Tag Archives: graphs

qPCR – Black Abalone DNA with Varying Levels of RLO/RLOv

Carolyn & Stan Langevin have agreed that the DNA helicase qPCR should be tested on 10 black abalone DNA extractions that fall into multiple levels of the Friedman Lab’s withering syndrome histology scoring.

Earlier today I identified samples at three different histology scoring levels of RLO: 0, 1, & 2.

Here’s the list of samples that will be qPCR’d. There were only eight samples that had histology scores of 2 in both PE and Dg.

RLO/RLOv 0 RLO/RLOv 1 RLO/RLOv 2
06:5-18 06:5-35 06:5-31
06:5-30 06:6-32 06:5-32B
06:50-04 06:6-39 06:6-46
06:50-05 06:6-42 06:6-49
07:12-01 06:6-44 08:3-05
07:12-02 06:6-52 08:3-07
07:12-03 06:6-54 08:3-15
07:12-04 06:50-08 08:3-16
07:12-07 06:50-10
07:12-09 07:12-18

 

Ran qPCR using the RLOv DNA helicase standard curve from 20151106.

All samples were run in duplicate on the CFX96 (BioRad).

Master mix calcs are here: 20151120 – qPCR RLOv Black Abs

Plate layout, cycling params, etc. can be seen in the qPCR Report (see Results).

Results:
qPCR Report (PDF): Sam_2015-11-20 15-00-27_CC009827.pdf
qPCR Data File (CFX96): Sam_2015-11-20 15-00-27_CC009827.pcrd

Quick summary of the results:

  • 50% of the RLO/RLOv 0 score samples are positive for RLOv DNA helicase. Will talk to Carolyn to see if she has withering syndrome qPCR data for these samples to compare RLOv-positive samples with WSN-positive samples. If not, will run withering syndrome qPCR.
  • All RLO/RLOv 1 & 2 scored samples are positive for RLOv DNA helicase
  • All RLO/RLOv 2 scored samples come up before the standar curve; these should be diluted and re-run.
  • Standard curve isn’t perfect (the 3 copy sample is throwing it off).

 

STANDARD CURVE AMP & SCATTER PLOTS

 

 

RLO/RLOv 0 AMP PLOTS

 

 

RLO/RLOv 1 AMP PLOTS

 

 

RLO/RLOv 2 AMP PLOTS

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Finishing out with the mechanical

Currently there is a pretty robust spreadsheet and over the past few days Jake has cranked through some reps to see how the oysters that were mechanically stressed hold up. Below is how these data are integrated.

Jake_Heare_Research_Central__8_10_2015_EF1d_Mech_Stress_2_rep_qPCR_1B821B44.png

Currently the 8-10 samples (yellow) have been skipped, but we might have a look.

First up is having a look at the new HSP 70 reps. The mechanical data still needs some better resolution. Hopefully teh 8-10 samples migh shed some light.

Screenshot_8_17_15__9_53_AM_1B821ECC.png

Next up is two more reps of PGEEP4.
Looks good, and given the doubling of reps we could easily drop ‘outlier’ runs and still have triplicates, tight triplicates.

Screenshot_8_17_15__10_15_AM_1B822404.png

GRB2… now good to go, with the first pair of reps dead on.

BMP2…. could use some help from the other mechanical stress runs
Screenshot_8_17_15__11_03_AM_1B822F48.png

TLR….seemed like a relatively easy fix (besides no detection) in that just needed to correct for machine.
Screenshot_8_17_15__11_10_AM_1B8230E7.png

And the correction indicating the fact that expression was so low, only able to be detected by Opticon
Screenshot_8_17_15__11_17_AM_1B82327D.png

The 8-15 runs had minimal control and temp samples with mechanical run in dups.

Screenshot_8_17_15__11_24_AM_1B82344E.png

This needs a little carressing before integrating into data.
This should be in two columns with empty cells where no samples were run- in this order.

