Monday, July 20, 2015

7 17 2015 GABABR qPCR

Today I ran more targets that may be of interest due expected changes in expression. Here I explore GABABR which is expected to have decreased expression due to exposure to increased temperatures. 

Primers:

1620GABABR1_FWDCCGAGGAGGACACGAAACTCJH5/21/20152055O.luridaGamma-aminobutyric acid type B receptor subunit 1 (GABA-B receptor 1) (GABA-B-R1) (GABA-BR1) (GABABR1) (Gb1)Q9WV18
1619GABABR1_REVCGGACAGGTTCTGGATTCCGJH5/21/20152055O.luridaGamma-aminobutyric acid type B receptor subunit 1 (GABA-B receptor 1) (GABA-B-R1) (GABA-BR1) (GABABR1) (Gb1)Q9WV18

Reagent Table:
VolumeReactions X116
Ssofast Evagreen MM101160
FWD Primer0.558
REV Primer0.558
1:9 cDNA9
  1. Added reagents from greatest to least volume
  2. Vortexed
  3. Centrifuged briefly
  4. Pipetted 11 ul Master Mix to each tube
  5. Pipetted 9 ul of 1:9 cDNA each column using a channel pipetter
  6. Centrifuged plate at 2000 rpm for 1 minute
  7. Ran Program Below
Program:
StepTemperatureTime
Initiation95 C10 min
Elongation95 C30 sec
60 C1 min
Read
72 C30 sec
Read
Repeat Elongation 39 times
Termination95 C1 min
55 C1 sec
Melt Curve Manual ramp 0.2C per sec Read 0.5 C55 - 95 C30 sec
21 C10 min
End
Plate Layout:
1234567
DNased 42215 HC1DNased 42215 NC1DNased 42215 SC1DNased 42215 HT1 1DNased 42215 NT1 1DNased 42215 ST1 1NTC
DNased 42215 HC2DNased 42215 NC2DNased 42215 SC2DNased 42215 HT1 2DNased 42215 NT1 2DNased 42215 ST1 2NTC
DNased 42215 HC3DNased 42215 NC3DNased 42215 SC3DNased 42215 HT1 3DNased 42215 NT1 3DNased 42215 ST1 3NTC
DNased 42215 HC4DNased 42215 NC4DNased 42215 SC4DNased 42215 HT1 4DNased 42215 NT1 4DNased 42215 ST1 4NTC
DNased 42215 HC5DNased 42215 NC5DNased 42215 SC5DNased 42215 HT1 5DNased 42215 NT1 5DNased 42215 ST1 5
DNased 42215 HC6DNased 42215 NC6DNased 42215 SC6DNased 42215 HT1 6DNased 42215 NT1 6DNased 42215 ST1 6
DNased 42215 HC7DNased 42215 NC7DNased 42215 SC7DNased 42215 HT1 7DNased 42215 NT1 7DNased 42215 ST1 7
DNased 42215 HC8DNased 42215 NC8DNased 42215 SC8DNased 42215 HT1 8DNased 42215 NT1 8DNased 42215 ST1 8
Results:

All samples
NTCs

The amplification curves look great in this one. There is no amplification in the NTCs which is perfect. To better analyse the data I ran the raw fluorescence through my script to produce adjusted expression bar graph, Two Way ANOVA, One Way ANOVA, Tukey's Test, and T-Test. 

Adjusted Expression Graph

TWO WAY ANOVA with Tukey's TEST

Call:
   aov(formula = expression ~ Pop + Treat + Pop:Treat, data = rep2res2)

Terms:
                         Pop        Treat    Pop:Treat    Residuals
Sum of Squares  5.831470e-24 4.605870e-23 1.717210e-24 1.500405e-22
Deg. of Freedom            2            1            2           22

Residual standard error: 2.611517e-12
Estimated effects may be unbalanced
> TukeyHSD(fit)
  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = expression ~ Pop + Treat + Pop:Treat, data = rep2res2)

$Pop
             diff           lwr          upr     p adj
N-H  2.366774e-13 -2.711956e-12 3.185311e-12 0.9778584
S-H -8.557194e-13 -4.043450e-12 2.332011e-12 0.7806364
S-N -1.092397e-12 -4.140705e-12 1.955911e-12 0.6458397

$Treat
            diff           lwr           upr     p adj
T-C -2.51348e-12 -4.581732e-12 -4.452286e-13 0.0194822

