Gordon Sanghera - Opening
Intro music - Arctic Monkeys
- A band that was around when most ONT staff were alive
- In 2005, they went straight in at number 1
- No sales, no marketing, used myspace to allow people to download one sing
- It was a bunch of kids
- Since then, there's been no need to pander to the large organisations
Sequencing landscape
- So many things have been proposed for nanopore sequencing
- The oil industry has problems with microbes
- The shipping industry has problems with ballast tanks
Statistics
- The conference has 600 people - 500 customers, and 100 Nanopore people (with blue lanyards)
- Goal of ONT: Allowing anyone to sequence anything anywhere
- There are 7,000 MinIONs; 140 GridIONs; 40 beta PromethIONs; all done with community-based campaigns
What it all means
- We are at the cusp of the fourth industrial revolution
- We are seeing things that are in sci-fi films
- Uber's actual goal: delivering anything to anyone anywhere
- We are bringing testing closer to the customers
- People can use Air B&B instead of hotels
- With nanopore, we are enabling the Internet of Living things
- There are 12500 sequencing centres in the world
- When people are provided access to real-time tools, we open up new opportunities
- Genoscope has 85 coral species
- General theme: More people, more diverse applications
Service Provision
- KeyGene is the first authorised PromethION service provider
- Providing service to the lettuce industry
Zoe McDougall
- The Dunbar Number - 150; about the number that were in the first nanopore conference
- Need to work out how to help people
- Ninja programming schedule
- Repeating some breakout sessions
- A workshop to improve the digital community (Andy Davies)
- 300 people have downloaded the software App
- Interact button allows people to ask questions during plenary sessions
Angela Brooks
- Every cell has the same genome, but different cell types have different functions
- The transcriptome is what distinguishes cells
Polyadenylated RNAs
- Have non-coding as well as protein-coding
- Can be edited or modified; over 100 types of modifications exist
- Limitations of short-read sequencing
- Fragmentation
- Conversion into cDNA
- doing PCR (even a problem with long-read cDNA)
Nanopore Sequencing
- Sequencing is 3´ to 5´ (not typical)
- RNA consortium was formed to look at human cell lines
- 6 universities sequencing GM12878
- The same cell culture was sent to five institutes, a separate culture was done by Birmingham
- Can go to github to see the data
- 13 million native RNA reads, 24 million cDNA reads
Observations
- Native RNA was longer than cDNA
- Error rates about the same
- Good correlation in gene expression levels
- Also good correlation with Illumina
- Birmingham clustered separately when using PCA
- Same sample clustered well together
Read fragmentation
- A lot of reads that seemed to be fragmented
- MTCO1
- Read length doesn't drop over time (so there's no fragmentation happening within the flow cell)
- 45% of the reads were full length
- 20% were partial due to artefacts (e.g. basecaller truncating the read)
- 35% other partial reads, maybe due to sample prep, or degredation of RNA
Full-length assembly
- Using orthogonal information to distingush full-length transcripts
- e.g. ChipSeq - looking for the promoter region. If not correlated, then it's probably not full-length
- Using short-read support for read correction
- Can look at full length and compare to annotation
- Can pick up novel transcripts
- Largest high-confidence transcript: 10313 nucleotides with 48 exons
How many sequenced reads are needed?
- At about 5M reads, the number of transcripts start to plateau
- Transcripts keep getting detected at high coverage (more than 75k transcripts)
Challenges
- Allele bias
- Also looking at polyA tail lengths [see polya_estimator]
- Generally 30-150 nucleotides
- Detecting m6A, found that it was kmer-dependent
- More differences for some, but not others
- Remaining challenge: hard to distingush full from partial RNA
In-depth analysis of 100 reads
- Done manually by Mark Akeson
Questions
- Looked at squiggle for capturing the 5´ cap (methods in progress)
- Using minimap
- Longest read from titin (aiming for 100 kb)
Dan Turner
ONT Applications Team
- Team in Oxford, New York, San Francisco
- Oxford: sample prep
- New York / San Francisco: showcase
- Concerned with what's going in and what's coming out
- Not all library prep options are good ones
- Need to be clued up about the analysis at the start
- Vision: End-to-end workflow selector
Worked example: Structural variation across the rabbit genome
- First question: what is your end goal / aim?