H_C_1
H_C_2
H_C_3
H_C_4
H_C_5
H_C_6
H_C_7
H_C_8
N_C_1
N_C_2
N_C_3
N_C_4
N_C_5
N_C_6
N_C_7
N_C_8
S_C_1
S_C_2
S_C_3
S_C_4
S_C_5
S_C_6
S_C_7
S_C_8
H_T_1
H_T_2
H_T_3
H_T_4
H_T_5
H_T_6
H_T_7
H_T_8
N_T_1
N_T_2
N_T_3
N_T_4
N_T_5
N_T_6
N_T_7
N_T_8
S_T_1
S_T_2
S_T_3
S_T_4
S_T_5
S_T_6
S_T_7
S_T_8
H_M_1
H_M_2
H_M_3
H_M_4
H_M_5
H_M_6
H_M_7
H_M_8
N_M_1
N_M_2
N_M_3
N_M_4
N_M_5
N_M_6
N_M_7
N_M_8
S_M_1
S_M_2
S_M_3
S_M_4
S_M_5
S_M_6
S_M_7
S_M_8

8-15 run update

Actin
Screenshot_8_17_15__3_55_PM_1B8273B6.png

Mechanical looks decent after correcting.

However taken together, bothersome the difference in crude expression levels.
Screenshot_8_17_15__3_57_PM_1B827441.png

Carm

Had some wet works issues

Jake_Heare_Research_Central__8_15_2015_CARM_CTM2_reps_qPCR_1B8274C8.png

H2AV
Assuming correction is correct- still a big differences in mechanincal here- could be real.

Screenshot_8_17_15__4_11_PM_1B8277A0.png

PGRP
No correction required as these were run on cfx, downside is some reps are not detected that would have been picked up with Opticon.

Do not see be shift in expression of mechanical stressed.
Screenshot_8_17_15__4_18_PM_1B827900.png

CRAF
Easy correction but skeptical of some very, very low Cts

Screenshot_8_17_15__4_25_PM_1B827AA2.png

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Bioinformatics – Trimmomatic/FASTQC on C.gigas Larvae OA NGS Data

In another troubleshooting attempt for this problematic BS-seq Illumina data, I’m going to use Trimmomatic to remove the first 39 bases of each read. This is due to the fact that even after the previous quality trimming with Trimmomatic, the first 39 bases still showed inconsistent quality:

 

Ran Trimmomatic on just a single data set to try things out: 2212_lane2_CTTGTA_L002_R1_001.fastq.gz

Notebook Viewer: 20150506_Cgigas_larvae_OA_trimmomatic_FASTQC

Jupyter (IPython) notebook: 20150506_Cgigas_larvae_OA_trimmomatic_FASTQC.ipynb

Results:

Trimmed FASTQ: 20150506_trimmed_2212_lane2_CTTGTA_L002_R1_001.fastq.gz

FASTQC Report: 20150506_trimmed_2212_lane2_CTTGTA_L002_R1_001_fastqc.html

You can see how flat the newly trimmed data is (which is what one would expect).

Steven will take this trimmed dataset and try additional mapping with it to see if removal of the first 39 bases will improve the mapping.

 

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DNA Quantification – Claire’s Sheared C.gigas Mantle Heat Shock Samples

I previously checked Claire’s sheared DNA on the Bioanalyzer to verify the fragment size and to quantify the samples. Looking at her notebook, her numbers differ greatly from the Bioanalyzer, possibly due to the fact that the DNA1000 assay chip used only measures DNA fragments up to 1000bp in size. If her shearing was incomplete, then there would be DNA fragments larger than 1000bp that wouldn’t have been measured by the Bioanalyzer. So, I decided to quantify the samples on the NanoDrop1000 (ThermoFisher) again.

 

Results:

Spreadsheet: 20150226_Claire_sheared_Emma_1000ppm_OD260s

 

 

 

Comparison of NanoDrop1000 and Bioanalyzer measurements.

