Laura’s Notebook: Temperature data from Clam Bay, Mud Bay, Fidalgo Bay

Over the past 2 years I have accumulated temperature data from a few locations in Puget Sound, WA. Using HOBO data loggers, I collectet temperature (& some light intensity data) from Clam Bay, which is where the Manchester research station is located, from Mud Bay, which is near Bremerton and has a very productive Olympia oyster bed, and from Fidalgo Bay, which is near Anacortes and the location of an assemblage of Olys that are uniquely large.

The following screenshots from the HOBOware plots are saved in this GitHub repo, and HOBO/.csv files.

Clam Bay Data, various dates Aug. 2017 – Sept. 2019

Data Files: Clam-Bay-Temperatures

Loggers held alongside Olympia oysters hanging off dock ~1-3 meters below surface (“dock”), and inside a tumble bag attached to the racks installed on the beach (accessible below -1’). Clam bay is located at the NOAA Manchester Research Station




Fidalgo Bay Temperature, Winter 2017-2018

Data Files: Fidalgo-Bay-Temperatures

Deployed attached to a sunken raft at (48°28’41.7”N 122°34’26.6”W) aka (48.478238, -122.574057)


Mud Bay, Winter 2017-2018

Data Files: Mud-Bay-Temperatures

Deployed at 3 locations in Mud Bay, Dyes Inlet, approximately here: (47°35’22.9”N 122°40’22.2”W) aka (47.589681, -122.672831). Exact deployment coordinates for the 3 probes are here: 2017-11-06_Mud Bay-Temp-Logger-Locations.kml





from The Shell Game

Laura’s Notebook: Analyzing MACAU results, take 3

New and improved with the following:

  • Included a False Discovery Rate correction as per this paper doi:10.3390/genes10050356
  • 2 heat maps created with % methylation:
    1) excluding loci for individual samples where coverage <5x (retained for other samples), and
    2) excluding loci for all samples if any had <5x coverage
  • Barplot of lengths in same order as 2nd heat map

See new RMarkdown notebook: 006-analyzing-MACAU-results-rev1

Preview of new plots


from The Shell Game

Laura’s Notebook: Analyzing MACAU results, take 2

I revisited the MACAU result again to:

  • re-do heat maps with only loci that has 10x or greater coverage
  • Generate heat maps of % methylation (and coverage >= 10x)
  • Generate PC plot using count data (>= 20x coverage)

Check out my RMarkdown notebook, 06-Analyzing MACAU results

from The Shell Game

Laura’s Notebook: Analysis of QuantSeq Larval Sizes

Check out my RMarkdown notebook where I analyze larval size upon release by parental pH and temperature treatment: laura-quantseq/notebooks/Larval-size-on-release.html

Here’s a sneak peak at one of the plots generated in this notebook:


from The Shell Game

Laura’s Notebook: September, 2019 Goals

Review of last month’s goals


  • Quantify remaining RNA with Qubit – complete
  • Assess RNA quality via Bioanalyzer on subset of samples – complete
  • Concentrate dilute samples. Goal is 500 ng in 5 uL – not done
  • Acquire all materials for QuantSeq library prep – complete
  • Test protocol on 8 samples (“extra” samples). – in progress


  • Identify and reach out to potential new committee members – complete. GSR is Jen Ruesink!
  • Read Jackie’s stack of papers, take notes and organize using Evernote – in progress!
  • Get study lists from Rick & Steven – in progress. Received from Rick


  • Finish simplifying O. lurida temperature/food methods, results and discussion – complete, sent to Steven for review
  • sBegin revising, or at least organize thoguhts on, Polydora MS as per discussion with Chelsea & Julieta – not started!


  • Review presentation from Aquaculture 2019 for PCSGA. – in progress
  • Measure larvae from 2017 OA/T study – complete

## New Goals

### QuantSeq

  • Troubleshoot issues with trial run :/
  • Make headway on preparation of actual samples

### Degree:

  • Continue reading to prep for Quals – need to pick up speed
  • Get reading list from Steven
  • Meet with Jen
  • Meet with Krista & Mac re: GRIP
  • Can I submit dissertation proposal?


