Data analysis

There are two common methods of analyzing gene expression data generated by real-time PCR; absolute quantification and relative quantification (see also Chapters 2, 3, and 6). For routine gene expression analysis, it is not necessary to know precise copy number and the relative changes in expression will suffice. For example, it is not important that a drug increased the copy of gene x from 10,000 to 50,000 copies per cell, only that the change in expression was increased by five-fold. For this reason, only an example of the relative quantification method will be given here. The most commonly used method for relative quantification is the 2-AACt method. Derivation and examples of this method have been described elsewhere (Livak et al., 2001).

Calculate the relative difference in gene expression using the 2-AACt method.

Relative fold change in gene expression = 2-AACt

Where: AACt = ACt treated - ACt untreated and ACt = (Ct target gene — Ct reference gene)

Refer to section on critical steps

38. The reference gene should be properly validated. Selection of the reference or internal control gene is critical as the expression of the reference gene will often fluctuate with treatment or disease. While the user is welcome to try commonly used internal controls (e.g. P-Actin, GAPDH, or P-2 microglobulin), in our experience, highly expressed, non-protein coding genes, such as 18S rRNA or U6 RNA, have performed the most consistently for most applications. Primer sequences have been

log cDNA dilution

Figure 7.2

An example of the plot used in amplification efficiency calculation.

log cDNA dilution

Figure 7.2

An example of the plot used in amplification efficiency calculation.

published for 18S rRNA (Schmittgen et al., 2000) and U6 RNA (Schmittgen et al., 2004). It may be the best strategy to use multiple reference genes as described elsewhere in this book (Chapters 4, 6, and 8).

Refer to section on critical steps

39. Determine the amplification efficiency of the reaction for both the target and reference genes (Figure 7.2 and see below). The 2-AACt method assumes that the amplification efficiency for both the target and reference genes is similar (Livak et al., 2001).

Calculation of fold-change in gene expression

40. Export the raw Ct values from the real-time PCR analysis into Microsoft Excel®. Assign sample number, gene name and treatment to each data set.

41. Sort the data such that it groups the sample number (in triplicate), treatment and gene. Calculate the mean Ct value for the internal control gene.

42. Enter the mean Ct for the internal control into one column of the spreadsheet and write a macro to calculate the 2-AACt. A sample spreadsheet is presented (Figure 7.3).

43. Calculate the mean fold change, standard deviation and coefficient of variation for the triplicate PCRs for each sample. Acceptable coefficient of variation for triplicate PCRs from the identical sample of dilute cDNA is 2-30%.

Refer to section on troubleshooting

Sample #

Well

Type

Gene

Time (h)

Primer/Probe

CT Time X

2

Mean Fold Change in gene expression S.D.

C.V.

1

A1

UNKN

fos-

glo-myc

0

PR1

22.3

21.9

1.023

2

B1

UNKN

fos-

glo-myc

0

PR1

22.0

21.9

0.786

-► 1.02 0.228

22.4

3

C1

UNKN

fos-

glo-myc

0

PR1

21.5

21.9

1.243

4

D1

UNKN

fos-

glo-myc

0.5

PR1

19.8

21.9

1.845

5

E1

UNKN

fos-

glo-myc

0.5

PR1

20.2

21.9

2.019

2.00 0.152

7.61

6

F1

UNKN

fos-

glo-myc

0.5

PR1

20.0

21.9

2.149—►!

2A-((20.0-21.7)-(21.9-22.5))

7

G1

UNKN

fos-

glo-myc

1

PR1

19.5

21.9

2.271

8

H1

UNKN

fos-

glo-myc

1

PR1

18.9

21.9

3.466

2.86 0.598

20.9

9

A2

UNKN

fos-

glo-myc

1

PR1

19.2

21.9

2.855

A5

UNKN

Beta Actin

0

PR2

22.9

1

22.5

2

B5

UNKN

Beta Actin

0

PR2

22.3

22.5

3

C5

UNKN

Beta Actin

0

PR2

22.4

22.5

4

D5

UNKN

Beta Actin

0.5

PR2

21.2

22.5

5

E5

UNKN

Beta Actin

0.5

PR2

21.7

22.5

6

F5

UNKN

Beta Actin

0.5

PR2

21.7

22.5

7

G5

UNKN

Beta Actin

1

PR2

21.2

22.5

8

H5

UNKN

Beta Actin

1

PR2

21.2

22.5

9

A6

UNKN

Beta Actin

1

PR2

21.3

22.5

A sample spreadsheet showing the calculation of relative quantification by the 2-AAct method. (Reproduced by permission of Elsevier.)

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