7 22 2015 HSPb11 qPCR 2

Today I ran duplicates for the targets I ran last week. I'm hoping to get strong replicates for analysis. Here I ran the HSPb11 which last week had issues with the NTC. 

Primers:

1650	Hspb11_FWD	ATGTTTCCTGGTCTCCGTCA	JH	5/21/2015	20	55		O.lurida	Heat shock protein beta-11 (Hspb11) (Placental protein 25) (PP25)	Q9Y547
1649	Hspb11_REV	CATCAACGCCAGGGGAACTT	JH	5/21/2015	20	55		O.lurida	Heat shock protein beta-11 (Hspb11) (Placental protein 25) (PP25)	Q9Y547

Reagent Table:

	Volume	Reactions X116
Ssofast Evagreen MM	10	1160
FWD Primer	0.5	58
REV Primer	0.5	58
1:9 cDNA	9

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:

Step	Temperature	Time
Initiation	95 C	10 min
Elongation	95 C	30 sec
	60 C	1 min
Read
	72 C	30 sec
Read
Repeat Elongation 39 times
Termination	95 C	1 min
	55 C	1 sec
Melt Curve Manual ramp 0.2C per sec Read 0.5 C	55 - 95 C	30 sec
	21 C	10 min
End

Plate Layout:

1	2	3	4	5	6	7
DNased 42215 HC1	DNased 42215 NC1	DNased 42215 SC1	DNased 42215 HT1 1	DNased 42215 NT1 1	DNased 42215 ST1 1	NTC
DNased 42215 HC2	DNased 42215 NC2	DNased 42215 SC2	DNased 42215 HT1 2	DNased 42215 NT1 2	DNased 42215 ST1 2	NTC
DNased 42215 HC3	DNased 42215 NC3	DNased 42215 SC3	DNased 42215 HT1 3	DNased 42215 NT1 3	DNased 42215 ST1 3	NTC
DNased 42215 HC4	DNased 42215 NC4	DNased 42215 SC4	DNased 42215 HT1 4	DNased 42215 NT1 4	DNased 42215 ST1 4	NTC
DNased 42215 HC5	DNased 42215 NC5	DNased 42215 SC5	DNased 42215 HT1 5	DNased 42215 NT1 5	DNased 42215 ST1 5
DNased 42215 HC6	DNased 42215 NC6	DNased 42215 SC6	DNased 42215 HT1 6	DNased 42215 NT1 6	DNased 42215 ST1 6
DNased 42215 HC7	DNased 42215 NC7	DNased 42215 SC7	DNased 42215 HT1 7	DNased 42215 NT1 7	DNased 42215 ST1 7
DNased 42215 HC8	DNased 42215 NC8	DNased 42215 SC8	DNased 42215 HT1 8	DNased 42215 NT1 8	DNased 42215 ST1 8

Results:

All samples

Amp

Melt

NTCs

Amp

Melt

The amplification and melt curves look good. There's no amplification in the NTCs. To analyze this data I ran it through a script to do stats and make some graphs. 

Expression Bar Graph

Statistics

Call:

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

Terms:

                         Pop        Treat    Pop:Treat    Residuals

Sum of Squares  1.913763e-14 3.460040e-15 6.197430e-15 2.482985e-13

Deg. of Freedom            2            1            2           42

Residual standard error: 7.688868e-08

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

              p adj

N-H  0.6743300

S-H  0.1825199

S-N  0.6131938

$Treat

               p adj

T-C  0.4485315

$`Pop:Treat`

                   p adj

N:C-H:C   0.9968662

S:C-H:C   0.4617887

H:T-H:C  0.9999847

N:T-H:C   0.9924229

S:T-H:C   0.9930620

S:C-N:C   0.7546118

H:T-N:C  0.9879773

N:T-N:C   0.9999986

S:T-N:C   0.9999992

H:T-S:C  0.3687373

N:T-S:C  0.8077927

S:T-S:C  0.8022228

N:T-H:T   0.9771056

S:T-H:T   0.9785530

S:T-N:T  1.0000000

The Stats show there are no significant differences between the treatment or controls or populations which can be seen in the expression graphs and boxplot. 

This like the BMP2 data shows there are huge differences in the stats between the reps. I re ran the previous data without removing the outliers to see how it changes the data. 

Expression Bargraph

Statistics

Call:

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

Terms:

                         Pop        Treat    Pop:Treat    Residuals

Sum of Squares  3.811151e-19 2.405560e-20 3.873500e-21 1.510927e-18

Deg. of Freedom            2            1            2           42

Residual standard error: 1.896693e-10

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

                p adj

N-H   0.0145606

S-H   0.9658692

S-N  0.0273635

$Treat

               p adj

T-C  0.418125

$`Pop:Treat`

                    p adj

N:C-H:C   0.4354280

S:C-H:C   0.9999831

H:T-H:C  0.9888451

N:T-H:C   0.5629155

S:T-H:C  0.9980358

S:C-N:C  0.5358964

H:T-N:C  0.1506397

N:T-N:C  0.9999464

S:T-N:C  0.2184309

H:T-S:C  0.9688693

N:T-S:C   0.6656163

S:T-S:C  0.9911381

N:T-H:T   0.2232571

S:T-H:T   0.9999602

S:T-N:T  0.3113530

Even with the outliers the expression changes enough that stats still show there being a significant difference between the oyster bay population and the other two sites. This can be seen with the boxplot below. 

