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.
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.
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.
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.
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.
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
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
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?
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.