Deep Sequencing

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Deep Sequencing
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IV. Background--Deep Sequencing
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Illumina Sequencing Technology

• Relies on the attachment of randomly fragmented
  and amplified DNA (clonal clusters) to a planar,
  optically transparent surface (flow cell).
• High-sensitivity fluorescence detection is
  achieved using laser excitation and total
  internal reflection optics.
• Sequence reads are aligned against a reference
  genome and genetic differences are called using
  proprietary software.

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Illumina Cluster Station

• Amplification of clonal clusters from single
  molecule fragments covalently bound to the flow
  cell surface.
• Software-controlled system.
• Walk-away automation.
• In 5 hours (lt1 hour of hands-on time).
• Generates clonal clusters for up to eight samples
  in parallel.
• Where DNA or RNA is prepared for
  sequencing-by-synthesis on the Genome Analyzer.

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Paired-End Module

• After completion of the first read, the templates
  can be regenerated in situ to enable a second gt50
  bp read from the opposite end of the fragments.
• The Paired-End Module directs the regeneration
  and amplification operations to prepare the
  templates for the second round of sequencing.
• First, the newly sequenced strands are stripped
  off and the complementary strands are bridge
  amplified to form clusters.
• Once the original templates are cleaved and
  removed, the reverse strands undergo
  sequencing-by-synthesis.
• The second round of sequencing occurs at the
  opposite end of the templates, generating gt50 bp
  reads for a total of gt10 Gb of paired-end data
  per run.

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Illumina Flow Cell

• One (1) flow cell.
• Eight (8) channels.
• Each channel can run up to twelve (12)
  differently tagged libraries (Multiplexed
  Sequencing).
• Input requirement 0.11.0 µg (single- and
  paired-end reads),
• 10 µg (Mate Pair reads).
• 1.4-mm wide channels.
• Relies on the binding of randomly fragmented DNA
  to attached oligos on a planar, optically
  transparent surface (flow cell).
• 96-120 million reads (clusters) per flow cell,
  each containing 1,000 copies of the same
  template.

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Work Flow
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Sequencing Technology Overview
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Sequencing Technology Overview
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Sequencing Technology Overview
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Sequencing Technology Overview
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VI. The Different Sequencing Platforms Offered
by the DGML.
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(No Transcript)
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Single-read sequencing for shorter reads to
achieve quicker turnaround times.
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Paired-end libraries (200-500 bp) best for large
and small insertions, deletions (indels),
inversions, and other rearrangements. Good for
characterizing repetitive sequence elements and
filling gaps.
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Mate pair libraries (2-5 kb) are best for de
novo assembly, including genome scaffolding
and genome finishing. Best for identifying
large structural variants.
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RNA-Seq

• Full sequence of all RNAs
• mRNAs, miRNAs, etc,
• Quantifiable
• Alternate splice variants
• Alternate poly(A) variants
• Rare transcripts
• Novel transcripts
• Full coverage
• Great depth
• 36 cycles

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Digital Gene Expression (DGE)-Tag Profiling

• Great depth
• Quantifiable
• Only 16 cycles required

Contains a MmeI site
MmeI cuts 17 bp downstream
Restriction site every 256 bp, will cut 99 of
mRNAs. Can also use DpnII.
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Illumina Tag Sequencing vs. Microarrays 't Hoen
et al. (2008). Nucleic Acids Res. 36(21) e141.

• Solexa/Illumina deep sequencing technology and
  five different microarray platforms were
  compared.
• The hippocampal expression profiles of wild-type
  and transgenic mutant dC-doublecortin-like kinase
  mice.
• Illumina DGE 2.4 million sequence tags per
  sample, spanning four orders of magnitude.
• Results were highly reproducible, even across
  laboratories.
• Found differential expression of 3,179
  transcripts with an estimated FDR of 8.5.
• Overlap was most significant for Affymetrix.
• Changes in expression observed by deep sequencing
  were larger than observed by microarrays or
  quantitative PCR.
• While undetectable by microarrays, antisense
  transcription was found for 51 of all genes and
  alternative polyadenylation for 47.

