Nanopore Sequencing - The Long and the Short of it

Nanopore Sequencing - The Long and the

Short of it

Monolina Binny

Field Applications Specialist

© Copyright 2019 Oxford Nanopore Technologies Oxford Nanopore Technologies products are currently for Research Use Only. Not for use in diagnostic procedures

Our goal: to enable the analysis of any living thing,

by any person, in any environment

Reproductive health

Consumer genomics

Clinical genetics

Infectious disease

Oncology

Pharmaceuticals

Health

Biodefense

Outbreak surveillanceEnvironmental

monitoring

Checkpoint species ID

Security

Research

Plants/crops

Genome Science

Human genetics

Cancer research

Transcriptomics

Clinical research

Pathogens /microbiology

Environmental

Industry

Food safety and efficiency

Agriculture

Biopharma production

Environmental

Water testing

Forensics

Education

Schools

Citizen Science

Universities


NANOPORE DNA SEQUENCINGHow does it work?

Multiple nanopore sensors arrayed in one

device

Operate independently but at the same

time

Motor

(E6, E7, E8)

Nanopore Reader

(R7, R8, R9, R10 etc...)

Membrane

(M9, M10 etc...)

Run Conditions

(Salt, fuel, script, temperature...)

Algorithm

(HMM, RNN etc...)

Nanopore sensing


2048 (512*) channels

Nanopore products: fully scalableOne core technology: real-time, on-demand

*up to this number of nanopore channels may be available for sequencing at any time

Single-test

sequencing

128 channels

Portable, USB powered

biological analysis

2048 (512*) channels

Commercially available

Five flow cells and

integrated computing

5 x 2048 (5 x 512=2,560*)

channels

Commercially available

High-throughput, versatile

benchtop system

48 x 12,000

(3,000 = 144,000*) channels

Commercially availableCommercially available


2019

Yield per flow cell, 1D chemistry

1Gb

10Gb

20Gb

2014

5Gb

30Gb

2015 2016 2017

target

R6

30bps

R6

30bps

R7

70bps

R9

250bps

R9.4

450bps

2018

R9.4

450bps

Evolution of

MinION/GridION flow

cell performanceR9.4

450bps

Software

upgrades

Increased

runtime

Current

record ~50Gb


Which DNA kit?

(SQK LSK109)


DNA Sequencing Kits

RAPID SEQUENCING (SQK-RAD004)

10 minutes. Fragmentation based, no third-

party ligase required.

Ligation vs Rapid

1D LIGATION SEQUENCING (SQK-LSK109)

60 minutes. Flexible high yield library prep.

RNA Sequencing Kits


RNA sequencing with Nanopore technology

Gene

Short

reads

Nanopore

reads

Span the entire length of a fragment

Full splice information for a fragment

Differential gene expression

Isoform counting made simple

Strand specific information

Normalisation to read length not required

Detect fusion genes



Overview of library preparation for long read RNA sequencing

PCR-cDNA Direct cDNA Direct RNA


Base modification detection with Direct RNA

Different current disruption

caused by modified bases

Third party tools have been

developed for detection

(nanopolish, signalAlign)

Tombo – found on ONT github


Extraction methods

Internally investigating impact of extraction methods on performance and providing guidance

Time

Protocol builder available to assist

users with choosing the best protocol

for their sample and desired analysis

yie

ld

Improving accuracy


1D2, R9.5

100%

90%

80%

1D, R7

1D, R9

1D, R9.4

1D, R6

90% of

readsMost

frequent

1D, R9.4.1

flip-flop

basecaller

Single molecule accuracy: internal results

20192014 2015 2016 2017 2018

1D, R9.4.1

Shift from event-based

basecalling to signal-based

basecalling (transducer)

Improved

basecalling

network


Q50: 99.999%

Benchmark

Q40: 99.99%

Q30: 99.9%

Consensus accuracy: internal results

R9

Estimated

spread

R9.4.1

Target: consolidate Q50

then Q60 by further

evolving pores, base

callers, sample chemistry,

mixed signals

Improved references also

greatly impact accuracy

and sequencing

community is continuously

improving these

R10

Q43

Transducer

+

Medaka

20192016 2017 2018

R10

Q50

(99.999)

flip-

flop+

Medaka

Results shown include various consensus methods including Medaka polishing of base calls and Nanopolish signal level polishing, end 2018