$`Pop:Treat`
                 diff           lwr          upr     p adj
N:C-H:C  5.477504e-13 -4.597423e-12 5.692924e-12 0.9993875
S:C-H:C -8.619841e-13 -7.668409e-12 5.944440e-12 0.9985849
H:T-H:C -2.942336e-12 -8.399616e-12 2.514944e-12 0.5583572
N:T-H:C -2.420009e-12 -7.346137e-12 2.506119e-12 0.6494947
S:T-H:C -2.597238e-12 -7.523366e-12 2.328891e-12 0.5810595
S:C-N:C -1.409734e-12 -8.216159e-12 5.396690e-12 0.9860417
H:T-N:C -3.490086e-12 -8.947367e-12 1.967194e-12 0.3777506
N:T-N:C -2.967759e-12 -7.893888e-12 1.958369e-12 0.4412795
S:T-N:C -3.144988e-12 -8.071116e-12 1.781140e-12 0.3795617
H:T-S:C -2.080352e-12 -9.125670e-12 4.964967e-12 0.9371575
N:T-S:C -1.558025e-12 -8.200415e-12 5.084365e-12 0.9758792
S:T-S:C -1.735254e-12 -8.377644e-12 4.907137e-12 0.9618634
N:T-H:T  5.223269e-13 -4.728944e-12 5.773597e-12 0.9995598
S:T-H:T  3.450983e-13 -4.906172e-12 5.596369e-12 0.9999425
S:T-N:T -1.772287e-13 -4.874108e-12 4.519650e-12 0.9999963


ONE WAY ANOVA comparing POPULATIONS CONTROL

> fit2<-aov(expression~Pop, data=rep2res2[Treat=="C"])
> fit2
Call:
   aov(formula = expression ~ Pop, data = rep2res2[Treat == "C"])

Terms:
                        Pop   Residuals
Sum of Squares  2.90037e-24 1.41338e-22
Deg. of Freedom           2           9

Residual standard error: 3.962855e-12
Estimated effects may be unbalanced
> TukeyHSD(fit2)
  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = expression ~ Pop, data = rep2res2[Treat == "C"])

$Pop
             diff           lwr          upr     p adj
N-H  5.477504e-13 -6.449936e-12 7.545437e-12 0.9740886
S-H -8.619841e-13 -1.011905e-11 8.395085e-12 0.9635753
S-N -1.409734e-12 -1.066680e-11 7.847334e-12 0.9061601


ONE WAY ANOVA comparing POPULATIONS TREATMENT

> fit3<-aov(expression~Pop, data=rep2res2[Treat=="T"])
> fit3
Call:
   aov(formula = expression ~ Pop, data = rep2res2[Treat == "T"])

Terms:
                         Pop    Residuals
Sum of Squares  6.585500e-25 8.702475e-24
Deg. of Freedom            2           13

Residual standard error: 8.181816e-13
Estimated effects may be unbalanced
> TukeyHSD(fit3)
  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = expression ~ Pop, data = rep2res2[Treat == "T"])

$Pop
             diff           lwr          upr     p adj
N-H  5.223269e-13 -8.721776e-13 1.916831e-12 0.5963155
S-H  3.450983e-13 -1.049406e-12 1.739603e-12 0.7937301
S-N -1.772287e-13 -1.424511e-12 1.070054e-12 0.9257775


T-TEST FOR DABOB
> fit4<-t.test(expression~Treat, data=rep2res2[Pop=="H"])
> fit4

Welch Two Sample t-test

data:  expression by Treat
t = 1.3399, df = 4.024, p-value = 0.2509
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -3.140394e-12  9.025065e-12
sample estimates:
mean in group C mean in group T 
   3.618621e-12    6.762853e-13 


T-TEST FOR FIDALGO

> fit5<-t.test(expression~Treat, data=rep2res2[Pop=="N"])
> fit5

Welch Two Sample t-test

data:  expression by Treat
t = 1.8959, df = 4.684, p-value = 0.1204
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -1.139381e-12  7.074900e-12
sample estimates:
mean in group C mean in group T 
   4.166372e-12    1.198612e-12 


T-TEST FOR OYSTER BAY
> fit6<-t.test(expression~Treat, data=rep2res2[Pop=="S"])
> fit6

Welch Two Sample t-test

data:  expression by Treat
t = 5.4509, df = 5.775, p-value = 0.001794
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 9.488834e-13 2.521624e-12
sample estimates:
mean in group C mean in group T 
   2.756637e-12    1.021384e-12 

The stats show there are no differences between populations but that there is a significant difference between the treatment and control. The T-TESTs show that this difference lies in the Oyster Bay Population which is different between treatment and control. This is apparent when looking at the boxplot. Though looking at the data set it appears that its only based on an n of 5 which severely limits the strength of this data. 


You can see the raw data set here. 

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