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

7 20 2015 p29ING qPCR

Today I ran more targets that may be of interest due expected changes in expression. Here I explore p29ING which is expected to have increased expression due to exposure to increased temperatures. 

Primers:

1624	p29ING4_FWD	TACCTTTGGGCTTCACCGTC	JH	5/21/2015	20	55		O.lurida	Inhibitor of growth protein 4 (p29ING4)	Q8C0D7
1623	p29ING4_REV	GTCCATCACACACCCCTCAG	JH	5/21/2015	20	55		O.lurida	Inhibitor of growth protein 4 (p29ING4)	Q8C0D7

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 much better than the GRB2. There is some minor amplification in 2 of the 4 NTCs but the product was smaller than the target. The one weird issue is that one sample has a double peak in the melt curve. I'm not sure what caused this as it doesn't appear anywhere else. It may be something odd with the gene being expressed. I then analyzed the data with my stats and graphs script to see what the significant differences are. 

Adjusted Expression Bargraph

Adjusted Statistics

One Way ANOVA comparing Population Controls 

Call:

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

Terms:

                         Pop    Residuals

Sum of Squares  1.026249e-21 2.641735e-21

Deg. of Freedom            2           21

Residual standard error: 1.121592e-11

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  0.1997946

S-H   0.5595058

S-N   0.0263669

Only the Oyster Bay was significantly different from Fidalgo in the control group.The bloxplot represents this very well.  

Adjusted Expression Boxplot

You can see the raw data here. 

7 20 2015 GRB2 qPCR

Today I ran more targets that may be of interest due expected changes in expression. Here I explore GRB2 which is expected to have decreased expression due to exposure to increased temperatures. 

Primers:

1612	GRB2_FWD	AACTTTGTCCACCCAGACGG	JH	5/21/2015	20	55		O.lurida	Growth factor receptor-bound protein 2 (Adapter protein GRB2) (Protein Ash) (SH2/SH3 adapter GRB2)	P62994
1611	GRB2_REV	CCAGTTGCAGTCCACTTCCT	JH	5/21/2015	20	55		O.lurida	Growth factor receptor-bound protein 2 (Adapter protein GRB2) (Protein Ash) (SH2/SH3 adapter GRB2)	P62994

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 curves don't look great. The 3/4 NTCs have amplification with a product that is the same size as the target. This qPCR needs to be re run to see if the data is valid. I went ahead and ran the stats script on the data anyway assuming that the NTCs were accidentally contaminated. 

Adjusted Expression Bargraph

Adjusted Statistics Summary

Two Way ANOVA 

Call:

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

Terms:

                         Pop        Treat    Pop:Treat    Residuals

Sum of Squares  1.209760e-20 4.221308e-19 7.201400e-21 6.405789e-19

Deg. of Freedom            2            1            2           42

Residual standard error: 1.234985e-10

Estimated effects may be unbalanced

  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   0.9388267

S-H  0.8500743

S-N  0.6540849

$Treat

              p adj

T-C  4.5e-06

$`Pop:Treat`

                 diff           lwr           upr     p adj

N:C-H:C  0.9998943

S:C-H:C  0.9793619

H:T-H:C  0.0109104

N:T-H:C  0.0674973

S:T-H:C  0.0093246

S:C-N:C 0.9967000

H:T-N:C  0.0205525

N:T-N:C  0.1139468

S:T-N:C  0.0176867

H:T-S:C  0.0672949

N:T-S:C  0.2845566

S:T-S:C  0.0589259

N:T-H:T   0.9791965

S:T-H:T  0.9999999

S:T-N:T  0.9709791

One Way ANOVA comparing Population Controls

Call:

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

Terms:

                         Pop    Residuals

Sum of Squares  8.045000e-21 6.051431e-19

Deg. of Freedom            2           21

Residual standard error: 1.697538e-10

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  0.9840303

S-H  0.8632357

S-N  0.9358047

One Way ANOVA comparing Population Treatments

Call:

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

Terms:

                         Pop    Residuals

Sum of Squares  1.125392e-20 3.543572e-20

Deg. of Freedom            2           21

Residual standard error: 4.107816e-11

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

               p adj

N-H   0.104549

S-H  0.984109

S-N  0.075302

T-Test for DABOB

Welch Two Sample t-test

data:  expression by Treat

t = 2.9537, df = 7.1, p-value = 0.02095

alternative hypothesis: true difference in means is not equal to 0

95 percent confidence interval:

 4.449457e-11 3.966833e-10

sample estimates:

mean in group C mean in group T 

   2.429139e-10    2.232492e-11 

T-Test for FIDALGO

Welch Two Sample t-test

data:  expression by Treat

t = 2.6905, df = 9.489, p-value = 0.02369

alternative hypothesis: true difference in means is not equal to 0

95 percent confidence interval:

 2.685431e-11 2.971352e-10

sample estimates:

mean in group C mean in group T 

   2.284042e-10    6.640939e-11 

T-Test for Oyster Bay

Welch Two Sample t-test

data:  expression by Treat

t = 3.8083, df = 7.192, p-value = 0.006313

alternative hypothesis: true difference in means is not equal to 0

95 percent confidence interval:

 6.887209e-11 2.913015e-10

sample estimates:

mean in group C mean in group T 

   1.989093e-10    1.882251e-11 

There is a strong difference between the treatment and control. This is apparent in every population. The populations though are not statistically different from one another. You can see this in the boxplot generated from the data. 

You can see the raw data file here.