Thanks to the Lipper Center for Computational Genetics Government and private grant agencies: NHLBI, NSF, ONR, DOE, DARPA, HHMI, Armenise Corporate collaborators & sponsors: Affymetrix, GTC, Mosaic, Aventis, CHI Macroresults through Microarrays 3 George Church 1-May-02 Array quantitation for modeling mutations affecting RNA, protein interactions & cell proliferation.
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Thanks to the Lipper Center for Computational Genetics
Array quantitation for modeling mutations affecting RNA, protein interactions & cell proliferation. CHI Macroresults through Microarrays 3. George Church 1-May-02. Thanks to the Lipper Center for Computational Genetics Government and private grant agencies: NHLBI, - PowerPoint PPT Presentation
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Thanks to the Lipper Center for Computational Genetics
Government and private grant agencies: NHLBI,
NSF, ONR, DOE, DARPA, HHMI, Armenise
Corporate collaborators & sponsors:
Affymetrix, GTC, Mosaic, Aventis, Dupont, Cistran
CHI Macroresults through Microarrays 3
George Church 1-May-02
Array quantitation for modeling mutations affecting RNA, protein interactions & cell
Microbes Cancer & stem cells DarwinianIn vitro replicationSmall multicellular organisms
RNAiInsertionsSNPs
Functional Genomics Challenges • Systems dynamics and optimality modeling.• Multiple genetic domains per gene: high density readout of whole genome mutant phenotypes.• Multiple RNAs & regulatory proteins per gene.• Many causative genes & haplotypes per disease.
• Polony RNA exon-typing• Multiplex in situ RNA & protein analyses • Automated differentiation• Homologous recombination genome engineering
Human Red Blood CellODE model200 measured parameters
Common diseases: billions of “new” allelesplus a millions of balanced polymorphisms
• 60 new mutations per generation * 5,000 generations since major bottleneck(s) which set up the linkage patterns (=300,000 per genome)
• Each of the 3 Gbp in the genome exist in all SNP forms: A,C,G,T, 600,000 of each SNP on earth (spread over the common haplotypes).The population frequency will be <0.01%. (Aach et al, 2001 Nature 409: 856)
• Functional genomics (FG) may provide better leads for therapies & diagnostics. (Accuracy goal 1 ppb?)
Projected costs affect our view of what is possible.
In 1985, the dawn of the genome project, $10 per bp, would have been $30B per genome.In 2002, Perlegen or Lynx: $3M (103 bits/$, 4 logs)
In 2001, the cost of video data collection? 1013 bits/$
Genotyping & functional genomics demand will probably be as high as permitted by costs.
Femtoliter (10-15) scale & low-cost scannersPolymerase DNA colonies (polonies)Fluorescent in situ sequencing (FISSEQ)
•Multiplex polonies spanning all likely variable exons
•Sequential probing of each exon.
Functional Genomics Challenges • Systems dynamics and optimality modeling.• Multiple genetic domains per gene: high density readout of whole genome mutant phenotypes.• Multiple RNAs & regulatory proteins per gene.• Many causative genes & haplotypes per disease.
• Polony RNA exon-typing• Multiplex in situ RNA & protein analyses • Automated differentiation• Homologous recombination genome engineering