R9.4.1

~Q40

flip-flop+

Medaka


CONSENSUS SEQUENCING ACCURACYSources of error in consensus

Modified / damaged

bases

Untrained context /

diversity of training sets

Base calling and training Assembly and polishing

Single read chunking

and scaling

Similar currents for

different sequences

Flat regions of signal

(e.g. homopolymers)

Generalisation of

models to all runs

Unoptimised methods

for longer reads

Chemistry

Many tools do not use

dwell time information

Quality scores poorly

represent error

Simplified to bases

(information loss)

Not fully utilising raw

data / alternative paths

Dependence on high

quality reference

Limitations of Viterbi

decoding


BASECALLINGGenerations of algorithms – 1D raw read

Strong history of improving accuracy

• Algorithms for base calling improving continuously

• Track record of cutting-edge base calling

• New methods can be applied to old “raw” data

Current “Flip-flop”

Mode ~ 95%

Albacore 2.3.4 Transducer

Guppy 2.3.1 Transducer

Guppy 2.3.1 Flip–flop

Guppy 2.3.5 Flip-flop

84% 88% 92% 96% 100%80%

Alignment 1D raw read accuracy

Read c

ount

1D R9.4.1 read

accuracy

S. Aureus

HMM

RNN (raw)

Transducer

RNN (events)

RNN (events)

Transducer


BASECALLINGSignal to Sequence

New “flip-flop” algorithm

• Network is learning to call the correct sequence NOT a

set of pre-labelled classifications

• All paths of signal to sequence are considered

• Samples in signal are not directly associated with bases

• Flip(+) and Flop(-) discriminates between no-movement

and repeats (e.g. in homopolymer)

• Network outputs transitions between single bases

• Simple decoding

• Trace output - human interpretable

• More meaningful quality scores TTACAGGTGCTCAGTACCATTTGTT

A+T+ C+T-

A+G+G-T+G+ C+T+C+ A+ T+G+ A+C+

C-A+T+

T-G+T+ T+

T-

A(+)→ C(+), G(+), T(+)

A(+)→ A(-)

A(-)→ A(+)

A(-)→ C(+), G(+), T(+)

Raw signal

Recurrent Neural

Network

(over time-steps)

Base call

RNN

Per-flipflop

Base probabilities

Base to base

transitions

(per time-step)Transitions


BASECALLINGFlip-Flop for DNA and direct RNA

Raw read 1D accuracies

• Moving over to Flip-flop for all base calling

• “Fast” network as accurate as transducer

• “High accuracy” 1D base caller at ~95% modal

accfast

Direct RNA Tra

nsd

uce

rF

lip-flo

p

80 85 90 95 100

density

1D accuracy (%)

DNA

80 85 90 95 100

density

Tra

nsd

uce

rF

lip-flo

p

accfast

1D accuracy (%)

RNA raw read 1D accuracies

• Direct RNA accuracy now comparable to DNA

• Hitting ~94% modal direct RNA with “high accuracy” caller

• Accuracy for GUAC, modifications possible in RNA signal


BASECALLINGModified bases

Base calling multiple modifications

• Categorical approach to base calling – scales gracefully

• Single model trained to call 5mC and 6mA

• Train for any modification and context given training data

Availability and roadmap

• Released in Taiyaki – training and calling

• Integrating calling into Guppy & MinKNOW – July 2019

• “All context” methods in R&Ddensity

Modified base score Modified base score

density

5mC

Canonical Canonical

6mA

CCWGGGATC


CONSENSUSMedaka

Medaka: pileup-based consensus correction

• Align reads to draft assembly

• Count bases in reads segregated by strand

• Bi-directional GRU network to form base probabilities

• 1 minute per 10Mb of draft on GPU

• Available from: Github, PyPI, Bioconda

• Epi2Me coming soon (Oct 2019)

