I'm editing the qPCR section, did anyone do a 50ul reaction? If so for what genes? (That's what it says right now, but I know I did a 25ul reaction...) It's an easy fix so we can change it at 730.-
You're welcome to do it. I agree with you that it would look better, but I think it's a bit late to ask anyone to make big changes.
I think the paper would look a lot better is we all formatted our graphs the same... Or is it too late to even bother? -
I can meet too ----Lauren
I can meet too, PF
Is the building open that early? I can be there at 7:30. Brianna I'm finishing up my slides right now, I should have them to you soon! -
Hey guys, would you be up for meeting like an hour before class to make sure we sort out the logistics of our presentation (who goes in what order, etc.). What do you think? -Josh
7:30!?! - ugh, that's early. I'm in though. The order is pretty much worked out by the order of the slides (as done in the outline below), but it would still be good to meet and rehearse.
It's fine with me too. Let me know what we decide. -
PowerPoint presentation in google docs: https://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0Bx0ep7zxsFejMzkzMmZmNDktZTUxNy00ZWFkLWJjNWUtYTVhZmFmMWZhM2Nk&hl=en
Broken link?
Chris, I went to room 242 a little while ago and it was empty. I don't know if I'm doing the ANOVA right, I'm in the FSH computer lab right now so if you see this can you come take a look? Otherwise I guess we'll figure it out at 5!-
Josh - jkm28@u.washington.edu
Chris - monson.chris@gmail.com
Erica's email is ericaj2@u.washington.edu
Peggy's email is pforeman20@yahoo.com
Mine is lcolpo@u.washington.edu
Yes, the final paper is due Wednesday. My email is mwudma@uw.edu
Lauren and Model: can you post your email addresses so we can collaborate on who is doing what in the introduction. Mine is bblaud@gmail.com
Also, I inserted some of the paragraphs that I consolidated/deleted for the draft that we submitted. I forget if the paper is due Wednesday when we present. Does anyone know?
-
Statistics: We need to decide on the way we're going to look at our data. We talked about this a little yesterday, but didn't come to a real conclusion. I still think the most appropriate measure we can use for our expression data is comparing it to the control level. This means dividing your gene expression data by the normalizer expression data and then finding the group average of the normalized data. To find the fold change over the control, you would then divide each group mean by the control group mean (ie control mean / control mean = 1.0, treatment mean / control mean = something other than 1.0). This would basically set the axis at 1 and allow you to look at up-regulation or down-regulation of your gene relative to control levels. Once you have the average fold change from control for each group average, you can again divide each normalized expression value by the average normalized control expression value to find a fold change from the average control for each data point individually. You can then use this set to find standard deviations within each group (or standard error) to add as error bars to your graph. For statistical analysis, you can still use the normalized expression value data in an ANOVA with a post hoc Tukey test. To do this in SPSS, copy your normalized expression value data set into the SECOND column of the SPSS spreadsheet and fill in the first column with 1's for the 1st group and 2's for the 2nd group etc (rows 1-8 should all be 1's in the first column), so that you have each data point in the 2nd column and the group number in the 1st column. From here you go to analyze - compare means - one-way ANOVA. you can also do a posy-hoc Tukey test to determine which groups are significant from each other. -
I will be in Monday around 3 in FTR 242 if anyone needs help with stats. Just come get me and we can go over to the SAfS computer lab. -
Is anyone else having problems copying from the google spreadsheet and pasting into Excel/SPSS? Any tips? Thanks! -
We'll be in Collaboration Studio 3. I have already reserved it for us. -
Meeting @ 5pm, Monday in Odegard, 2nd floor
Presentation Outline:
I. Introduction
A. Pesticide vs. salmon - Lauren, Model, Brianna
a. how pesticides effects salmon
b. pesticide/disease interaction
- what is known/ not known
c. the difference between immune genes and stress genes
d. the purpose of our project
B. Methods - Erica, Peggy
a1. experimental design
a2. quantified RNA
b. normalized (diluted) RNA
c. qPCR on RNA (test for contamination)
d. DNase
e. qPCR on GOI
C. Results
i. What your gene is, what it does
ii. What the results of qPCR were - graphs
a. lfab - Chris
b. SAA - Peggy
c. CYP 1A -
d. COX 2 - Erica
e. CRH - Model
f. Vtg - Brianna
g. IL 12 - Josh
h. SOD - Lauren
D. Discussion- Josh, Chris
a. Discussion of the results for genes - what it means
b. Future projects
E. Literature Cited, Acknowledgments
I messed up! I'm so sorry guys, I guess we're meeting at 12. Same place. see you then!
