DNA Isolation – Geoduck gDNA for Potential Illumina-initiated Sequencing Project

We were approached by Cindy Lawley (Illumina Market Development) yesterday to see if we’d be able to participate in some product development. We agreed and need some geoduck DNA to send them, in case she’s able to get our species greenlighted for use.

Isolated DNA from ctenidia tissue from the same Panopea generosa individual used for the BGI sequencing efforts. Tissue was collected by Brent & Steven on 20150811.

Used the E.Z.N.A. Mollusc Kit (Omega) to isolate DNA from two separate 50mg pieces of ctenidia tissue according to the manufacturer’s protocol, with the following changes:

• Samples were homogenized with plastic, disposable pestle in 350μL of ML1 Buffer
• Incubated homogenate at 60C for 1hr
• No optional steps were used
• Performed three rounds of 24:1 chloroform:IAA treatment
• Eluted each in 50μL of Elution Buffer and pooled into a single sample

Quantified the DNA using the Qubit dsDNA BR Kit (Invitrogen). Used 1μL of DNA sample.

Concentration = 19.4ng/μL (Quant data is here [Google Sheet]: 20161221_gDNA_qubit_quant

Yield is low (~1.8μg), but have enough to satisfy the minimum of 1μg requested by Cindy Lawley.

Evaluated gDNA quality (i.e. integrity) by running ~250ng (12.5μL) of sample on 0.8% agarose, low-TAE gel stained with ethidium bromide.

Used 5μL of O’GeneRuler DNA Ladder Mix (ThermoFisher).

Results:

Overall, the sample looks good. Strong, high molecular weight band is present with minimal smearing. However, there is a smear in the ~500bp range. This is most likely residual RNA. This is surprsing since the E.Z.N.A Mollusc Kit includes n RNase step. Regardless, having intact, high molecular weight DNA is the important part for this project. Will prepare to send remainder (~1.5μg) of geoduck to Illumina with other requested samples.

Data Management – Integrity Check of Final BGI Olympia Oyster & Geoduck Data

After completing the downloads of these files from BGI, I needed to verify that the downloaded copies matched the originals. Below is a Jupyter Notebook detailing how I verified file integrity via MD5 checksums. It also highlights the importance of doing this check when working with large sequencing files (or, just large files in general), as a few of them had mis-matching MD5 checksums!

Although the notebook is embedded below, it might be easier viewing via the notebook link (hosted on GitHub).

At the end of the day, I had to re-download some files, but all the MD5 checksums match and these data are ready for analysis:

Final Ostrea lurida genome files

Final Panopea generosa genome files

Jupyter Notebook: 20161214_docker_BGI_data_integrity_check.ipynb

DNA Isolation – Ostrea lurida DNA for PacBio Sequencing

In an attempt to improve upon the partial genome assembly we received from BGI, we will be sending DNA to the UW PacBio core facility for additional sequencing.

Isolated DNA from mantle tissue from the same Ostrea lurida individual used for the BGI sequencing efforts. Tissue was collected by Brent & Steven on 20150812.

Used the E.Z.N.A. Mollusc Kit (Omega) to isolate DNA from two separate 50mg pieces of mantle tissue according to the manufacturer’s protocol, with the following changes:

• Samples were homogenized with plastic, disposable pestle in 350μL of ML1 Buffer
• Incubated homogenate at 60C for 1.5hrs
• No optional steps were used
• Performed three rounds of 24:1 chloroform:IAA treatment
• Eluted each in 50μL of Elution Buffer and pooled into a single sample

Quantified the DNA using the Qubit dsDNA BR Kit (Invitrogen). Used 1μL of DNA sample.

Concentration = 326ng/μL (Quant data is here [Google Sheet]: 20161214_gDNA_Olurida_qubit_quant

Yield is good and we have more than enough (~5μg is required for sequencing) to proceed with sequencing.

Evaluated gDNA quality (i.e. integrity) by running ~500ng (1.5μL) of sample on 0.8% agarose, low-TAE gel stained with ethidium bromide.

Used 5μL of O’GeneRuler DNA Ladder Mix (ThermoFisher).

Results:

Overall, the gel looks OK. A fair amount of smearing, but a strong, high molecular weight band is present. The intensity of the smearing is likely due to the fact that the gel is overloaded for this particular well size. If I had used a broader comb and/or loaded less DNA, the band would be more defined and the smearing would be less prominent.

Will submit sample to the UW PacBio facility tomorrow!

Data Managment – Trim Output Cells from Jupyter Notebook

Last week I downloaded the final BGI data files and assemblies for Olympia oyster and geoduck genome sequencing projects. However, the output from the download command made the Jupyter Notebook files too large to view and/or upload to GitHub. So, I had to trim the output cells from that notebook in order to render it usable/viewable.

The notebook below details how I did that and also examines the original version of that jumbo notebook to give some idea of what the command outputs were, for posterity.

Jupyter Notebook: 20161214_docker_notebook_trimming.ipynb

We received info to download the final data and genome assembly files for geoduck and Olympia oyster from BGI.

In total, the downloads took a little over three days to complete!

The notebook detailing how the files were downloaded is below, but it should be noted that I had to strip the output cells because the output from the download command made the file too large to upload to GitHub, and the size of the notebook file would constantly crash the browser/computer that it was opened in. So, the notebook below is here for posterity.

qPCR – RLOv DNA helicase and XenoCal prophage on Ab Endo Water Filters

Stan Langevin was interested in seeing if the RLOv (phage) and/or the prophage portal genes were detectable in water samples from Lisa’s Ab Endo project.

