1. Epidemiology 217 Omics, Bioinformatics, & Resources at UCSF John Witte

2. Follow-up from HW’s Assignment #3 For linkage looking for sharing departing from 50% Genotypes 677TT and 1298CC never observed together. –Lethal –T and C rare (T=6%) –Recent SNP, insufficient meiosis to separate.

3. Questions on Assignment #4? CodingCCCTTT Co-dominant010 001 Dominant011 Recessive001 Log Additive012

4. Harry Potter’s Pedigree Harry Potter Lily PotterJames Potter Aunt Petunia Uncle Vernon Dudley Dursley

5. What happened to Filch ? Argus Filch

6. Genomics Not looking at a single candidate gene or SNP. Genome: complete DNA sequence Raises issues of multiple comparisons. In HW, when looking at MTHFR we used P < 0.05 for a single comparison. What happens when looking for linkage or association on a genome-wide scale?

7. Moving Beyond Germline DNA

8. omicsno of occurrences genomics7522 proteomics4420 pharmacogenomics533 toxicogenomics141 metabolomics74 bionomics73 metabonomics63 transcriptomics63 glycomics23 chemogenomics22 ionomics19 nutrigenomics19 Phenomics17 http://biocomp.dfci.harvard.edu/tgi/omics_count.html

9. Moving Beyond Genome Transcriptome: All messenger RNA molecules (‘transcripts’) Proteome: All proteins in cell or organism Metabolome: all metabolites in a biological organism (end products of its gene expression). Systems Biology

10. Transcriptome mRNA: takes information from DNA during transcription to sites of protein synthesis. Undergoes translation to yield gene product. Can vary with external environmental conditions. Reflects the genes that are being actively expressed at any given time.

11. Example: Expression Microarrays Compare tumor vs normal mRNA expression levels. Tells the relative amounts of different mRNAs. But not directly proportional to the expression level of the proteins they code for.

12. Characterize proteins. Each protein has a particular shape and function that determine its role in the body. Compare variations in their expression levels under different conditions. Study their interactions. Identify their functional role. Proteomics

13. Proteome Complexity Recall that genome is relatively static. In contrast, many cellular proteins are continually moving and undergoing changes such as: 1.binding to a cell membrane, 2.partnering with another protein, 3.gaining or losing a chemical group such as a sugar, fat, or phosphate, or 4.breaking into two or more pieces.

14. Size of Proteome? > 1 Million Proteins >>> 21,000 genes in humans. Large number due to complexity (a given gene can make many different proteins) Features such as folds and motifs, allow them to be categorized into groups and families. This should help make it easier to undertake proteomic research.

15. How to Analyze Proteomes Broad range of technologies Central paradigm: –2-D gel electrophoresis (2D- GE), and mass spectrometry (MS). –2D-GE is used to separate the proteins by isoelectric point and then by size. –MS determines their identity and characteristics.

16. 2-D gel electrophoresis Large mixtures of proteins separated by electrical charge and size. The proteins first migrate through a gel- like substance until they are separated by their charge. They are then transferred to a second semi-solid gel and are separated by size.

17. http://www.lecb.ncifcrf.gov/phosphoDB/2d-description.gif

18. Mass spectrometry MS measures two properties: 1.the mass-to-charge ratio (m/z) of a mixture of ions (particles with an electric charge) in the gas phase under vacuum; and 2.the number of ions present at each m/z value. The end product is a mass spectra (chart) with a series of spiked peaks, each representing the ion or charged protein fragment present in a given sample.

19. Mass spectrometry The height of the peak is related to the abundance of the protein fragment. The size of the peaks and the distance between them are a fingerprint of the sample and provide a clue to its identity.

20. Metabolome All small molecule (<1500 Da) metabolites found in a cell, organ or organism. E.g., metabolic intermediates, hormones and other signalling molecules, and secondary metabolites.

21. Copyright restrictions may apply. Wishart, D. S. et al. Nucl. Acids Res. 2007 35:D521-D526; doi:10.1093/nar/gkl923 "> Human Metabolome Database http://www.hmdb.ca Brings together: chemical, physical, clinical and biological data Thousands of metabolites.

22. HMDB http://www.hmdb.ca Brings together: –chemical, –physical, –clinical and –biological data on thousands of endogenous human metabolites.

23. Lots of Data!

24. “The study of genetic and other biological information using computer and statistical techniques.” A Genome Glossary, Science, Feb 16, 2001

25. Bioinformatics in Genetic Epi Some key aspects: Data management Candidate regions / genes (selection and SNP mining) Genetic Analyses (e.g., genotyping) Statistical Analyses

26. Data Management 5/20 Demogr. Database Laboratory Database Clinical Database Health and Habits Database Nutritional Database Genomic Database CaP Genes Databases Hub

27. Bioinformatics in Proteomics Creation and maintenance of databases of protein info. Development of methods to predict the structure and/or function of newly discovered proteins and structural RNA sequences. Clustering protein sequences into families of related sequences and the development of protein models. Aligning similar proteins and generating phylogenetic trees to examine evolutionary relationships

28. Resources at UCSF Study Design & Biostatistics (Dept & Cancer Center) www.biostat.ucsf.edu/services.html Genomics Core Facility genomics.ucsf.edu/ Gladstone Genomics Core Laboratory www.gladstone.ucsf.edu/gladstone/site/genomicscore/ Genomics and Proteomics Core http://derisilab.ucsf.edu/core Mass Spectrometry http://www.ucsf.edu/brc

29. Genetic Testing: Sciona

31. Test for SNPs in 7 Genes GSTM1, CYP1A1, GSTT1 and GSTP1 –Phase I and II detoxification genes. MnSOD –Codes for enzyme that may defend against free radical damage. MTHFR –Encodes enzyme that helps the body to use folate so that cells can grow and repair, or maintain their DNA. ALDH2 –Codes for aldehyde dehydrogenase 2 enzyme, which converts acetaldehyde (metabolized from ETOH) into acetic acid and water.

32. “Preventive Health Profile” Antioxidants - Your Personal Advice –Diet questionnaire shows low consumption of antioxidants. –Gene test shows that you have a beneficial SNP that helps fight oxidative stress. –But you still need to increase your daily intake of antioxidants to support your body's antioxidant abilities. Antioxidants - Putting Advice Into Action –Increase your consumption of foods rich in the most important antioxidants: vitamins C, A and E, beta carotene and selenium. –Eat plenty of fruits and vegetables, major sources of antioxidants. Make sure to include at least one portion of citrus fruit. –Common foods particularly rich in various antioxidants are soy products, tea and garlic, as well as red wine.

33. Concerns with Testing ? 1.Misleading statements about value of results. 2.No genetic counseling. 3.Use of confidential genetic (and dietary) information

35. Final Project Based on the current state of the literature (from your reviews): –Describe a molecular / genetic project that you can justify undertaking. One page description, due March 4 th by email to Nerissa.