We are not far away from routinely #genome sequencing every newborn suspected of having a rare/hereditary disorder.
In fact, there will be a point, especially in single-payer health care systems, where it'll be logistically preferable to routinely #genome sequence every newborn.
What will it take? Management, machines, and money (3M), in that order: 1/ A management system that handles sample collection, carries on the sequencing effectively, and makes the result available: we are not far away from this in, e.g. the UK's (@NHS+Wales/Scotland/NI).
We are much better at this now than, say, 1-2 years ago. See a successful system of coordinating this for lower throughput sequencing but high numbers of samples in #COVID19cogconsortium.uk
2/ Machines: we need higher global throughput of #NGS than currently: bit.ly/ngsspecs. Even if dedicating current install base #NovaSeqs to newborn sequencing, we would still need 8.2x more machines to keep up worldwide. But @MGI_BGI, @PacBio and @nanopore will grow up.
E.g.
A/ @MGI_BGI has shown new tech that's many-fold higher throughput than a #NovaSeq (#DNBSEQTx / Surface coating tech).
B/ @nanopore#PromethION48 can now produce 1.0-1.2x the throughput of a #NovaSeq and the machine/flowcell production can be scaled up significantly.
C/ @Pacbio#Sequel2e and iterations on path to produce lots of contiguous, haplotype-aware genome assemblies (see results from @lh3lh3 Hifiasm et al.)
D/ Other technologies can be used to "contiguate" / fill-in the gaps from short-reads, e.g. @bionanogenomics (see @genomeark).
So a possible scenario: a single-payer system (e.g. @NGS or #MedicareForAll) where the newborn's genome is sequenced to high quality, and results are available to the health system during their entire lives (from cradle to grave omics). From then onwards, the info is used
to check for newborn/infant rare diseases (0-1yo), children's cancer (1-5yo), testicular cancer (15-30yo), colorectal cancer screening (45+yo), etc. Lots of benefits to the system for regular #LiquidBiopsy monitoring using #epigenomic profiling.
Then there is a second wave of Precision Medicine and Omics that will benefit from large-scale Population Genomics. I have to confess that I lost touch with these in the last few years, so someone else will have to give colour to these here.
Again, this is not far away, and as George Church described in a recent podcast: we are now underestimating scientific advances in the general public, compared to the perception we had in the 1950-60s, so all this is happening, and will be part of our daily lives soon.
The is a tech bubble in the stock market, and it will burst soon. The question is, which of the #NGS companies below will come out stronger from the stock market tech bubble bursting? $ILMN $PACB @nanopore@MGI_BGI
Looking at the NASDAQ for the last 5 years, there was a big drop in March 2020, triggered by the first wave of worldwide #COVID19. The tech bubble was already inflated back then. But the market recovered with a matter of weeks, and kept climbing up.
By 9/8/2020 there was another attempt of a correction, mostly #COVID19 related, but again, with a highly inflated tech bubble, the market recovered and quickly jumped another 1,000 points (around 11,800):
#JPM2021#BiologicalDynamics@BiodynSD My Highlights: I'll cover this from the point of view of #LiquidBiopsy and #Epigenomics profiling, which is where my interest lies: their next-gen multiomics intro is about exosomes (and EVs, exosomal vesicles?)
The slide about Verita Biomarker Isolation Platform seems to be about isolating cells, with the right-most image showing "Visualized EV", which I presume is exosome vesicles
Later on, they do mention methylation markers, above the exosomes image, so I wonder if it's only DNA inside or bound to the exosomes?
#JPM2021@GenapSys My Highlights: I think it's fair to say I am more excited than most about this #NGS company, as I see them as an example of how to enter the market while keeping a small profile ($249M raised so far).
They now are aiming at 2021 to ship two new chips: 50MM read chip and 144MM sensor chip (not sure what the difference is between read/sensor).
They show a slide of price per Gb with #Illumina products as a reference, and their products now lined up, I think, for the first time with price per Gb info. Lowest will be the 144MM chip at ~$27/Gb.
#JPM2021#ExactSciences#LiquidBiopsy My highlights: I will focus on the liquid biopsy / #epigenomics profiling side of the presentation, which is where my interest lies: Exact described the data from Thrive multi-cancer screening, based on 'mutation+protein'
The details they gave on their other recent acquisition, #BaseGenomics are illuminating: they will use their bisulfite-free methylation profiling method for their Cologuard 2.0 test for CRC, but also for the multi-cancer test, and possibly the MRD test as well.
So this means that #ExactSciences intend to upgrade their tech in two steps: from current Cologuard 1.0 to a new test that includes Thrive's tech, and then a second upgrade using the #BaseGenomics#Epigenomics profiling tech.
Some stats and facts about the #Takifugu#rubripes assembly by @genomeark: this is the third iteration of the assembly. The first was completed in 2002. There was another iteration done in 2011. Why was the pufferfish sequenced so early? A lot has got to do with Sydney Brenner...
Indeed, as we can see in this archived version of @ensembl, the Fugu genome was the 5th vertebrate genome to be completed, after human/mouse/rat and zebrafish. Even though zebrafish is widely used as a model organism, Sydney Brenner argued that Fugu was worth sequencing ...
... The reason is that Sydney Brenner was passionate (obsessed?) with gene duplications and functional diversification. I.e. a gene duplicates in two copies, and over time, each copy can specialize in doing something slightly different. ...
#JPM2021@TwistBioscience My Highlights: back to the #DNAWrite field. TwistBio chip: 1M oligos but only as centralised factory setting.
Expanding to a new factory in Portland (roadmap 2022) to reduce TAT. Also mentioned the "long tail" of Clonal Ready Gene Fragments.
They have a few slides on #DNAasStorage with a denser chip in prototype phase where they think they can archive 1Tb for $100 (pay once, archive forever*) which, if my calculations are correct, would allow for 10-12 years of @awscloud Deep Glacier or similar mth/GB=0.00099*12*1E3