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Diabetes Research in the Era of Complete Genomes. American Diabetes Association June 17, 2002 Francis S. Collins, M.D., Ph.D. Fulfilling the Promise of Genomics for Better Health. Medical Genomics. Functional Genomics. Proteomics. Comparative Genomics.

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diabetes research in the era of complete genomes

Diabetes Research in the Era of Complete Genomes

American Diabetes Association

June 17, 2002

Francis S. Collins, M.D., Ph.D.

slide7

Fulfilling the Promise of Genomics for Better Health

Medical Genomics

Functional Genomics

Proteomics

Comparative Genomics

slide8

Positional cloning of a gene for a highly penetrant Mendeliandisorder is now straightforward –but tracking genetic susceptibility factors for non-Mendelian disorders continues to be vexing

study design
Study design
  • Linkage study using affected sibling pairs (ASPs)
  • In the presence of linkage, siblings show excess sharing
  • Additional relatives collected to determine haplotypes
study sample
Study sample
  • Collected from Finland
    • Founder population
    • High participation rate

FUSION 1: 580 families n = 3584

FUSION 2: 275 families n = 877

Elderly controls n = 231

slide12

Linkage analysis

Positive LOD score identified

Fine mapping with SNPs

Association identified

Causative variant identified

genome scan linkage results
Genome scan linkage results

Ghosh et al (2000) AJHG 67:1174

slide14

HNF4A

SLC2A10

PTPN1

Microsatellites

slide15

Linkage analysis

Positive LOD score identified

Fine mapping with SNPs

Association identified

Causative variant identified

primer extension mass spectrometry

Mass in Daltons

GACCTGGAGCCCCCACC

5430.5

GACCTGGAGCCCCCACCC

5703.7

GACCTGGAGCCCCCACCTG

6047.9

Primer extension massspectrometry

Primer extension reactions designed to generate different sized products

C

T

primer

association is much more powerful than linkage to identify common susceptibility variants
Association is much more powerful than linkage to identify common susceptibility variants

N. Risch and S. Merikangas

Science 273: 1516-1517, 1996

slide19

Linkage analysis

Positive LOD score identified

Fine mapping with SNPs

Association identified

Causative variant identified

slide20

Fine mapping with SNPs

Association identified

Causative variant identified

genome scan association results

-log10(p-value)

-log10(p-value)

Genome scan association results

Ghosh et al (2000) AJHG 67:1174

slide23

Fine mapping with SNPs

Association identified

Causative variant identified

whole genome association approach to common disease
Whole Genome Association Approach to Common Disease
  • Identify all 10 million common SNPs
  • Collect 1000 cases and 1000 controls
  • Genotype all DNAs for all SNPs
current high throughput snp genotyping methods
Current high throughput SNP genotyping methods
  • DNA chips
  • Beads/fiberoptics
  • Fluorescent single base extension
  • Pyrosequencing
  • Mass spectrometry
  • TaqMan
  • Invader
  • Etc., etc.
shortcut 1

Shortcut #1:

