1. Predicting the Function of Single Nucleotide Polymorphisms Corey Harada Advisor: Eleazar Eskin

2. Background Polymorphisms  A change to a DNA sequence.  Source of genetic variation. Single Nucleotide Polymorphism (SNP)  Mutation of a single nucleotide. AGATCGATC AGATTGATC

3. Single Nucleotide Polymorphisms We can figure out the locations of SNPs by looking at genotypes.  How do we figure out the function of each SNP? Many SNPs are do not affect phenotypes at all. A way to determine which SNPs are significant and which are not could be useful.

4. Approach Only work on SNPs in coding regions. Translate the protein using the sequence with and without the SNP. Use BLAST to find similar proteins.

5. BLAST Basic Local Alignment and Search Tool Searches a database of proteins for various organisms. Proteins in humans are related to those that other mammals produce.  Finding better results for one SNP would indicate selection.  May indicate that it is linked to a disease.

6. BLAST BLAST bit score  Score S is based on how well the sequences align  K – Scale factor for search space size  λ – Scale factor for scoring system Bit score is the normalized score which indicates how well the protein aligns. Normalization is needed to compare scores for multiple alignments.

7. Results Based off of SNPs in exon regions of human chromosome 1 (from HapMap rel23a)

8. Analysis The program provided a number of SNPs with a zero difference in byte score, in some cases SNPs known to cause phenotypic changes. Possible causes:  SNPs that cause changes to protein transcription.

9. Future Work Consider SNPs not in coding regions  SNPs in introns could be ranked similarly based on binding data.