Talk on AMR genes by @johnpenders at Maastricht UMC+ (I hope it's the right one), and how these increase/decrease for example with intercontinental travel patterns. Travelers to South-Eastern Asia acquire the mcr-1 gene.
Mcr-1 gene is identified and well-known from 2015, but the patterns of AMR migration started earlier
My conclusions: very similar parallel patterns between the acquisition of AMR genes with travel and the spread of #COVID19 variants across the globe: the former doesn't kill millions of people but the #NGS technology to track them is very equivalent.
Next talk Prof. Miguel Esteban, CAS: single-cell transcriptomic atlas of Macaca fascicularis. Showing the large factory-like DNBSEQT10 in the picture
Older people overreact to #SARSCoV2 infection in a cytokine storm that affects prognosis. Tocilizumab brings down storms to manageable levels. Correlates with genome-wide markers in blood cells but also surprisingly ADHD.
Next talk is from Dr. Ao Chen, BGI Group: "Large field of view-spatially resolved transcriptomics at nanoscale resolution"
Spatio-Temporal Enhanced Resolution Omics-Sequencing (Stereo-seq) at nanoscale resolution - Ao Chen. Current methods include bit.ly/scspatial
The 6-step stereo-seq method at @MGI_BGI uses the same nano ball technology as the #DNBSEQ technology *and* the same type of flowcells. The slide can be as large as the flowcell (i.e. massive).
Specs of @MGI_BGI stereo-seq : the size of the palm or a monkey brain. Subcellular localization (500nm / 0.5um)
Comparing DNB blood vessels of different sizes vs 100um resolution (right). Example mouse embryo (16.5 days).
Stepless zoom-in analysis in stereo-seq (a-la google maps). Combining with imaging data.
Introns can be subcellular localized within the cell nucleus. Some of the introns can be secreted outside of the nuclei, but the majority stay (as textbooks say) inside the nuclei.
Very large FOV and resolution means billions of nanoballs which can be analysed in 3D within the slice. Digital pathology (liver cancer) applications.
More applications to come, some demoed on this website: stereomap.cngb.org
As we approach Q30+ on now 4 competing platforms, 2 short read and 2 long read platforms, it's a useful reminder that only PCR-free preps benefit from high quality base-calling, as any PCR-based method incorporates errors wrt the original material.
More importantly, any PCR-based method devised so far also erases #epigenetic marks, which can only be read in conjunction with the 4-base alphabet if it's from a PCR-free method.
So if your application where to benefit from, say, a Q33 better than a Q31 modal base-calling, first ask yourself: have I got enough DNA for a PCR-free prep?
My highlights of the @10xGenomics#Xperience2021 event. The list of products keeps growing, I would highlight Chromium Connect as an underappreciated tool to bring the products up another level of throughput. Important as with #NGS, it won't take long to go from n=1 to n=96+.
#CellPlex species-agnostic multiplexing up to 12 samples: not dissimilar to products such as TotalSeq, but baked-in so that it's been tested to work with the rest of the workflow.
Going close to 1M cells, the #ChromiumX brings about 100x fold throughput increase, all marked with 'HT' in the Kits. I'd be interesting to know how the different #BodyAtlas projects embrace this and for what.
There are a bunch of Twitter accounts, real or fake to some extend, doing the rounds every time someone tweets about #NGS#genomics or #LiquidBiopsy. They seem clearly wanting to hype a certain listed company
in a pump-and-dump fashion, which is not new, and existed before the GameStop/Robin Hood saga. I chose to mute the accounts, so my threads are not polluted from these accounts. I may start blocking them if it gets worse.
I am not muting the ticker for the company itself, as I am genuinely interested in following their developments, and they are not responsible for the behaviour of the pump-and-dump accounts.
I received an email from @NebulaGenomics today, with a discount code for a $299 genome sequencing offer. Which made me wonder: are they using the already cheaper @MGI_BGI#DNBSEQTx sequencing for this? It would mean they can run it at cost or make a small profit from it.
Then you realise there is "analysis" charge on top of the $299 which you can't untick, so the $299 #WGS 30x genome goes up to $499. Still, at $499, you would find it difficult to make money if you were @NebulaGenomics and you were using something like an @illumina#NovaSeq
Epigenomic biomarkers are becoming more established for #LiquidBiopsy and #CancerScreening, and we have seen the big players positioning themselves in this #epigenomics race recently.
Catching signs of #cancer early is crucially important to the disease management and survival rates, so the question is: how can we find out if there is something wrong going on early enough, ideally in a low-cost assay that can be performed regularly on healthy individuals?
@sbarnettARK Catching signs of #cancer early is crucially important to the disease management and survival rates, so the question is: how can we find out if there is something wrong going on early enough?
@sbarnettARK The first generation of high-throughput technologies was predicated on finding mutated (tumor) DNA in the individual's body (somatic), different from their (normal) DNA. Tumor/Normal (T/N) comparisons of the individual's samples, biopsies or ctDNA will indicate if there