Laura’s Notebook: QuantSeq Library Generation Batches 3 and 4

IMG_9282

IMG_9283

Batch 3 Sample Information

Sample order in plate Sample No. [RNA] (ng/ul) Vol RNA used Vol H2O to add ng RNA used
1 35 94.4 3.71 1.29 350
2 524 63.0 5.00 315
3 453 196.0 1.79 3.21 350
4 554 188.0 1.86 3.14 350
5 442b 69.8 5.00 349
6 489 68.0 5.00 340
7 462b 106.0 3.30 1.70 350
8 533 6.5 5.00 32.6
9 522 32.2 5.00 161
10 474 77.2 4.53 0.47 350
11 452b 97.2 3.60 1.40 350
12 443 60.2 5.00 301
13 477 164.0 2.13 2.87 350
14 526 138.0 2.54 2.46 350
15 562 126.0 2.78 2.22 350
16 432 74.0 4.73 0.27 350
17 37 74.6 4.69 0.31 350
18 413 130.0 2.69 2.31 350
19 45 25.1 5.00 125.5
20 561 28.0 5.00 140
21 542 32.8 5.00 164
22 527 124.0 2.82 2.18 350
23 492 82.6 4.24 0.76 350
24 475 27.4 5.00 137
25 541 44.4 5.00 222
26 565 31.2 5.00 156
27 B3 – NTC1 NA 5.00 #VALUE!
28 B3 – NTC2 NA 5.00 #VALUE!

Batch 3 Plate Configuration

1 2 3 4 5 6 7 8
A 35 524 453 554 442b 489 462b
B
C 533 522 474 452b 443 477 526
D
E 562 432 37 413 45 561 542
F
G 527 492 475 541 565 B3 – NTC1 B3 – NTC2
H

Batch 4 Sample Information

Sample order in plate Sample No. [RNA] (ng/ul) Vol RNA used Vol H2O to add ng RNA used
1 571 LOW 5.00 NA
2 525 140.0 2.50 2.50 350
3 563 47.0 5.00 235
4 404 112.0 3.13 1.88 350
5 484 58.4 5.00 292
6 531 95.4 3.67 1.33 350
7 34 104.0 3.37 1.63 350
8 490 186.0 1.88 3.12 350
9 523 71.4 4.90 0.10 350
10 473 124.0 2.82 2.18 350
11 485 19.1 5.00 95.5
12 402 114.0 3.07 1.93 350
13 487 118.0 2.97 2.03 350
14 476 39.2 5.00 196
15 421 57.6 5.00 288
16 553 186.0 1.88 3.12 350
17 41 108.0 3.24 1.76 350
18 46 98.6 3.55 1.45 350
19 551 96.4 3.63 1.37 350
20 486b 148.0 2.36 2.64 350
21 445 160.0 2.19 2.81 350
22 43 156.0 2.24 2.76 350
23 506 29.2 5.00 146
24 482 22.2 5.00 111
25 412 31.2 5.00 156
26 488 60.0 5.00 300
27 47 128.0 2.73 2.27 350
28 B4 – NTC2 NA 5.00 0

Batch 4 Plate Configuration

1 2 3 4 5 6 7 8
A 571 525 563 404 484 531 34
B
C 490 523 473 485 402 487 476
D
E 421 553 41 46 551 486b 445
F
G 43 506 482 412 488 47 B4 – NTC2
H

Notes

  • Aliquoted 20 uL RNA into new tubes and froze in -80. Except, for the following samples I aliquoted 7 uL: 34, 35, 41, 46, 46
  • Sample #35 was not fully sealed during either the RNA removal step or the second strand synthesis step, and I believe I lost some volume to evaporation. I proceeded normally, but will see how that library looks.
  • Not sure if I mentioned this previously, but I’m using 350 ng RNA, except for low concentration samples (I use 5 uL to get the maximum amount of RNA possible).
  • To “quickly spin down” samples at room temperature I put the sample plate in the centrifuge, push start, then push stop immediately when the speed does not read 0. I also set the temperature to room temperature so it doesn’t actively cool.

