Yaamini’s Notebook: Larval Mortality Analysis

Do I have a story for my larval data?

The short version: Maybe not

The long version:

I’m preparing to write up my submission for the Journal of Shellfish Research’s Special Issue on Ocean Acidification. My paper will follow the general outline of the talk I gave at NSA 2018, so at least the difficult, conceptual thinking part is done! The only thing I have left is to figure out if it’s worth adding my larval data to the story. To do this, Steven suggested I first plot all of my data with error bars. I decided to go back a step and plot my data without error bars first. Calculating all of the standard deviations and manually adding error bars is annoying, and if there’s already a lot of overlap between my data points, I can get a good understanding for whether or not their mortality rates were different. Cue the R graphics

When analyzing my Day 0 count data, I saw a significant maternal effect from the pregametogenic pH treatment. The goal with these graphs is to see if the carryover effect persists into larval survival. In my R script, I visualized all of my data from the four different parental pH treatment families (i.e. everything besides the heat shock data). I plotted all of the data together, as well as the data from each family separately.

I know what you’re thinking. The axis labels and points are too small, the y-axis label is cutoff, and the colors aren’t high contrast enough. I was too lazy to adjust these aspects of my plots if I wasn’t sure if they would be used later on. Lazy, but efficient…?

all-dataFigure 1. All larval count data over the course of the experiment. The big takeaway here is that all of the colors are overlapping.

FLML

FLMAFigures 2-3. Larval count data from families with females exposed to low pH conditions. Males were exposed to either low pH (top) or ambient pH (bottom).

FAML

FAMAFigures 4-5. Larval count data from families with females exposed to ambient pH conditions. Males were exposed to either low pH (top) or ambient pH (bottom).

It may be useful to create a multipanel plot to look at the families side by side. I’ll see if this is necessary. There is evidence of human error when counting larvae (how did I count more larvae than I started with?!), but it seems to be day-dependent as opposed to treatment-dependent. It doesn’t look like there’s any significant difference in survival between treatments, which could also be an interesting point. While we saw a carryover effect when counting larval output, that same effect may not persist into larval survival. Sometimes a null result is still a cool result.

My next step is to channel my inner Mac and write the methods and results section of my paper (or, at least get a Google Doc and paper repository started first). I’ll include this section and if I or others feel it is not relevant, I’ll eliminate it.

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Sam’s Notebook:FastQC/MultiQC – Illumina HiSeq Genome Sequencing Data

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Since running SparseAssembler seems to be working and actually able to produce assemblies, I’ve decided I’ll try to beef up the geoduck genome assembly with the rest of our existing genomic sequencing data.

Yesterday, I transferred our BGI geoduck data to our Mox node and ran it through FASTQC

I transferred our Illumina HiSeq data sets (*NMP*.fastq.gz) to our Mox node (/gscratch/scrubbed/samwhite/illumina_geoduck_hiseq). These were part of the Illumina-sponsored sequencing project.

I verified the MD5 checksums (not documented) and then ran FASTQC, followed by MultiQC.

FastQC slurm script: 20180328_fastqc_illumina_geoduck_hiseq_slurm.sh

This was followed with MultiQC (locally, after copying the the FastQC output to Owl).

Results:

FASTQC output: 20180328_illumina_hiseq_geoduck_fastqc

MultiQC output: 20180328_illumina_hiseq_geoduck_fastqc/multiqc_data

MultiQC HTML report: 20180328_illumina_hiseq_geoduck_fastqc/multiqc_data/multiqc_report.html

Well, lots of fails. I high level of “Per Base N Content” (these are only warnings, but we also haven’t received data with these warnings before). Also, they all fail in the “Overrepresented sequences” analysis.

I’ll run these through TrimGalore! (probably twice), and see how things change.

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Sam’s Notebook:FastQC/MultiQC – BGI Geoduck Genome Sequencing Data

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Since running SparseAssembler seems to be working and actually able to produce assemblies, I’ve decided I’ll try to beef up the geoduck genome assembly with the rest of our existing genomic sequencing data.

I transferred our BGI geoduck FASTQ files to our Mox node (/gscratch/scrubbed/samwhite/bgi_geoduck/).

I ran FASTQC on them to actually check them out and see if they needed any trimming, as I don’t believe this has been done!

FASTQC slurm script: 20180327_fastqc_bgi_geoduck_slurm.sh

Side note: Initial FASTQC failed on one file. Turns out, it got corrupted during transfer! Serves as good reminder about the importance of verifying MD5 checksums after file transfer, prior to attempting to work with files!

This was followed up with MultiQC (run locally from my computer on the files hosted on Owl). This was performed the following day (20180328).

Results:

FASTQC output: 20180327_bgi_fastqc

MultiQC output: 20180328_bgi_multiqc

MultiQC HTML report: 20180328_bgi_multiqc/multiqc_report.html

Everything looks nice and clean! Waiting on transfer and FASTQC of Illumina NMP data before proceeding to next assembly attempt.

