Category Archives: Ava's Abalone RLO Transmission Experiment

Ava's Abalone RLO Transmission Experiment

DNA Quantification – Ava’s RLO Trasmission Samples

Quantified DNA extractions from Ava’s samples that I isolated earlier this month, as well as some older samples that I hadn’t quantified yet.

Used the Roberts Lab Qubit 3.0 and the Qubit dsDNA BR Kit (broad range). Used 5uL of template for the first and third groups and 1uL of template for the second group (see Results below).

All data was added to the master extraction spreadsheet (Google Sheet): ava_abalone_master_extraction_list

Results:

20171101_ava_rlo_quantification_qubit_01 (Google Sheet)

20171101_ava_rlo_quantification_qubit_02 (Google Sheet)

20171101_ava_rlo_quantification_qubit_03 (Google Sheet)

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DNA Quantification – Ava’s RLO Trasmission Samples

Quantified DNA extractions from Ava’s samples that I isolated earlier this month, as well as some older samples that I hadn’t quantified yet.

Used the Roberts Lab Qubit 3.0 and the Qubit hsDNA Kit (high sensitivity). Used 5uL of template for all samples.

All data was added to the master extraction spreadsheet (Google Sheet): ava_abalone_master_extraction_list

Results:

20171026_Ava_RLO_quantification_qubit_01 (Google Sheet)

20171026_Ava_RLO_quantification_qubit_02 (Google Sheet)

There were 65 samples with concentrations that were too high for the high sensitivity assay. Will re-quantify this samples using the broad range assay.

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qPCR – Ava’s RLO Transmission Samples

Ran five plates of qPCRs on bunch of DNA I extracted ealier this month.

Standard curve was p18RK7 from 20161128.

All samples were run in duplicate.

Master mix calcs are here (Google Sheet): 20171026_qPCR_WSN1_Ava_Samples

Plate layouts, cycling params, etc. can be seen in the corresponding qPCR Reports (see Results below).

Baseline threshold was manually set to 580, based on Lisa’s development of the withering syndrome qPCR assay.

Results:

Curves looked great on each plate. See images at bottom of post.

NOTE: Plate #5 had a missed rep; I think this was due to a bad pipette tip. I excluded the 3e4 point of the curve in the analysis.

PLATE #1

qPCR Report (PDF): Sam_2017-10-26 07-31-12_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-26 07-31-12_CC009827.pcrd

PLATE #2

qPCR Report (PDF): Sam_2017-10-26 09-02-31_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-26 09-02-31_CC009827.pcrd

PLATE #3

qPCR Report (PDF): Sam_2017-10-26 10-32-10_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-26 10-32-10_CC009827.pcrd

PLATE #4

qPCR Report (PDF): Sam_2017-10-26 12-01-33_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-26 12-01-33_CC009827.pcrd

PLATE #5

qPCR Report (PDF): Sam_2017-10-26 13-31-05_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-26 13-31-05_CC009827.pcrd


PLATE #1


PLATE #2


PLATE #3


PLATE #4


PLATE #5

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qPCR – Ava’s RLO Transmission Samples

Ran five plates of qPCRs on bunch of DNA I extracted ealier this month.

Standard curve was p18RK7 from 20161128.

All samples were run in duplicate.

Master mix calcs are here (Google Sheet): 20171025_qPCR_WSN1_Ava_Samples

Plate layouts, cycling params, etc. can be seen in the corresponding qPCR Reports (see Results below).

Baseline threshold was manually set to 580, based on Lisa’s development of the withering syndrome qPCR assay.

Results:

Curves looked great on each plate. See images at bottom of post.

NOTE: Plate #5 had a missed rep; I think this was due to a bad pipette tip. I excluded the 3e4 point of the curve in the analysis.

PLATE #1

qPCR Report (PDF): Sam_2017-10-25 08-35-04_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-25 08-35-04_CC009827.pcrd

PLATE #2

qPCR Report (PDF): Sam_2017-10-25 10-05-57_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-25 10-05-57_CC009827.pcrd

PLATE #3

qPCR Report (PDF): Sam_2017-10-25 11-36-44_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-25 11-36-44_CC009827.pcrd

PLATE #4

qPCR Report (PDF): Sam_2017-10-25 13-10-13_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-25 13-10-13_CC009827.pcrd

PLATE #5

qPCR Report (PDF): Sam_2017-10-25 14-40-08_CC009827.pdf
qPCR Data File (CFX96): Sam_2017-10-25 14-40-08_CC009827.pcrd


PLATE #1


PLATE #2


PLATE #3


PLATE #4


PLATE #5

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DNA Isolation – Ava Withering Syndrome Transmission Study Tissues

Isolated DNA from 17 red abalone digestive gland tissue samples.

Tissue was weighed, minced with a razor blade, and transferred to 2mL snap cap tube containing 1mL of InhibtEX Buffer.

DNA was extracted using the QIAmp Fast DNA Stool Mini Kit (Qiagen) following the manufacturer’s protocol with the following options:

Minced tissue was incubated at 70C O/N.

These samples were actually incubated O/N on 20171012. I dropped the rack containing these tubes after the initial incubation and these tubes popped open and spilled.

Since I used all of the tissue, I have nothing to go back to. I’ve attempted to recover as much of the remaining supernatant in each of these tubes. I brought the volume of each tube up to 600mL with Inhibitex Buffer and proceeded with the isolations.

