Motivations to study human genetic variation. The evolution of our species and its history. Understand the genetics of diseases, esp. the more common complex ones such as diabetes, cancer, cardiovascular, and neurodegenerative.
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The evolution of our species and its history.
Understand the genetics of diseases, esp. the more common complex ones such as diabetes, cancer, cardiovascular, and neurodegenerative.
To allow pharmaceutical treatments to be tailored to individuals (adverse reactions based on genetics).
A chromosome region with only the SNPs shown. Three haplotypes are shown. The two SNPs in color are sufficient to identify (tag) each of the three haplotyes. For example, if a chromosome has alleles A and T at these two tag SNPs, then it has the first haplotype.
Make Genetic Profiles
The SNP database today
March, 2010 105,098,087
The 1000 Genomes Project submitted 17.3M SNPs
The 2008 SNP Submissions for the James Watson Genome totaled 3,542,364
The 2008 SNP Submissions for the J. Craig Venter Genome totaled 4,018,050
The 2008 SNP Submissions for the Individual Chinese Genome totaled 5,077,954
The 2008 SNP Submissions for the Individual Korean Genome totaled 1,750,224
Derived from dbSNP release 130
SNP’s aren’t everything: Introducing Copy Number Variations
Redon et al. Nature 2006
Genome Structural Variation Consortium
Array-CGH using a whole genome tile path array
Median clone size ~170 kb
All 270 HapMap individuals
Measures amount of DNA, not RNA
Comparison between two samples
‘Test’ sample vs ‘Reference’ sample
Values are typically normalized so that the mean log2 value for the entire array (or an individual chromosome) is 0
Analysis consists of identifying segments where the test and reference samples have unequal copy number
1,447 CNVRs from 270 HapMap samples
More than 10% of the genome sequence
Structural Variation Project
Nature 447: 161-165, 2007
Copy Number Variations are ubiquitous in the human genome
The number of genome structural variants (>1 kb) that distinguish genomes of different individuals is at least on the order of 600–900 per individual.
J.O. Korbel et al., Science318(2007), pp. 420–426
ASW African ancestry in Southwest USA
CEU Utah residents with Northern and Western European ancestry from the CEPH collection
CHB Han Chinese in Beijing, China
CHD Chinese in Metropolitan Denver, Colorado
GIH Gujarati Indians in Houston, Texas
JPT Japanese in Tokyo, Japan
LWK Luhya in Webuye, Kenya
MXL Mexican ancestry in Los Angeles, California
MKK Maasai in Kinyawa, Kenya
TSI Toscani in Italia
YRI Yoruba in Ibadan, Nigeria
SNP allele frequency estimation
Linkage disequilibrium analysis
Genomic locations of human CNVs
Genotypes for CNVs
Population genetic properties of CNVs (allele frequencies, population differentiation, etc.)
Mutation rate (frequency of de novo CNV) and potential mutational mechanisms
Linkage disequilibrium properties of CNVs
Tagging and imputation of CNVs
Signals of selection around CNVs
Association of SNPs and CNVs with expression phenotypes
Computational detection of structural genomic variation
Direct comparison of genomes through sequence alignments
All types of genomic variation can be identified, including balanced variants (inversions or translocations)
No limit in the resolution and breakpoints can be defined at nucleotide level
Generate a lot of false positives due to sequence misassembly and gaps
Out of Africa
Scientific American, August 1999)
Modern humans arose in Africa and replaced other human species across the globe.
Out of Africa again and again
Itai Yanai, 2003
Templeton, A. Nature 416 (2002): 45 - 51