Sample NanoDrop (ng/μL) Bioanalyzer (ng/μL)
2M sheared 48.03 16.28
4M sheared 190.96 58.52
6M sheared 141.56 42.98
2MHS sheared 221.93 32.45
4MHS sheared 257.48 43.82
6MHS sheared 202.02 51.12

The NanoDrop is known to overestimate sample quantities due to the indiscriminate nature of UV spectrophotometry and that could be the reason for the large discrepancy between the two measurements (i.e. RNA carryover may lead to overestimation). As such, I’ll quantify the samples using a fluorescence-based assay for double stranded DNA tomorrow in hopes of getting the most accurate measurement.

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qPCR – C.gigas COX1/COX2 Tissue Distribution

Performed qPCR using pooled cDNA from 20110311. Pooled 2uL from each of the following samples groups: Dg 3hr C, Gill 1hr C, Gill 1hr E, Mantle 3hr C, and Muscle 3hr C. Master mix calcs are here. Plate layout, cycling params, etc can be found in the qPCR Report (see Results). Primers sets run were:

EF1_qPCR_5′,3′ (SR IDs: 309, 310)

Cg_COX1/2_qPCR_F (SR ID: 1192) + Cg_COX1_qPCR_R (SR ID: 1191)- Target = COX1

Cg_COX1/2_qPCR_F (SR ID: 1192) + Cg_COX2_454align1_R (SR ID: 1190) – Target = COX2

Results:

qPCR Report (PDF)

qPCR Data File (CFX96)

Graphs were generated using the BioRad CFX Manager v2.0 software. Expression was normalized to EF1. Also to note, gene efficiency was assumed as 100% by the software since no standard curve was run on the plate. As such, analysis of this data may not be exact.

It’s clear by examining the graphs that the primers being used to differentiate COX1 and COX2 (since they share a common primer: SRID 1192) are differentially expressed. This indicates that the primer sets are indeed amplifying different targets as hoped. This was the primary intention of this qPCR. However, we also now have an idea of tissue distribution of the two genes, as well as their response to V. vulnificus exposre after 1hr. Next step is to perform this qPCR on all the individuals from this experiment as well as the different tissues.

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Data Analysis – Young Lab ABI 7300 Calibration Checks

All runs (3 runs were conducted) were created using a master mix containing C.gigas gDNA (either 50ng or 100ng), 1X Promega qPCR Master Mix, 0.2uM each of forward/reverse primers (18s; Roberts SR ID: 156, 157). The master mix was mixed well and 10uL were distributed in each well of ABI plates. Plates were sealed with ABI optical adhesive covers.

It should also be noted that this analysis was only done with a single primer set and was not tested on any other qPCR machines. This can easily be done if it is desired, however I think one of the issues still being observed with the machine is sample-independent (see Results section below).

Results:

Here’s an extremely quick and dirty analysis of what these qPCR runs have revealed (across the entire plate, 3 plates of data):

Avg. Range of Cts Across Plates – 1.70

Avg. Std. Deviation of Cts Across Plates – 0.352

Based off of the graphs below (particularly the Ct vs Well Position plot), my conclusion is that the machine reads plates inaccurately in Rows A, B, C, F, G, & H. Rows D & E exhibit the most consistent well-to-well readings and, potentially, could be used for qPCR.

The entire work up (which includes a breakdown of each well position relative to each other) is here (Excel Workbook .xlsx). Below are screen captures of one of the three plates (as an example, since all looked the same) that were used for analysis of the amplification plots, melt curves and Ct vs Well Position and a quick description/assessment of what I have observed.

The amplification plot (below) clearly shows the type of spread in Cts across an entire plate that was observed in each run, as well as a large range in fluorescence detected (Rn) in each well.

The melt curve (below) reflects the large range of detected fluorescence seen in the amplification plot. Additionally, some wells exhibit small “bumps” between 75C and 80C. This provides more evidence for a problem with well-to-well consistency.