2018

30

32

34

36

38

40

42

44

25 50 75 100 125 150

coverage

co

nse

nsu

s Q

B.Subtilis

E.coli

E.faecalis

L.monocytogenes

S.aureus

S.enterica

R9.4.1

Highly accurate Nanopore genomes

• Data collected with the R9.4.1 baselines chemistry

• 1D flip-flop calls with “high accuracy” model

• Medaka consensus correction

• S. aureus consensus now at Q44

Pores


Approx. 5 bases

dominate the

current signal

R9.4.1: Mixed sequence (highly accurate)

R9.4.1: Homopolymer sequence (difficult with “sharp reader”)

10xT 10xT 10xT

R9.X pores have a sharp reader head

• Very good in mixed sequence regions

• Okay when homopolymers are short (< 5)

• Struggle to discriminate longer homopolymers

• Weak information in current levels for homopolymers > 5

• Some additional information is in dwell time (motor speed)

• Fix: longer reader → more information → higher accuracy

CONSENSUS SEQUENCING ACCURACYReasons for the accuracy gap


New pore accurately calls homopolymers

• A pore with a longer or multiple “readers” has more bases dominating the signal

• Longer homopolymers are “seen” by the pore and can be decoded with high accuracy

Unpolished homopolymer accuracy

R9.4.1

R10

0

20

40

60

80

100

Accura

cy %

Homopolymer length

3 4 5 6

R10

R9.4.1

CONSENSUS SEQUENCING ACCURACYNew chemistry for improved accuracy – R10


CONSENSUS SEQUENCING ACCURACYR10 consensus accuracy

Consensus accuracy > Q50

• Accuracy > Q40 at 30X coverage

• Q54 achieved for Staphylococcus aureus (May 2019)

• Significant improvements from the R9 chemistry

Consensus correction trained for R10

• Medaka optimised for new pore chemistry

• Significant uplift in consensus accuracy

• R10 models will be made available

Q score Number of errors

Q40 1 error in 10,000 bases

Q50 1 error in 100,000 bases

Q60 1 error in 1,000,000 bases

30

35

40

45

50

55

25 50 75 100 125 150

coverageco

nse

nsu

s Q

B.Subtilis

E.coli

E.faecalis

L.monocytogenes

S.aureus

S.enterica

R10 consensus accuracy (May 2019)


R101D raw read accuracy and output

Upgrading orders

• Support can upgrade open R9 flow cells orders to R10 or

R10.3

What happens to R9?

• R9.4.1 Available and supported across all devices

• R9.5.1 Available only on MinION / GridION

MinION / GridION R10 flow

cells:In store May Ships in June

PromethION R10 flow cells: In store May Ships in July

Flongle R10 flow cells: In store Sept Ships in Sept

R10 upgrade path

85 90 95 100

1D raw accuracy (%)

R10

R9.4.1

R10 1D raw read accuracy

R10 Output

• MinION/GridION flow cell: 26 Gb

• PromethION flow cell: 112 Gb

28 | © Copyright 2019 Oxford Nanopore Technologies. Oxford Nanopore Technologies products are currently for Research Use Only.

Beyond R10 (R10.3 is available now)

Further improvements to R10

Mutants for better signal-to-noise ratio

Improve purification

– Less blocking: better throughput

Base callers/ models

Tailored consensus tools

Direct RNA-specific improvements

New pores: “R10b”, “R11”

New reader heads with different signal profiles

Different base discrimination

Different signals in homopolymer regions

Even longer reader heads

Future nanopores for further accuracy enhancement

R10

R10b

10xT 10xT 10xT

10xT10xT 10xT

RH1

RH2

Consensus

accuracy

29 | © Copyright 2019 Oxford Nanopore Technologies. Oxford Nanopore Technologies products are currently for Research Use Only.


Q60

Sample chemistry

(“8B4”)

Nanopore chemistry

(R10, R11..etc..)