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miRNAs, non-coding RNAs, anti-sense RNAS
miRNAs, non-coding RNAs, anti-sense RNAS
Isolate small RNA
Universal Platform Analyze any small RNA without
prior sequence or secondary structure
information. Customizable Size Selection
Investigate any small RNA between 17 and 35
nucleotides. Broad Dynamic Range Profile gt10
million small RNA sequences in each flow cell
channel
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ChIP-Seq and RNA-IP-Seq
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Genomic DNA Methylation

• Generate genomic DNA libraries with and without
  bisulfite conversion.
• Continue with Paired-end and/or Mate-Pair
  sequencing.

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• Multiplexed
• Sequencing
• Allows multiple
• samples to be
• sequenced in a
• single channel.
• Great money saver!!

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Third-party Genome Analyzer Data Analysis
ToolsGenome Alignment BrowsersGbrowse -
Genomic BrowsingGeneric Model Organism Database
Project http//www.gmod.org/wiki/index.php/Gbrows
e UCSC Browser - Genome browsing and
comprehensive annotationGeneric Model Organism
Database Project http//genome.ucsc.edu/goldenPat
h/help/customTrack.html Staden Tools (GAP4,
TGAP) - Alignment and Visualization for Small
Data SetsJames Bonifield (initially developed by
Rodger Staden), Wellcome Trust Sanger Institute
http//sourceforge.net/projects/staden/
Alignment and Polymorphism DetectionBFAST
Blat-like Fast Accurate Search ToolNils Homer,
Stanley F. Nelson and Barry Merriman, University
of California, Los Angeles, http//genome.ucla.edu
/bfast MAQ Mapping and Assembly with
QualityHeng Li, Sanger Centre
http//maq.sourceforge.net/maq-man.shtml Bowtie
- An ultrafast memory-efficient short read
alignerBen Langmead and Cole Trapnell, Center
for Bioinformatics and Computational Biology,
University of Maryland http//bowtie-bio.sourcefo
rge.net/ Genomic AssemblyVelvet De novo
assembly of short readsDaniel Zerbino and Ewan
Birney, EMBL-EBI http//www.ebi.ac.uk/zerbino/ve
lvet/ SSAKE Assembly of short readsRene
Warren, et al, British Columbia Cancer Agency
http//bioinformatics.oxfordjournals.org/cgi/conte
nt/full/23/4/500 Euler Genomic AssemblyPavel
Pevzner and Mark Chaisson, University of
California, San Diego http//nbcr.sdsc.edu/euler/
ChIP SequencingChIP-Seq Peak FinderBarbara
Wold, Cal Tech and Rick Meyers, Stanford
University http//woldlab.caltech.edu/html/softwa
re/ Digital Gene ExpressionComparative Count
DisplayAlex Lash, NIH ftp//ftp.ncbi.nlm.nih.gov
/pub/sage/obsolete/bin/ccd/ SAGE DGED
Tool Cancer Genome Anatomy Project
http//cgap.nci.nih.gov/SAGE/SDGED_Wizard?METHODS
S10,LS10ORGHs
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Microarrays

• RNA 470 / array
• miRNA 480 / array
• CpG Island 530 / array
• CGH 580 / array
• Note Prices may drop depending on volume.

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Sequencing

• Library construction (optional service)
• 1000 / sample for single reads
• 1250 / sample for paired-end reads
• Kits
• DNA Prep (10 samples) 500
• ChIPseq (10 samples) 350
• Small RNA Prep Kits (10 samples) 350
• Sequencing
• Single-end runs 1000 / lane
• Paired-end runs 1700 / lane
• Multiplexing
• Multiplexing samples makes the total costs
  to an investigator who performs a typical
  experiment such as ChIPseq quite reasonable. For
  example, with the purchase of a single (10
  sample) 500 ChIPseq kit and the ability to
  barcode the non-IP-selected and ChIP-selected DNA
  with two different DNA linkers, an investigator
  can obtain ChIP sequences and control genomic
  sequences in a single 1000 run. Given the costs
  of whole genome tiling arrays, few investigators
  would opt to do this experiment by ChIP-on-chip.

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Contact us. http//dms.dartmouth.edu/dgml/Lab
603-653-9978Can contact anyone in the
pipeline and will be properly directed.
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The END