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Laura’s Notebook: QuantSeq Purification and qPCR Assay Batches 1 & 2

ds cDNA purification, pre-PCR

I purified the ds cDNA from batches 1 and 2. Notes on how to improve that process:

  • Bubbles! Bubbles make it difficult to use a mutichannel pipette. Need to improve handling to minimize bubble formation.
  • Should reduce amount of time I keep samples on magnet and to dry. The beads seem to crack a bit, and it’s difficult to resuspend them in the final elution step.
  • Max # of PCR plate columns for purification step = 8

qPCR assay for optimal endpoint PCR cycles

I performed the qPCR assay on all the ctenidia samples (batches 1 and 2). Here are the amplification curves:

image

Batch 1 end-point PCF cycle calculations

Sample No. 50% max No. Cycles @ 50% No. Cycles @ 50% minus 3 cycles Cycles, round down
328 1,662 16.51 13.51 13
299 1,603 18.54 15.54 15
301 1,572 18.66 15.66 15
342 1,673 18.85 15.85 15
331 1,572 18.94 15.94 16
307 1,001 28.77 25.77 25
295 1,498 21.86 18.86 18
qPCR NTC 1,352 29.1 26.1 26
304 1,392 18.05 15.05 15
305 1,334 19.41 16.41 16
311 1,449 19.09 16.09 16
NTC2 – B1 1,521 25.92 22.92 23
298 1,437 18.27 15.27 15
348 1,394 19.33 16.33 16
315 1,496 18.74 15.74 15
qPCR NTC 1,483 28.23 25.23 25
344 1,545 18.19 15.19 15
325 2,029 17.64 14.64 14
338 1,572 19.31 16.31 16
347 1,547 17.9 14.9 15
312 1,510 18.77 15.77 15
321 1,561 18.03 15.03 15
333 1,651 18.07 15.07 15
291 1,265 18.06 15.06 15
308 1,297 19.1 16.1 16
NTC1 – B1 1,538 25.23 22.23 22
335 1,449 18.86 15.86 15
318 1,586 19.01 16.01 16
294 1,444 19.3 16.3 16
324 1,648 19.34 16.34 16

Batch 2 end-point PCR cycle calculations

Sample No. RFU @ endpoint 50% max No. Cycles @ 50% No. Cycles @ 50% minus 3 cycles Cycles, round down
343 3583 1791.5 16.62 13.62 13
345 4129 2,065 17.31 14.31 14
303 3543 1,772 17.28 14.28 14
346 2823 1,412 17.75 14.75 14
302 3153 1,577 16.81 13.81 13
336 3300 1,650 22.82 19.82 19
292 3253 1,627 18.6 15.6 15
NTC1 -B2 3079 1,540 20.67 17.67 17
317 3576 1,788 18.8 15.8 15
322 2540 1,270 19.31 16.31 16
332 2689 1,345 20.02 17.02 17
334 2851 1,426 20.78 17.78 17
349 2825 1,413 18.57 15.57 15
337 3325 1,663 18.65 15.65 15
341 3152 1,576 17.61 14.61 14
313 3184 1,592 18.47 15.47 15
309 2962 1,481 18.05 15.05 14
327 2973 1,487 18.89 15.89 15
319 3037 1,519 20.88 17.88 16
326 2810 1,405 18.12 15.12 15
306 3698 1,849 21.19 18.19 18
323 3537 1,769 18.47 15.47 15
314 2996 1,498 20.58 17.58 17
316 2929 1,465 19.02 16.02 16
339 2761 1,381 19.33 16.33 16
293 2213 1,107 19.67 16.67 16
329 2164 1,082 18.72 15.72 15
296 2182 1,091 18.1 15.1 15

Notes

  • The highest quality RNA samples require 12 cycles. According to my QuantSeq rep, the very lowest quality and concentration RNA samples require 25 cycles.
  • I should use the optimal cycle number for end-point PCR, BUT some people that are in a hurry run all samples using the average of three consecutive cycles. For instance, if some samples need 14, some need 15, and some need 16, one can run all samples for 15 cycles. However, that is not the optimal protocol. I will proceed, but may need to re-generate a few libraries, which I will determine using Qubut and high sensitivity DNA chip on the Bioanalyzer.

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Laura’s Notebook: QuantSeq Library Generation Batch 2

Generated libraries on my second batch of ctenidia RNA samples.

Samples processed, volumes used for RNA and DEPC-treated water, and total RNA used.