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Grace’s Notebook: Updates

RNA Isolation

So yesterday was a success. However, I have used up essentially all of the 2-propanol, which means that today there is not enough for me to do another batch of 9…

I ordered more and hopefully they’ll come really soon!

Pam has been here in lab the past several days performing qPCR on crab hemolymph from the project to determine the infection status of the samples. Many of the samples that were supposedly negative, are coming up as positive for Hematodinium infection. She is still working and the results of her qPCR will likely change my work on RNA isolation in terms of picking samples for pooling. To be continued…

DIA 2015 oysterseed

I’m still stuck on the error rate portion… at lab meeting today, Steven said the crab project is priority, so I will focus on that.

DecaPod

Pam and I were going to try to record a new episode (episode 1) today to explain the background of the project and why we’re doing it, but she’s a bit too busy with qPCR. So, we’re aiming for setting some time aside next week after our crab meeting on Thursday.

I am considering just recording a short episode tonight or tomorrow just giving an update on what I’m doing with the hemolymph and explaing what RNA isolation is and why I’m doing it.

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Sam’s Notebook:Data Recived – Crassostrea virginica MBD BS-seq from ZymoResearch

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Received the sequencing data from ZymoResearch for the <em>Crassostrea virginica</em> gonad MBD DNA that was sent to them on 20180207 for bisulfite conversion, library construction, and sequencing.

Gzipped FASTQ files were:

  1. downloaded to Owl/nightingales/C_virginica
  2. MD5 checksums verified
  3. MD5 checksums appended to the checksums.md5 file
  4. readme.md file updated
  5. Updated nightingales Google Sheet

Here’s the list of files received:

 zr2096_10_s1_R1.fastq.gz zr2096_10_s1_R2.fastq.gz zr2096_1_s1_R1.fastq.gz zr2096_1_s1_R2.fastq.gz zr2096_2_s1_R1.fastq.gz zr2096_2_s1_R2.fastq.gz zr2096_3_s1_R1.fastq.gz zr2096_3_s1_R2.fastq.gz zr2096_4_s1_R1.fastq.gz zr2096_4_s1_R2.fastq.gz zr2096_5_s1_R1.fastq.gz zr2096_5_s1_R2.fastq.gz zr2096_6_s1_R1.fastq.gz zr2096_6_s1_R2.fastq.gz zr2096_7_s1_R1.fastq.gz zr2096_7_s1_R2.fastq.gz zr2096_8_s1_R1.fastq.gz zr2096_8_s1_R2.fastq.gz zr2096_9_s1_R1.fastq.gz zr2096_9_s1_R2.fastq.gz 

Here’s the sample processing history:

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Laura’s Notebook: Oly gonad & larvae RNA isolation

Gonad RNA isolation:

Olympia oyster gonad samples were fixed in PAXgene tissue fixative/stabilizer in April, 2017, directly after removing them from pH treatments (~7.2, ~7.8 for 8wks; prior to the pH treatments animals had been in temperature treatments, 6C & 10C for 8wks). Sam previously extracted RNA from 12 of my gonad samples, 6 of which were from the South Sound F1 groups. Today, I extracted (most of) the remaining South Sound gonad samples.

First, I used a razor blade to dig tissue out of the paraffin blocks, using the corresponding slides to identify and target only gonad area for my tissue sections.

For RNA extraction, I used the same kit – PAXgene fixed tissue RNA kit, following the instructions for for tissue in histology blocks. I followed the kit procedure, with the following alterations:

  • To homogenize: Added 1 spoonful of glass beads (autoclaved) to each sample, and vortexed for ~45 minutes on the vortexer speed 9 with the foam tube holder attachment. At minute ~25, moved samples from the inside ring to the outside ring.
  • Max centrifuge speed for steps 4, 7 & 12 = 13rpm
  • Max centrifuge speed for steps 22-24 = 15rpm
  • Final elution volumes: 1st elution of 20ul, 2nd with 30ul, for total volume ~48-50ul (kit says I will lose ~2ul to the column).
  • I began extracting 30 samples, but then found that I only had 26 columns, so I terminated 4 samples, one from each treatment.
  • Sample #23: I ran out of the DNase + Buffer mixture for this final sample at step 18, I only had ~1/4 of the required mix. Because I had no more volumes of DNase left, but noticed a few small droplets on the walls of a DNase tube, I added 20ul of buffer to the DNase tube, flicked to mix, then centrifuged for 2 seconds and added that (~20-ish ul) to sample 26.

Quantified RNA using the Qubit RNA assay with Qubit 3.0 Fluorometer. Used 2.0ul of each sample for quantification. Approximate RNA (ng) is calculated using concentration (ng/ul) in 46ul.

