Yaamini’s Notebook: Another Skyline Fail

The DIA pipeline has been quite a #strugglebus

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It’s unfortunate that the strugglebus website no longer works :/ Let’s go through our current struggle:

  • I showed Emma my error checking results
  • She said my error rate was pretty high (and I agreed)
  • She looked at my blib and Laura’s blib with people from her lab (a.k.a. the Skyline creators)
  • They found asterisks at the end of some of the blib sequences that could affect Skyline’s ability to peak peaks
  • Another problem may be that brecan reports the same peptide multiple times, and Skyline doesn’t like that

Overall, this means that my current Skyline output isn’t valid anymore. I can’t work on MSstats or target identification using Skyline data, but I can still look through the literature for proteins of interest. Emma and her team are working on fixing Skyline for our files, so I just have to wait! After everything’s fixed, I will need to check error rates again for the same peptides.

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Katie’s Notebook: Getting Started!

Successfully made it to my first day at the Roberts Lab yesterday! I attended the lab meeting and logged into all the sites and platforms that I will need access to this summer. I left for the day with some readings to catch myself up on basic information pertaining to Olympic and Pacific Oysters. I also did a lot of browsing of Yaamini’s and Laura’s notebooks to learn about their current projects!

Yaamini’s Notebook: Protein Extractions Round 2, Part 2

More cowbell? More samples.

I started thinking about my next round of protein extractions a few weeks ago, but now I have a better plan. I’m going to focus solely on the first outplant. I also noticed that the second ouptlant Case Inlet organisms had the lowest sample size. There were only five in the bare treatment, and one in the eelgrass treatment. For this reason, using only the first outplant would give me a larger sample size and allow me to understand the differences between all sites and eelgrass conditions.

I’m going to extract proteins in two blocks of 25 samples each:

Table 1. Proteins to extract. The bolded samples are those I will extract in the first block.

Site Condition 1 2 3 4 5
PG B O25 O83 O54 O51 O52
PG E O31 O71 O78 O56 O30
FB B O36 O70 O43 O40 O35
FB E O64 O46 O32 O24 O49
WB B O129 O126 O135 O121 O122
WB E O140 O145 O147 O131 O144
SK B O111 O120 O99 O96 O113
SK E O103 O101 O106 O102 O91
CI B O11 O13 O16 O21 O22
CI E O01 O08 O10 O06 O04

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Yaamini’s Notebook: Protein Extractions Round 2, Part 2

More cowbell? More samples.

I started thinking about my next round of protein extractions a few weeks ago, but now I have a better plan. I’m going to focus solely on the first outplant. I also noticed that the second ouptlant Case Inlet organisms had the lowest sample size. There were only five in the bare treatment, and one in the eelgrass treatment. For this reason, using only the first outplant would give me a larger sample size and allow me to understand the differences between all sites and eelgrass conditions.

I’m going to extract proteins in two blocks of 25 samples each:

Table 1. Proteins to extract. The bolded samples are those I will extract in the first block.

Site Condition 1 2 3 4 5
PG B O25 O83 O54 O51 O52
PG E O31 O71 O78 O56 O30
FB B O36 O70 O43 O40 O35
FB E O64 O46 O32 O24 O49
WB B O129 O126 O135 O121 O122
WB E O140 O145 O147 O131 O144
SK B O111 O120 O99 O96 O113
SK E O103 O101 O106 O102 O91
CI B O11 O13 O16 O21 O22
CI E O01 O08 O10 O06 O04

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Yaamini’s Notebook: Heat Shock Practice

It’s always good to practice your methods of torture.

On May 12, I figured out my methods for the heat shock experiment I wnat to conduct with the C. gigas we brought back from Manchester. The reason why I want to conduct a heat shock is because I want to see if different stressors methylate different regions of the genome, and if a combination of stressors will create a unique methylation pattern.

The first thing I did was create a hot water bath with saltwater from our flow-through system. Although the water bath has a temperature reading on it, I also added a thermometer to double check. The temperature I aimed for was 40 ºC.

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After checking that the temperature was at 40ºC, I grabbed four oysters from our set-up…

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…and plopped them in the water bath!

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I started the heat shock treatment at 4:17 p.m., and let it run for an hour. At 5:17 p.m., I killed the heat and took the oysters out. The temperature on the water bath and on the thermometer read around 40ºC.

img_7384img_7385

I checked mortality everyday since then, and they’re still alive! Looks like one hour at 40ºC should work for a heat shock.

