Laura’s Notebook: Oly OA RNA isolation – juvenile ctenidia

I’m done with my adult ctenidia & larvae libraries, and have enough kit leftover for ~17 more samples. I’ve decided to prep a few of my juvenile samples, which were collected at the end of the summer deployment. It could be very interesting to assess differences in juveniles and whether they are similar to those observed in the parents that were directly exposed.

I’m doing the whole body samples collected from the Hood Canal and Fidalgo Bay populations after they were deployed in Port Gamble Bay. I have n=4 per population and parental pH treatment (high or ambient). I had wanted to do ctenidia tissues, but then I checked out the frozen samples and noticed that they definitely are not just gill – lots of mantle tissue in there too. Therefore, I decided to do whole-body samples to try to standardize the tissue type.

Step 1: Homogenize tissue (March 6th, 2020)

Need: LN, dry ice, bleach, DI water, mortar + pestle, metal spatulas

• Added 1mL RNAzol to 1.5 mL microcentrifuge tubes.
• Cleaned mortars, pestles, and metal spatulas. Did this by cleaning under hot water, soaking in 10% bleach/DI solution for a minimum of 10 minutes, rinsing thoroughly with DI water, then rinsing with 190 proof ethanol and letting dry.
• Put tubes with RNAzol on scale. Ground tissues to powder, scraped with metal spatula and carefully transferred powder to tube. Added approximately 50 mg.
• I did 8 samples at a time (the # of mortar+pestle kits I have), then cleaned and repeated with another 8.

Step 2: RNA isolation (March 7th, 2020)

Need: RNAzol, DEPC-treated water, isopropanol, 200-proof ethanol, 1.7 mL tubes

Followed the RNAzol® RT RNA Isolation Reagent protocol for Total RNA isolation, using half of my homogenate, so 500 uL.

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Laura’s Notebook: February 2020 goals

Yikes, it’s been a few months …

• Finish QuantSeq libraries – last step is to process some deployed juvnile Olys (RNA isolation, library prep)
• Coordinate sequencing – UW or UMinnesota?
• DMG and DMR analysis on Oly methylation data. Make sure that I’ve controlled for genotype (i.e. differences aren’t due to presence/absence of certain genes/loci) – does the filtering accomplish this?
• Prepare and deliver presentation at Aquaculture America 2020
• Revise Oly Temp/Food draft, and rough draft of introduction
• Submit Polydora paper to Aquaculture Research
• Meet OA/Reproduction deadlines

Also … Met with Krista – we are a go on the internship. I will get my hands on the data as soon as it’s ready (April?). She supports me doing the NSF INTERN in Fall/Winter, so should continue pursuing that. Need to have full analysis of data by November at latest.

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Laura’s Notebook: Oly DMG analysis, Jan. 30th, 2020

Today I identified 46 differentially methylated genes among two Olympia oyster populations, Hood Canal and South Sound. This was performed using a binomial GLM and Chi-square tests. The script was adapted from Hollie Putnam’s script (/hputnam/Geoduck_Meth/master/RAnalysis/Scripts/GM.Rmd), which may have been adopted from the Lieu et al. 2018 paper .

The analysis was performed in a RMarkdown notebook, please see that here: 09-DMG-analysis

Here are the GO terms associated with genes of known function. Some notes:
– 18 out of the 46 genes were annotated with GO terms
– 9 out of the 46 genes were annotated but did not have associated GO terms (may have to find those manually …)
– 19 out of the 46 genes were of unknown function

term ID	description	frequency	pin?	log10 p-value	uniqueness	dispensability
GO:0006468	protein phosphorylation	4.137 %	-3.7877	0.40	0.00
GO:0006807	nitrogen compound metabolic process	38.744 %	-2.2764	0.78	0.03
GO:0006207	‘de novo’ pyrimidine nucleobase biosynthetic process	0.192 %	-2.2764	0.46	0.06
GO:0006281	DNA repair	2.234 %	-2.4853	0.50	0.20
GO:0006030	chitin metabolic process	0.077 %	-1.6311	0.49	0.21
GO:0006520	cellular amino acid metabolic process	5.591 %	-2.2764	0.42	0.35
GO:0006412	translation	5.686 %	-2.4853	0.28	0.55
GO:0016567	protein ubiquitination	0.523 %	-1.4336	0.44	0.56