- Priorities can be re-ordered
- Options with crucial information
- Presented with extraction options (e.g. Qiagen genomic tip)
- Then bioinformatics
- Then a PDF protocol is created
- Bespoke, not about how to run the MinION
- All extraction protocols available on the website
Sample prep concerns
- If analysis can't use short fragments at all, beter off getting rid of them
- Working on syringe-based method
- How clean the prep is is important
- There's now a table of common contaminant concentrations
- For example, can get up to 20% ethanol contamination (i.e. could get away with wine)
London Calling Conference Demonstrations
- ONT is sequencing Sarasin's minnow
- Want to generate about 100Gb reads, read N50 of about 15-20kb
- Including control species
- Doing library sample prep on the VolTRAX
VolTRAX
- Portable sampling and library preparation device
- New video: devices in a backpack
- Find some poo on the side of a track, curious to know what it is
- Excess liquid into binding and lysis buffer
- Feed through ecotip to get rid of cell debris
- Was too clean
- Dry out
- Elute from filter
- VolTRAX; load DNA and other reagents
- Remove sample from extraction port, ready for MiNION
- Use FASTQ file for BLAST
- Discover that the poo sample was from a rat!
Direct RNA Sequencing
- A quick plug for the paper; see Dan Garalde
Tombo Software tool
- Signal deviation gives evidence of modifications
- "I don't know what the modification is, but I can see that it is modified"
- Now supports m5C
- Can also see DNA modifications
- AUC for m5C: 0.99; m6A: 0.98 (compared to existing method)
- Still optimising Tombo to work with the PromethION
- Have found CHG methylation, as well as CHH methylation
Structural Variation
- There are more structural variants in the genome than SNPs
- Duplication detection works with nanopore sequencing
- e.g. 1kb stretch, finding six copies in tandom
- Does it detect structural variation that isn't there?
- Some sequence contexts don't work with 1k chunks for base calling
- With 10k chunks, there is 90% support for found variants
- Ideally, want to do sequencing without any chunking at all
Pore-C
- Long-read chromatin confirmation capture
- Using long reads, not short reads
- Get a lot more information about interactions
- Plot the interaction map
- Only did with 1.5X coverage
- Can use information to verify assemblies
- The last of the analyses have been done
Breakout -- Assembly
Antony Bolger
Todd Michael
Danny Miller
Panel Discussion
- Cheaper / easier to use nanopore + Illumina; only need to use 30X for nanopore
- Nanopore + Illumina + Optical mapping
- Nanopore + Pore-C
- Should we error-correct reads prior to assembly?
- Canu still does metter on mammalian-type genomes, probably due to quality
- Reads passing the filter (Albacore/pass) produced the best assemblies
- If filtering, removing shorter reads is better than best quality reads
Lightning Talks / Day 1 (James Brayer)
Logan Mulroney
[No video?]
- Direct RNA sequencing issue: can't catch the last few bases
- When strand is sequencing through and motor lets go, bases move through quickly
- Add a few bases onto the end of the read
- Done on yeast RNA
- Helped by Dan Garalde, Mark Akeson
Kai Sohn [poster #1]
- Superman, Pope John Paul II, Muhammed Ali all died from sepsis
- Most methods to identify pathogens are failing
- Using cell-free DNA to identify pathogens in the blood
- Clinical cohort, 11% positive, Illumina 71% positive
- Time to result: Illumina sequencing took 16h
- MinION is not designed for cell-free DNA, DNA is mostly of human origin
- Working with 5ng, more increased throughput about four times
- About 50% of the reads were accurate enough for a diagnostic measure
- Find reads from infecting pathogen within minutes; sequencing within 5h with clinical samples
- Better to collect the sample, but no clear sepsis marker
Jennifer Idol [poster #35]
- Works in a sequencing core, not a research lab
- Three samples from 1000 genomes project, needs 6G to [end out] the Puerto-Rican
- Uses optimised version of 1D kit
- Phenol-chloroform with Qiagen MaxTract tubes for long reads
- Have 30X coverage for all samples
- 460/600μg DNA GM19240, HG00514
- N50 40kb, 30kb
- Normal yield for about 4Gb per flow cell
- got 30X in about 2 weeks on a GridION
- Fresh extractions a lot better than old extractions
- Have new protocol with max read length up to 450kb
- Cost of 1 human genome at 30X was about $20-30,000
Nick Schurch [poster #29]
- Anya and Kasia are amazing Direct RNA Sequencing wizards
- Want to look at reliability, replicability
- Very similar to humans in terms of transcriptional complexity
- Consistently getting 1-2 million reads, 1.4 million aligned
- RuBisCo Activae, extremely highly expressed, 52,501 alignments
- Good splicing structure, most splices are novel and not supported in the official annotation
- To get to 2 million reads, use 1μg RNA, be super-careful in lab prep
- Consistently getting 1-1.2 million reads, about 850k aligned reads
Wouter de Coster [poster #17]
- Using PromethION in February
- Currently highest yield on PromethION (98Gb)
- NA19240 (Yoruban reference genome)
- Well-characterised
- 5 Flow cells, not all fantastic [59, 50, 29, 29, 72]
- Shearing gives substantially higher read yield
- Shearing gives a tighter read length distribution, shorter tail
- Making data public as PRJEB26791
- Blog post available now
- Developing workflow [nano-snakemaker]
- Sniffles detects more structural variation than nanoSV
Olga Francino [poster #11]
- Looking at microbial samples
- Using 16s variable regions
- Can we reach lower taxonomic levels with 16s?
