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Facilitating analysis of genomic variation in Olympia oysters

Facilitating analysis of genomic variation in Olympia oysters. Bioinformatics, FISH546 Mackenzie Gavery 3/14/13. GOALS. U tilize existing genomic resources (transcriptome) for RAD- Seq design Generate useful generic feature files ( gff ) to facilitate functional annotation of SNPs

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Facilitating analysis of genomic variation in Olympia oysters

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  1. Facilitating analysis of genomic variation in Olympia oysters Bioinformatics, FISH546 Mackenzie Gavery 3/14/13

  2. GOALS • Utilize existing genomic resources (transcriptome) for RAD-Seq design • Generate useful generic feature files (gff) to facilitate functional annotation of SNPs • Generate a workflow for annotating synonymous and non-synonymous SNPs in a non-model species*

  3. Methods • Starting material: • Transcriptome: 41,000 contigs • SNP Table (CLCBio) ~52,000 • Annotations: blastx, GO • Tools: • Galaxy • Excel • Blastx

  4. Results

  5. Results • New data tracks: • Gene ID • GO annotation sub-groups • SNPs • Blastxregions (with frame)

  6. Applications • Assist with RAD-Seq experimental design • Ask interesting biological questions – are there differences in the number of SNPs in housekeeping v. inducible genes?

  7. Next steps • Do these SNPs result in functional changes (i.e. do they change the protein)? • Blastxcustom output -outfmt “6 sseqid, qseqid, frames…” • aachanges (Galaxy)

  8. Next steps • Do these SNPs result in functional changes (i.e. do they change the protein)? • Blastxcustom output -outfmt “6 sseqid, qseqid, frames…” • aachanges (Galaxy) SNP bed gene bed

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