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Laura’s Notebook: QuantSeq – inventory of finished libraries

Library prep is complete! However, I will need to redo many 😦 Based on Bioanalyzer results, any libraries with concentration <1.0 ng/uL will need to be re-done. Out of the total 132 samples that I prepped, 34 had concentrations that were LOW or <1.0 ng/uL (according to Qubit). That’s about a 25% incompletion rate. Here is the final inventory.

Next step – redo the 34 samples. Need to decide whether I should re-isolate RNA, or just try to re-do the library generation. This is a question for lab meeting tomorrow.

Ctenidia

Cohort	pCO2	HOMOGENATE TUBE #	TISSUE TYPE	TISSUE SAMPLE #	[RNA] after Dnase treatment (ng/uL)	End Point PCR cycles	ds cDNA concentration
Dabob Bay	High	291	CTENIDIA	HL10-10	158.0	15	LOW
Dabob Bay	High	292	CTENIDIA	HL10-11	29.6	15	1.32
Dabob Bay	High	293	CTENIDIA	HL10-12	39.6	16	1.03
Dabob Bay	High	294	CTENIDIA	HL6-10	110.0	16	1.95
Dabob Bay	High	295	CTENIDIA	HL6-11	34.8	18	LOW
Dabob Bay	High	296	CTENIDIA	HL6-12	180.0	15	3.46
Dabob Bay	High	298	CTENIDIA	HL6-14	182.0	15	3.08
Dabob Bay	High	299	CTENIDIA	HL6-15	50.4	15	2.46
Dabob Bay	Ambient	301	CTENIDIA	HL10-19	75.8	15	2.82
Dabob Bay	Ambient	302	CTENIDIA	HL10-20	62.4	14	4.90
Dabob Bay	Ambient	306	CTENIDIA	HL10-21	136.0	18	LOW
Dabob Bay	Ambient	304	CTENIDIA	HL6-19	200.0	15	2.80
Dabob Bay	Ambient	305	CTENIDIA	HL6-20	75.2	16	2.96
Dabob Bay	Ambient	303	CTENIDIA	HL6-21	95.2	14	2.40
Dabob Bay	Ambient	307	CTENIDIA	HL6-16	89.4	TOO LOW	TOO LOW
Dabob Bay	Ambient	308	CTENIDIA	HL6-17	73.6	16	2.48
Dabob Bay	Ambient	309	CTENIDIA	HL6-18	170.0	14	1.46
Oyster Bay	High	311	CTENIDIA	SN6-16	158.0	16	3.76
Oyster Bay	High	312	CTENIDIA	SN6-17	90.6	15	1.58
Oyster Bay	High	313	CTENIDIA	SN6-18	72.4	15	1.81
Oyster Bay	High	314	CTENIDIA	SN6-19	42.2	17	LOW
Oyster Bay	High	315	CTENIDIA	SN6-20	148.0	15	2.32
Oyster Bay	High	316	CTENIDIA	SN6-21	146.0	16	3.74
Oyster Bay	High	317	CTENIDIA	SN6-22	158.0	15	2.14
Oyster Bay	High	318	CTENIDIA	SN6-23	174.0	16	4.08
Oyster Bay	High	319	CTENIDIA	SN6-24	77.6	16	0.64
Oyster Bay	Ambient	321	CTENIDIA	SN6-25	148.0	15	3.64
Oyster Bay	Ambient	322	CTENIDIA	SN6-26	44.6	16	NOT QUANTIFIED
Oyster Bay	Ambient	323	CTENIDIA	SN6-27	102.0	15	3.70
Oyster Bay	Ambient	324	CTENIDIA	SN6-28	172.0	16	0.78
Oyster Bay	Ambient	325	CTENIDIA	SN6-29	180.0	14	2.92
Oyster Bay	Ambient	326	CTENIDIA	SN6-30	130.0	15	4.04
Oyster Bay	Ambient	327	CTENIDIA	SN6-31	85.2	15	1.97
Oyster Bay	Ambient	328	CTENIDIA	SN6-32	156.0	14	2.12
Oyster Bay	Ambient	329	CTENIDIA	SN6-33	162.0	15	0.33
Fidalgo Bay	High	331	CTENIDIA	NF6-16	42.2	16	LOW
Fidalgo Bay	High	332	CTENIDIA	NF6-17	65.8	17	LOW
Fidalgo Bay	High	333	CTENIDIA	NF6-18	78.6	15	2.98
Fidalgo Bay	High	334	CTENIDIA	NF6-19	64.8	17	LOW
Fidalgo Bay	High	335	CTENIDIA	NF6-20	180.0	15	2.58
Fidalgo Bay	High	336	CTENIDIA	NF6-21	94.8	20	LOW
Fidalgo Bay	High	337	CTENIDIA	NF6-22	194.0	15	4.02
Fidalgo Bay	High	338	CTENIDIA	NF6-23	81.6	16	2.74
Fidalgo Bay	High	339	CTENIDIA	NF6-24	77.2	16	1.91
Fidalgo Bay	Ambient	341	CTENIDIA	NF6-25	89.6	14	1.31
Fidalgo Bay	Ambient	342	CTENIDIA	NF6-26	162.0	15	1.78
Fidalgo Bay	Ambient	343	CTENIDIA	NF6-27	114.0	14	2.58
Fidalgo Bay	Ambient	344	CTENIDIA	NF6-28	25.0	15	1.58
Fidalgo Bay	Ambient	345	CTENIDIA	NF6-29	190.0	14	3.50
Fidalgo Bay	Ambient	346	CTENIDIA	NF6-30	43.6	14	1.36
Fidalgo Bay	Ambient	347	CTENIDIA	NF6-31	69.0	15	LOW
Fidalgo Bay	Ambient	348	CTENIDIA	NF6-32	54.4	16	3.06
Fidalgo Bay	Ambient	349	CTENIDIA	NF6-33	82.0	15	1.90

