Introduction to bioinformatics lecture 11 SNP by Ms.Shumaila Azam

1. Introduction to bioinformaticslecture 11SNPby Ms.Shumaila Azam

2. Human Genome and SNPs • Now that the human genome is (mostly) sequenced, attention turning to the evaluation of variation • Alterations in DNA involving a single base pair are called single nucleotide polymorphisms, or SNPs • Map of ~1.4 million SNPs • It is estimated that ~60,000 SNPs occur within exons;

3. Goals of SNP Initiatives • Immediate goals: • The hundreds of thousands of SNPs estimated to be present in the human genome • Interest also in other organisms, e.g. potatoes(!) • Establishment of SNP Database(s)

4. Longer term goals: Areas of SNP Application • Gene discovery and mapping • Diagnostics/risk profiling • Response prediction • Gene function identification

5. Polymorphism • Technical definition: most common variant (allele) occurs with less than 99% frequency in the population • Also used as a general term for variation • Many types of DNA polymorphisms, including RFLPs, VNTRs, microsatellites • ‘Highly polymorphic’ = many variants

6. Use of Polymorphism in Gene Mapping • 1980s – RFLP marker maps • 1990s – microsatellite marker maps

7. Gene Discovery and Mapping • Linkage Analysis • Within-family associations between marker • Linkage Disequilibrium (LD) • Across-family associations

8. Crossing over and Recombination

9. Disease-Marker Association • A marker locus is associated with a disease if the distribution of genotypes at the marker locus in disease-affected individuals differs from the distribution in the general population • A specific allele may be positively associated (over-represented in affecteds) or negatively associated (under-represented)

10. Examples: Alzheimer’s The E4 allele appears to be positively associated with Alzheimer’s disease: Odds Ratio = (58/16)/(33/55) = 6

11. Linkage Allele D is created Mutation occurs Nearby marker Allele M was nearby D and M subsequently transmitted together

12. Candidate Polymorphism Testing • Large SNP collections may allow testing for direct, physiologically relevant associations with trait

13. Diagnostics/Risk Profiling • Identified SNP associations can potentially be used to develop diagnostic tools

14. Response Prediction • Pharmaceutical companies especially interested in this: • Aim to identify those likely to respond • Predict toxicity reactions in susceptible individuals • Response to any kind of substance; creation of ‘functional foods’

15. Gene Function Identification • Alternative to other experimental procedures (e.g. knock-outs, which cannot be used in humans) • Studies to compare individuals with and without naturally occurring disease predisposing genetic profiles