Transcript Scott Sammons - Sequencing And Bioinformatics In The CDC

Sequencing and Bioinformatics in the CDC
Biotechnology Core Facility Branch
Sequencing Lab
• Mike Frace, Team Lead
• Lori Rowe
• Marina Khristova
• Mark Burroughs
• Milli Sheth
Computational Lab
• Scott Sammons, Team Lead
• Kevin Tang
• Kristen Knipe
National Center for Emerging and Zoonotic Infectious Diseases
Division of Scientific Resources
Genome Sequencing Lab sequencing platforms
Illumina 2500
Illumina MiSeq
Roche 454 Titanium +
PacBio SMRT sequencer
Illumina GA IIx
Ion Torrent PGM
Building 23 Server Room – Main ISLE
3
High Performance Computing Cluster (Aspen)
•
What is it?
• 35 compute nodes each with 12 processor cores,
total of 420 cores, 110GB of memory, and 2 Tesla
2050 GPU cards
•What can it do today?
40 cluster applications are
currently enabled including
MatLab, Beast, MrBayes, Blast,
MPI Blast, PacBio analysis tools,
Celera Assembler, CLC Server,
Geneious Server
4
Isilon
•
What is it?
• High speed, scalable, and redundant Network Attached Storage
• Connected to both the CDC network and the Aspen HPC cluster
utilizing Infiniband
• Total of 500TB usable space
•
What can it do today?
• It provides user workspace for end-users
and HPC applications
• Solves the problem of being out of
disk space on individual servers
•
What are we doing with it?
• Data warehouse for all scientific equipment
• Central network share for all scientific users
• Integrating directly with ITSO’s Active Directory forest
5
Private Cloud
•
What is it?
• Support science through front-end and back-end services
• Implementation of virtualized infrastructure
• Currently in the process of being deployed
•
What can it do today?
• Provide test environments for scientific projects
• Lay the foundation for hardware consolidation
and migration
•
What are we doing with it?
• Standardize platforms
• Centralize management
6
Sequencing Lab Origins
• Began in 2001
• Mission: sequence 8 human smallpox viruses
before the WHO revisits destruction of all
smallpox stocks
• By 2005, had sequenced over 150 smallpox and
related poxvirus genomes.
• 2006: Roche 454, focus moved to small bacterial
genomes
• 2010: Illumina GAIIx
• 2011: Ion Torrent, PacBio
Sequencing: extended PCR
Position of E-PCR overlapping amplicons
A3
A1
End-L
A2
D PO C





A5
A4
A9
A7
A6
A8
A11
A10
E R K H ML I
F N
Q
HindIII map
A15
A13
A12
A14
A
SJ
A17 End-R
A16 A18
B
G
Primers designed using VAR-BSH and VAC-CPN sequences
Primers target genes involved in reproduction & host response
Sequence sample: primers 40 sites, 1 enz. RFLP ~120 sites
PCR uses minimal DNA amounts, often no need to grow virus
PCR uses hifi expand long-template Taq & Pwo enzymes (Roche)
Sequencing Assembly: Phred/Phrap/Consed
Gene Prediction
• Heuristic algorithm to assign quality scores to
ORFs (from 1 to 100)
• Quality scores are based on a number of
factors including
– Gene Predictions (glimmer, genemark, getorf)
– Primary sequence homology to known genes
(BLAST)
– Presence of predicted promoter (MEME/MAST)
– Size of predicted ORF
– Presence of transcription terminal signals
Visualizing Gene Predictions and Differences
ORFs of CPVXs from 4 different clades
ITR
crm-D
ITR
45 Smallpox Strains
A. West African
int. CFR ~10%
C. Asian major
CFR ~5 - 35%
B. American alastrim
minor CFR <1%
C-1. non-WestAfrican-African
int CFR ~10%
C-2. non-WestAfrican African
minor CFR <1%
Unrooted tree phylogenetic relationships of
ORF encoding the hemagglutinin protein
Taterapox
Camelpox
Cowpox clade IV
CPXV90_ger2
Variola
AF375135
L22579
Ectromelia
AY902256
Cowpox clade III
(CPXV91_ger3)
AY603355
AF377885
Cowpox clade II
AF375086
VACLS1
Z99045
AY902297
Cowpox clade I
Vaccinia
AF375102
Monkeypox
INFLUENZA
GSL sequencing 2013
NCIRD
Haemophilus influenzae
Legionella pneumophila
Legionella spp.
Mycoplasma pneumonia
Water cooling tower metagenomics
Respiratory filter metagenomics
Bordetella spp.
