1. Information System for Comparative Analysis of Legume Genomes Anita Dalwani Advisors: Dr. Roger Innes, Dr. Haixu Tang

2. LAYOUT Motivation Participants Background Design Results/Demo Future Work

3. Motivation?

4. Motivation Goal of legume genome project -Investigate the process of genome restructuring following polyploidization in plants (soybean and its relatives in the Glycine genus) -Try answering questions like : - Genome evolution on both short( 50 million yrs) time scale - Evolution of disease resistance (R) genes.

5. Motivation To answer these questions: -1 Mbp syntenic genomic regions from six taxa as well as their duplicated regions in the polyploidy members (12 such regions in total) will be sequenced and analyzed. -These regions contain several important disease resistance (R) genes.

6. Motivation Plant species and accessionNo. of regions to be analysed Whole Genome size (megabases) G. max cultivar Williams 8221103 G. max PI 9698321103 G. tomentella G1188 (2n=80)42083 G. tomentella race D3 (2n-40)21103 Teramnus labialus1< 700 Medicago truncatula1466

7. Motivation Information System -central repository for the data -stores and retrieves updated information -bioinformatics and visualization tools

8. Participants ParticipantsUniversity Roles Roger Innes Tom Ashfield Anita Dalwani Murali Mohan Innes Lab Indiana University, Bloomington. Principal Investigator R gene evolution Database development, Web application. Database development. Nevin Young Steve Cannon Roxanne Denny Young Lab, University of Minnesota Co-PI phylogenetic; R genes; comparative genomics. Lab Manager Jeff Doyle Bernard Pfeil Doyle Lab Cornell University Co-PI phylogenetic and polyploidy Bruce Roe Majesta Siegfried Roe Lab, Oklahoma University Co-PI Bac sequencing Saghai Maroof Milind Ratnaparkhe Jafar Mammado Maroof Lab, Virginia Tech Co-PI R genes; comparative genomics

9. Background Procedure 1.Create and make available Bacterial Artificial Chromosome (BAC) libraries of each species. Indexing available BAC, BAC end sequences, library, probes, vector, gel images

10. Background 2. Assemble syntenic BAC contigs from each library i. Strategically chosen soybean clones are used as probes

11. Probe 53 - ACCCGT Probe 21 - AATTC Probe 9 - GTACTT Probe 26 - AAACT Probe 1 - CCCC Probe 3 - AATC ACCCGT AATTC GTACTT AAACT CCCC AATC

12. ii. Individual probes are hybridized to high-density BAC filters representing all the target genomes

13. Background

14. Background iii. Integrity of contigs is confirmed by fingerprinting iv. Set of clones that hybridize to two or more probes are selected v. BACs representing the tentative minimum tiling path will be end sequenced

15. Probe53Probe21Probe9Probe26Probe1Probe3 Bac1 Bac2 Bac3 Bac4 Bac5 Bac6 Bac7 Bac8

16. Probe53Probe21Probe9Probe26Probe1Probe3 Bac2 Bac3 Bac4 Bac8

17. ACCCGTAATTCGTACTTAAACTCCCCAATC ACCCGTAAATC CTTCTT CCGCAATCT AATCCCCC

18. Background 3. DNA sequencing, Assembly, Annotation 4. Compare the content, order and sequence of gene 5. Results available for public

19. Importance Information System -Centrally available data -User-friendly interface for retrieving the information -Updated progress information -Tools for interpreting the results. Works as an Laboratory Management Information System

20. Design Steps for designing the Information System. 1.Design the Database - Data: BAC, BES, Probes, Libraries, vector, library screen hits etc.

21. Design - Visualize the relationship between these large amount of data. For example, Library table stores detailed information about each library used rather than having each BAC storing the library information

22. Design -Created tables based on these relationship Main tables used in the database are: BAC BES GEL IMAGES GENOMIC SOUTHERNS GENOTYPE LIBRARY LIBRARY SCREENS LIBRARY SCREEN HITS PRIMER PROBE PROBE WITHIN BACS VECTOR

23. Design

24. Design

25. Design 2. Populate the database with initial set of data -Initial set of data was stored in form of MS- Excel. -Perl script for parsing information.

26. Design Web Database Application -understanding the needs for the project -Web database interface - displays information about the project - add and update interface - tools for analyses

27. Design For determining the tiling path - Designing a Visualization tool - displays the locations of the clones with respect to probes - Probes are strategically chosen from soybean genomes

28. Design - Input : library name - subset of probes with at least one hit with the library are selected -BAC clones for the library are generated which have hits with probes -Probes are arranged in order of their position -BACs are mapped to these probes.

29. Design System Specifications -Database: Oracle 9i -Languages: PHP, Perl, HTML, JavaScript -Web Server: Apache 1.3.29 -Platform: Unix (SunOS 5.9)

30. Results

31. Future Work Comparative physical Mapping Bioinformatics tools Public interface

32. Acknowledgements Dr. Roger Innes Dr. Haixu Tang Dr. Sun Kim Legume genome project team

33. References Innes, Roger W. Comparative Analysis of Legume Genome Evolution, Proposal submitted to National Science Foundation. Tang, Haixu. Comparative physical mapping: ordering clones by cross species hybridization Dec 2004. www.bio.indiana.edu/~nsflegume