Next now generation genomics methods and applications for modern disease research
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Next Now -Generation Genomics: methods and applications for modern disease research. Aaron J. Mackey, Ph.D. amackey@virginia.edu Center for Public Health Genomics Wednesday October 7 th , 2009 BIMS 853 Special Topics in Cardiovascular Research. “omic” Disease Research.

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Next now generation genomics methods and applications for modern disease research

Next Now-Generation Genomics:methods and applications formodern disease research

Aaron J. Mackey, Ph.D.

amackey@virginia.edu

Center for Public Health Genomics

Wednesday October 7th, 2009

BIMS 853 Special Topics in Cardiovascular Research


Omic disease research
“omic” Disease Research

source: Francis Ouellette, OICR



Basics of the old technology
Basics of the “old” technology

  • Clone the DNA.

  • Generate a ladder of labeled (colored) molecules that are different by 1 nucleotide.

  • Separate mixture on some matrix.

  • Detect fluorochrome by laser.

  • Interpret peaks as string of DNA.

  • Strings are 500 to 1,000 letters long

  • 1 machine generates 57,000 nucleotides/run

  • Assemble all strings into a genome.

source: Francis Ouellette, OICR


Basics of the new technology
Basics of the “new” technology

  • Get DNA.

  • Attach it to something.

  • Extend and amplify signal with some color scheme.

  • Detect fluorochrome by microscopy.

  • Interpret series of spots as short strings of DNA.

  • Strings are 30-300 letters long

  • Multiple images are interpreted as 0.4 to 1.2 GB/run (1,200,000,000 letters/day).

  • Map or align strings to one or many genome.

source: Francis Ouellette, OICR


Differences between platforms
Differences between platforms:

  • Nanotechnology used.

  • Resolution of the image analysis.

  • Chemistry and enzymology.

  • Signal to noise detection in the software

  • Software/images/file size/pipeline

  • Cost $$$

source: Francis Ouellette, OICR


Next now generation genomics methods and applications for modern disease research

Adapted from Richard Wilson, School of Medicine, Washington University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

3 Gb ==

source: Francis Ouellette, OICR


Ngs technologies
NGS technologies University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • Roche/454 Life Sciences

  • Illumina (Solexa)

  • ABI SOLiD

  • Helicos

  • Complete Genomics

  • Pacific Biosciences

  • Polonator


Roche 454 pyrosequencing
Roche/454 pyrosequencing University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


454 flowgram
454 flowgram University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

454 has difficulty quantizing luminescence of long homopolymers;problem gets worse with homopolymer length


Roche 454
Roche/454 University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • first commercially available NGS platform

  • long reads (most 100-500bp; soon 1000bp)

  • paired-end module available

  • relatively expensive runs

  • homopolymer error rate is high

  • common uses: metagenomics, bacterial genome (re)sequencing

  • James Watson’s genome done entirely on 454

  • UVA Biology Dept. has one (Martin Wu)


Illumina solexa
Illumina (Solexa) University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • 75 bp reads, PE

  • 150-250 bp fragments

  • 8 lanes per flowcell

  • ~3 Gbp per lane

  • < 5% error rate

  • available at UVA BRF DNA Core


Abi solid
ABI SOLiD University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Solid color space
SOLiD “color space” University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Abi solid1
ABI SOLiD University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • short reads (~35 bp)

  • cheapest cost/base

  • high fidelity reads (easy to detect errors)

  • Common uses: SNP discovery

  • 1000 genome project

  • with PET libraries, all applications within reach …


Comparing sequencers
Comparing Sequencers University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

source: Stefan Bekiranov, UVA


Other ngs platforms
Other NGS platforms University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • Helicos (Stephen Quake, Stanford)

    • single molecules on slide

    • like Illumina, but no PCR, greater density

  • Complete Genomics

    • sequencing factory

    • 10K human genomes/year, $10K each

  • Pacific Biosciences – SMRT

    • DNA polymerase bound to laser/camera hookup

    • records a movie of DNA replication with fluoroscent dNTPs as single strand moves through nanopore

  • Polonator (Shendure and Church)

    • homebrew, $200K flowcell+laser machine

    • allows custom chemistry protocols


Ngs applications
NGS applications University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • genome (re)sequencing

    • de novo genomes: 454 in Bact, small Euks

    • SNP discovery and genotyping (barcoded pools)

    • targeted, “deep” gene resequencing

    • metagenomics

  • structural/copy-number variation

    • Tumor genome SV/CNV: Illumina/PET

  • epigenomics – last week’s seminar

  • RNA-seq: now-generation transcriptomics

  • ChIP-seq: now-generation DNA-binding


Rna seq rna abundance
RNA-seq: RNA abundance University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Rna seq alternative splicing
RNA-seq: alternative splicing University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Rna seq
RNA-seq University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

  • “unbiased” digital measure of abundance

    • residual PCR artifacts? Helicos says “yes”

  • larger dynamic range than microarray

    • depends on sequencing depth  cost

  • ability to see alt./edited transcripts

    • multiple AS sites confounded; 454?

  • Total RNA vs. cDNA

    • 3’ end bias of cDNA

    • non-polyA transcripts in total RNA


Chip seq protein dna binding
ChIP-seq: protein-DNA binding University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Pet paired end tag libraries
PET: Paired End Tag libraries University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Pet applications
PET applications University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk


Some things i didn t get to talk about much
some things I didn’t University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alkget to talk about much:

  • personal genome sequencing/medicine

  • microbial metagenomics

  • ENCODE/modENCODE projects

  • HapMap project

  • human 1000 Genome Project (1KGP)

  • targeted- and/or deep-resequencing

  • microRNAs, piRNAs, ncRNAs, …

  • SVs and CNVs (cancer)

  • read alignment issues (“mapability”)


Questions

Questions? University, “Sequencing the Cancer Genome” http://tinyurl.com/5f3alk

amackey@virginia.edu


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