Kannapedia.net is getting a good face-lift.
Samples now have variant tables with annotation on their impact to the gene.
There is also an IGV integration. You need IGV installed locally but the Start|Jump links will open up you BAM file in IGV.
You must have IGV open and then click the start link.
The sample's BAM will show up for viewing in IGV.
Once open, you can use the jump link to move swiftly around to each variant. This is a variant in THCAS.
You can jump to other variants in the same gene. In this case we have one non-synonymous variant in phase with a synonymous variant in THCAS.
Cannabinoid synthase genes are cute but some folks can answer those questions with HPLC.
How about flowering genes?

This sample has a disruptive in frame deletion on a late flowering gene. And it's very rare in the population.
Looks to be heterozygous....
But its never this simple in cannabis.

Let's look at what other damaging variations it has.
7 Damaging inframe deletions or insertions (indels) in Early and Late flowering genes.
When it comes to Indels, IGV can be very helpful to inspect the read frequency and if there appears to be any read mismapping with short reads. They all look real and diploid.
Here is another one in AAE1-2. This gene is involved in making the pre-cursors to cannabinoid synthesis.

It is not just a simple presence or absence of the cannabinoid synthase genes. One has to pay close attention to variants up stream in the pathway as well.

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More from @Kevin_McKernan

14 Jan
1\But but... you ran it to 40-45 cycles?
This is an argument that needs dissection.

The protocols you see in EUAs are speaking to the Camera time not the Call time. To call at 37Ct... you need to see the slope of the curve out to 40. It doesn't mean they are calling at 40. Image
2/Summertime positivity rates cannot be used as a proxy for wintertime false positive rates.

The virome in the winter is rich in HCoVs not present in the summer. I would assume the background microbiome is as well. Image
But we tested the Primers against HCoV in our exclusion analysis!

Sure.... but Just 4.

We just witness the S-gene amplicon drop out in the second season of C19 and we should expect HCoVs to have similar diversity. Image
Read 12 tweets
11 Jan
We have written another 60 page dissection of the Drosten PCR protocol.

This should end all of the criticism of the initial retraction request not having enough “wet-lab” proof.

20 peer reviewed papers showing catastrophic problems.

@Eurosurveillanc

cormandrostenreview.com/downloads Image
Ironically, The origin of this quote is even debated but rightly describes the problem in society of Fake News.

It starts with Fake Science.

We will never end fake science if don’t address the lack of transparency in peer review. It must be decentralized and subject to audit. Image
The largest fatality in C19 was the public trust in science.

They have every right to be pissed.

For too long peer-review has remained ancient, ossified and secret.

It is not fit for our current world of rapid communication and transparency.

🦕 thrashing in tar pits Image
Read 10 tweets
11 Jan
I have finally read this in full.
Have not hit 255 references.

Anyone who tries to debunk this in a day... sorry. This would take many weeks to fact check

The PCR section is on point.
However, there is not enough attention paid to the significant false negatives also at play
While a lot has been written about false positives, the nasal swabs can vary 1,000-10,000 fold in their collection efficiency (Dahdouh et al) and many jurisdictions are using human gDNA internal controls to normalize for this large variance.
This variance implies many false negatives mixed in with many false positives.

More sensitive PCR tests won’t fix false negatives that are a result of poor swabs.

They aggravate the problem as track and trace becomes a completely futile boondoggle.
Read 4 tweets
11 Jan
We spend a lot of time calibrating our qPCR assays to replication competent organisms.

When we do this, we don't simply use a single culturing system as the results can vary significantly depending on the media used.

Here is DRBC(left) vs PDA (right) with Aspergillus niger. Image
You can see many more colonies on PDA.
This is likely due to DRBC having Chloramphenicol in it.

Chloramphenicol is an antibiotic with know inhibitory effects on Yeast and Molds.
ncbi.nlm.nih.gov/pmc/articles/P…
ncbi.nlm.nih.gov/pmc/articles/P…
pubmed.ncbi.nlm.nih.gov/25497707/
This begs the ? of which plating system to calibrate qPCR to. Also begs the ? of what a "gold standard" is.

95% of microbes cant be cultured, leaving DNA based methods as the only universal gold standard for absolute detection of wild samples.
See...
osf.io/vpxe5 Image
Read 4 tweets
9 Jan
🙏🏼 for the follows.
My goal is to simply share what I know about genomics with the public when it matters most.

I rarely get technical refutations but embrace the errors so as to correct.

The best they seem to be able to fire back is ad hominens and associative fallacies
From 1996 to 2000 I worked tirelessly to get as much as human genome public as possible.

Our team then built a DNA sequencer that dropped the price of DNA sequencer several orders of magnitude.

Published open access.

genome.cshlp.org/content/19/9/1…
In 2000 we started a genomic company called Agencourt.
It became the largest commercial seq shop at the time.
Turned profitable in 18 months from start-up.

We also built DNA and RNA purification kits for viruses using SPRI

Some of these kits are in use today for C19 prep.
Read 19 tweets
8 Jan
If you are in the UK, this is the serial dilution of the test being run on you for C19.

For each 10 fold drop in Copies/ml, you should see a 3.3 increment in Ct.

What do you see?
Why does a 5000 copies/ml sample have a lower Ct than a 10,000 cp/ml sample? Image
The paper does speak to a spike in MS-2 control but this isn't a true internal control like RNaseP.
Spike-in internal controls are important for measuring assay drop out. They prove the PCR was functional.

But RNaseP controls which amplify human DNA/RNA harvested on the Swab..
These ICs are more important as you really cant quantitate viral load and make claims about S gene knock outs being higher copy number if you don't normalize the Swab collection and sample prep issues. These can vary 10-16 Cts according to Dahdouh et al.

medrxiv.org/content/10.110…
Read 6 tweets

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