简单五步学会使用∆∆Cq法(∆∆Ct法)计算实时定量PCR(qPCR)基因表达差异
2014-06-24 16:14阅读：
用一个简单的例子，旨在演示某种处理(treatment)下某基因(TAR)的mRNA水平变化（为了简化，假设这次实验每组6个样，即生物重复，没有使用技术重复，并假定其内参基因(REF)稳定，不再涉及内参的可靠性等问题）
即只简单演示∆∆Cq法如何计算倍数改变。
主要分为如下五步：
第一步：经非参基因进行归一化(Normalize to REF):
∆Cq=Cq(TAR)-Cq(REF)
第二步：转化为指数表达(Exponential expression
transform)：∆Cq
Expression=2-∆Cq
第三步：组内样品指数表达的平均值与标准差(Average replicates and
calculate standard deviation)
第四步：以对照组为参照进行归一化(Normalize to treatment
control)
第五步：变化的百分比[%change=(1-
∆∆Cq)*100]
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
T
|
J
|
Groups
|
Cq FER
|
Cq TAR
|
∆Cq
|
∆Cq
Expression
|
Mean ∆Cq
Expression
|
∆Cq Expression Std.
Dev.
|
∆∆Cq
Expression
|
∆∆Cq Expression Std.
Dev.
|
%
change
|
|
|
|
=CqTAR-CqREF
|
=2^-Δ∆Cq
|
Average Replicates
|
Std. Dev.
Replicates
|
Normalized to mean in
control
|
Normalized to mean in
control
|
=(1-
∆∆Cq)*100
|
Treatment
|
20.6
|
27.6
|
7.0
|
0.0078
|
0.0215
|
0.0133
|
0.0639
|
0.0395
|
93.61
|
|
20.8
|
27.3
|
6.5
|
0.0110
|
|
|
|
|
|
|
20.9
|
27.6
|
6.7
|
0.0096
|
|
|
|
|
|
|
20.7
|
25.6
|
4.9
|
0.0335
|
|
|
|
|
|
|
20.6
|
25.4
|
4.8
|
0.0359
|
|
|
|
|
|
|
20.6
|
25.6
|
5.0
|
0.0313
|
|
|
|
|
|
Control
|
20.5
|
22.2
|
1.7
|
0.3078
|
0.3369
|
0.0707
|
1.0000
|
0.2098
|
|
|
21.2
|
22.5
|
1.3
|
0.4061
|
|
|
|
|
|
|
21.0
|
22.5
|
1.5
|
0.3536
|
|
|
|
|
|
|
21.2
|
22.5
|
1.3
|
0.4061
|
|
|
|
|
|
|
21.0
|
22.6
|
1.6
|
0.3299
|
|
|
|
|
|
|
21.2
|
23.4
|
2.2
|
0.2176
|
|
|
|
|
|
各栏目的含义如下：
Column A: 分组
Column B:
参考基因的Cq值(Cq value for
REF)
Column C:
靶基因的Cq值(Cq value for
TAR)
Column D: 归一化到相应参考基因的表达(Normalize
Cq values for all TAR samples to the REF gene of its corresponding
sample, ∆Cq)
Column E:
指数转化，该方法的前体是100%的扩增效率(Exponentially
transform ∆Cq to
∆Cq Expression for each biological replicate; 2
raised to the -∆Cq yields
∆Cq Expression. 100% qPCR amplification
efficiency for all reactions, or a doubling of amplicon with each
subsequent qPCR cycle.
Column F: 指数转化值的组内均值(Mean of
∆Cq Expression replicates.)
Column G: 指数转化值的组内标准差(Standard
deviation of the mean for ∆Cq Expression
replicates.)
Column H:
与对照组归一化处理，获得∆∆Cq表达值(Normalize
the TAR Mean ∆Cq Expression to that of
the Control to obtain ∆∆Cq
Expression.)
Column I:
∆∆Cq表达值的标准差(To find
the standard deviation of ∆∆Cq
Expression, divide the standard deviation of the targeted sample’s
Mean ∆Cq Expression by that of the
Control sample.)
Column J: 处理所致变化的百分比(Percent change
is calculated by subtracting the normalized
∆∆Cq Expression from 1 (defined by the level of
expression for untreated sample) and multiplying by
100.)
参考文献
Livak, K. J.; Schmittgen, T. D. Analysis of relative gene
expression data using real-time quantitative PCR and the 2(-Delta
Delta C(T)) method. Methods 2001, 25,
402–408.
Thermo. Demonstration of a ∆∆Cq
calculation method to compute thermo scientific relative gene
expression from qPCR data
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