Ran qPCR on the following samples that Lisa selected:

DNA from water filters collected in 2010. DNA isolated 20120111:

• CP 0M A
• CP 0M B
• MA 0M A
• MA 0M B
• PSN 0M A
• PSN 0M B
• RM A
• RM B

DNA from water filters collected in 2011. DNA isolated 20140822:

• AM Drain 2B
• PCI SRI PC 1B

RLOv_DNA_helicase master mix calcs are here (Google Sheet): 20161213 – qPCR RLOv DNA Helicase

XenoCal prophage master mix calcs are here (Google Sheet): 20161213 – qPCR XenoCal phage portal

RLOv_DNA_helicase standard curve from 20151224.

All samples were run in duplicate. Plate layout, cycling params, etc. can be seen in the qPCR Report below.

Results:

RLOv_DNA_helicase
qPCR Report (PDF): Sam_2016-12-13 14-52-05_CC009827_RLOv_helicase.pdf
qPCR Data File (CFX): Sam_2016-12-13 14-52-05_CC009827_RLOv_helicase.pcrd

XenoCal prophage
qPCR Report (PDF): Sam_2016-12-13 14-52-05_CC009827_XCprophage.pdf
qPCR Data File (CFX): Sam_2016-12-13 14-52-05_CC009827_XCprophage.pcrd

• RLOv DNA helicase amplified in all samples EXCEPT the two samples from 2011. These two samples were negative for the RLO (see Ab Endo sheet “water 2011″).
•  XC prophage amplfied inconsistently (i.e. replicates did not match/amplify) in only three samples. Additionally, the melt curve of one of those samples differs from the other two. Based on the inconsistencies in technical reps, I should probably repeat this, but technical reps across all of the RLOv DNA helicase samples are very tight, suggesting that my technique was fine (it would be odd if my technique faltered only on ALL of the XC prophage samples)…

RLOv DNA HELICASE

XENOCAL PROPHAGE

Paperpile vs Zotero for bibliographic citations in scientific coauthorship

Having recently felt some limitations of my $96/year Overleaf Pro account (both in collaborative writing and bibliographic citation) while preparing my recent PeerJ publication, I found myself last week pushing a new group of collaborators to try co-authoring within Google Docs (rather than their preferred, old-school exchange of .docx files). It quickly became apparent that using Zotero and/or exported bibtex files to insert citations and build a bibliography in Docs wasn’t going to be simple (for me or the Word users). One method of inserting from bibtex in Google Docs looked clunky to say the least and hadn’t been updated for about a year. Instead of trying to hack Zotero and Google Docs together, I found glowing recent reviews of Paperpile — a bibliographic manager that is tightly integrated with Google Docs and Drive through a cloud-based app and the Paperpile Chrome extension. I decided to give the free trial of Paperpile a go. It felt natural because a few months ago I (somewhat reluctantly) took the plunge and migrated from the opensource world of Thunderbird and Firefox to the proprietary world of Gmail and Chrome. Part of that was driven by some slight frustration I felt with having to have the Zotero stand-alone program running when collecting references via the Zotero extension for Chrome. I was also motivated by the realization that I am paying$60/year for 6 Gb of Zotero storage when Paperpile personal costs \$36/yr and uses the 15Gb of free Google Drive storage.

I signed up using my Google account and immediately found myself invited to pile on some papers.  How pleasantly surprising to find that importing references (and attached PDFs) was an option in the “Add Papers” button’s dropdown menu!  In the time it took me to make a cup of coffee (15 minutes), the app had imported my entire shared ~1/3 of my 4,000-reference Zotero library (with PDFs).  To get it to import my private shared group library I had to follow the instructions for changing the default permissions in the Paperpile-Zotero API key.

I’ll report on how it goes editing in Docs with Paperpile next week, but I’m immediately struck by two benefits of the GUI.  First, when you search in Google Scholar you get an indication of whether or not a search result is already in your Paperpile.  That’s a feature I’ve requested of the Zotero devs, but it’s not yet manifested.  I was surprised to see that quite a few references were missing — even from searches of keywords and topics about which I think of myself as an expert!  Secondly, in the Paperpile app it is a breeze to select multiple references (e.g. a suite you’ve just collected) and organize them — first by dragging and dropping into a folder, and then by dragging tags onto the group.  In comparison, I could open the shared library in the Zotero stand-alone and know that any references I collected with the Zotero Chrome extension would be added there, but sometimes I forgot to check and the references ended up in some random folder of my general Zotero library.  I could fix that by dragging and dropping, but sometimes it was confusing and files got accidentally deleted in multiple folders inadvertently…  Tagging in Zotero is clunky at best.  I haven’t discerned how to tag multiple files at once, so I just go through them one at a time — which is a big time sink when I collect a bunch from behind paywalls via a trip to the local University library.

I have to mention that Overleaf is trying to build better collaborative tools, but most of their work is still in beta and there hasn’t been a ton of evolution in the last year that I’ve used it.  Here’s a screengrab of where they are heading with their comment insertion (ok in Rich Text, but messy in LaTex), as well as their History and Revisions tab (recent activity; timeline; and the old Labeled versions).

We’ll see whether they can hold a candle to Google Docs simultaneous editing, conversational views of comments, and change notifications…