Tick metagenomics
NCEZID
Vibrio cholera
Vibrio spp
Camphylobacter
Salmonella
Bacillus anthracis
Listera
Bukholderia spp
Yersinia pestis
Brucella spp.
Klebsiella pneumonia
Fungal Meningiditis
Rift Valley Fever virus
Lujo virus
Marburg virus
CCHF virus
Lassa Fever virus
Clinical sample metagenomics
NCHHSTP
Neiseria spp
Hepatitis
Mycobacterium tuberculosis
CGH
Rhodoccocus
Cryptosporidium
Fasciola spp
Balamuthia spp
Next-Gen Diagnostic Sequencing Applications
Shotgun / Paired-End Sequencing: random shearing of DNA, even sequence
coverage over entire genome.
‘Massively parallel’ sequencing not only produces throughput, it provides
sequences of potentially millions of individual molecules (instant cloning). By
sequencing a PCR reaction it allows the detailed search for low expression
quasi-species or mutations which may signal growing drug or vaccine
resistance – a process called ultra-deep or amplicon sequencing.
Example: clinical case of poxvirus infection with
samples exhibiting a reduced sensitivity to an antiviral
drug.
Complex clinical, laboratory or environmental samples can be sequenced to
provide a diagnostic ‘snapshot’ of the resident organisms - an approach called
metagenomic sequencing.
Examples: tissue culture, soil, blood serum, sputum, stool
Shotgun / Paired-End Sequencing
De novo Assembly
• Newbler
• CLCBio
• Mira
• Geneious
• Velvet
• Celera Assembler
Reference Mapping
• Newbler
• CLCBio
• Mira
• Geneious
• BWA
• Bowtie
Genome Assembly Visualization
Genome Assembly Visualization
Genome Comparison
HGAP – Hierarchical Genome
Assembly Process
• PreAssembly
– Generation of long accurate reads
• Assembly
– Choice of assemblers, but OLC (Overlap
Layout Consensus) are best, MIRA and
Celera Assembler
• Consensus Polishing
– Quiver – a quality aware consensus algorithm
maps all reads back to the assembly and
creates a new consensus
HGAP: PreAssembly
30X
HGAP: PreAssembly/Assembly
• Correct seed reads with short reads
• Assemble with Celera Assembler or MIRA
HGAP - Quiver
• To reduce the remaining InDel and base substitution errors in the
draft assembly, we use the PacBio Quiver, a quality-aware
consensus algorithm. Four different per-base Quality Values (QV
scores) represent the intrinsically calculated error probabilities for
inserted, deleted, substituted and merged base calls in single pass
reads. These values allow Quiver to generate a highly accurate
consensus for the final assembly, which frequently exceeds QV50
(99.999% accuracy).
HGAP Example
HGAP Confirmation
with Physical Mapping
HGAP Assembly
Structural Confirmation
HGAP Sequence Confirmation
with Illumina reads
Amplicon (deep) sequencing project
Li, Damon - NCZEID/DVRD/PRB
• Clinical case of progressive vaccinia infection from
smallpox vaccination of an immune compromised
patient
• Pox antiviral ST-246 administered which targets pox
gene F13L, a major envelope protein which mediates
production of extracellular virus
• Oral ST-246 given daily and vaccination site sampled
over 3 week period
A region of gene F13L was amplified from clinical samples, deep sequenced,
and compared to the smallpox vaccine reference sequence (Acambis 2000)
Control swab prior to ST-246
2 weeks after ST-246
T>A
943
C>T
869
3 weeks after ST-246
C>T
869
T>A
943
What is Metagenomics?
•
•
Is the genomic study of DNA from uncultured
microorganisms, generally from environmental
samples
Related
• Metatranscriptomics
• Metaproteomics
Sample Coverage
Rarefaction Curves
Samples
Wooley JC, Godzik A, Friedberg I, 2010 A Primer on Metagenomics. PLoS Comput Biol 6(2)
Classification Techniques
•
Supervised Taxonomic Classification
• Homology-based
• Database searching by similarity (BLAST, SW)
• BLAST, BLASTX: genbank, specialized DBs: NCBI-ENV-NT,
NCBI-ENV-NR
• Composition-based
• N-mer frequency
• Markov Models, Support Vector Machines (SVM), need training
set
•
Unsupervised Taxonomic Classification
• Clustering methods
• SOM - self-organizing maps
• PCA – principal component analysis
Viral Metagenomic Pipeline
(Wash U scripts implemented at CDC)
Sample Collection
Contigs, Reads
DNA
Library Construction
Sequencing
Remove redundant sequences
Unique sequences
Mask repetitive and low complexity seqs
Good sequences
BLASTN against Human Genome (e ≤ 1e-10)
Basecalling
Vector Trimming
Assembly
Non-human sequences
BLASTX
vs nr
BLASTN
vs nt
BLASTN
vs GB-viral
Report Generation, Display in MEGAN, inspect top hits
Megan
Ugandan Outbreak Samples
•
4 patients
• Total RNA from patient sera
•
2 samples per 454 run
• ~ 565,000 reads/sample, avg length = 235nt
•
•
•
•
Sequences were screened for random library
amplication primers and low quality
Assembled each run de novo using the 454
gsAssembler
Performed a blastx database search using the
assembled contigs (overnight)
Visualized the blast output using MEGAN.