For comparison sake I pulled out the Ct values from qpcR for both the CFX and Opticon data to compare to the Ct values generated by the Opticon and CFX programs. Below are some line graphs produced from the Ct data. 

All

CFX/CFXqpcR

Opticon/OptiqpcR

Opticon/CFX

OptiqpcR/CFXqpcR

You can see that the Opticon and OptiqpcR values don't match. The qpcR values are somewhat deflated compared to the Opticon ct values. The CFX and CFXqpcR data looks much closer with only some small differences between the read outs. 

It looks like the qpcR package doesn't handle the raw fluorescence data from the Opticon as well as it does with the CFX data. This suggests that the CFX may be the better machine. 

Sadly this doesn't fix the issue between the reps as the BMP2 data was run on the same machine. I'm unsure what to do at this point. 

You can see the raw data for the qPCR runs last week here and this week here. You can also see the Ct value comparison CSV here. 

7 22 2015 BMP2 qPCR 2

Today I ran duplicates for the targets I ran last week. I'm hoping to get strong replicates for analysis. Here I ran the BMP2 which last week had issues with the NTC. 

Primers:

1640	BMP-2_FWD	TGAAGGAACGACCAAAGCCA	JH	5/21/2015	20	55		O.lurida	Bone morphogenetic protein 2 (BMP-2) (Bone morphogenetic protein 2A) (BMP-2A)	P12643
1639	BMP-2_REV	TCCGGTTGAAGAACCTCGTG	JH	5/21/2015	20	55		O.lurida	Bone morphogenetic protein 2 (BMP-2) (Bone morphogenetic protein 2A) (BMP-2A)	P12643

Reagent Table:

	Volume	Reactions X116
Ssofast Evagreen MM	10	1160
FWD Primer	0.5	58
REV Primer	0.5	58
1:9 cDNA	9

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:

Step	Temperature	Time
Initiation	95 C	10 min
Elongation	95 C	30 sec
	60 C	1 min
Read
	72 C	30 sec
Read
Repeat Elongation 39 times
Termination	95 C	1 min
	55 C	1 sec
Melt Curve Manual ramp 0.2C per sec Read 0.5 C	55 - 95 C	30 sec
	21 C	10 min
End

Plate Layout:

1	2	3	4	5	6	7
DNased 42215 HC1	DNased 42215 NC1	DNased 42215 SC1	DNased 42215 HT1 1	DNased 42215 NT1 1	DNased 42215 ST1 1	NTC
DNased 42215 HC2	DNased 42215 NC2	DNased 42215 SC2	DNased 42215 HT1 2	DNased 42215 NT1 2	DNased 42215 ST1 2	NTC
DNased 42215 HC3	DNased 42215 NC3	DNased 42215 SC3	DNased 42215 HT1 3	DNased 42215 NT1 3	DNased 42215 ST1 3	NTC
DNased 42215 HC4	DNased 42215 NC4	DNased 42215 SC4	DNased 42215 HT1 4	DNased 42215 NT1 4	DNased 42215 ST1 4	NTC
DNased 42215 HC5	DNased 42215 NC5	DNased 42215 SC5	DNased 42215 HT1 5	DNased 42215 NT1 5	DNased 42215 ST1 5
DNased 42215 HC6	DNased 42215 NC6	DNased 42215 SC6	DNased 42215 HT1 6	DNased 42215 NT1 6	DNased 42215 ST1 6
DNased 42215 HC7	DNased 42215 NC7	DNased 42215 SC7	DNased 42215 HT1 7	DNased 42215 NT1 7	DNased 42215 ST1 7
DNased 42215 HC8	DNased 42215 NC8	DNased 42215 SC8	DNased 42215 HT1 8	DNased 42215 NT1 8	DNased 42215 ST1 8

Results:

All samples

NTCs

These amplification curves look better than the last run of BMP2. There is some minor amplification in the NTCs but it is larger than the target and is probably an artifact of the PCR process. To analyze these data I ran them through an updated stats and graphs script which runs a Two Way ANOVA and produces a boxplot and expression bar graph. The data did not have its outliers eliminated which worked fine with this as most samples showed some expression. 