- Full-length 16s (1500bp)
- Tested with mock community
- Tested with mastitis buffalo / milk samples
- 5 healthy, 6 subclinical
- Completely different betweeen the two samples
- 75% of the sequences were categorised down to species level
- Infective agent was Staphylococcus aureus
- [Excellent workflow image]
- 12 samples, need a flongle now
Clive Brown
Novel statements selected by David Eccles
- Live sample prep, sequencing, and WIMP analysis of Clive Brown's DNA by Ruth Moysey
- Voucher for Series D ASIC; longer run time, potentially 30 Gb from a single MinION
- ONT has a roadmap for moving to 500 Gb from a single PromethION flow cell (NovaSeq-busting prices)
- [Read-until is coming back [in anger]
- MinIT is orderable in the store
- Mk1C sequencer (MinION combined with MinIT) should be available December
- Epi2me will be embedded in MinIT, GridION, PromethION (local analysis workflows)
- Epi2me will be commercialised via MetriCoin (workflow currency, included with flow cell / kit purchases)
- New 1D² kit coming that uses UMIs in adaptors, increasing accuracy to Q20 and allowing amplicon sequencing
- Miyagi tool for combining reads from different pores for increased consensus accuracy
- Slightly mutated forms of R9.4 have been tested; could release a variant-pore flow cell in a few weeks if there is interest
- Flongle early-access begins now, released commercially in Q3
- Zumbador's official name is Ubiquibopsy (or Ubik tube)
- V2 VolTRAX (heat, PCR, 10 samples) is available for ordering in the store
- New SkunkWorx technology: a combined MinION + VolTRAX, dynamically embeds pores between droplets
- Too much novel stuff to summarise, see here
Introduction
- Next year O2 arena -- looks like a nanopore, fits 20,000 people
- Every year, I have been told that I need to do this: promised investors I would do a live demo.
- Have been spitting in tubes, but soomeone else will do the prep.
- Ruth Moysey takes a tubefull of spit from Clive.
Recap - get into rhythm
- Aim: Anybody to sequence anything anywhare
- Trying to make runnable outside labs
- real-time full-length reads
- ultra-low cost.
- In the past day, a few people have been demonstrating all features.
- This was a dream a few years ago.
Olbigatory nanopore slide
- An array of membranes on a chip that we designed
- catch DNA from solution
- stream through the pore
- generate tiny signals (a lot of work decoding) All asynchronous
- get a full-lenth read in a few seconds
- Electronics can be made small, cheap
- Design breaks the traditional mould - Would be stupid to make an electronic device with fluidics
- Also key for ONT was designing array in the factory
Other talks
- There have been a number of previous talks [by Clive]
- recently spoke about sub-1000 sequencing run; mostly on PromethION ($600)
- GridION conceived Feb last year, has been relatively successful
Platform
- Product line as it stands, all in-field
- MinION is the most established
- Out there GridION is doing well; easy to own, people using it as service
- PromethION - a beast of a machine, now out, runnable, generating pretty high yields
- Over 1000 Customers for GridION; We think we can ship within a week of an order.