Base callers

(CTC, flip-flop)

Combine pores

(R9 + R10, R10a + R10b)

Major focus on improving accuracy

• Achieving > Q50 with single nanopore option

• Many different paths to higher accuracies

• Algorithms, chemistry, data combinations

Single chemistry options

• Higher accuracy from R10 improvements

• Novel base calling architectures

• Randomised signals with chemistry (e.g. “8B4”)

Multiple data types

• Nanopores capable of multiple chemistries

• Generate different signals and errors

• Could combine different pores, chemistry…etc…

CONSENSUS SEQUENCING ACCURACY – ROUTE TO Q60Combining data from a single platform


What are the advantages for Long reads and Clinical genomics

Sensitivity

Long reads enable you to

detect:

SVs

CNVs

Phasing

STR length

Abnormally spliced

transcripts

Flexibility

Sequence what you want,

when you want

Real time analysis

– No fixed run time -

run until you have

your answer then

stop

Random access

– No batching required

– Reduce TAT for time

critical tests

Multifunctionality

One platform and one

assay can yield:

Aneuploidy

Sub-chromosomal SVs

and CNVs

SNVs

Methylation

Affordability

No capital required to buy

the box:

$1000 gets you started

with a MinION

GridION and

PromethION available

on consumables

purchase models

No need to ‘fill’ the

machine to make the

numbers work

Whole genome sequencing


Rapid preimplantation genetic screening (PGS) using a handheld DNA sequencerWei et. al, March 2018, BioRxiv, https://doi.org/10.1101/274563

In this paper, Wei et al. demonstrate a 2.5 hour WGA amplification, 45 minute library preparation and < 2 hour sequencing workflow for

correct detection of aneuploidy.

https://doi.org/10.1101/274563

© Copyright 2019 Oxford Nanopore Technologies Oxford Nanopore Technologies products are currently for Research Use Only. Not for use in diagnostic procedures34

HIGHER-RESOLUTION ANALYSES FROM LOW COVERAGE

Chromosome 5p- deletion detected in Cri-du-chat syndrome cell line

Partial deletion of the short

arm of chromosome 5

These results are a 50/50 mix of sheared gDNA and whole genome

amplified (~500 bases) reads and the coverage is 1.6x

By downsampling we can see the deletion by using:

Non-amplified, sheared gDNA: 0.07x or 25k reads

Whole genome amplified DNA: 0.025x or 70k reads


Wigard Kloosterman

Center for Molecular Medicine, UMC Utrecht

Mapping and phasing of structural variation

TECHNIQUES: Structural variants

Using the data:

Comparison between short and long reads identified

the de novo chromothripsis sample

Nanopore reads resulted in:

– de novo breakpoint identified and verified

– Resolution of a deletion and tandem duplication in

two SVs

– Phasing of the > 2000 SVs

Phasing of the de novo chromothripsis sample using

long reads showed SVs were from the father.


Deciphering complex SV in neonates with developmental disorders

“…we identified a de novo duplication-inversion-

duplication overlapping CDKL5 in an individual with

neonatal hypoxic-ischaemic encephalopathy. Long-

read sequencing technology used to resolve the

breakpoints demonstrated the presence of both a

disrupted and an intact copy of CDKL5 on the same

allele; therefore, it was classified as a variant of

uncertain significance.”

“…Accurate resolution of cxSVs is essential for

clinical interpretation, and here we demonstrate that

long-read WGS is a powerful technology by which to

achieve this.”


Simultaneous profiling of chromatin accessibility and methylation on human cell

lines with nanopore sequencingLee et al., Dec 2018, BioRxiv, https://doi.org/10.1101/504993

Developed nanoNOMe – combined NOMe-seq

detection of methylation and chromatin

accessibility with nanopore sequencing

Combining NOME-seq with long-read nanopore

sequencing obtains long-range information; as

nanopore can directly discriminate methylated

from unmethylated bases, bisulfite conversion

and PCR are unnecessary

Nanopore sequencing enabled the analysis of

methylation, chromatin accessibility and

investigation of structural variants and their

sequencing context in a single assay

Understanding the relationship between the

genome and epigenome with nanoNOMe

https://doi.org/10.1101/504993


Systematic analysis of dark and camouflaged genes: disease-relevant genes

hiding in plain sight

The human genome has “dark” regions which

are those that cannot be assembled or aligned

using short-read sequencing.