  • Oly temp/food
    • Revise methods -> discussion based on Steven’s feedback
    • Write intro
  • Polydora -> redraft (!)
  • Maybe get reviewer comments from Ecological Applications? (Not to-do, but something to anticipate)

### Other

  • NSA quarterly newsletter piece
  • Present @ PCSGA
  • Figure out Jackie’s scope calibration situation …

from The Shell Game

Laura’s Notebook: QuantSeq Library Prep test-run

Katherine suggested I work through the library prep protocol with a few samples to practice and work out kinks. From her experience, the libraries she generated later in the game were of higher quaity. I’m generating 8 test libraries – this was her recommendation based on the heavy use of 8-channel pipettes.

Following the QuantSeq manual and tips from Katherine.

Quick reference for Libary Generation


Notes from this test run:

Started on 8/20/2019

Prior to beginning, I created programs on the PTC-200 DNA Engine Cycler. Programs are labeled “Quantseq-#”, with the # corresponding to step number in the QuantSeq manual.

first strand cDNA synthesis

  • Based on Katherine’s suggestions, I will generate 40 libraries at one, in 5 rows of 8 on a PCR plate. When adding solutions to each well, rather than using a single channel pipette and transferring solutions to individual wells, I’m going to use PCR strips, load enough of each solution into 8 wells (with a bit excess), and use a multichannel to distribute. This way I can hopefuly reduce time.
  • Between each step I need to quickly “spin down” my PCR plate. Our benchtop centrifuge has a minimum run time of 1 minute, and with the time it takes to accelerate and decelerate total time is ~4 minutes. The “quickly spin down” instructions do not define a centrifuge speed to use, so I set it to 3 rcf based on whatt is specified in the equipmentt list – “Benchtop centrifuge (3,000 x g, rotor compatible with 96-well plates”. To reduce the amount of time to spin down plates, I should either set the speed lower, OR simply start, then stop the centrifuge manually.

RNA removal

  • No notes.

second strand cDNA synthesis

  • SS1 and USS are indeed viscous; hold pipette in place when pulling volumes.

Placed in -20C overnight.


(this is 1 of 2 purifications, dubbed “pre-PCR”)

  • As Katherine hinted, it’s important to have a magnetic plate that fits the PCR plates used. The plates we have just have rods – no wells for plates to hold plates in place, which doesn’t work. I ordered a magnet/plate from ebay to hopefully improve the process.

Placed in -20 on 8/21/19 until next step (qPCR assay).

qPCR assay for optimal # cycles

Performed on 9/3/2019

  • Created a custom qPCR protocol with Sam’s help –
qPCR Assay Mastermis Calcs
Item per rxn (uL) all rxns (inc. NTC) (uL) all rxns * 1.1
Number of samples 1 9
cDNA, diluted to 19uL 1.7 15.3 16.8
PCR mix (PCR) 7 63 69.3
P7 Primer (7000) 5 45 49.5
Enzyme mix (E) 1 9 9.9
2.5x SYBR Green I nucleic acid dye 1.2 10.8 11.9
Elution Buffer (EB) 14.1 126.9 139.6
Mastermix total vol 28.3 254.7 280.2
SYBR Green Calcs Volumes
Stock concentration 100
Desired concentratino 2.5
Total volume needed 2.5x 11.9
Volume 100x 0.2970
Volume DMSO 11.58
Dilution ratio (should be 1:40) 0.025
Final concentration 2.5

Results: Located on Owl, with today’s date.

No amplification :/ max RFU should be ~10×10^12, and my no-template control (NTC) has same curve as samples.

2019-09-03_ qPCR-assay-test-run

First troubleshooting step is to see if I actually synthesized cDNA – I believe I can use the Qubit for that. If yes, then I messed up the qPCR somehow (wouldn’t surprise me). Perhaps there is an issue with bubbles? Maybe BioRad settings needed be adjusted for sybr green?