- Certification program, growing quite rapidly
Grab bag
- In your bags is a token that gets you access to a slightly modified version of the MinION flow cell: a series D ASIC
- It's just better
- First design had a few faults, including current cross-talk; all things ate into yield
- This is a fixed-up version of the ASIC
- Can now enable very-long run times with sustainable yield of up to 100 hours
- Enables 30Gb on a MinION
PromethION
-
48 individually-controllable flow cells
-
144,000 concurrent independent nanopore channels
-
Can hot-swap
-
Designed for quite lumpy workflows
-
Can be run as a high-throughput sequencer, just like any other.
-
Now dependent on Ruth on the Maracas
-
Now dependent on You lot for reporting on what's happening on PromethION
-
Now out of the Early access phase; $160,000 starter pack
-
Can take box back
-
When you buy PromethION can have access to upgrades
-
Next version will run 48 flow cells
-
Have shipped 40 PromethION by this conference
-
should get to 60 by end of June.
PromethION Yields
- What do new customer yields look like?
- Most getting over 50 Gb (this was the target)
- Some getting over 60
- ONT is getting internally over 170 Gb
- A roadmap to move to 500 Gb per flow cell
- These are NovaSeq-busting prices, provided you get the yields.
- New flow cell: single channel. Also a redesign of the multi-channel flow cell.
- Will make sure that all of MinION kits will work on PromethION (RNA coming in June)
MinKNOW
- MinKNOW upgraded
- Very nice UI, innards of the GUI have been completely refactored.
- Thinking about things like read-until
- Including progressive unblock & dynamic voltage control, should increase data quality.
Progressive unblock
- Blockages when you shove DNA thought a hole. Single strand forms structures on the other side of the pore.
- Can unblock by inverting potential.
- The old software was the simplest thing that worked
- Unblocking was quite violent, would remove channels
- The new version doesn't destroy the channel; a more subtle, sophisticated version of unblocking the pore
- Probably a larger uplift in difficult samples.
- Have generally improved kit quality
Software
-
3-4 years ago pulled in software team to talk about Read Until
-
As DNA is going through the pore, can basecall and do something with it before it's gone through the pore
-
An in-silico selection
-
We wrote an API.
-
Entire innards of MinKNOW have been rejigged, read-until is coming back
-
balancing amplicons
-
Sequencing a certain region of human
-
Coming back in second-half of year, coming back in anger
-
Will be able to dynamically select molecules on the fly
MinIT
-
For MinION: Common complaint is the computer; that has caused a lot of trouble
-
Making a device called MinIT
-
It should be almost zero configuration.
-
Plug it in, connect it, pair your iPhone display, ready to sequence.
-
Can run off batteries. Can run off 12V supply.
-
Will put Guppy in there, will keep up with MinION basecalling, critical for ReadUntil
-
Also embedding Epi2Me.
-
Pretty confident that a large number of people will want a hand with analysis
-
MinIT Should be orderable today.
-
Have gone for GPUs in MinIT; going for neural-network based AI
-
A bunch of sequential matrix computations
-
Quite a large number of bioinformatics things can be optimised on the same hardware with the same performance.
-
MinION Mk1C - MinIT with the aility to load a flow cell, or flongle
-
Target December
-
Should be able to run a single flow cell without any external needs
-
It's the kind of thing a dentist can run
-
It also looks really cool
Epi2Me
-
A bioinformatics platform
-
Embedded workflows doing the kind of analyses that people want to run
-
Can be run in the cloud, or workflows can come to the computer: GridION, PromethION, MinIT.
-
Lots of reasons, 1) a lot of computing in the boxes.
-
Expertise in optimising on GPUs
-
Sometimes people don't want to pipe data over to the over side of the world
-
We think it's more usable now, can upload custom reference, will provide data storage
-
We will release Epi2Me on MinIT in Q3 - a MinIT with MinION will do this locally in Q3
Epi2Me Commercialisation
- Will be commercialised
- When you buy a flow cell; have invented something called MetriCoin
- When you buy flow cells or reagents, will get MetriCoin, can use to run workflows
- People who don't have bioinformatics support will have access to bioinformatics services
Chemistry improvements
- Platform performance is now much closer to what Clive tweets
- Customer runs by kits is converging, variance is decreasing
- Largely due to kit simplification
- Early kits had a cholesterol tether; it sticks to everything that is hydrophobic
- We have been removing that from all of our kits.
- Generally customer performance has started to converge with nanopore.
