sequencing technology › roche/454 gs-flx (‘454’) › illumina prokaryotic profiling › de...
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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Classic chain-terminator sequencing
Dye chain-terminator sequencing
Next-generation sequencing
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Next-gen sequencing principle› Massive parallel› Add ACTGs› Catch a signal
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Roche/454 GS-FLX+ (‘454’)› Pyrosequencing
problems with homopolymers (e.g. AAAAAA)
› Long-read sequencing: 500-1000 bp› Variable sequencing length› 1 million reads/run
1Gb/run
› Sequencing speed: ~ 1 day/run› Next-next generation: IonTorrent
PGM/Proton
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Illumina › Sequence by synthesis› Short-read sequencing: 36, 72, …, 150bp› Fixed sequencing length› 1 billion reads/run
100Gb/run (= 33 x human genome!)Sequencing speed: 3 day – 10 days ~ length
Solid› Short-read sequencing (similar to Illumina)
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454 Illumina
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Price per run: $10000/run Price per machine: $200-500.000
› Supporting IT hardware› Peripheral devices such as fragmentation
instrument, PCR equipment …› Negotiating power…
Use service centers!› Nxtgnt (BE), GATC(EU), Baseclear(NL), BGI …› No overhead cost, no maintenance etc.› Cheaper
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Next-generation sequencing has become 2nd generation sequencing
Next-next-generation sequencing is almost there: 3rd generation sequencing› Helicos: True Single Molecule Sequencing› IonTorrent/Life: Cheap and fast› Nanopore: Unlimited read size› …
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Evolution sequencing technology goes hand in hand with evolution of› IT infrastructure/hardware› Analysis software
Hardware› 1 Illumina run ~ 100Gb text-file ~ 5million
page book › Processing power/storage are an issue!
Software› Mapping to a human genome: ‘couple of hours’
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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Prokaryotic genomics 101› Prokaryotes = bacterias + archaea› Prokaryotic genomes
Large circular genome (0.5 – 10 Mb) ‘chromosome’
Small plasmids (1-1000 kb) (virulence factors, antibiotics resistance …)
(Almost) no introns Easy ORF annotation
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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1953: Watson/Crick discover DNA helix 1977: First complete genome
bacteriophage φX174 1995: First genome of free-living organism
H. influenza 2001: First draft of the human genome 2006: >200 complete bacterial genomes 2012: An uncountable number of bacterial
genomes have been sequenced using next-gen sequencing
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Complete bacterial genomes used to be› Expensive› Difficult to obtain› ‘Nature’ or ‘Science’ work› Remained complex until the invention of
next-generation sequencing
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Using next-generation sequencing, de novo sequencing has become› Relatively easy› Relatively cheap› Routine research
Already >10 complete bacterial genomes published in 2012› More than just an assembly!
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Practical1. Get some DNA from an isolated species
of interest2. Sequence: long or short reads (1-10 days)3. Obtain your sequences4. Assemble (1h)
Pure de novo assembly Guided assembly
5. Annotate the genome (days-weeks)
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Assembly:Multiple ‘short’ reads
1 long sequence Existing software
› Velvet› SSAKE› Newbler› SSAKE› …
Source: Nature 2009, MacLean et al.
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Relatively cheap› Sequencing cost: depending on coverage
Illumina, 30x, 5Gb genome: $10-$100 454, 30x, 5Gb genome: $1000-$5000
› Equipment IT infrastructure, sequencing equipment, people
… Relatively easy
› Need for IT support› No out-of-the-box standard solution for
everything› Several different software packages for
assembly
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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De novo genome assembly› Study of 1 single species› Need for species isolation
Metagenomics analysis› Study of a community of species› No need for isolation (culturing bias!)› Study the collective gene pool and
function of the community/ecology› No need for individual functions
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Practical1. Get bacterial DNA or RNA from a sample
Soil Gut/Fecal Ocean water (e.g. Craig Venter) …
2. Sequence: long or short reads (1-10 days)3. Obtain your sequences4. Map on a database of known genes (1 day)5. Annotate/analyse the community (weeks)
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2010: Giant Panda genome (2nd carnivore)› No umami taster receptor -> no meat
affinity› The panda is more a dog than a bear› The panda is a carnivore eating bamboo!
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Still 2010 !: Panda ‘microbiome’ Gut microbiome of the panda reveals
the presence of bamboo/cellulose degrading pathways
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A clinical example: gut microbiome can predict diabetes and malnourishment
Plos One (2011), Brown et al.Plos One (2010), Valladares et al.Gut Pathology (2011),Gupta et al.
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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Classical SNP analysis - practical1. Design PCR primers2. Generate amplicons3. Re-sequence using long read sequencing
Conserve ‘SNP blocks’
4. Detect SNPs 5. Correlate SNPs to drug resistance,
severity of symptoms …
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Amplicon resequencing is the same for human, prokaryotic, viral analyses
Many standardized out-of-the-box solutions available
Very simple analysis Watch out for the overkill…
› Don’t use a bazooka to kill a fly!› Throughput can be too high
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Profile the coding region of hepatitis C
Lauck et al. 2012
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Use next-generation sequencing to predict the optimal HIV therapy
Thielen et al. 2012
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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Imagine the following research questions› Which (known) species/groups are present
in a certain sample› Does this composition alter given a certain
treatment, change of conditions, patients etc.
No need for de novo genome sequencing
No metagenomics: species instead of functions
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Prokaryotes have the gene 16S rDNA, coding for ribosomal RNA
The 16S rDNA region is 1.5 kb long 16S rDNA is specific for each
species/strain Theoretical: 4
1,500 = 10
903 possibilities
In practice: 16S rDNA sequence known for millions of species
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16S rDNA can be isolated in different species using universal PCR primers› Isolate/amplify different regions using the
same primers Compare the isolated sequences
against a database of known sequences
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Practical procedure1. Sample an environment and isolate DNA2. Do a universal PCR amplification3. Sequence using long read sequencing:
the longer the better!4. Obtain sequences5. Map sequences against a reference
database6. Annotate the data
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Example: The Antarctica project› Which parameters determine the
composition of bacterial communities in antarctical lakes?
› 20 different samples/lakes› Sequence 16S rDNA genes› 1 x 454 run (1 million 500bp sequences)› Map all sequences back to the RDP
database
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Analyse the data using computing power› Compare different locations
Is species A present in location1, location2,…› Assess the distribution in a single location
How dominant is the most dominant species in location 1
How many species are in location 1 …
Visualize !
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Analyse different samples on different taxonomic levels› Include taxonomic tree of life of bacterias› Use a ‘taxonomy browser’
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Analyse a single location
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Compare different locations
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Analysis Lab work difficulty
Analysis difficulty
De novo genome ++ (isolate) +
Metagenomics + +++ (pathways etc.)
SNP +++ (design primers)
++ (correlate)
Species quantification ++ (universal primers)
++
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Sequencing technology› Roche/454 GS-FLX (‘454’)› Illumina
Prokaryotic profiling› De novo genome sequencing› Metagenomics› SNP profiling› Species quantification
Viral profiling› De novo genome sequencing
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Viral profiling› Viral profiling = prokaryotic profiling, but…
Cheaper Faster Easier
› De novo genome sequencing = OK› Don’t spend $10.000 on a 100kb genome!› Multiplexing/pooling capacity is limited!
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Watch out for the overkill› An illumina run can be split into 8 lanes› >20 samples per lane can be combined
Still >100Mb per sample…
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Thanks for your attention !