I ordered a trial QuantSeq kit (n=4) for trouble shooting, and as a result spoke with the WA respresentative. Notes from our call:

  • If cDNA synthesis did not occur, then I most likely had contamination with organics or salts, which can inhibit 1st strand synthesis and cause cDNA to degrade when trying to degrade RNA.
  • The TurboDNase method might be an issue, since it did not include a column.
  • Using a cleaner column on existing RNA may do the trick. I did order one box of Zymo Cleaner-Concentrator (n=50), so could run all my samples through this column.
  • 500 ng of input RNA is not necesary (she said that “no one uses that much”). 100 ng should be adequate!

I will receive the trial kit tomorrow, and Kristy is connecting me with the tech support guy.

from The Shell Game

Laura’s Notebook: Measuring QuantSeq larvae

The QuantSeq run I am prepping for will look at gene expression in O. lurida larvae, which were produced by adults that had previously been held in varying winter temperature and pCO2. All larvae were collected and frozen within a day or two of being released from the brood chamber, therefore they should all be at the same developmental stage. The size upon release, however, could be slightly different depending on the larval growth rate, and if larval release is triggered by something (e.g. food, tank cleaning). Since larval size could correspond with developmental stage which impacts gene expression profiles, I measured all the larvae that will also be sequenced.

While homogenizing frozen larvae with mortar + pestle, I preserved some of the larvae in ethanol, held in a fridge. To measure, I used the Nikon camera + microscope in Jackie’s lab, and the NIS-Element software’s automatic measurement capabilities. Steps:

  • Suspend larvae in ethanol with a pipette, transfer to a slide with cover slip
  • Capture image of larvae that are lying on their side, so the full width/length could be measured
  • Apply a binary layer to the image using the pre-determined threshold setting (based on color). The threshold also uses circularity and size to determine where the binary boundaries occur, and what to include.
  • Use the automatic measurement option to draw perimeters around all binary objects, then generate measurement statistics about each object. Here are details of the measurements I pulled for each object, from the NIS-Element user manual. Note: I believe the MaxFeret is the best representation of shell width, and MaxFeret90 is shell height.


When measuring objects, it’s important to do quality control – some larvae should not be included since they are at a weird angle, or tissue/junk is included in the auto-generated object, thus making the measurements erroneous. After doing this QC, I exported 2 images simultanously: 1) microscope image without any annotations, layers, etc.; 2) binary layer showing objects that were measured, object IDs, and scale bar. It took me a long time to figure out the software, which I don’t think is very intuitive. I made a screen recording of the process – check it out:

I measured at minimum 50 larvae from each of my 58 larval sample. Here are some quick and dirty plots of MaxFeret90 (aka shell height) and MaxFeret (aka shell width):




I need to measure the following larvae – missed these since I already had RNA:

Date Collected Spawning Group Population Treatment Larval sample # RNA Sample # Date homogenized
5/21/17 SN-10 Low B Oyster Bay C1 10 Low 06-A 41 na
5/23/17 SN-10 Low B Oyster Bay C1 10 Low 08-A 43 na
5/26/17 SN-10 Low B Oyster Bay C1 10 Low 24-A 46 na
5/27/17 SN-10 Low B Oyster Bay C1 10 Low 26-A 47 na
5/31/17 SN-10 Low A Oyster Bay C1 10 Low 32-A 44 na
6/14/17 SN-10 Low B Oyster Bay C1 10 Low 62-A 506 07/20/19
6/24/17 SN-10 Low A Oyster Bay C1 10 Low 79-A 45 na
5/23/17 SN-6 Ambient B Oyster Bay C1 6 Ambient 10-A 35 na
6/5/17 SN-6 Ambient B Oyster Bay C1 6 Ambient 45-A 513 07/23/19
6/6/17 SN-6 Ambient B Oyster Bay C1 6 Ambient 48-A 39 na
6/15/17 SN-6 Ambient B Oyster Bay C1 6 Ambient 69-A 37 na
6/19/17 SN-6 Ambient A Oyster Bay C1 6 Ambient 77-A 34 na

from The Shell Game