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WG1

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Title: WG1


1
  • WG1
  • Petri Auvinen
  • DNA Sequencing and Genomics Laboratory
  • Institute of Biotechnology
  • University of Helsinki
  • http//www.biocenter.helsinki.fi/bi/dnagen/

2
Deliverables WG 1 Sequence Production Analysis
  • Scientific workshops
  • Design and analysis of NGS data
  • Whitepaper
  • Gaps between existing techniques and needs to
    analyze NGS data
  • Short Term Scientific Missions
  • Competitive calls, preference for early-stage
    scientists
  • Community-driven wiki-webpage
  • Frequently updated list of references to
    state-of-the-art designs and analysis tools
    their applications to NGS data on plants

3
Working Groups
WG1 Sequence Production Analysis
Locus-sequencing variability
WG2 Sequence To Phenotype Integration
Locus-penetrance
4
  • Parallel Sequencing Technology
  • Massive throughput
  • Fast sequencing
  • No cloning step
  • PCR
  • Currently three systems
  • Genome Sequencer (http//www.454.com/,http//www.r
    oche.com)
  • 454 Life Sciences, Roche
  • Launched in October 2005
  • Solexa (http//www.illumina.com)
  • Illumina
  • Launched 2006
  • SOLiD (http//www.appliedbiosystems.com)
  • Applied Biosystems
  • Launched in October 2007

5
  • Genome Sequencer GS20 FLX Titanium
  • 454 Life Science, Roche
  • Shotgun sequencing
  • No plasmid libraries
  • Linkers ligated to fragments
  • Emulsion PCR
  • Picotiter plate, 1 600 000 wells
  • Titanium 3 400 000 wells
  • Pyrosequencing
  • (Nyren, P. et al Anal Biochem. 1993, 208,171-5)
  • Detection with sensitive CCD camera
  • Read length 100 -120 bp 250 300 bp 400 bp
  • Run time ca. 4,5 h 7,5 h 10h
  • Raw sequence ca. 25 35 Mb/run 80 100 Mb/run
    400-600 Mb/run

6
Illumina/Solexa Genome Analyzer
(http//www.illumina.com)
  • Clonal Single Molecule Array technology
  • Sequencing-by-synthesis technology
  • Reversible terminator-based sequencing
  • removable fluorescence
  • Flow cell with gt 10 million clusters
  • Each cluster 1,000 copies of template /cm2
  • 18 samples / run
  • 3 laser system (660, 635, and 532 nm)
  • Read length 35 50-100 bp, 1- 2 Gb / run
  • Run time 3 6 days,

Cluster Station
Flow cell
7
SOLiD, Applied Biosystems(http//www.appliedbiosy
stems.com)
  • Sequencing by Ligation
  • emPCR
  • Small beads, 1mm
  • Attaching to glass slides
  • Labelled probes
  • Fuor colours
  • 2 base encoding system
  • Repeated ligation steps
  • Detection with 4 Mpixel camera
  • Read lenght 25-30-50 bp
  • 1-2 slides / run
  • 1-2 Gb / run
  • Run time 5 -10 days

Shendure, J. et.al. Science 2005, 309, 1728-1732

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9
Next next gen technologies
  • Helicos (www.helicosbio.com)
  • Sequencing-by-synthesis
  • No PCR amplification
  • 25-90 Mb/h
  • VisiGen (www.visigenbio.com)
  • Real-time detection of DNA synthesis, FRET
  • Intact DNA fragments
  • 1Mb/sec/machine

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  • Pacific Biosciences (www.pacificbiosciences.com)
  • (Korlach, J. et.al. PNAS 2008, 105, 1176-81,
    Levene, MJ. et.al. Science 2003, 299, 682-86)
  • Single-Molecule, Real-Time (SMRT) DNA sequencing
    technology
  • SMRT chip
  • Thousands zero-mode waveguides (ZMWs)
  • Holes 100 nm metal film, measurement volume 20
    zeptoliters (10-21 liters)
  • Real-time detection of DNA synthesis
  • Fluorescent dNTPs

16
Exon capture, Hodges et al 2007
17
Assembly Huse S, Huber J, Morrison H, Sogin M,
Mark Welch D Accuracy and quality
of massivelyparallel DNA pyrosequencing. Genome
Biology 2007, 8R14310.1186/gb-2007-8-7-r143. Butl
er J, MacCallum I, Kleber M, Shlyakhter IA,
Belmonte MK, Lander ES, Nusbaum C, Jaffe DB
ALLPATHS De novo assembly of whole-genome
shotgun microreads. Genome Research Warren R,
Sutton G, Jones S, Holt R Assembling millions of
short DNA sequences usingSSAKE. Bioinformatics
2007, 23500-1. Zerbino D, Birney E Velvet
Algorithms for De Novo Short Read Assembly Using
DeBruijn Graphs. Genome Research 2008,
4510.1101/gr.074492.107. Simpson, J, Wong K,
Jackman S, Schein J, Jones SJM, Birol I ABySS A
parallel assembler for short read sequence data.
Genome Research (2009).doi10.1101/gr.089532.108
Annotation Parra G, Bradnam K, Korf I CEGMA a
pipeline to accurately annotate core genes in
eukaryotic genomes. Bioinformatics 2007,
10.1093/bioinformatics/btm071
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