- I have class from 10:30 - 11:20 ....so I'll be a half hour late. see you there though!-
We are going to meet around 11am at the grad student computer lab to analyze our results tomorrow.
Normalizing gene (Elongation Factor) PCR is done and data exported-
I have put a sign-up for last qPCRs on the message board. Please sign-up ASAP -
The google doc link is https://docs.google.com/document/d/1t9OWnI_GmumzIE4VN_fc3-ff1g-wkkLF7E21giC2zHU/edit?hl=en&authkey=CIKXgsUO
The google spreadsheet link is https://spreadsheets4.google.com/ccc?key=tZBs24Z-6lxd6ZUtwMeDaFg&hl=en&authkey=CNij6u4J#gid=0
I read an earlier post that says "Please look over the outline in the google doc and add anything you think is missing (especially to the introduction!). Also, please sign up for a section, and write about your gene of interest in the results."
Can somone post this link? Thanks -
Is my computer doing funny things? I swear the formating on this wikipage is totally messed up. I can't get to the google doc anymore? PF Here is a paragraph from my proposal for the intro:
Introduction
The Puget Sound watershed consists for thousands of rivers and streams, which make up an extensive migration corridor and juvenile rearing area for anadromous salmonids, including several stocks that are listed as endangered, threatened, and species of concern under the Endangered Species Act (http://www.nwr.noaa.gov/ESA-Salmon-Listings/). The health and physiological condition of salmon is of concern as these waterways are contaminated with heavy metals, pesticides (herbicides, insecticides, fungicides, or rodenticides) and persistent pollutants (USGS, 1999). Sublethal exposures to chemicals like pesticides may impact behaviors such as homing, growth, immune response, foraging, or even predator awareness or avoidance that might impact survival. Studies have shown that juvenile salmon passing through polluted waters may suffer indirect effects (Macneale et al. 2010), however the direct effect of pesticides on immune response, increased susceptibility to disease, and impaired growth remains unstudied in coho salmon. Chemical exposures have reduced growth in juvenile Chinook salmon (Baldwin, 2009), which could be critical to survival. Some contaminants are immunotoxic, disrupting the critical role of the immune system in maintaining health. Adverse effects can be either immunosuppressive, which decreases resistance to infection or enhancement, which can cause autoimmune diseases or allergies. ….LPS (I have a paper that speaks of SAA in regards to LPS, but haven’t found how LPS is present in urban streams, how it is acquired, how it is transferred…)
Understanding how salmonids respond to xenobiotics at a cellular level and determining the mechanisms of detoxification are complex. Looking at biomarkers that influence immune and stress responses, reproductive parameters will determine which genes are being expressed.
Literature Review
Macneale, K.H., P.M. Kiffney, and N.L. Scholz. 2010. Pesticides, aquatic food webs, and the conservation of Pacific salmon. Frontiers in Ecology and the Environment 8: 475–482.
Baldwin, D.H., J.A. Spromberg, T.K. Collier, and N.L. Scholz. 2009. A fish of many scales: extrapolating sublethal pesticide exposures to the productivity of wild salmon populations. Ecological Applications 19: 2004–2015.
12/3 - The results for the CRH qPCR are ready and we can look at the raw data on Monday.-
Please look over the outline in the google doc and add anything you think is missing (especially to the introduction!). Also, please sign up for a section, and write about your gene of interest in the results.