Sample order in plate Sample No. [RNA] (ng/ul) Vol RNA used Vol H2O to add ng RNA used
1 343 114.0 3.07 1.93 350
2 345 190.0 1.84 3.16 350
3 303 95.2 3.68 1.32 350
4 346 43.6 5.00 218
5 302 62.4 5.00 312
6 336 94.8 3.69 1.31 350
7 292 29.6 5.00 148
8 NTC1 -B2 5.00 0
9 317 158.0 2.22 2.78 350
10 322 44.6 5.00 223
11 332 65.8 5.00 329
12 334 64.8 5.00 324
13 349 82.0 4.27 0.73 350
14 337 194.0 1.80 3.20 350
15 341 89.6 3.91 1.09 350
16 313 72.4 4.83 0.17 350
17 309 170.0 2.06 2.94 350
18 327 85.2 4.11 0.89 350
19 319 77.6 4.51 0.49 350
20 326 130.0 2.69 2.31 350
21 306 136.0 2.57 2.43 350
22 323 102.0 3.43 1.57 350
23 314 42.2 5.00 211
24 316 146.0 2.40 2.60 350
25 339 77.2 4.53 0.47 350
26 293 39.6 5.00 198
27 329 162.0 2.16 2.84 350
28 296 180.0 1.94 3.06 350

Volumes of solutions needed – I aliquoted volumes into 7 pcr tubes, so I could then add to samples using a multichannel pipette.

Step, Chem. Vol per rxn (uL) Total + 10% or 15% Vol per aliquot (n=7) Vol per sample
Step 3 MM: FS2 9.5 305.9 46 10
Step 3 MM: E1 0.5 16.1
Step 6: RS 5 154 22 5
Step 7: SS1 10 308 44 10
Step 9 MM: SS2 4 128.8 23 5
Step 9 MM: E2 1 32.2

PCR Plate setup

1 2 3 4 5 6 7 8
A 343 345 303 346 302 336 292
B
C NTC1 -B2 317 322 332 334 349 337
D
E 341 313 309 327 319 326 306
F
G 323 314 316 339 293 329 296
H

Notes

  • I worked in 4 rows of 7 (27 samples + 1 NTC).
  • I accidentally used 4.51 uL of sample #326, which is ~585 ug of RNA (exceeds the 500 ug max). I proceeded anyway, and will see if it influences the library quality.
  • Protocol was slightly improved by shortening the amount of time samples sit at 42C at step 2/3 (from 15 mins to ~7 minutes), and I cut the PCR plate to only have 8 of the 12 columns, which freed up space for pre-warming master mix #1 (steps 2/3).
  • I aliquoted 20uL of each sample to new tubes and placed in -80 freezer.

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Laura’s Notebook: QuantSeq Library Generation Batch 1

Began my full QuantSeq library prep today. I am processing ctenidia samples first, and since there are 53 samples I’m doing ~half at a time. Today I generated double stranded cDNA for 26 samples + 2 NTC (28 total). I loaded samples onto a PCR plate in 4 rows of 7.

Samples processed, volumes used for RNA and DEPC-treated water, and total RNA used.

cDNA synthesis 12/5/19 # samples + 2 NTC 28 Work in 4 rows of 7
Sample order in plate Sample No. [RNA] (ng/ul) Vol RNA used Vol H2O to add ng RNA used
1 328 156.0 2.24 2.76 350
2 299 50.4 5.00 252
3 301 75.8 4.62 0.38 350
4 342 162.0 2.16 2.84 350
5 331 42.2 5.00 211
6 307 89.4 3.91 1.09 350
7 295 34.8 5.00 174
8 304 200.0 1.75 3.25 350
9 305 75.2 4.65 0.35 350
10 311 158.0 2.22 2.78 350
11 NTC2 – B1 5.00 0
12 298 182.0 1.92 3.08 350
13 348 54.4 5.00 272
14 315 148.0 2.36 2.64 350
15 344 25.0 5.00 125
16 325 180.0 1.94 3.06 350
17 338 81.6 4.29 0.71 350
18 347 69.0 5.00 345
19 312 90.6 3.86 1.14 350
20 321 148.0 2.36 2.64 350
21 333 78.6 4.45 0.55 350
22 291 158.0 2.22 2.78 350
23 308 73.6 4.76 0.24 350
24 NTC1 – B1 5.00 0
25 335 180.0 1.94 3.06 350
26 318 174.0 2.01 2.99 350
27 294 110.0 3.18 1.82 350
28 324 172.0 2.03 2.97 350

Volumes of solutions needed – I aliquoted volumes into 7 pcr tubes, so I could then add to samples using a multichannel pipette.