Ebbert et al., Jan 2019, BioRxiv, https://doi.org/10.1101/514497

These regions could contain mutations

associated with disease so their analysis

would be highly valuable

Long reads were used to try and resolve

“dark” (few mappable reads) and

“camouflaged” (ambiguous alignment e.g. due

to duplication) regions in short-read whole-

genome sequencing data

In short-read data, identified 37,873 dark

regions across 5,857 genes; 28,751

intronic, 2,657 in protein-coding exons

https://doi.org/10.1101/514497


Systematic analysis of dark and camouflaged genes: disease-

relevant genes hiding in plain sight


• SMN1 and SMN2, involved in spinal muscular

atrophy and ALS, reduced from 89.9% and 88.2%

“camouflaged”, respectively,Both genes were 0% camouflaged CDS based

on ONT and PacBio

https://doi.org/10.1101/514497


Systematic analysis of dark and camouflaged genes: disease-

relevant genes hiding in plain sight


• Top-ten Alzheimer’s gene CR1 reduced

from 26.5% “camouflaged” to 0% using

nanopore data

• SMN1 and SMN2, involved in spinal

muscular atrophy and ALS, reduced from

89.9% and 88.2% “camouflaged”,

respectively, 0% using nanopore data

• Top-ten Alzheimer’s gene CR1 reduced from

26.5% “camouflaged” to 0% using nanopore

data

https://doi.org/10.1101/514497


Systematic analysis of dark and camouflaged genes: disease-relevant genes

hiding in plain sight Ebbert et al., Jan 2019, BioRxiv, https://doi.org/10.1101/514497

Resolution of “dark” coding sequences =

81.8% in nanopore data, compared to 66.6%

and 54.9% for other long-range technologies

Nanopore ultra-long reads have greater

mapping ability than other long-range

technologies, allowing resolution of difficult

“dark” coding sequences

“Comparing long-read sequencing technologies…the

ONT platform performed best, both when assessing

entire gene bodies, and when considering only CDS*

regions.”

*CDS = coding sequences

https://doi.org/10.1101/514497

Targeted sequencing


Detecting and phasing SNPs in GBA for Gaucher’s and Parkinson’s Disease

Results: We detected all known missense

mutations in these samples, including the

common p.N409S (N370S) and p.L483P

(L444P) in multiple samples, and nine rarer

ones, as well as a splicing and a truncating

mutation, and intronic SNPs. We

demonstrated the ability to phase mutations,

confirm compound heterozygosity, and

assign haplotypes.. Rare false positives

were easily identified and filtered, with the

Nanopolish

Conclusion: The Oxford Nanopore MinION

can detect missense mutations and an

exonic deletion in this difficult gene, with the

added advantage of phasing and intronic

analysis.


The workflowSimple, fast

enrichment with

CRISPR- Cas


Multiplex CRISPR-Cas enrichment of clinically relevant genomic repeat structuresMartin Elferink (University Medical Center, Utrecht), Nanopore Community Meeting 2018

>40 neurological & neurodegenerative diseases caused by

repeat expansions; can be several kilobases long

– Number of repeats often indicates disease severity

– Long nanopore reads can span entire repeat expansions

Multiplex CRISPR/Cas enrichment of 10 loci in healthy control

sample - Cas9: just under 600x; Cas12a: 200x

– High-specificity cleavage sites

– All alleles & relevant SNPs detected in 7; remaining 3

detected but no informative variants seen

Cas9 workflow tested on patient samples: all but one

(degraded) sample >100x coverage of ROIs

– Identified alleles agreed with patient’s diagnosis

– repeat expansion counts broadly agreed with those from

traditional assays

Watch Martin’s full talk here: https://nanoporetech.com/resource-centre/martin-elferink-multiplex-crispr-cas-

enrichment-clinically-relevant-genomic-repeat

https://nanoporetech.com/resource-centre/martin-elferink-multiplex-crispr-cas-enrichment-clinically-relevant-genomic-repeat


Targeted Nanopore Sequencing with Cas9 for studies of methylation, structural

variants and mutations

Profiling SVs in driver genes from breast cancer cell lines using a low cost, PCR free approach

Gilpatrick et al., April 2019, BioRxiv, http://dx.doi.org/10.1101/604173.

• Probes designed to bind up/down stream of two

known deletions

• Heterozygous vs homozygous deletions could

be distinguished and phased to the parent of

origin in all cases

• Breakpoints were defined and methylation

profiles observed.

Oncology

03


Same-day genomic and epigenomic diagnosis of brain tumours using real-time

nanopore sequencing

In the same sequencing run, from native tumour DNA:

Copy number profile

Methylation profile

Structural variation

Point mutations

…after 6 hours of sequencing.

