Today I went through the DNase-free plan with 4 of the extracted crab samples. There was initially quite a bit of DNA, then after I used the Turbo DNA-free Kit, there was significantly less DNA. The Bioanalyzer still didn’t look super great… detail in post. Also, I’m working through kallisto and have abundance files - working to figure out next steps in order to hopefully create a heatmap of differential expression between the infected and uninfected crabs (combining day 12 and day 26). Details in post.

DNA-free plan and results

GitHub Issue: #792

Plan:

  1. Run four samples from the above group on Qubit using DNA HS
  2. Use Turbo DNA-free Kit on those samples
  3. Run those samples on Bioanalyzer
  4. Re-run those samples on Qubit using DNA HS

Results:

  1. Done –> results
  2. Done (Did the routine DNase treatment)
  3. Done (screenshots below) ran each of the 4 samples twice (##-a and ##-b)
  4. Done - samples were eluted in ~40-45ul
    (ran dsDNA HS results; ran RNA HS results)

Electropherogram:
img

Gel:
img

Summary:

There was a LOT less DNA in the samples after the DNA-free Kit process. However, it resulted in pretty dilute RNA because I had to add enough RNA-free water in the beginning in order to have 50ul of sample for the reagents. Also, the RNA still didn’t band very well on the bioanalyzer. I think Steven said we’ll just pool them and send them off the NWGC… will confirm next week.

I’ll have to re-extract those 11 samples that I worked with this week on the qubit and bioanalyzer becuase there is not much material left!! Not a big deal. I can do that Monday or Friday (want to have enough time to prepare for GSS talk next Thursday as well).

Working for new analyses for GSS: Kallisto

Sam helped me a TON today.

He helped me set up hummingbird in FTR 213 so that I have my own user account, and that made everything a lot easier. He also helped me get git working from command line so that I can keep all of my work on GitHub in project crab.

Here’s my jupyter notebook: 2019-11-06-bairdi-kallisto.ipynb

There are so many cells because each sample (4 total) has 2 samples for both lanes (4 files total per sample).

I made individual directories in project-crab/analyses for each sample (number starting with 3#####) and each lane.
project-crab/analyses

Each directory contains three files:

  • abundance.h5
  • abundance.tsv
  • run_info.json

The interesting stuff is in the abundance.tsv files because it has all the count data.

Next steps are to create a table combining all the count data for all the samples, and then using that in DESeq2 in R to create a heatmap… I think. Still trying to figure that out…

Notes:

GitHub Issue #790