Application of Bioinformatics in Genetics Research

1. Instructors: Dr. Henry Baker Dr. Luciano Brocchieri Drs. Michele Tennant / & Rolando Milian Dr. Lei Zhou Application of Bioinformatics in Genetics Research Course web page: Sakai/UFL for lecture notes and homework & http://159.178.28.30/GMS6014/home.htm for classroom practice.

2. Application of Bioinformatics in Genetic Research Time and location: M. W. F. : 1:00-2:00 in CGRC-291. Except: 2/12, 14 & 2/19 in HSCL C2-3.

3. Evaluation • 50% classroom participation • 50% homework

4. History of bioinformatics – sequence analysis • Sequence comparison • Similarity search • Phylogenetic analysis • Structure predication • Gene prediction

5. Bioinformatics in the post genome era The opportunity provided by genome sequence and genomic / proteomic technology is matched by the challenge to bioinformatics / computational biology • Information Representation. - many new types of data, such asFunction, Location, Interaction, Regulatory pathway, Expression profile, etc. needs to be recorded • Data Management - Infrastructure for inputting, managing, access and retrieval of relevant information in a “sea of databases”. Cloud computing. • Systematics

6. Bioinformatics in the post genome era • Whole genome sequencing - SNP and whole genome wide association studies. • Genomic/proteomic expression profiling (RNA and protein levels). • Epigenomics, Comparative genomics, … • Regulatory pathway simulation – systems biology. $1,000 genome and … $500,000 analysis ?

7. Objectives of GMS6014 • Basic skills for retrieving and storing data, using web-based applications. • Ability to install and run standalone local applications. • Understanding the basis of bioinformatics applications using sequence similarity search as the example. • A brief survey of available bioinformatics tools for HTS analysis and introduction to functional genomics and systems biology.

8. Sequence Representation - nucleotide N G R C W T G Y C Y A G A C A T G C C C C G T T T G T For complete list, see table 2.1, Mount 2nd Ed Or http://www.ncbi.nlm.nih.gov/blast/fasta.shtml

9. Sequence Representation - amino acids Q: What’s the common property of these amino acids ? • D, E • I, L, V, M, F • A, S, P

10. W W D D L L L L A A Q Q I I L L C C Y Y A A L L R R I I Y Y W W R R F F L L A A T T V V V V L L E E T T L L R R Q Q Y Y W W K K F F L L A A I I T T M M C C K K V V L L K K Q Q F F R R C C L L L L C C N N K K L L Y Y Y Y L L L L R R K K V V L L N N R R L L L L A A E E L L Y Y E E V V L L C C H H I I L L R R L L L L Q Q Q Q Q Q Q Q M M V V L L Q Q R R Q Q Y Y Sequence Representation - amino acids Example: Coloring based on aa property.

11. Representation of sequence – sequence file format 1.) FASTA – simple and clean > gene_name, (other info) MASASASKJHKLJLKJLDSDFSF SSDSASFSFD… Practice / DIY: retrieve sequence in Fasta format and save the file in the local computer.

12. How to store sequence files • .txt format is clean and allows down stream sequence analysis • .doc or .rtf allows formatting during annotation – however, extra information are inserted thus NOT suitable for computational analysis.

13. Practice – file types • Using Windows Explorer (with your own computer) or IE with “C:\” in the address window. • Change the “ToolsFolder Options” so that the file extensions (.xxx) are revealed. • Edit the downloaded sequence file in MS Word, highlight a section of the sequence with Bold font or color and save as .doc • Open the .doc file in NotePad – observe the inserted characters.

14. Practice – file types (Cont.) • Load the “Mysequence.doc” file to Webcutter using “Choose file” and then “Upload sequence file”. -Notice that the “sequence” in the sequence box are nonsense characters. • Clear input; Browse and then load the .txt file. Run an analysis. Always keep you sequences in .txt file for downstream analysis.

15. Representation of sequence The need to include annotations and functional information with each sequence. • Structured data entry • GeneBank • EMBL / SwissProt Observe: The difference of data structure between SwissProt, NCBI protein, and NCBI Genes.

16. Representation of sequence The need to represent associated info with sequence • Structured data entry • Specialized databases • 3-d Structure • Mutation / Diseases • Protein family / Protein domain • Interaction • Pathway • ….

17. Representation of sequence The need to represent associated info with sequence • Structured data entry • Specialized databases • Complex / customized data structure - Object-oriented data representation (Mount, p44-45)

18. Public Resources for Bioinformatics Databases Analysis Tools Observe: List of databases and service at NCBI, EBI, KEGG, and Ensembl.

19. Pet Project: TNF, or your favorite gene What can we know about this gene? • Search for “curated” databases. • To prepare for future analysis, save annotated sequence files as genename.html (in a target folder). • For downstream sequence analysis, save pure sequence as FASTA format file.

20. Where and how much information are available for my gene? Observe: The information contents and presentation format for the same gene in SwissProt, NCBI protein, NCBI Genes, etc..

21. Public Resources (I) – Databases and data sources • Over 1,000 in the sea of databases. • Content-specific, such as DNA, Protein, Structure, etc. • Species-specific, such as flybase, wormbase, OMIM, etc. • System-specific, such as MetaCyc, AFCS, etc.

22. Database concept: Database - efficiently store, update, and retrieve information (data). Types of Databases – Relational DB, Object DB, native XML DB. Database management systems – Access, Sybase MySQL, Oracle, etc.

23. Database concept – tables in relational databases “TNF”=TNF[All Fields] TNF[Name] Protein table

24. Database concept – relationship between tables Protein table Reference table

25. Representation of sequence The need to represent associated info with sequence • Structured data entry • Specialized databases • Complex / customized data structure - Object-oriented data representation (Mount, p44-45)

26. Observe/Practice • Search for TNF in the Gene database and the Nucleotide and Proteins databases. • Search for TNF in “All Text” v.s “gene name” the in the Gene database. • Compare results. • Download the human TNF nucleotide sequence. • Download three protein sequences in FASTA format from the RefSeq search result save as 3TNF.txt.

27. Practice: navigating the related resources through links • Using the “PubMed” link, search annotated references on TNF. • Using the “GEO Profiles” link, search gene expression information on TNF. • Using the “Map Viewer” link to observe the chromosome location and gene structure of the TNF locus – change the option of “Map Viewer” to include prediction of CpG island.

28. Public Resources (II) – Analysis tools • Web-based analysis tools – easy to use, but often with less customization options. • Stand-alone analysis tools – requires installation and configuration, but provides more customizatio0n options. • Commercial analysis tools • Scripting for bioinformatics projects

30. Bioinformatics / Computational biology • Bioinformatics - Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. • Computational Biology - The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. (Working Definition of Bioinformatics and Computational Biology - July 17, 2000). NIH / BISTI