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