RNA Sample # Sample # pH Tissue Type Sample date Extraction Date RNA Concentration (ng/ul) Approximate ng RNA (in ~46ul) Notes
1 SN-6-16 Low Fixed Gonad 4/8/17 3/27/18 17.5 805
2 SN-6-17 Low Fixed Gonad 4/8/17 3/27/18 84 3864
3 SN-6-18 Low Fixed Gonad 4/8/17 3/27/18 43.9 2019.4
x SN-6-19 Low Fixed Gonad 4/8/17 Did not fully extract (ran out of columns)
5 SN-6-20 Low Fixed Gonad 4/8/17 3/27/18 33.2 1527.2
6 SN-6-21 Low Fixed Gonad 4/8/17 3/27/18 8.94 411.24
7 SN-6-22 Low Fixed Gonad 4/8/17 3/27/18 56 2576
8 SN-6-23 Low Fixed Gonad 4/8/17 3/27/18 18.3 841.8
9 SN-6-24 Low Fixed Gonad 4/8/17 3/27/18 24.2 1113.2
10 SN-6-25 Ambient Fixed Gonad 4/8/17 3/27/18 76 3496
11 SN-6-26 Ambient Fixed Gonad 4/8/17 3/27/18 51 2346
12 SN-6-27 Ambient Fixed Gonad 4/8/17 3/27/18 7.08 325.68
13 SN-6-28 Ambient Fixed Gonad 4/8/17 3/27/18 34.6 1591.6
14 SN-6-29 Ambient Fixed Gonad 4/8/17 3/27/18 49.6 2281.6
15 SN-6-30 Ambient Fixed Gonad 4/8/17 3/27/18 57 2622
x SN-6-31 Ambient Fixed Gonad 4/8/17 Did not fully extract (ran out of columns)
17 SN-6-32 Ambient Fixed Gonad 4/8/17 3/27/18 19.6 901.6
18 SN-6-33 Ambient Fixed Gonad 4/8/17 3/27/18 18.3 841.8
19 SN-10-18 Low Fixed Gonad 4/8/17 3/27/18 63 2898
20 SN-10-19 Low Fixed Gonad 4/8/17 3/27/18 11.3 519.8
21 SN-10-21 Low Fixed Gonad 4/8/17 3/27/18 46.5 2139
22 SN-10-22 Low Fixed Gonad 4/8/17 Did not fully extract (ran out of columns)
23 SN-10-23 Low Fixed Gonad 4/8/17 3/27/18 28.6 1315.6
24 SN-10-24 Low Fixed Gonad 4/8/17 3/27/18 47 2162
SN-10-25 Ambient Fixed Gonad 4/8/17 7/?/2017 Did not do – already sent to Katherine
SN-10-26 Ambient Fixed Gonad 4/8/17 7/?/2017 Did not do – already sent to Katherine
27 SN-10-27 Ambient Fixed Gonad 4/8/17 3/27/18 35.4 1628.4
28 SN-10-28 Ambient Fixed Gonad 4/8/17 3/27/18 83 3818
29 SN-10-29 Ambient Fixed Gonad 4/8/17 3/27/18 69 3174
SN-10-30 Ambient Fixed Gonad 4/8/17 Did not fully extract (ran out of columns)
SN-10-31 Ambient Fixed Gonad 4/8/17 7/?/2017 Did not do – already sent to Katherine
32 SN-10-32 Ambient Fixed Gonad 4/8/17 3/27/18 Out of range – too high #VALUE!
33 SN-10-33 Ambient Fixed Gonad 4/8/17 3/27/18 47.6 2189.6

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Grace’s Notebook: Rna Isolation And Qubit Results So Successful

RNA Isolation

Today I tested out the revised RNA isolation protocol (link: here). It adds a lot more centrifuging steps, which I think really helped.

I worked on a set of 9 (uninfected, ambient) from my previously selected samples: img

Today’s Qubit results (tubes 55 (day 9) and 469 (day 26)) were AWESOME!!!! I used 5µL of sample, as per usual, but the results were good for both even though I was unsure during the isolation protocol because I had a hard time avoiding the RNAzol when I was pipetting because it was in the middle of the tubes. img

The RNAzol is a salty substance, and ideally it would centrifuge down to the bottom of the tube, so that I could take the clear supernatant. Howver, it is very inconsistent and is sometimes at the top, the middle, or the bottom and mixed throughout the tube. Here are some examples of three different tubes that were part of today’s batch of 9:

I just had to do my best and avoid the RNAzol as best I could when removing 790µL of supernatant (hopefully containing isolated RNA) into clean 1.7mL snap cap tubes.

imgimgimg

Take-aways

I really think that this new revised protocol is the way to go for me from here on out!! It involved several more centrifuge steps which helped isolate the junk from the RNA, and I think that made a big difference. I will keep isolating RNA tomorrow and Friday, and likely into next week.

My goal is to have a large subset of samples with isolated RNA.

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