Things I need to do before Monday:

  • Find a heater for the 100 L tanks
  • Figure out how many oysters to shock
  • Find a time to start heating the water before the day of the shock

The bigger question, however, is whether or not I’m going to do a heat shock at all! Because I have 45 oysters for each OA condition, and not all of those oysters will be fertile when I’m ready to spawn and the sex ratio of oysters can’t be predicted, I don’t want to use oysters I could have spawned with. I may apply a heat shock to some of the oysters that were kept on the ambient line continously, and then cross those with oysters from the OA treatment. Either way, I’m going to expose spat to both OA and heat shock conditions, so I’m still going to assess the effect of multiple stressors on the next generation.

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Sean’s Notebook: EpiTEome and Bismark revisited.

Steven found a new program for simultaneously finding transposable element insertion points as well as their methylation levels called epiTEome and asked me to see how applicable it was to our data. I read through some papers, and it looks like it should work, and give us some interesting information regarding CHH context methylation at transposable element insertion points. I’ve been trying to get it installed on my laptop, but some of the perl modules won’t install correctly. I’ll update this with a guide once it’s behaving properly.

Also, Mackenzie Gavery came by and offered some suggestions about our mapping efficiency issue in Bismark. We apparently have PBAT libraries, that are the complement of the strand of interest. This is obvious, once you know what to look for, in the FastQC report due to the sequence files being G depleted, as opposed to C depleted as one would expect in bisulfite treated samples. I’m trying Bismark again on a single file with the --non_directional flag, which should output all 4 strand possibilities so we can see if anything changes.

On the Hyak front, platanus assemble finished after running only overnight. Which is a little disturbing since the last time I ran it, it ran for a week before finally crashing due to lack of memory. I guess that’s the power of 500gb of ram and a pair of Skylake Xeons? Next we move on to the scaffolding step, which will hopefully be as fast!

Update:

Finished the Bismark run on that one file, and went from 8% mapping to 28% mapping. Pretty huge increase!

Bismark report for: trimmed-2112_lane1_ACAGTG_L001_R1.fastq (version: v0.16.3)
Option '--non_directional' specified: alignments to all strands were being performed (OT, OB, CTOT, CTOB)
Bismark was run with Bowtie 2 against the bisulfite genome of /home/srlab/Documents/C-virginica-BSSeq/genome/ with the specified options: -q -N 1 --score-min L,0,-0.2 --ignore-quals

Final Alignment report
======================
Sequences analysed in total:	12260444
Number of alignments with a unique best hit from the different alignments:	3439005
Mapping efficiency:	28.0%
Sequences with no alignments under any condition:	6508309
Sequences did not map uniquely:	2313130
Sequences which were discarded because genomic sequence could not be extracted:	4

Number of sequences with unique best (first) alignment came from the bowtie output:
CT/CT:	194297	((converted) top strand)
CT/GA:	177441	((converted) bottom strand)
GA/CT:	1574633	(complementary to (converted) top strand)
GA/GA:	1492630	(complementary to (converted) bottom strand)

Final Cytosine Methylation Report
=================================
Total number of C's analysed:	72855963

Total methylated C's in CpG context:	15487306
Total methylated C's in CHG context:	5008319
Total methylated C's in CHH context:	15081081
Total methylated C's in Unknown context:	5

Total unmethylated C's in CpG context:	2557484
Total unmethylated C's in CHG context:	14183192
Total unmethylated C's in CHH context:	20538581
Total unmethylated C's in Unknown context:	78

C methylated in CpG context:	85.8%
C methylated in CHG context:	26.1%
C methylated in CHH context:	42.3%
C methylated in Unknown context (CN or CHN):	6.0%

Sean’s Notebook: Water Samples at DNR in Olympia

vwMin

After many trials and tribulations, I’ve finally started running real honest to god TA samples from Hollie’s geoduck experiment. It took a few CRM runs for the new probe on the titratior to settle down, but I got three reps within 10 TA units of each other (They were reading ~20 units higher than expected, so I’ll likely just use an offset to account for that). Progress!

Now only a few hundred more samples to go…

On the Hyak front, after finishing Andrew’s salmon run, I’ve started running the platanus assembler on the Oly Illumina data. After Platanus finishes, we’ll try to integrate the long read PacBio stuff via Redundans. Hopefully PBJelly will finish the gap filling process so we will have two assemblies to compare.