12/2 - I added a sheet to the google spreadsheet for our sample qPCR data. It is arranged by sample ID number (by row) and gene of interest C(t) value replicates in the columns. As you get your data, please add to the spreadsheet so we can do the analysis as a group.-
12/2/2010 - Something came up and I can't make it into lab to help people with setting up their qPCR. -
should I not come in then as planned tomorrow morning----or are you accounting for our convo? -
Unless you have already signed-up, the qPCR thermocyler is full for this week. -
Also, we will be scaling down our qPCR reactions to a volume of 25ul. That is:
For a 25μl reaction volume:
| Component |
Volume |
Final Conc. |
| Master Mix, 2X (Immomix) |
12.5µL |
1x |
| Syto-13 dye (50uM) |
1µL |
2µM |
| upstream primer, 10μM |
1.25μl |
2.5μM |
| downstream primer, 10μM |
1.25μl |
2.5μM |
| Ultra Pure Water |
7uL |
NA |
1 DEC 2010
Sign up for a gene! These genes were amplified in our primer test, please choose one and write a date/time you plan to come set up and run a qPCR plate. cDNA samples to be used: 49-80
GENE.................... NAME ...................DATE................... TIME
Cyp1a....................Brianna....................12/6.....................12:00
IL12......................Josh.................12/7
Cox2.....................Erica........................12/9......................5:00pm
LFabp....................Chris....................... 12/1.....................2:00
CRH......................Model.......................12/3.....................9:30
SOD----------------------lauren------------------------
VTG.......................Brianna....................12/1.....................12:00
SAA.......................Peggy......................12/2.....................12:00
TNF alpha
Normalizer ..............Chris........................12/6......................2:00
30 NOV 2010
Remaining samples were reverse transcribed following RT protocol described below.
All samples that were previously RT'd were normalized for the amount of RNA used in the standard RT reaction. The normal amount used according to the protocol was 1ug RNA/25ul reaction. Several samples deviated from this based on RNA concentration and volume used and are noted in the spreadsheet. These were normalized in diluting cDNA to the same initial total RNA used for total cDNA volume. normal samples were diluted by a factor of 1:10, to compensate for lower total RNA amounts used in some samples, dilution factors varied from the norm.
All primer pairs were reconstituted at 100uM and diluted to working stocks of 10uM. Each primer was run in a standard qPCR reaction, as described below, using mixed cDNA samples.
Results: pending.-
__
How many reverse transcriptions reactions do you still need to do and aprox how many qPCR reactions (including primer tests) do you need to do? -
11/29 RNA samples (26, 27, 30, 33, 36, 43, 55, 74, 101, 107, 110) were DNased as below and were spec'd on the nanodrop. Updated concentrations are on the google spreadsheet, as are the volumes of each sample to be added to RT reaction (under columns: amount to add for 1ug and amount of water up to 15ul). All new samples are ready to RT tomorrow - 11/30.-
Peggy, I can't come in until after 11:30 or so tomorrow... I hope you look at this and don't come at 9!!!-
Your primers are in large white envelope labeled "salmon group" in the lab. I have put you guys down for the qPCR thermocycler this afternoon. -
11/22/10 We have more samples! Apparently there was another box in the -80C freezer that we weren't give, so we now have an additional 33 samples to fill in all the missing ones. Peggy and I did RNA quantification on the nanodrop, normalized them, and set them up for qPCR. When we get the qPCR results tomorrow, we will DNase the samples that need it and reverse transcribe all the remaining samples while we test the primers on qPCR. A lot of people are leaving to go out of town on Wednesday, so we were thinking of beginning to run qPCR on our samples (with our designed primers) starting next Monday. We could set up a schedule and determine if we have enough time to run all of our samples on all of our primers, or if we should just do a subsample.-
Update: so someone is running samples on the qPCR right now, so the samples will be done in 4 hours rather than just 2.
Your primers will be in Tuesday morning. Let me know when you want to test them and then I will sign up for the qPCR machine. -
19 NOV 2010
reverse transcription of remaining samples.
samples 75-92, 111-112, DNAsed samples: 11, 25, 28, 32, 41, 42, 45, 58, 59, 61, 76, 77
1ug (5ul of 200ng/ul) of each sample was used in the standard RT rxn described below, in samples of 200ng/ul or higher concentration.
DNased samples were normalized to 1ug RNA per RT reaction where able by substituting additional RNA volume for total H2O volume in the reaction.
see google spreadsheet. edited for cDNA dilutions in last column.
Monday or Tuesday, cDNA will need to be diluted by adding the volume (H2O) of the last column to each sample, highlighted samples deviate from the norm. Sample 77 will have to be trashed. [normal samples: 1000ng of RNA used per reaction, diluted to 250ul total = 4ng RNA used per 1ul cDNA; highlighted samples diluted by same factor, 4ng RNA used in reaction to 1ul total cDNA output.]
-
11.18.10 -
I went over the instructions that Briannia, Peggy, and I discussed with Steven. We came up with the following workflow so that you should not have to make a second batch of normalized RNA:
1. Check that you have at least 5 ul of your normalized RNA left. (i.e. spin down your sample and try to suck up 5ul with your pipet).