Step, Chem. Vol per rxn (uL) Total + 15% Vol per aliquot (n=7) Vol per sample
Step 3 MM: FS2 9.5 305.9 46 10
Step 3 MM: E1 0.5 16.1
Step 6: RS 5 161 23 5
Step 7: SS1 10 322 46 10
Step 9 MM: SS2 4 128.8 23 5
Step 9 MM: E2 1 32.2

PCR Plate setup

1 2 3 4 5 6 7 8 9 10 11 12
A 328 299 301 342 331 307 295
B
C 304 305 311 NTC2 – B1 298 348 315
D
E 344 325 338 347 312 321 333
F
G 291 308 NTC1 – B1 335 318 294 324
H

Notes

  • Samples were thawed on wet ice, and vortexed once before use.
  • I loaded the first 3 samples, 328, 299 and 301, onto the PCR plate but then had to wait a few minutes (~3-5) for the rest to thaw.
  • Step #2: held samples at 42C for 14 minutes while preparing master mix. Probably a bit too long.
  • I used a whole PCR Plate, which took up the entire thermocycler space. Next time, I should use partial PCR plates to leave room for a PCR strip to pre-warm the master mix needed for step 3 & 4.
  • The centrifuge gradually cooled as I was using it, which was weird since I didn’t change the temp. I think I need to set temperature to 22C every time I use it, b/c it may default to 4C.
  • I aliquoted 20uL of each sample to new tubes and placed in -80 freezer.

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Laura’s Notebook: Oly methylation analysis, Nov 20, 2019

Revisiting Oly methylation data. We now have two lists of loci:

  • 1) DMLs between two Olympia oyster populations, Hood Canal and South Sound, which were identified using MethylKit.
  • 2) Loci where methylation status is associated with oyster shell length, filtered by a) loci have 10x coverage in all samples, and b) loci have 10x coverage in any sample.

Today I re-plotted heatmaps using MACAU loci, based on feedback from Steven & Katherine:

  • Only use loci with 10x coverage
  • Add heatmaps where samples are NOT ordered by cluster analysis, but instead by 1) tree from MethylKit, and 2) shell length. See my notebook, 06-analyzing-MACAU-results-rev1.html, and here’s one of the new heatmaps, with samples (columns) ordered by shell length, and a barplot of shell length below (red = Hood Canal oysters, green = South Sound oysters).

69304438-6e9ddb00-0bd5-11ea-950a-64b24e80fbf4.png69304447-78bfd980-0bd5-11ea-995a-149f7b6a6b83.png

Then I used bedtools to see where DMLs and MACAU loci are located, see my notebook here:
07-DML-MACAU-annotation.ipynb.

Finally, I began annotating loci locations for DMLs and MACAU loci; see my notebook: 08-Annotations.html. Here’s a barplot showing which features overlap with the DMLs: image

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Laura’s Notebook: November 2019 goals

Tasks that must be completed in November

  • GRIP application (Due Dec. 4)
  • NSF INTERN program (No due date, sooner the better)
  • Address Ecological Applications formatting changes & submit
  • Jackie class – lots of writing
  • Finish larval measurements for Oly temp/food paper
  • Finish final revisions on Polydora MS

Longer-term tasks

  • Revise Oly temp/food paper to incorporate larval size differences
  • Can I automate oocyte measurements for Oly temp/food paper to get time series of oocyte size?
  • Get cracking on the QuantSeq library prep!
  • Revisit Oly methylation data and begin next steps in analysis. Need to determine steps, probably visualize results from MethylKit + MACAU + SNPs together, describe locations including function if possible.
  • Oly methylation data –> what’s the angle in my Aquaculture America talk?
  • Revisit/revise QuantSeq pipeline using Salmon and the Oly genome
  • Make sure Christian knows which samples are which
  • Identify possible Aquaculture 2020 funding

Other responsibilities

  • Start Polydora research position (goes through January)
  • Help with GSS
  • NSA quartlerly newsletter
  • Any Baltimore tasks?

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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

Clam-bay-beach-jun2018-jun2019.png

Clam-bay-dock-jun2018-sept2019.png

Clam-bay-dock_aug2017-jun2018.png

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)

Fidalgo-bay-beach-Nov2017-Jun2018.png

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

Mud-Bay-intertidal-winter2017-2018_depl1

Mud-Bay-intertidal-winter2017-2018_depl2

Mud-Bay-low-intertidal-winter2017-2018

Mud-Bay-subtidal_winter2017-2018

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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

image

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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

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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:

larval-min-feret-mean.png?raw=true

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