Larvae

Spawning Tank	Cohort	Treatment	Homo./RNA TUBE #	[RNA] after Turbo Dnase treatment (ng/uL)	End Point PCR cycles	ds cDNA concentration
HL-10 Ambient	Dabob Bay	10 Ambient	401	93.4	16	1.24
HL-10 Ambient	Dabob Bay	10 Ambient	402	114.0	16	2.76
HL-10 Ambient	Dabob Bay	10 Ambient	403	136.0	14	4.16
HL-10 Ambient	Dabob Bay	10 Ambient	404	112.0	15	2.92
HL-10 Low	Dabob Bay	10 Low	411	72.6	16	3.08
HL-10 Low	Dabob Bay	10 Low	412	31.2	17	LOW
HL-10 Low	Dabob Bay	10 Low	413	130.0	15	1.97
HL-10 Low	Dabob Bay	10 Low	414	168.0	15	0.86
HL-6 Ambient	Dabob Bay	6 Ambient	421	57.6	14	1.63
HL-6 Low	Dabob Bay	6 Low	431b	83.0	16	3.36
HL-6 Low	Dabob Bay	6 Low	432	74.0	17	LOW
HL-6 Low	Dabob Bay	6 Low	434	63.0	15	5.58
NF-10 Ambient A	Fidalgo Bay	10 Ambient	441	16.2	15	LOW
NF-10 Ambient A	Fidalgo Bay	10 Ambient	442b	69.8	17	LOW
NF-10 Ambient A	Fidalgo Bay	10 Ambient	443	60.2	15	1.36
NF-10 Ambient B	Fidalgo Bay	10 Ambient	444	70.6	14	4.08
NF-10 Ambient B	Fidalgo Bay	10 Ambient	445	160.0	15	4.00
NF-10 Low B	Fidalgo Bay	10 Low	451	68.4	14	2.24
NF-10 Low A	Fidalgo Bay	10 Low	452b	97.2	16	2.68
NF-10 Low B	Fidalgo Bay	10 Low	453	196.0	14	0.97
NF-6 Ambient B	Fidalgo Bay	6 Ambient	461b	84.0	14	2.02
NF-6 Ambient A	Fidalgo Bay	6 Ambient	462b	106.0	16	0.21
NF-6 Low B	Fidalgo Bay	6 Low	471b	108.0	15	5.20
NF-6 Low B	Fidalgo Bay	6 Low	472b	97.0	15	2.42
NF-6 Low B	Fidalgo Bay	6 Low	473	124.0	14	2.34
NF-6 Low A	Fidalgo Bay	6 Low	474	77.2	14	3.02
NF-6 Low A	Fidalgo Bay	6 Low	475	27.4	14	2.44
NF-6 Low A	Fidalgo Bay	6 Low	476	39.2	14	4.24
NF-6 Low A	Fidalgo Bay	6 Low	477	164.0	15	2.28
SN-10 Ambient A	Oyster Bay C1	10 Ambient	481	89.2	14	0.88
SN-10 Ambient B	Oyster Bay C1	10 Ambient	482	22.2	14	1.42
SN-10 Ambient B	Oyster Bay C1	10 Ambient	483	99.0	16	1.22
SN-10 Ambient A	Oyster Bay C1	10 Ambient	484	58.4	15	1.67
SN-10 Ambient B	Oyster Bay C1	10 Ambient	485	19.1	14	2.90
SN-10 Ambient A	Oyster Bay C1	10 Ambient	486b	148.0	16	LOW
SN-10 Ambient B	Oyster Bay C1	10 Ambient	487	118.0	16	1.27
SN-10 Ambient A	Oyster Bay C1	10 Ambient	488	60.0	14	3.06
SN-10 Ambient A	Oyster Bay C1	10 Ambient	489	68.0	15	3.84