Read Length
-
Fragment length is read length; largely in customer hands
-
Most platforms, the optics / chemistry conks out
-
If you can present with long reads, it will sequence it
-
Some of thought-leading developers have tried to present pore with enormous, intact lengths of DNA
-
The developers found a bug in the software, ONT software was chopping up reads
-
In principle, if you can do 2 Megabases, can do 20 Megabases
-
Challenge is whole-chromosomal sequencing
Yield Drop-off
-
Initial software that classified data was the simplest that worked
-
Software misclassified reads, which would degrade the data
-
Low-complexity regions, rectified in next software release in June
-
Need to Scale data, scaling can be biased, to be fixed (fix went out 2 weeks ago)
Unblocking
-
Extracting from chitinous insect won't be the same as a drop of blood
-
Not the whole story, can get DNA out
-
There have been issues with things sticking to tubes
-
If initial yield was high, would drop off suddenly
-
Chickens do this
-
Software that you need to kick out DNA is different for different samples
-
Some kinds of DNA form secondary structure as they get to the other side of the pore, creating a block that kills the pore.
-
Another upgrade coming to change the unblock logic that should level out yield differences over time.
Kits
-
Recently settled lawsuit about hairpin
-
Came up with a system to do 1D²
-
Version 1 went out a few months ago
-
It is now due for a revamp
-
Adapters will be improved to imporoved the performance of the system
-
Looking for 60% reads 1D², should get to Q20
-
Software is antediluvian, 4 years old
-
A lot of people have complained that they can't do amplicons
-
New kit optimised for PCR uses a special set of barcodes that will enable barcodes to be paired up (UMI).
-
Will go back again, revamp it, and make a performant version.
Targeted sequencing
- Technology was to take a deactivated Cas9
- Guide RNA, hybridised to sample, subset of reads is pulled down to pore
- Working quite nicely
- Will be out as a kit later in the year.
Direct RNA sequencing
-
Can put RNA through the pore just like DNA
-
Proven very popular, there's lots of stuff in RNA
-
Not as performant as DNA product
-
Get full-length RNA molecules, can see all the modifications
-
Can really get to the full-length biology.
-
Nanopore is quantitative, see all the splice formas.
-
Now focusing on making RNA as performant as DNA
-
Want to increase speed RNA goes through the pore
-
Will move to 110 bases per second
-
Looking at improved adapters, simpler, fast library prep, incremental advances in basecalling
Field sequencing
-
Despair when looking at what people take to the field - polystyrene ice bucket kills me
-
A lot of work has gone to ambient shipping
-
Looking to post flow cells without cooling
-
Can ship at ambient, most reagents
-
Looking at storing ambient, a few kits left to lyophilise
-
Especially an issue in places where don't have a lab
Consensus Accuracy
-
Looked at fixing this issue a few months ago
-
The thing that most people hold up to nanopore
-
Cornering the rat, and then stamping on it
-
We're now tickling the rat
-
We're not at the limit yet
-
Worth talking to the team who are here
-
There are some limitations in the current software
-
Current training set, issues with scaling / chunking of data
-
Still aren't learning all the context
-
We still train on bacteria
-
We don't learn in damage and modifications
-
There are some software limitations, and other issues.
-
People assemble and polish, not fully-utilising all the signal
-
People don't exploit alll the information in the signal
-
Quite a lot of work to do.
-
Bases are not modelled, similar current for different sequences.
-
Progress on homopolymers, over past few months.
-
Nanopolish is still the gold standard for treating these data, but medaka can do well in some contexts.
Nanopore solutions
-
Have medaka, only works in base-space
-
Comparable to nanopolish, but much faster
-
Have been working on a new tool, miyagi, for correcting homopolymers
-
HMM based, that's the way to do it
-
comparable or better to nanopolish in some circumstances
Fixing the problem
-
One way: improve the chemistry.
-
People are alreads combining data with another certain company
-
Has been long on our agenda to do the same thing on one platform
-
Would then not need the other company
-
If you could combine multiple pores, would get flattening out of errors
-
R9.4 pore signal comes mostly from 3-4 bases
-
A run of Ts bigger than 3-4 gives flat signal
-
Can estimate bases using time domain
-
Would be better if we could de-flat the sections of data
-
Using read-ahead to look at more bases, rather than less
-
Will always be averaging over more bases
-
Deal with more bases using machine learning
Pore changes
-
Use Pore R8 - Lysenin based
-
R10 has two points about 9 bases apart
-
A particularly pathocogical error is a round of 5 Ts followed by two Gs
-
R10 spans the homopolymer giving an uppy-downy signal that the software can decode
-
Equally, number of percentage correct homopolymers with R10 is better
-
Think that green accuracy line will shift up.