A graph of Ct vs. Well Position (below) reveals some enlightening information. From looking at this plot, it’s clear that the machine reads from A1 to A12, then B1 to B12 (reads by row, not column) and so on. This plot reveals that most of the variation seen in Ct values occurs in the two rows closest to the edge of the plate, and within those rows, the middle wells’ Cts are more similar to the Cts observed throughout the rest of the plate.

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Genomic PCR – C.gigas cyclooxygenase (COX) genomic sequence

Attempt to obtain full genomic sequence for C.gigas COX. PCR set up/cycling params/etc are here. Primer set combinations(master mixes) are as follows:

MM01 – Cg_COX_5’UTR_3_F (SR ID: 1150) + Cg_COX_1009_R (SR ID: 1147) Band size w/o intron = ~1000bp

MM02 – “” + Cg_COX_1545_R (SR ID: 1148) Band size w/o intron = ~1540bp

MM03 – “” + Cg_COX_2138_R (SR ID: 1149) Band size w/o intron = ~2135bp

MM04 – Cg_COX_982_F (SR ID: 1151) + Cg_COX_1545_R (SR ID: 1148) Band size w/o intron = ~550bp

MM05 – “” + Cg_COX_2138_R (SR ID: 1149) Band size w/o intron = ~1130bp

MM06 – Cg_COX_1519_F (SR ID: 1146) + Cg_COX_2138_R (SR ID: 1149) Band size w/o intron = ~620bp

Results:

Bioline Hyperladder I used for marker. Gel is loaded with template samples at the far left of each master mix group with two no template controls (NTC) in the remaining two wells of each master mix group. All NTCs on the gel are clean.

All bands surrounded by a green box were excised from the gel.

MM01, MM02 and MM03 – The smallest expected band (i.e. no intron present) would have been 1000bp in MM01. Instead, we see faint banding of multiple sizes less than 1000bp in both MM01 and MM02. MM03 fails to produce any bands. This potentially suggests a couple of things. Firstly, the multiple banding produced in MM01 and MM02 suggests that the PCR conditions lead to some non-specific priming and should be optimized. Secondly, the fact that no bands were produced that are equal to or larger than the “no intron size” suggests that intron(s) may exist in the 5′ region of the COX gene and are large enough that the polymerase had insufficient time/ability to amplify.

MM04 – Three distinct bands were produced: 2000bp, 1500bp and 550bp. The size of band that would have been produced had an intron NOT been present would have been ~550bp. A band of this size was produced in this PCR reaction. However, two additional bands were produced. The presence of these two larger bands lends additional evidence for the existence of multiple isoforms of COX (which is also supported by the fact that multiple isoforms of COX are known to exist in most other species). The 2000bp band was excised and purified with Millipore Ultra-free DA spin columns and stored @ -20C until a sequencing plate is readied.

MM05 – A distinct band of ~5000bp was produced. This is significantly larger than the “no intron size” of ~1130bp, suggesting the presence of an intron. This band was excised, but not purified due to the low concentration of DNA in the gel. The gel slice was stored @ -20C until this PCR reaction could be repeated to accumulate sufficient product for sequencing.

MM06 – A distinct band of ~2200bp was produced. This is significantly larger than the “no intron size” of ~620bp, suggesting the presence of an intron. The band was excised and purified with Millipore Ultra-free DA spin columns and stored @ -20C until a sequencing plate is readied.

The PCR reactions reveal the presence of intron(s) in the COX gene we’re investigating as well as providing evidence for the existence of multiple isoforms in C.gigas. Since the PCR products that have been excised for sequencing are so large, additional primers will need to be designed closer to the introns in order to generate smaller products that can be fully sequenced. Additionally, all reactions using the primer designed to anneal in the 5’UTR of COX (SR ID: 1150) failed to produce useful results. This is either due to poor performance of the primer under these reaction conditions or due to the presence of a large intron in the 5′ region of the gene. Additional reverse primers will be designed that anneal closer to the 5′ portion of the COX gene in hopes of characterizing the 5′ genomic sequence better.