MEGAN (MetaGenomeANalyzer)
Ugandan Outbreak - results
•
•
•
Run1 - 5 contigs (out of 2463 > 100nt) matched YF
virus, covering 98% of the genome (10,441 of
10,823bp)
Mapped each sample from Run1 using an Ethiopian
YF virus as reference. 3229 individual reads from
Sample 1 indentified as YF.
Run 2 – no YF reads found
Phylogenetic analysis of yellow fever virus
sequences
Laura McMullan (DHPP/VSPB)
Comparative Metagenomics
•
•
One 454 run
Two samples
• Sample 1 – ~578,000 reads, avg read length 438 bases
• Sample 2 – ~550,000 reads, avg read length 425 bases
•
Total number of bases sequenced - ~488,000,000
Sample 1 – Rarefaction Curve
Sample 1 Taxa tree (collapsed at the Order
level)
Comparison of Sample 1 and 2
Bioinformatics Tools
•
•
•
•
Bioinformatics Packages
– EMBOSS
– CLCbio
– Geneious
– LaserGene-Ngen
– Galaxy
General Tools/ Languages
– Java/BioJava
– Perl/BioPerl
– R
– BLAST Suite
– BioEdit
Genome Comparison/Alignment Tools
– Mavid
– Mauve
– Clustal
– Muscle
– MAFFT
Gene Prediction
– Glimmer
– GeneMark
•
•
•
•
•
Assembly/Mapping Tools
– 454 Suite
– Mosaik Tools
– Mummer
– BWA
– Velvet
– AHA (pacbio)
Functional Annotation
– Manatee
Phylogenetics
– Paup
– Phylip
– MrBayes
– Beauti/Beast
– MEGA
– DnaSP
Metagenomics
– MEGAN
– Galaxy
– Carma
In-House
– WAMS
– POCs/VOCs
Challenges
Data Management – image files are large moving these files around the
network is slow
Assembly/Mapping Software – Some are provided with the instrument,
but additional methods and algorithms are needed
Finishing Tools – gap filling, primer design
Visualization Tools – tools to graphically display contigs on reference
sequence as well as genome multiple alignments
Generic Robust Annotation Tools – Researchers need tools to
intelligently choose predicted ORFs as genes, assign function, and
submit to GenBank
What are the weaknesses of current next-gen sequencers?
Complicated and time consuming library preparation
Requires micrograms of DNA to begin
3 days to prepare library
Requires amplification of library
Low copy number polymorphisms may be missed
Emulsion PCR is an inefficient, time consuming, oily mess
Potential to introduce PCR bias into sample
Instruments require repetitive sequential ‘flows’ of reagents
Repetitive flows of nucleotides, blocking/unblocking chemistry, washing out
reaction byproducts all slow synthesis and hinder read-length
Consumes liters of reagents ($)
Repetitive flows and imaging extend sequence runs to days (or weeks)
Pacific Bioscience SMRT sequencer
(single-molecule sequencer)
Ion Torrent Personal Gene Machine
(solid-state sequencer)
Nanopore sequencing
Pacific Biosciences SMRT sequencer
Sponsor: Influenza Research Agenda
Pacific Biosciences SMRT Technology
Individual ZMW with attached
polymerase and DNA strand
Laser excitation/detection volume
glass 
~ 50 nm
SMRTcell = 160,000 ZMW
Functional volume (red) is in zL!
SMRTcell array = 1.5 million ZMW
Nucleotide incorporation is a realtime data movie
100 ms
Pacific Biosciences Advantages
 Read lengths of 1,000 – 10,000 bases
 No reagent ‘flows’ =10-fold increase in sequencing speed
 Substitute reverse transcriptase for polymerase and sequence RNA directly
 Bacteria genomes sequenced in hours
 Sequence run costs 99$; take 15 minutes to complete