-
Can generate orthogonal errors that can shift consensus
-
These are now under very active development as potential products
-
What about combining together?
-
50-fold R9 with 50-fold R10
-
can easily exceed Q40 in consensus, proof of concept
-
These methods are being implemented in miyagi tool, can use yourself (if you had R10 data).
-
Still not using dwell in these data
-
Using time domain, can boost these further.
-
The principle is shown.
-
Why not 5 pores?
-
Why not 500, each with completely different error modes?
-
We're going to crack this this year, and get it out to you as soon as you can.
-
Doing very well on variant calling, specifically on SNVs.
-
Have made at least one mutant of R9.4; R9.6. 9.4 gets one homopolymer wrong, 9.6 doesn't.
-
Can make even variants of 9.4 that have significantly uncorrelated signal. Could release this in 2-3 weeks.
Template changes
-
Could mess with the complement of the sequence
-
About 20 minutes, a pot of nucleotides in the kits, swap T for U and train basecaller
-
A/C/G/U version has different errors from A/C/G/T version. More complicated.
-
My preference is to put multiple pores in the chip.
-
Can provide these tools to allow people to mess with the pores.
-
Combining all three: two pores plus complement
-
Combining data that isn't correlated, as long as you pick the right data.
-
Will keep 9.4, but could make 9.6, could make R10
-
Question: is this useful? is that of interest? When would you like it? [let ONT staff know]
Flongle
-
It's coming, really soon
-
MiNION + 1-off adapter, that's the flongle
-
Has most of the electronics that's in the MinION
-
An array of copper electrodes
-
Can then make a very cheap crappy plastic flow cell with magical chemistry
-
Separates the cheap bits from the expensive bits
-
128 channels, limited by the forces that are needed to make connections
-
The data is the same, can flongleise a MinION
-
Can flongleise a GridION
-
Projecting that v1 up to a Gb from one flow cell, should get 3Gb from a flongle.
-
People don't want lots of data, problem is about how quickly enough data can be obtained.
-
Also good for bacteria and virused
-
People should buy more if it's cheaper
-
Flongle works, just like MinION
-
Squiggles are squiggles, they are the same
-
Invites for early adopers have going out
-
Looking at $90-$100 per flow cells, about 5-10% of the total treatment cost for dentist
-
Early access begins now, will release commercially in Q3
Where to go
- Drive is to get sequencing out of the lab
- Can survey what's going on in a river
- Cheaper, easier, package it up, remove any extraneous equipment.
Zumbador
-
Clive had the largest office, but had to rename Zumbador.
-
Idea is that you can take something very cheap, a piece of plastic, introduce a liquid because they're easy
-
After some reasonable time, like 10 minutes, can just sequence what's in there.
New name: Ubikwibopsy (Ubik tube)
-
Ubiquitious
-
Kwick
-
Liquid
-
Biopsy
-
Turns out that DNA is really informative
-
Don't want to ship samples off to california
-
Want anyone to be able to do this themselves, and have complete control over their own data.
-
Video: can put spit in a tube, a bunch of stuff happens in the tube, can bind DNA onto solid phase support, then separate. It drops onto the flow cell.
-
Have embedded the library prep onto the flow cell, comes ready to run.
-
DNA in, sample prep appears early in the pore
-
Can get meaningful data really quickly
-
Yields aren't massive, but we've got it
-
10 minutes from spit prep to WIMP
-
Had bacterial infection, could fix it, see a drop in the bacteria.
-
Saliva, lysis 10 minutes on Ubik tube.
-
Dentist offered to buy one.
-
If you encapsulated enrichment, could use read-until to exclude human, or include human.
-
We Might not be the right audience for that.
-
Future versions like flongle and smidgION will move towards anybody being able to touch a sample to a flow cell and know what's in.
-
Metrichor will make quantitative analysis of the self available direct ot the consumers.
VolTRAX
-
Version 1 a while back.
-
Main use is the proper version, version 2 ready to go out a bit later this year.
-
Supports all kinds of complex lab workflows.
-
15 inlets.
-
Can do heat, PCR, fluorescence detection. It is a lab on a chip.