2. If YES, then DNase the samples Brianna has listed below using the manufacture's protocol and the rigorous treatment.
If, NO then you need to make more normalized RNA first.
3. Reverese transcribe all of your samples including the ones you just DNased.
DNase protocol
dilute high concentration samples to 200ng/ul.
add 3ul 10x TURBO Buffer
add 1ul TURBO DNase enzyme
add 30ul RNA sample (diluted to 200ng/ul)
incubate at 37C for 30 min
add additional 1ul TURBO DNase enzyme
incubate additional 30 min at 37C
add 3ul DNase inactivation reagent and mix well
incubate at RT for 5 min, mixing occasionally
spin down and transfer supernatant to 1.5ml tube
centrifuge supernatant at 10,000rpm for 1.5 min
spec with nano drop
REVERSE TRANSCRIPTION PROTOCOL
Mix your NORMALIZED RNA sample by inverting tube several times.
In a 0.5 ml labeled PCR tube combine the following:
5 μl of NORMALIZED RNA
0.5 μl of oligo dT
4.5 μl of nuclease free H20
Incubate the mixture for 5 min at 70C on the thermocycler then immediately transfer to ice. Briefly centrifuge you tube and the add the following:
5 μl of M-MLV 5X Reaction Buffer
5 ul of dNTPs
1 μl of M-MLV RT
4 μl of nuclease free H20
Incubate the mixture for 60 min at 42C and then heat inactivate at 70C for 3 min on the thermocycler.
Spin down the sample in a desk top centrifuge.
Store on ice or at -20C
4. After reverse transcription, dilute you cDNA by adding your entire volume of cDNA to 225 ul of nuclease free water in a clean and labeled 1.5 ml snap cap centrifuge tube.
Your samples should now be ready for PCR.
Reverse transcription was done on samples1-74, and 93-104, with the exception of the samples that were being DNased. Samples 1-47 and 93-104 all received an extra ul of M-MLV 5X Reaction buffer due to confusion of the labels between the buffer and M-MLV RT. The total quantities for those samples are as follows:
5 μl of NORMALIZED RNA
0.5 μl of oligo dT
4.5 μl of nuclease free H2O
6 μl of M-MLV 5X Reaction Buffer
5 ul of dNTPs
1 μl of M-MLV RT
4 μl of nuclease free H2O
Samples 75-92, 111-112 and the samples that were DNased will be reverse transcribed on 11.19.10 after lecture. - ericaj2
11/17/10
We created a folder in the Roberts Lab on the special computer, but I will post the Ct values in a new spreadsheet in Google Docs I added a column showing C(t) values to the existing spreadsheet. We analyzed all of our samples and found that only 12 need to be DNased:
11, 25, 28, 32, 41, 42, 45, 58, 59, 61, 76, 77. The next step: tomorrow in lab, we need to DNase only those twelve. We also need to normalize more RNA. The amount we have left after running the qPCR test (9.5uL) is only enough RNA for 20uL of cDNA, and we will need approximately 72uL of cDNA to run all fourteen of our primers (14 primers x 2 for replicates x 2.5 for 2uL of cDNA used in qPCR (0.5 extra in case of error) = 72 uL). We should also reverse transcribe five or so samples to test the primers when they arrive. Then, when the qPCR is running for the primer test, we could reverse transcribe the remaining samples.
We also need to weigh in on how many samples we feel comfortable doing. We could break down the samples and just run the 24 hour group, or something else. I talked to some co-workers, and you will not have to make a new set of new noramilzed DNA as long as you have at least 5ul of RNA. Will dilute the cDNA after reversea transcription to make sure there is enough volume for all of your qPCR reactions. -
To Summup:
DNase: 11/18
Normalize: 11/18
Reverse Transcribe (5 samples): 11/18
Primer test qPCR: 11/22 or 11/23?
Reverse transcribe remaining samples: 11/22 or 11/23?