SN-10 Ambient B	Oyster Bay C1	10 Ambient	490	186.0	14	2.32
SN-10 Ambient B	Oyster Bay C1	10 Ambient	491	58.4	15	6.64
SN-10 Ambient B	Oyster Bay C1	10 Ambient	492	82.6	15	2.02
SN-10 Low B	Oyster Bay C1	10 Low	41	108.0	17	LOW
SN-10 Low B	Oyster Bay C1	10 Low	43	156.0	15	2.48
SN-10 Low B	Oyster Bay C1	10 Low	46	98.6	18	LOW
SN-10 Low B	Oyster Bay C1	10 Low	47	128.0	17	LOW
SN-10 Low A	Oyster Bay C1	10 Low	44	41.4	TOO LOW	TOO LOW
SN-10 Low B	Oyster Bay C1	10 Low	506	29.2	15	1.63
SN-10 Low A	Oyster Bay C1	10 Low	45	25.1	20	LOW
SN-6 Ambient B	Oyster Bay C1	6 Ambient	35	94.4	20	LOW
SN-6 Ambient B	Oyster Bay C1	6 Ambient	513	142.0	15	5.92
SN-6 Ambient B	Oyster Bay C1	6 Ambient	39	89.8	15	2.04
SN-6 Ambient B	Oyster Bay C1	6 Ambient	37	74.6	20	LOW
SN-6 Ambient A	Oyster Bay C1	6 Ambient	34	104.0	18	LOW
SN-6 Low A	Oyster Bay C1	6 Low	521	66.6	17	LOW
SN-6 Low A	Oyster Bay C1	6 Low	522	32.2	16	2.42
SN-6 Low B	Oyster Bay C1	6 Low	523	71.4	16	2.16
SN-6 Low B	Oyster Bay C1	6 Low	524	63.0	14	3.24
SN-6 Low B	Oyster Bay C1	6 Low	525	140.0	14	2.44
SN-6 Low A	Oyster Bay C1	6 Low	526	138.0	14	2.20
SN-6 Low B	Oyster Bay C1	6 Low	527	124.0	15	1.42
SN-6 Low B	Oyster Bay C1	6 Low	528	87.6	14	4.48
SN-6 low A	Oyster Bay C1	6 Low	529	56.8	15	2.86
K-10 Ambient	Oyster Bay C2	10 Ambient	531	95.4	15	2.10
K-10 Ambient	Oyster Bay C2	10 Ambient	532	93.6	14	2.12
K-10 Ambient	Oyster Bay C2	10 Ambient	533	6.5	17	LOW
K-10 Low	Oyster Bay C2	10 Low	541	44.4	15	1.40
K-10 Low	Oyster Bay C2	10 Low	542	32.8	16	2.22
K-10 Low	Oyster Bay C2	10 Low	543	162.0	14	5.24
K-6 Ambient	Oyster Bay C2	6 Ambient	551	96.4	14	1.69
K-6 Ambient	Oyster Bay C2	6 Ambient	552b	74.6	15	1.84
K-6 Ambient	Oyster Bay C2	6 Ambient	553	186.0	14	3.28
K-6 Ambient	Oyster Bay C2	6 Ambient	554	188.0	14	2.38
K-6 Low	Oyster Bay C2	6 Low	561	28.0	17	LOW
K-6 Low	Oyster Bay C2	6 Low	562	126.0	17	LOW
K-6 Low	Oyster Bay C2	6 Low	563	47.0	15	0.19
K-6 Low	Oyster Bay C2	6 Low	564	152.0	14	2.24
K-6 Low	Oyster Bay C2	6 Low	565	31.2	17	LOW
homog. Control	RNA Control	571	LOW	18	LOW
homog. Control	RNA Control	572	TOO LOW	TOO LOW