Euskirchen et. al, June 2017, Acta Neuropathologica,10.1007/s00401-017-1743-5

“aiming to make precision medicine

possible for every cancer patient,

even in resource-limited settings”

10.1007/s00401-017-1743-5


Same-day genomic and epigenomic diagnosis of brain tumours using real-time

nanopore sequencing

“Same-day diagnosis of CN alterations, epigenetic modifications, and single nucleotide

variants using nanopore sequencing is feasible with minimal capital cost and without

need for sophisticated laboratory equipment.

For CNS tumors, molecular features demanded for diagnosis by current guidelines can

be obtained, which, together with histological data and grading, enable accelerated

integrated diagnosis and improve patient care.”

Euskirchen et. al, June 2017, Acta Neuropathologica,10.1007/s00401-017-1743-5

Classification of tumours subjected to R9.4 WGS using ad hoc random forests, 500

trees per sample. Distributions from copy number, methylation and combined profiles.

Indication of time required to reach 1000X

coverage of each target amplicon.Comparison of selected variant

calls nanopore to reference.

10.1007/s00401-017-1743-5


Long read sequencing reveals a novel class of structural aberrations in lung

cancers

Whole genome and transcriptome profiling of cancer cell lines and clinical samples using

PromethION detects novel complex SVs, novel gene fusions and recurrent SNVs

Sakamoto et al. April 2019, Biorxiv, https://doi.org/10.1101/620047

• Identified known driver SNVs in KRAS and

NRAS

• Pinpointed genomic break point of the

CCDC-RET fusion

• Delineated differences between cell lines in

the size of the deletion of the CDKN2A

gene

https://doi.org/10.1101/620047


Long read sequencing reveals a novel class of structural aberrations in lung

cancers

Whole genome and transcriptome profiling of cancer cell lines and clinical samples using

PromethION detects novel complex SVs, novel gene fusions and recurrent SNVs

Sakamoto et al. April 2019, Biorxiv, https://doi.org/10.1101/620047

• Detected “cancerous local

genomic lesions” (CLCLs) that

could not be resolved by short

read seq.

• STK11 gene disrupted by two

inversions and a deletion in a cell

line

• CLCL’s also found using

PromethION seq. of clinical

samples

• Strongly associated with LINE,

SINE and LTR elements

https://doi.org/10.1101/620047

Pore C


Pore-C: using nanopore reads to delineate long-range interactions between genomic loci in the human

genome

Clinical and public health microbiology


the advantage of long reads

Nanopore ultra-long reads enable the highest

sensitivity for detection of trends in:

Antimicrobial resistance

Virulence

Vaccine escape

What do I mean by ultra long?

• 10-100’s Kb routinely

• Up to >2 Mb (so far) using ‘ultra long’ DNA prep

methods

• Can cover E. coli genome in as few as 8 reads

PlasmidsSingle-contig assemblies enable comprehensive resistance

and virulence profiling

Repetitive elementsLong reads map across repetitive elements containing

virulence and resistance genes

Complete genomesCreate more accurate and contiguous reference assemblies

PhylogeneticsConstruct longitudinal profiles of strain evolution, track

mobile elements and monitor prevalence trends


Resolving the complex Bordetella pertussis genome using barcoded nanopore

sequencingRing et al., Nov 2018, Microbial Genomics, doi: 10.1099/mgen.0.000234

Unlike short reads, nanopore long reads span

repetitive regions, enhancing their resolution

Resolved genomes of five B. pertussis strains

with a single MinION flow cell

Ultra-long duplications detected in two strains

Most accurate assembly method is hybrid

assembly with pre-correction of reads with Canu

followed by Unicycler assembly

Resolving a repeat-rich bacterial genome

with high GC content

“This work expands the recently emergent theme that even the most complex genomes can be

resolved with sufficiently long sequencing reads”

Alignment of the five sequenced strains, showing genomic

rearrangement. The five strains were assembled using a nanopore-

only pipeline, resulting in single, closed-contig, assemblies.


Completing your genomes – Hybrid Assembly

“…This approach paves

the way for high-

throughput and cost-

effective generation of

completely resolved

bacterial genomes to

become widely

accessible.”