After speaking with Steven today about the potential existence/”discovery” of multiple isoforms, he decided to map the newly-released C.gigas 454 NGS data to the existing COX coding sequence in GenBank (FJ375303). The alignment is shown below.

The two 454 reads that map closest to the 5′ end of the COX coding sequence match up nearly perfectly, with periodic SNPs. The remaining 454 reads that map to the COX coding sequence are very different and provide very good evidence of a previously unidentified isoform of COX in C.gigas. Primers will be designed from both the existing COX sequence in GenBank (FJ375303) and the other potential isoform. These primers will likely be used in both qPCR and for sequencing purposes, in order to be able to distinguish and characterize both isoforms. Additionally, BLASTing will be performed with the sequences from both isoforms to evaluate how they match up with existing COX isoforms in other species.

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qPCR – COX qPCR Vibrio Exposure Response Check

Used COX primers (SR IDs 1060, 1061) and cDNA from 20080327, which consisted of 7 control gigas gill and 7 vibrio-exposed (24hrs) gigas gill samples, labeled as C# and VE#, respectively. The experiment was a 24hr. exposure live Vibrio vulnificus, parahaemolyticus Cf = 2.055×10^11 (6.85×10^7 Vibrio cells/oyster).
Note: Used a free sample of 2x Brilliant III Ultra Fast SYBR Green QPCR Master Mix (Stratagene) for this qPCR. Mixed components and set up cycling params according to the manufacturer’s recommendation for the BioRad CFX96.

Master mix calcs are here. Plate layout, cycling params, etc. can be see in the qPCR Report (see Results).

Results:

qPCR Report (PDF).

PCR Miner analysis is here. There appears to be an increase in COX expression in samples exposed to Vibrio sp. (see graph below), however, I have not determined if the results are significant.

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Opticon Calibration

Distributed 50uL of FAM calibration dye to wells. Ran out of dye!!

Looking back at old purchasing logs, it turns out we need 2 orders of dye packs to have enough for a 96-well plate.

Will cap existing plate with dye, wrap in foil and store @ -20C.

Ordered an additional pack of dye (Cat# 10006046; not available online, must call BioRad to order). Will ship on Monday. Will finish calibration procedure on Tuesday (20100928). Ugh.

Results:

Empty Plate:

Plate with dye (presumably calibrated):

After running the calibration protocol with the dye, all the wells should show consistent fluorescence levels. Clearly, they do not. Oddly enough, there appears to be a cyclical pattern across the wells of low -> high -> low fluorescence. The calibration protocol advises that if the wells do not exhibit consistent fluorescence across wells, then the plate should be read again. The graph above is the 2nd reading, which appears to be the same as the 1st. Conclusion is that the Opticon 2 is not working correctly and will contact BioRad for price quotes on repairs.

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qPCR – Hard Clam Primers on cDNA from yesterday

Performed qPCR on Friedman Lab machine targeting immune-related genes in hard clam. Rough plate layout/master mix calcs are here. qPCR report from Friedman Lab machine is here (PDF) and shows cycling params, plate layout and Cts.

Results:

CFX96 Data file is here.

The following primer sets failed to produce an amplicon:

Mm_TRAF6

Mercenaria_Rel

TLR

STI

CytP450-like

Raw fluorescence data was extracted (No baseline subtraction) and processed with PCR Miner. Data workup/analysis is here. Here is a graph of those primer sets producing an amplicon. All were normalized to actin, which exhibited the smallest amount of deviation across all three samples of the normalizing/housekeeping genes analyzed.

As a preliminary run with these genes, there are a number of promising candidates that could yield some interesting data regarding the physiological response of hard clam to exposure to QPX.

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