Expression Bar Graph

Statistics

Call:

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

Terms:

                         Pop        Treat    Pop:Treat    Residuals

Sum of Squares  1.703293e-20 3.032145e-20 2.201442e-20 6.077281e-20

Deg. of Freedom            2            1            2           42

Residual standard error: 3.803908e-11

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  0.4089519

S-H  0.0041846

S-N  0.1002050

$Treat

             diff           lwr           upr    p adj

T-C  4.14e-05

$`Pop:Treat`

                 diff           lwr           upr     p adj

N:C-H:C   0.6348257

S:C-H:C   0.0001275

H:T-H:C  0.9973637

N:T-H:C  0.9999701

S:T-H:C  0.9814628

S:C-N:C   0.0134535

H:T-N:C  0.3564950

N:T-N:C  0.5192134

S:T-N:C  0.2393859

H:T-S:C  0.0000292

N:T-S:C  0.0000710

S:T-S:C  0.0000133

N:T-H:T   0.9997768

S:T-H:T  0.9998827

S:T-N:T  0.9953619

There definitely appears a significant difference between treatment and control. From the stats it appears the Oyster Bay population control has significantly larger expression of BMP2 than the other two populations as well as it the Oyster Bay treatment. You can see this in the bar graph generated below.

The most distressing thing about these data is that it doesn't match the graphs from last week. The controls have much lower expression than they did last week which should not have changed between replicates. I reran the previous data with all the outliers but it still doesn't change the statistics. 

Previous Expression Data

Previous Data Stats

Call:

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

Terms:

                         Pop        Treat    Pop:Treat    Residuals

Sum of Squares  3.918260e-22 9.723005e-21 1.573763e-21 9.279358e-21

Deg. of Freedom            2            1            2           38

Residual standard error: 1.56267e-11

Estimated effects may be unbalanced

4 observations deleted due to missingness

> TukeyHSD(fit)

  Tukey multiple comparisons of means

    95% family-wise confidence level

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

$Pop

                 p adj

N-H   0.4224591

S-H   0.8174685

S-N  0.8189700

$Treat

         p adj

T-C  2e-07

$`Pop:Treat`

                    p adj

N:C-H:C   0.6961640

S:C-H:C  0.9298189

H:T-H:C  0.0032438

N:T-H:C  0.0048368

S:T-H:C  0.2481527

S:C-N:C  0.1806352

H:T-N:C  0.0000405

N:T-N:C  0.0000732

S:T-N:C  0.0140727

H:T-S:C  0.0411016

N:T-S:C  0.0532668

S:T-S:C  0.7297433

N:T-H:T   1.0000000

S:T-H:T   0.7788719

S:T-N:T   0.7991437

The stats don't match which is distressing. Even the boxplots dont seem to match. 

You can see the raw data files for this week here and last week here. 

7 21 2015 Target Gene Functions

Today in an effort to better understand what each of my targets may be contributing due to differences in expression, I made up a short list of the genes. I included the full name, general function of the protein, and proteins they make work in concert with. This will help with analysis down the road.

TARGET FUNCTIONS

GABABR

What: Gamma-aminobutyric acid receptor

Function: Receptors receive signals that could be related to signals needed for immediate actions such as closing the shell or moving in response to stimuli

PGE/EP4

What: Prostaglandin E receptor 4 (EP4)

Function: Receptor for Prostaglandin E2 which suppresses inflammation due to injury

HSPb11

What: Heat Shock Protein beta-11

Function: Small Heat Shock Protein also used during gonad development

BMP2

What: Bone Morphogenic Protein 2

Function: Directs calcification in shell creation

PGRP

What: Peptidoglycan recognition protein

Function: Recognition of bacteria in an immune response

Works with: TNFa, HSP70

HSP70

What: Heat Shock Protein 70kDa

Function: Molecular chaperone and protein preservation in heat response

Works with: PGRP

H2A

What: Histone 2A

Function: One of 5 main Histone Proteins involved in the structure of chromatin and the open reading frame of DNA

Works with: H3.3, H2A.V

H2A.V

What: Histone 2A.V

Function: One of 5 main Histone Proteins involved in the structure of chromatin and the open reading frame of DNA

Works with: H2A, H3.3

H3.3

What: Histone 3.3

Function: One of 5 main Histone Proteins involved in the structure of chromatin and the open reading frame of DNA

Works with: H2A, H2A.V

TLR

What: Toll-like Receptor 2

Function: Recognize foreign pathogens and endogenous materials for consumption by phagocytes in early stages of inflammation.

Works with: TNFa

Actin

What: Actin

Function: Globular protein that forms microfilaments

CRAF

What: Tumor Necrosis Factor receptor-associated factor 3

Function: Related to immune response specifically cell death initiation

Works with: NFkBINA

CARM

What: Coactivator-associated arginine methyltransferase 1

Function: Transfers methyl groups to H3 and H4 to change how DNA is bound up in Chromatin

Works with: H3.3, H2A.V, H2A

GRB2

What: Growth factor receptor-bound protein 2

Function: Signal Transduction/Cell Communication

p29ING

What: Inhibitor of growth protein 4

Function: Inhibits cell growth and induces apoptosis