Wick et al. . M Gen 3(10): doi:10.1099/mgen.0.000132

Li et al. GigaScience, Volume 7, Issue 3, 1 March 2018,

gix132, https://doi.org/10.1093/gigascience/gix132

https://doi.org/10.1093/gigascience/gix132


Direct RNA Sequencing of the Coding Complete Influenza A Virus Genome

“…successful sequencing of the

coding complete influenza A virus

genome with 100% nucleotide

coverage, 99% consensus identity, and

99% of reads mapped to influenza A

virus”

Keller et al., Sep 2018, Scientific Reports, https://doi.org/10.1038/s41598-018-32615-8

(A) Influenza A viruses contain highly conserved 12 and 13 nt sequences

at the 3′ and 5′ termini. (B) The key component of Oxford Nanopore direct

RNA sequencing is a Reverse Transcriptase Adapter (RTA) which targets

poly(A) mRNA and is ligated to the 3′ end of the mRNA. A sequencing

adapter is then ligated to the RTA which directs the RNA strand into the

pore for sequencing. (C) The RTA was modified to target the 3′ conserved

12 nt of the influenza A virus genome. (D) The modified RTA hybridizes

and is ligated to vRNA in the first step of direct RNA sequencing.

Used a modified adaptor to target the 3’ of the negative

sense RNA into the nanopore

https://doi.org/10.1038/s41598-018-32615-8

Metagenomics


Nanopore Sequencing as a Surveillance Tool for

Plant Pathogens in Plant and Insect TissuesBadial et al., Aug 2018, Plant Disease,

https://doi.org/10.1094/PDIS-04-17-0488-RE

Metatranscriptome analysis of infected

plant and insect tissues

Candidatus Liberibacter asiaticus or plum pox virus

infection

MinION sequencing identified all target pathogens in the

samples tested

Reads with favourable mapping quality produced

throughout entirety of the run

“Plum pox virus and Ca. L. asiaticus were detected in

both tissue and insect samples near the beginning of

each sequencing run, demonstrating the capability of

this methodology to obtain results rapidly”

https://doi.org/10.1094/PDIS-04-17-0488-RE


Why is Lake Hillier pink?

The eXtreme Microbiome Project (XMP) is a global

scientific collaboration to characterize, discover, and

develop new pipelines and protocols for studying novel

microorganisms in extreme environments.

XMP collected and analysed lake water and sediment

samples using a variety of metagenomics techniques

MinION with the WIMP workflow was used for rapid

species identification and characterisation

The analysis revealed a surprising range of microbial

diversity in the lake, and indicated that many algal,

bacterial, and archaeal halophiles contribute to the

persistent pigmentation of this pink paradise

Metagenomics with What’s In My Pot (WIMP)

Courtesy of Ken McGrath


Rapid Diagnosis of Lower Respiratory Infection using Nanopore-based Clinical

Metagenomics

Urgent need for rapid microbiological diagnosis for timely, specific antibiotic therapy

Charalampous et al., Aug 2018, BioRxiv, https://doi.org/10.1101/387548

Clinical metagenomics pipeline –

removal of host nucleic acid, nanopore

sequencing on MinION, WIMP analysis

Turn around time 6 hours

Sensitivity of detection 96.6%

Antibiotic resistance analysis using ARMA

$130 per sample (6 samples per flow cell)

INHALE clinical trial (evaluation of pipeline

for diagnosis of hospital-acquired and

ventilator-associated pneumonia)MRSA genome coverage of depleted vs undepleted during two hours of sequencing

https://doi.org/10.1101/387548


Metagenomic sequencing at the epicenter of the Nigeria 2018 Lassa fever outbreak

L. E. Kafetzopoulou et al., Science, 2019

Performed metagenomic sequencing on

samples from 120 patients over 7 weeks

48 hours sequencing on FLO-MIN106. Up

to 6 samples multiplexed per flow cell along

with a negative control (water blank).

Analysis tools: Canu for de novo assembly.

Called variants using Nanopolish;

performed metagenomic classification

using Centrifuge.

Performed phylogenetic analysis by

comparing all sequences with those

available in GenBank and unpublished

sequences obtained between 2012-2017.

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Documents

Nanopore Sequencing - The Long and the Short of it