not always 100% complete. If you find DNA contamination in your RNA samples (see later), you need to complete DNase treatment using DNase 1 and use a column to clean up the RNA from the reaction mix.

Reverse Transcription

- Use the high capacity reverse transcription kit from ABI.

Per sample:

RNA

500ng – 1ug

H2O

Up to 14.2ul

10x buffer

2ul

dNTPS

0.8ul

Random primers

2ul

RTase

1ul

Conditions:

25°C 10’

37°C 120’

85°C 5’

Store cDNA at -20°C, or for longer durations, -80°C

qPCR

There are two approaches to qPCR, the most efficient and cost effective will depend on what you are trying to do. If you are designing an assay for a transcript that you think you will use over and over again, use method 2. If you are looking tyo answer one very specific question, use method 1.

In either case, you will load each well with the following:

Both primers are in included in the total volume here (i.e. 0.25ul each).

The cDNA is diluted (see below).

It makes a lot of sense to get used to loading a 5ul rxn if you are going to use a lot of biological replicates, as you can load this small volume onto 384 well plates. It is very cost and time effective to do so and it takes only a few plates to get accurate readings across technical replicates.

Method 1

PCR #1

GOALS:

- Test that primers work

- Verify single products via a melt curve analysis

- Determine approximate Ct (cycle threshold) of PCR amplification

- Test RNA for gDNA contamination

Typical plate setup for single reference gene and single target (you must test all candidate reference genes):

Primer concentration is the final concentration in the rxn.

The cDNA used for this is a pool of all your experimental samples.

The RNA sample used is a pool of your RNA samples, diluted to the same extent as the 1:25 cDNA dilution (i.e. dilute 500ng of your pooled RNA 1:25).

What you are looking for:

- PCR products that produce a single peak in your melt curve analysis

- a dilution of cDNA that produces Ct values of between 13-30 cycles (If your Cts are less than or greater than this, the assay can still work, but depending on machine, standard deviations can get a bit noisy if amplification happens too early or late.)

- No contamination in RNA, or contamination that is >10 cycles later than the signal in your experimental sample.

-- Main.SimonDAlton - 06 Feb 2017

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Contributors to this topic Edit topic KateElston, SimonDAlton, JuliePerreau, DanielDeatherage
Topic revision: r1 - 2017-02-06 - 22:34:27 - Main.SimonDAlton
 
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