-
Starter pack for V2 $8,000
-
As I speak, the shop is open for orders, can buy a VolTRAX v2.
-
Will prioritise people who got a V1.
-
Can do up to 10 samples, 2xGridION.
-
Pricing starts to get quite attractive for multiple samples.
SkunkWorx
-
A few years ago, pulled people into my office, asked them to do a thing.
-
Amazingly, people went off and did it.
-
A VolTRAX - MinION hybrid, amalgamating into a single device.
-
Now have another DNA sequencer that can be made.
-
Completely automated, very complicated droplet-based workflows can be built in.
-
No physical handling, can work directly from cells.
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Form dynamic membranes between droplets on the VolTRAX.
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Can insert a pore, and have a sequencer.
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Move the droplet to a certain part of the array and droplets look like a MinION channels.
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Squiggles are the squggles; they are the same.
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Droplets can be quite small, or quite big.
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Can swap the droplet.
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Can access the trans side.
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Can take the things you sequenced, and PCR them, or sequence again.
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Target is to get to 128 channels.
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More likely to be less than that.
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Currently 8-channel breadboard.
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Extraction zone, Library zone, sequencing zone.
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Henrietta Lacks cells being aligned and lysed.
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No shearing; what if you could just get whole chromosomes and put it between two droplets.
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Lots of things you can do.
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We tend to stick DNA to the membrane.
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Can coat up the droplet with DNA, DNA whizzes around and will find pore within seconds.
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If you have a tiny amount of material that you want to mine digitally, can mine out that cell.
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With read-until, can eject high-abundant stuff.
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Schemes where you can re-pair sequenced DNA and put it through again.
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Can also just hybridise things to DNA.
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Some Cas9 are SNP sensitive, can count thousands of presence - absense.
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Spit blood in, all in one, very flexible measuring device.
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We have the proof of concept, all now about making the box.
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Will be coming your way; not talking years.
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The mind boggles of what you can do.
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A small platform at relatively low plex. Our next likely major product launch.
Timeline
- Revision D ASIC, can get now. Probably broadly by middle of Q3. Should see 20-30 Gb.
- Kit9 much improved ligation kit
- PromethION went on commerical release today
- PromethION flow cells orderable
- Epi2Me commericalisation
- Software umblocking fixes
- MinIT shipping in July
- Ambient shipping in July
- First flongle shipments in July
- Voltrax V2 in August
- Much more performant 1D² in August
- RNA upgrade in terms of yield / quality in September
- In December fully-performant PromethION (48 flow cells)
- ONT has just got 3Tb internally
- target is 12 Tb per run, equivalent to 3-4 NovaSeqs
- December Mk1C MinION
Questions
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Flongle flow cells should be able to be chuckable; throwing away electronics is difficult.
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Multiple pores - Coverage will be reduced because errors aren't correlated. As long as you can pick the right one, which is the high and low quality base.
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Trying to get the same kits and settings on all devices.
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SmidgION - We can make it, that's not a problem. ASIC is reallyy cheap. Flongle comes first.
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R10 pore - frequency of homopolymers. Current software can call homopolymers as -1, some bias in software that is consistently doing it wrong. Will get a lot further with just incremental improvements.