Also, Peggy and I may be late tomorrow. Caroline showed us that the reagents needed for reverse transcription are on the top shelf of the fridge in lab. Someone (probably Sam) will be there to open the door at 1pm. -
Link to download qPCR analysis software. Windows only. -
Here is the link to the DNase protocol. I recommend following the regerious treatment. -
Your primers have been ordered -
11/15/10
Peggy and I just finished up quantifying all of the RNA samples. There are 79 samples total, and a couple of those will be excluded due to the small RNA sample, but overall the results are great. We have a lot of RNA to work with. I tried to upload the spreadsheet with the results into a google spreadsheet, but am having problems, so I'll keep working on that. We have the opportunity to decrease the amount of samples we're working with by choosing to focus on only one area. For example, we could just look at the samples collected 48 hours after injection, and not the 24 hour ones. I would like to process all the samples, because that will give us the opportunity to have more results to work with down the line when we have to put separate presentations together, but that is just my opinion. What do you guys think?
We should also set up a tentative schedule for what needs to be done, and who would like to be involved with which steps:
Measure RNA - completed 11/15 (Peggy, Brianna)
Make dilutions - 11/16
Run qPCR on RNA - 11/16, discuss results 11/17 after class
DNase (if necessary) - 11/18 @ 1PM, meet in lab
Reverse Transcription- 11/18?
qPCR
If I'm missing something, please let me know. The dilutions need to be made before anything else can be done with the RNA. I will add a column on the spreadsheet doing the math on how much RNA is added to water to create a volume we agree upon. The total volume depends on the amount of primers we will be running. Because the RNA amounts were so high, I don't think they will be a limiting factor, but we could still decide together which primers we would like to run once we get them. Caroline is ordering the ones from the spreadsheet today, and Chris is picking up other "house keeping" primers, so we have plenty of options. Once we decide on the amount of primers to run (and also have some to run qPCR on RNA), we will get the total volume of RNA we will need for the project, and can make our dilutions. We want a concentration of 5ug/uL, and will use the equation (C1)(V1)=(C2)(V2) where C1 is our sample, C2 is 5ug/uL, V1 is the volume of RNA we will use to make the dilution, and V2 is the total volume needed.
(1-2ug of RNA is generally used in a reverse transcriptase reaction and the total volume in the reaction is adjusted by adding water. Our protocol called for 5 ul sample + 8ul H2O, meaning we have 13ul volume to work with to get a total of 2ug RNA) if that makes sense. So we would need a minimum of around 50ng/ul per sample, preferably 400ng/ul to get through the first step in the Rt rxn.-
I misspoke earlier when I informed Peggy and Briannia that they needed 25ug for reverse transcription. It is 1-2 ug. You will not be able normalize some of the lower concentration samples. So I recommend noting this and then diluting the rest of your samples to something like 200ng/ul. This will mean that 5ul of RNA added to the reverse transcription reaction will conation 1 ug of RNA. -
I will follow up with the google spreadsheet soon... -
Google Doc spreadsheet: https://spreadsheets4.google.com/ccc?key=tZBs24Z-6lxd6ZUtwMeDaFg&hl=en&authkey=CNij6u4J#gid=0
We can still run the DNA contamination test with the RNA samples, prior to dilution them. Since the RT reaction (making cDNA) will do nothing to the DNA that's potentially in the sample, the test qPCR with RNA template will simply be a volume or RNA template issue. We can load a plate tomorrow on Tuesday 11/16 with our prior protocol's dilution factor for the original sample RNA template, and our answer will be the same as if we calculated a dilution factor for each sample. The prior protocol called for 5ul RNA template in the 25ul RT rxn and 2ul of that in the 50ul qPCR rxn. Doing the calculations (I think) we would need 0.4ul RNA template per qPCR reaction. Since the concentration will undoubtedly change if we need to do a DNase, it makes sense to run the contamination control PCR prior to diluting anything. -
The dilutions still need to done before the RNA can be tested for carry-over DNA. This is because we are only interested in DNA carry-over if it is above the detection limit in our final qPCR (i.e. that horizontal line that our measured fluorescence crosses in the qPCR plots).