Followed “human DNA analysis” protocol (to maximize sample recovery)
Eluted DNA with 100μL Buffer ATE
Sample information is in this spreadsheet (Google Sheet): ava_abalone_master_extraction_list

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DNA Isolation – Ava Withering Syndrome Transmission Study Tissues

Isolated DNA from 96 red abalone digestive gland tissue samples.

Tissue was weighed, minced with a razor blade, and transferred to 2mL snap cap tube containing 1mL of InhibtEX Buffer.

DNA was extracted using the QIAmp Fast DNA Stool Mini Kit (Qiagen) following the manufacturer’s protocol with the following options:

Minced tissue was incubated at 70C O/N
Followed “human DNA analysis” protocol (to maximize sample recovery)
Eluted DNA with 100μL Buffer ATE
Sample information is in this spreadsheet (Google Sheet): ava_abalone_master_extraction_list

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DNA Isolation – Ava Withering Syndrome Transmission Study Tissues

Isolated DNA from 144 red abalone digestive gland tissue samples.

Tissue was weighed, minced with a razor blade, and transferred to 2mL snap cap tube containing 1mL of InhibtEX Buffer.

DNA was extracted using the QIAmp Fast DNA Stool Mini Kit (Qiagen) following the manufacturer’s protocol with the following options:

Minced tissue was incubated at 70C O/N
Followed “human DNA analysis” protocol (to maximize sample recovery)
Eluted DNA with 100μL Buffer ATE
Sample information is in this spreadsheet (Google Sheet): ava_abalone_master_extraction_list

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DNA Isolation – Ava Withering Syndrome Transmission Study Tissues

Isolated DNA from 58 red abalone digestive gland tissue samples.

Tissue was weighed, minced with a razor blade, and transferred to 2mL snap cap tube containing 1mL of InhibtEX Buffer.

DNA was extracted using the QIAmp Fast DNA Stool Mini Kit (Qiagen) following the manufacturer’s protocol with the following options:

  • Minced tissue was incubated at 70C O/N
  • Followed “human DNA analysis” protocol (to maximize sample recovery)
  • Eluted DNA with 100μL Buffer ATE

Sample information is in this spreadsheet (Google Sheet): ava_abalone_master_extraction_list

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DNA Isolation – Ava Withering Syndrome Transmission Study Tissues

Isolated DNA from 26 red abalone digestive gland tissue samples.

Tissue was weighed, minced with a razor blade, and transferred to 2mL snap cap tube containing 1mL of InhibtEX Buffer.

DNA was extracted using the QIAmp Fast DNA Stool Mini Kit (Qiagen) following the manufacturer’s protocol with the following options:

  • Minced tissue was incubated at 70C O/N
  • Followed “human DNA analysis” protocol (to maximize sample recovery)
  • Eluted DNA with 100μL Buffer ATE

Sample information is in this spreadsheet (Google Sheet): ava_abalone_master_extraction_list

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Data Aggregation – Ava’s Complete Sample List

I received Ava’s master sheet of all the samples she collected for this project. I needed to aggregate a full list of the samples I’ve previously extracted DNA from, so that I can compare to her master sample list and generate a list of the remaining samples that I need to extract DNA from..

Here are the files I needed to work with (Google Sheets):

The files required multiple formatting steps in order to produce accession numbers that were formatted in the same fashion across all three sheets. This was needed in order to be able to successfully merge all of the sheets into a single sheet containing all of the data, which will make it easy to sort, and generate a list of samples that need to be extracted.

Text file manipulations were performed in a Jupyter notebook, which is linked below. All files were downloaded from Google Sheets as tab-delimited files prior to working on them.

Jupyter Notebook file: 20170831_ava_ab_samples_aggregation.ipynb
Jupter Notebook on NBviewer: 20170831_ava_ab_samples_aggregation.ipynb

Now that we have the tables formatted, we can use the accession number as a common field by which to combine the two tables. This will allow easy sorting and identification of the remaining samples that I need to extract. I’ll do this by using SQLite3.

Use SQLite3 (in Linux Ubuntu):

Change to directory containing files:

cd ~/Dropbox/Sam Friedman Lab/tmp

Start SQLite3:

sqlite3

Set field separator as tab-delimited:

.separator "t"

Create databases by importing files and providing a name for corresponding databases:

.import ava_master_ab_list_formatted.tsv master_list
.import Ava_WS_Transmission_DNA_Extractions_all.tsv extracted_list

Set output display mode to tabs:

.mode tabs

Set output display to include column headers:

.headers on

Set the output to write to a file instead of the screen:

.output 20170905_master_extraction_list.tsv

SELECT statement to combine the two tables:

SELECT * FROM (SELECT * FROM master_list UNION ALL SELECT * FROM extracted_list) s GROUP BY accession_number ORDER BY accession_number;

The SELECT statement above works in the following fashion:

Uses a sub-query (contained in the parentheses) that combines all of the rows in both tables and creates an intermediate table (that’s the s after the sub-query). Then, all of the columns in that intermediate table are selected by the initial SELECT * FROM and organized by the GROUP BY clause (which combines any rows with identical values in the accession_number column) and then sorts them with the ORDER BY clause.

After that’s finished, we want to reset the output to the screen so we don’t overwrite our file:

.output stdout

The output file is here (Google Sheet): ava_abalone_master_extraction_list

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