Lightning Talks / Day 2 (Thomas Bray)
Franz Josef Müller
- Nanopore sequencing of short repetitive DNA
- A number of short repeat disorders (e.g. fragile X: GGC repeat, usually 30-50, but can expand up to 200 repeats)
- Why nanopore sequencing? Looking at kilobase stretches of 100% GC sequence, southern blot remains a diagnostic tool
- Good news: raw signal allows tracing / counting cases
- Regardless of the system, no real ground truth of the repeat number (in the normal case)
- Used nanopore-simulation (crohrandt)
- Pulls data, generates raw signal
- Entered defined repeat expansions based on the ground truth
- Made another tool: nanostrike
- Uses a signal model to identify repeat boundaries, quite good agreement with manual counts
- Cpf1 enrichment
- Poster actually describes a different tool
Natacha Couto
- University of gronigen
- Looking at vancomycin-resistant enterococci
- Intrinsic resistance to several microbial classes
- VRE dissemination can exchange mobile genetic elements
- Colleagues studying 36 isolates
- Did Illumina sequencing, found 7 clusters
- Some strains were clustered differently, but isolated from the same patient, or the same ward
- Wanted to look at transposons
- [Showed photo of PI - John, because he kept showing photos of her] -- she did the sequencing herself, it wasn't John's work
- No shearing, assemblies using Unicycler
- Could see transposons, look for differences, two on the chromosome, other two in a plasmid
- Looking back at the tree, found that core genes could be linked by common transposons
- Important to study structures, combine short-read sequencing with long-read sequencing
Stefanos Siozios
- Works with microbes and arthropods
- Microbes that pass from mother to offspring
- Image of maternal transmission to oocytes, paternal transmission as well (but rare)
- Biologically important, can alter vector competence
- Can, for example, kill of male offspring
- Has been hard to complete genomes
- Only a minority of microbes can be cultured outside the host
- Microbes have highly repetitive genomes
- Repetitive content is difficult to resolve
- Trying to make an improved reference genome (estimated size of about 3.5 Mb)
- Large amount of extra-chromosomal elements; PacBio also failed
- Two different library protocols. Very long reads provided the ability to assemble the main chromosome into a single circular contig - got extra-chromosomal elements as well
Rainer Waldmann
- Likes idea of VolTRAX-based single-cell sequencer
- Doing Illumina sequencing, need to fragment DNA, end up with only 3´ sequences
- Problem with amplification, need to correctly identify UMIs and cell barcodes
- Clustering gets easier if you know the barcode + UMI sequences
- Did 1 nanopore run with 190 cells, 30M reads needed for 5X UMI
- Did 951 cells using targeted nanopore sequencing
- With one cell: reads with the same UMI should be the same molecule; some outliers
- Nanopore data can be linked to Illumina
- Good idea to use Illumina data with single-cell data
Yutaka Suzuki
- Sequencing core laboratory
- Started analysis with cancer cells
- 9 patients, some initial success for cancer results
- Used the same process to genotype malaria patients
- Making a geographic distribution of modifications
- Moving to Papua, needed to modify protocols
- Replaced PCR with isothermal amplification
- Expanded to global G-RAID meeting
- BBC (UK) found out about this
- Wanted to do the first human cancer genome
- With the field kit, first do Malaria in Indonesia
Markus Haak
- In spare time, likes to detect unnatural bases (e.g. isoG, isoC)
- Detection method should be PCR-free and polymerase-independent
- MAX: looking at different restriction enzymes, method applicable for certain sequencing contexts
- Developed iCG ased on sequencing reference DNA samples
- Unnatural bases have substantial influence
- Automated model, does event correction
- During event correction, bad events are redistributed
- Data points are based on Dynamic Time Warping, shift to correct misalignment due to unnatural base calling
- Quite potentially adoptible to other bases or base calling
- Haven't tested against existing modified natural bases
Liana Kafetzopoulou
Intro
- ONT managed to fit her name on a MinION two years ago
- Want to be able to sequence all RNA viruses with a single protocol
- Charles Chiu published a protocol: reverse transcription using a random nonamer [9-mer]
- creates a cDNA library
Samples for testing
- RIPL
- Samples that were the most prevalent: chikungunya & Dengue
- Had to test sensitivity as well
- Even at higher CTs, can get the whole genome with the random nonamer protocol
- Percentage of reads (coverage) on MinION match Illumina and MinION
- What about when you don't know what is there?
- When you can assemble 80% of the genome, it's probably there
- Three different kits, consistent results
Taking it into the field
- Testing on Lassa virus, a very divergent RNA virus
- Lassa is endemic in Nigeria, outbreaks twice a year
- Take positive samples for sequencing
- Working great until Nigeria hit more cases than were ever before seen
- Got data out as soon as it was generated
Processing
- Only doing DNAse treatment
- PoreChop
- Using Canu to assemble, then BLAST to find the closest reference
- Used De-novo approach to feed mapping
Diagnostics
- Existing in-country diagnosis uses two RTPCRs
- Looked at the phylogeny; MinION assemblies were all spread around, all independent spillovers
- MinION is definitely accurate enough to tell if there's human to human transmission
- There were two samples that looked marvelously identical
- Looked at patient forms, found out that they were from the same patient, taken 6 hours apart, one SNP difference
- NCDC and WHO had a great need to know what was happening; the country as well...
- Country took the time and attention to listen
Challenges
- MinION overheated in the first run
- Time scale changed massively, changed from pilot run to something else
Outcome
- Were able to make 35 lassa virus sequences in a month