We need to dilute the RNA as if we were preparing it for reverse transcription and the subsequent qPCR. So after normalizing (to 200 ng/ul), you need to dilute 1 ul of your RNA in 4 ul of water (this mimics the dilution of our RNA that occurs when we set up our reverse transcription reaction). Then set up a qPCR as in lab 5 and using this 5 ul as if it were cDNA. -
If we do find contamination, we will need to DNase the samples, likely further reducing the concentration. Some of the samples do not have large volumes, we will not necessarily be able to dilute them to 200ng/ul, and then find we need to DNAse them and have a high enough concentration and volume to carry out RT reactions. I still think we are better off running the contamination control qPCR prior to diluting the RNA. If contamination shows up, we will have the highest concentration and largest volume to DNase. Diluting first will give a better idea of what our actual carryover will be, but it is not crucial that this be exact. Carryover will be carryover, whether or not we dilute if first, and will amplify millionsfold anyway in the PCR reaction. It is crucial that we have the highest concentration and volume possible in the off chance that we need to DNase everything. There are many samples that we can definitely get away with diluting right now, and preferably aliquoting as well, but again, this test is just a preliminary test and it's quite a bit of a risk to dilute samples prior to DNasing. -
I'm done with class at 11:50 on Tues, so I can start on the dilutions and maybe qPCR around noon tomorrow if anyone wants to join! What days are we planning on doing the other steps? Wed after class and Thurs after noon is good for me. -
11/13/10
We discussed some people working in the lab on Monday to measure how much RNA we have in the samples. Some other people could meet Monday as well and run qPCR on the samples to determine if they are contaminated. It would also be helpful to sit down and decide on a specific project plan. If we could meet after class on Monday, we could hash out a lot of these details and get ready for the next steps in the project. If meeting after class doesn't work for people, let me know and we could set up another time to meet.
Hi salmon group, let me know me know what you decide about Monday and I will reserve the qPCR machine for you as well as get you set up in lab. -
I set up a google doc https://docs.google.com/document/d/1t9OWnI_GmumzIE4VN_fc3-ff1g-wkkLF7E21giC2zHU/edit?hl=en&authkey=CIKXgsUO -
NOTE: I suggest running a qPCR on RNA (diluted to proper amount based on what would be in cDNA) and doing a quick qPCR before going to trouble of DNAsing. -
see Caroline if you need help with this.
Gene sets to analyze:
Immune response
Stress response
normalizers/internal controls
What do we want to say?
Option 1: Is the acute immune response compromised in pesticide exposed fish? use un-dosed mock injected vs un-dosed injected with un-dosed/uninjected control
What are the immune response genes doing in relation to controls?
differences between bacterial and viral simulated infection
Option 2: Is the stress response compromised from chronic exposure to pesticide? use non-dosed non-injected vs dosed/non-injected
What are the stress response genes doing?
difference between dosed and non-dosed
time point differences (recovery?)
Option 3: Does chronic pesticide exposure during development predispose fish to infection?
need both immune response genes and stress response genes
differences between inj/uninj, dosed/non-dosed, dosed + inj vs dose (for each LPS and PolyIC)
Probably need 10-15 genes per pathway (immune response viral, immune response bacterial, stress response)
For all, need normalizers (ie GAPDH, Beta-actin, Liver fatty acid binding protein (liver tissue control) and need cell death control (ie p21, caspase 3).
These are the references to the papers from where I got the primers:
http://www.sciencedirect.com.offcampus.lib.washington.edu/science?_ob=MImg&_imagekey=B6WFN-4TVJNK0-1-4&_cdi=6799&_user=582538&_pii=S1050464808002349&_origin=search&_coverDate=02%2F28%2F2009&_sk=999739997&view=c&wchp=dGLzVtb-zSkzV&md5=44879c9afb47fd804a28bb6fd1cb49b3&ie=/sdarticle.pdf Djordjevic, B. S. Skugor, S.M Jorgensen, M. Overland, L.T. Mydland, and A. Krasnov. 2009. Modulation sf splenic immune responses to bacterial lipopolysaccharide in rainbow trout (Onchorhynchus mykiss) fed lentinan, a beta-glucan from mushroom Lentinula edodes. Fish and Shellfish Immunology 26: 201-209
http://ajpregu.physiology.org.offcampus.lib.washington.edu/cgi/reprint/299/2/R486 Palstra, A.P., D. Crespo, G. van den Thillart, and J.V. Planas. 2010. Saving energy to fuel exercise: swimming suppresses oocyte development and downtregulates ovarian transcriptomic response of rainbow trout. Am J Physiol Regul Integr Comp Physiol 299: R486-R499.-
RNA Samples are in my Lab's -80 Freezer on bottom shelf. -
PRIMERS: Please provide the required info for your primers using this spreadsheet. You can order up to 14 pairs of primers. When you have decided as a group to order a pair of primers type YES into the column "ready to order?". -
It would be great to see a project plan posted on this wiki as well as updates on what you are working on. -
SAMPLE INFO
