Diabetes research in the era of complete genomes
Download
1 / 50

Diabetes Research in the Era of Complete Genomes - PowerPoint PPT Presentation


  • 137 Views
  • Uploaded on

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.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Diabetes Research in the Era of Complete Genomes' - saima


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
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.


Diabetes research in the era of complete genomes

Fulfilling the Promise of Genomics for Better Health

Medical Genomics

Functional Genomics

Proteomics

Comparative Genomics


Diabetes research in the era of complete genomes

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


F inland u nited s tates i nvestigation o f n iddm
FinlandUnitedStatesInvestigation OfNIDDM


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


Diabetes research in the era of complete genomes

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


Diabetes research in the era of complete genomes

HNF4A

SLC2A10

PTPN1

Microsatellites


Diabetes research in the era of complete genomes

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


Diabetes research in the era of complete genomes

Linkage analysis common susceptibility variants

Positive LOD score identified

Fine mapping with SNPs

Association identified

Causative variant identified


Diabetes research in the era of complete genomes

Fine mapping with SNPs common susceptibility variants

Association identified

Causative variant identified


Genome scan association results

-log common susceptibility variants10(p-value)

-log10(p-value)

Genome scan association results

Ghosh et al (2000) AJHG 67:1174



Diabetes research in the era of complete genomes

Fine mapping with SNPs T2DM

Association identified

Causative variant identified


Whole genome association approach to common disease
Whole Genome Association Approach to Common Disease T2DM

  • 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 T2DM

  • DNA chips

  • Beads/fiberoptics

  • Fluorescent single base extension

  • Pyrosequencing

  • Mass spectrometry

  • TaqMan

  • Invader

  • Etc., etc.


Shortcut 1

Shortcut #1: T2DM

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


Diabetes research in the era of complete genomes

Sequence from chromosome 7 T2DM

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, different haplotypesonly 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…


Diabetes research in the era of complete genomes

~ 25 kb different haplotypes


A haplotype map of human variation
A Haplotype Map of Human Variation different haplotypes

  • 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: different haplotypes

Use DNA pooling to greatly reduce amount of genotyping


Diabetes research in the era of complete genomes

Creating DNA Pools different haplotypes

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


Diabetes research in the era of complete genomes

G frequency differences in pools

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


Diabetes research in the era of complete genomes

Frequency frequency differences in pools

Difference from

Pooled

Genotypes

(MALDI-TOF)


2 dnas x 250 000 snps 500 000 genotypes
2 DNAs x 250,000 SNPs = 500,000 genotypes frequency differences in pools


Diabetes research in the era of complete genomes

Fine mapping with SNPs frequency differences in pools

Association identified

Causative variant identified


Diabetes research in the era of complete genomes

http://genome.ucsc.edu frequency differences in pools


Diabetes research in the era of complete genomes

Fulfilling the Promise of Genomics for Better Health frequency differences in pools

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


Diabetes research in the era of complete genomes

The Mouse Genome Sequencing Consortium sequencing projects

The Sanger Institute

Washington University

Whitehead Institute

NHGRI

Wellcome Trust

www.ensembl.org


Diabetes research in the era of complete genomes

100% sequencing projects

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 sequencing projects Era of Complete Genomes

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


The fusion research team
The FUSION Research Team sequencing projects