1. An analysis of “Bioinformatics analysis of SARS coronavirus genome polymorphism” by Pavlović-Lažetić, et. al Angela Brooks July 9, 2004 SoCalBSI Article Presentation

2. Outline  Background  Purpose  Experimental Methods  Results  Conclusions  Possible Future Studies  Importance of the work to society

3. Background  The authors analyzed the genomes of 38 isolates of the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) Isolates: virus “strains” that are apart/cut off from one another by location  Looking for: single nucleotide polymorphisms(SNPs) insertions and deletions sequence similarity between isolates to determine the phylogeny of the SARS-CoV isolates

4. SNPs – Single Nucleotide Polymorphisms  A single point mutation in the genome  Types of mutations caused by SNPs: Silent  no change Missense  AA change in protein product Nonsense  Change AA to “stop” Other  Change in other functional/regulatory region

5. Purpose of Paper  Establish the origin of the virus.  Find regions in genome with high levels of sequence polymorphisms  Discover the evolutionary path of the virus lead towards preventing or curing the disease that it causes

6. 2 Step Sequence Comparisons 1.Structurally Identical Parts Identify regions of insertions and deletions with a reference set 2.SNPs in Structurally Identical Parts From regions in Part 1, find SNPs in those regions

7. 2 Step Sequence Comparisons 1.Structurally Identical Parts Similar to sequence alignment 2.SNPs in Structurally Identical Parts Reference Set (database) Other isolate sequences (queries)

8. How were sequences obtained?  Our old friend NCBI: LabelIDAccession No.Length Revision dateCountry/Source 1.TWHAp006557.12972702-AUG-2003Taiwan: patient #01 TWC2Ay362698.113-AUG-2003Taiwan: Hoping Hospital 2.TWC3Ay362699.12972713-AUG-2003Taiwan: Hoping Hospital 3.TWKAp006559.12972702-AUG-2003Taiwan: patient #06 4.TWSAp006560.12972702-AUG-2003Taiwan: patient #04 5.TWYAp006561.12972702-AUG-2003Taiwan: patient #02 6.UrbaniAy278741.12972712-AUG-2003USA: Atlanta 7.TWJAp006558.12972502-AUG-2003Taiwan: patient #043 8.TWCAy321118.12972526-JUN-2003Taiwan, first fatal case

9. Finding structural similarity

10. SNPs identified

11. Density distribution of polymorphisms

12. Qualitative Analysis of Sequence Variation  Based on structural similarity and SNPs, a tree was constructed to show sequence divergence

13. ClustalW used as a control for tree  ClustalW with PhyloDraw was used to draw a tree for comparison with “homemade” tree ZMY1 and ZJ01 are distant from representative group.

14. Side by Side Comparison of Trees

15. New Problems to Address  Not much analysis was done on results from study i.e. Found SNPs and structurally similar regions but not significant without analysis  What could be analyzed further? Examine regions of conservation for functional importance Examine phenotypic affect of amino acid mutation For isolates in a similar group, compare phenotypic characteristics to genotypic similarites  Uncover phenotypic/genotypic relationships

16. Why is SARS-CoV research important?  Previous year’s “outbreak” uncovered in China Anxiety over viruses Possible bioterrorism Understanding SARS-CoV may help to understand similar virus