Use haplotypes to reduce number of SNPs that have to be genotyped

slide28

Sequence from chromosome 7

GAAATAATTAATGTTTTCCTTCCTTCTCCTATTTTGTCCTTTACTTCAATTTATTTATTTATTATTAATATTATTATTTTTTGAGACGGAGTTTCACTCTTGTTGCCAACCTGGAGTGCAGTGGCGTGATCTCAGCTCACTGCACACTCCGCTTTCC/TGGTTTCAAGCGATTCTCCTGCCTCAGCCTCCTGAGTAGCTGGGACTACAGTCACACACCACCACGCCCGGCTAATTTTTGTATTTTTAGTAGAGTTGGGGTTTCACCATGTTGGCCAGACTGGTCTCGAACTCCTGACCTTGTGATCCGCCAGCCTCTGCCTCCCAAAGAGCTGGGATTACAGGCGTGAGCCACCGCGCTCGGCCCTTTGCATCAATTTCTACAGCTTGTTTTCTTTGCCTGGACTTTACAAGTCTTACCTTGTTCTGCCTTCAGATATTTGTGTGGTCTCATTCTGGTGTGCCAGTAGCTAAAAATCCATGATTTGCTCTCATCCCACTCCTGTTGTTCATCTCCTCTTATCTGGGGTCACA/CTATCTCTTCGTGATTGCATTCTGATCCCCAGTACTTAGCATGTGCGTAACAACTCTGCCTCTGCTTTCCCAGGCTGTTGATGGGGTGCTGTTCATGCCTCAGAAAAATGCATTGTAAGTTAAATTATTAAAGATTTTAAATATAGGAAAAAAGTAAGCAAACATAAGGAACAAAAAGGAAAGAACATGTATTCTAATCCATTATTTATTATACAATTAAGAAATTTGGAAACTTTAGATTACACTGCTTTTAGAGATGGAGATGTAGTAAGTCTTTTACTCTTTACAAAATACATGTGTTAGCAATTTTGGGAAGAATAGTAACTCACCCGAACAGTGTAATGTGAATATGTCACTTACTAGAGGAAAGAAGGCACTTGAAAAACATCTCTAAACCGTATAAAAACAATTACATCATAATGATGAAAACCCAAGGAATTTTTTTAGAAAACATTACCAGGGCTAATAACAAAGTAGAGCCACATGTCATTTATCTTCCCTTTGTGTCTGTGTGAGAATTCTAGAGTTATATTTGTACATAGCATGGAAAAATGAGAGGCTAGTTTATCAACTAGTTCATTTTTAAAAGTCTAACACATCCTAGGTATAGGTGAACTGTCCTCCTGCCAATGTATTGCACATTTGTGCCCAGATCCAGCATAGGGTATGTTTGCCATTTACAAACGTTTATGTCTTAAGAGAGGAAATATGAAGAGCAAAACAGTGCATGCTGGAGAGAGAAAGCTGATACAAATATAAATGAAACAATAATTGGAAAAATTGAGAAACTACTCATTTTCTAAATTACTCATGTATTTTCCTAGAATTTAAGTCTTTTAATTTTTGATAAATCCCAATGTGAGACAAGATAAGTATTAGTGATGGTATGAGTAATTAATATCTGTTATATAATATTCATTTTCATAGTGGAAGAAATAAAATAAAGGTTGTGATGATTGTTGATTATTTTTTCTAGAGGGGTTGTCAGGGAAAGAAATTGCTTTTTTTCATTCTCTCTTTCCACTAAGAAAGTTCAACTATTAATTTAGGCACATACAATAATTACTCCATTCTAAAATGCCAAAAAGGTAATTTAAGAGACTTAAAACTGAAAAGTTTAAGATAGTCACACTGAACTATATTAAAAAATCCACAGGGTGGTTGGAACTAGGCCTTATATTAAAGAGGCTAAAAATTGCAATAAGACCACAGGCTTTAAATATGGCTTTAAACTGTGAAAGGTGAAACTAGAATGAATAAAATCCTATAAATTTAAATCAAAAGAAAGAAACAAACTA/GAAATTAAAGTTAATATACAAGAATATGGTGGCCTGGATCTAGTGAACATATAGTAAAGATAAAACAGAATATTTCTGAAAAATCCTGGAAAATCTTTTGGGCTAACCTGAAAACAGTATATTTGAAACTATTTTTAAA

Three variants are present

these three variants could theoretically occur in 8 different haplotypes

These three variants could theoretically occur in 8 different haplotypes

…C…A…A…

…C…A…G…

…C…C…A…

…C…C…G…

…T…A…A…

…T…A…G…

…T…C…A…

…T…C…G…

but in practice only two are observed

But in practice, only two are observed

…C…A…A…

…C…A…G…

…C…C…A…

…C…C…G…

…T…A…A…

…T…A…G…

…T…C…A…

…T…C…G…

a haplotype map of human variation
A Haplotype Map of Human Variation
  • Goal is to define all common haplotypes in the human genome
  • Genome-wide association studies can then be done with a haplotype tag set of about 250,000 SNPs
  • Pilot studies underway to determine how many populations to sample, and best strategy for defining haplotype blocks
shortcut 2

Shortcut #2:

Use DNA pooling to greatly reduce amount of genotyping

slide36

Creating DNA Pools

Case DNA Samples

Control DNA Samples

“Case” Pool

“Control” Pool

testing performance of methods for determining allele frequency differences in pools
Testing performance of methods for determining allele frequency differences in pools
  • Tested 16 non-optimized SNPs with:
    • MALDI-TOF mass spec
    • Pyrosequencing
    • Fluorescent primer extension
  • Each assay carried out 8 – 16 times
  • Each method tested on three pools with n > 100
    • Diabetics
    • Spouses
    • Elderly non-diabetics
slide38

G

A

Diabetic Probands

38% A

G

Spouse Controls

34% A

A

G

Elderly

Non-diabetic Controls

30% A

A

MALDI-TOF Mass Spectrometric Detection

of Allele Frequencies in Pooled DNA Samples

slide39

Frequency

Difference from

Pooled

Genotypes

(MALDI-TOF)

slide41

Fine mapping with SNPs

Association identified

Causative variant identified

slide43

Fulfilling the Promise of Genomics for Better Health

Medical Genomics

Functional Genomics

Proteomics

Comparative Genomics

a sample of ongoing public large scale animal genome sequencing projects

A sample of ongoing public large scale animal genome sequencing projects

Mouse – now at 7X

Rat – now at 4X

Tetraodon – now at 6X

Fugu – now at 5X

Zebrafish – now at 2X

Ciona intestinalis – now at 10X

Ciona savignyi – now at 12X

C. briggsae – now at 10X

slide45

The Mouse Genome Sequencing Consortium

The Sanger Institute

Washington University

Whitehead Institute

NHGRI

Wellcome Trust

www.ensembl.org

slide46

100%

50%

Reference = HUMAN

CAV2,1

MET

CAPZA2

ST7

WNT2

GASZ

CFTR

CORTBP2

PipMaker: Human-Mouse Alignment

diabetes research in the era of complete genomes1

Diabetes Research in the Era of Complete Genomes

The major predisposing genes for type 1 and type 2 diabetes should be identified in the next 5 – 7 years

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