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Global Variation in Copy Number in the Human Genome

Presentation by Chris Wescott and Angelica Stamegna. Global Variation in Copy Number in the Human Genome. Purpose. We, as humans, are 99.5% similar in our genetic make up 1 in 1,000 bp different Used the dissimilarities across populations, to come up with a whole genome CNV map

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Global Variation in Copy Number in the Human Genome

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  1. Presentation by Chris Wescott and Angelica Stamegna Global Variation in Copy Number in the Human Genome

  2. Purpose • We, as humans, are 99.5% similar in our genetic make up • 1 in 1,000 bp different • Used the dissimilarities across populations, to come up with a whole genome CNV map • Clinically applicable

  3. CNV classification 5 Types of CNV’s • Deletions • Duplications • Deletions and Duplications at the same locus • Multi-allelic loci • Complex loci that could not be determined

  4. Definitions • CNV (copy number variation)- difference in genome due to deletions, duplications, insertions, and complex-multisite variants that are 1kb or larger • Affymetrix 500K EA- analyzes SNPs • No reference genome

  5. Affymetrix Array- How does it work?

  6. Affymetrix 500K EA

  7. Definitions • CNV (copy number variation)- difference in genome due to deletions, duplications, insertions, and complex-multisite variants that are 1kb or larger • Affymetrix 500K EA- analyzes SNPs • WGTP (Whole Genome Tile Path)- uses large scale clones of a euchromatic section of a reference genome

  8. WGTP- How does it work?

  9. Whole Genome TilePath

  10. Methods Compared haplotypes of four different populations 30 parent-offspring from Nigeria (YRI) 30 parent-offspring from Utah, USA (CEU) 45 unrelated Japanese from Tokyo (JPT) 45 unrelated Han Chinese from Beijing, China (CHB)

  11. CNVR’s and CNV’s

  12. CNV map

  13. Discussion • Found 1,447 discrete CNVR’s covering 12% of the human genome • 6-19% of each chromosome • Deletions and Duplications • Not different frequencies but different lengths • Deletions were 1/3 of the size of duplications • Selective pressures

  14. Evolutionary Significance • Gene Families • Linkage Disequilibrium- alleles that do not behave at Hardy-Weinberg • Observed lower linkage disequilibrium for CNV’s than SNP’s • CNV’s happen on transposons • CNV’s might preferentially undergo recurrent mutations • CNV’s might occur preferentially in lower density SNP regions

  15. Diseases and Clinical Significance • CNV’s help with disease study rather than immediate clinical diagnostics • 285 out of 1,961 diseases in OMIM (Online Mendelian Inheritance in Man ) overlap CNV’s • Reliability of using SNP’s to confer disease-related CNVs

  16. Issues • Problems resolving genotype/phenotype correlations • Map itself is variable among populations of people • Human genome variation • No technology available to capture full variation, and multiple steps must be taken

  17. Conclusion • Using SNP genotyping arrays and clone-based comparative genomic hybridization • CNVRs encompass 12% of the genome and encompass genes, disease loci, functional elements and segmental duplications • CNVRs cover more nucleotide content than SNPs

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