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Laura’s Notebook: QuantSeq library amplification, purification, and QA

The final step in the QuantSeq library prep is to amplify my cDNA libraries (using the optimal cycle number) and then purify. Finally, to assess quantity and quality of finished libraries I use the Qubit High Sensitivity DNA kit to measure cDNA concentration, and the Bioanalyzer High Sensitivity DNA chip kit to measure fragment lengths. I worked in batches based on the number of cycles needed to amplify.

IMPORTANT NOTE: I have 2 sets of indexes with the same numbers. I therefore prepped the ctenidia samples with one set, and the larvae with another set. Therefore, I SHOULD NOT run ctenidia and larval samples in the same lane (since two samples have the same index number).

The spreadsheet where I have all this information organized is in the laura-quantseq repo, file is: 2019-July_RNA-isolation-ctenidia-larvae.xlsx

12/30/2019 – 16 cycles

• I noticed that I didn’t have the full 17 uL in any of the ds cDNA libraries, probably missing ~ 2uL. Not sure why, possibly due to pipette loss?
• Sample #331 volume depleted after PCR, maybe due to evaporation b/c there was a small crease in the foil? This was located at well A1 – should ensure tight seal for all future plates.

Amplification plate configuration

1/1/2020 – 14 cycles

• Again, samples <17 uL.

Amplification plate configuration

1/2/2020 – 15 cycles

• Again, most samples <17 uL.

Amplification plate configuration

1/4/2020 – 17, 18 and 20 cycles

• I amplified 3 batches of samples today – those needing 17, 18 and 20 cycles (ran in that order). I held amplified samples at 10C until all groups were done, then combined all samples onto one plate, purified, and quantified.
• Unfortunately, none of these libraries amplified! I don’t know whether there was an error in the amplification step, OR if the high number of cycle needed represent low concentration/quality. Looking/thinking back through all my steps I do not see any possible errors that could have been made in the PCR mix (it’ a simple master mix using 2 reagents), or during purification. Regardless, I will need to re-do all these libraries!

Amplification plate configuration & index

Amplified and Indexed QuantSeq cDNA libraries

This is the plate configuration of the finished libraries. Based on the quantification/Bioanalyzer results, some of these libraries will need to be re-done. However, this is an important map!

Bioanalyzer quality check

• I ran 1-2 chips per amplification group. The first 2 chips, which I did for the 16 cycle group, worked great! Results below.
• I had some issues with the next few chips. Not sure why, but I suspect that it had to do with the fact that I used the Seeb lab’s pipette/pipette tips.
• I have other chip results, but did not take screen shots at the time – will follow up with those, but for the time being all files are saved in the repo: laura-quantseq/data/library-prep

Results for samples ran for 16 cycles

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

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:

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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