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Aquaculture 2013, Nashville TN

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  • 1. DNA methylation as a source ofepigenetic regulation in the Pacific oyster (Crassostrea gigas) Mackenzie Gavery & Steven Roberts University of Washington, School of Aquatic and Fishery Sciences
  • 2. Outline Background  Epigenetics  DNA methylation Results Characterization of DNA methylation in Pacific oysters Discussion & Future Directions
  • 3. Background color disease resistance growth TRAITS temperature pathogens nutritionGENES (DNA) ENVIRONMENT
  • 4. Background color disease resistance growth TRAITS temperature pathogens nutrition EPIGENOME (DNA methylation)GENES (DNA) ENVIRONMENT
  • 5. Background color disease resistance growth TRAITS temperature pathogens nutrition EPIGENOME (DNA methylation)GENES (DNA) ENVIRONMENT
  • 6. TF X CG Gene A G C Me
  • 7. DNA Methylation Invertebrates?
  • 8. DNA Methylation Invertebrates?  Model invertebrates lack DNA methylation  Distribution & function unclear
  • 9. DNA Methylation Invertebrates?  Model invertebrates lack DNA methylation  Distribution & function unclear Objectives:  Characterize DNA methylation in C. gigas  Gain an understanding of the functional role
  • 10. Part 1
  • 11. Part 1 Approach  In silico analysis  Experimental analysis: MBD-Seq
  • 12. Measured degree of DNA methylation (Roberts & Gavery, 2011) Enrichment level in MBD library Part 1: Results CpG O/E (Gavery & Roberts, 2010)Predicted degree of DNA methylation
  • 13. Measured degree of DNA methylation (Roberts & Gavery, 2011) Enrichment level in MBD library Part 1: Results CpG O/E (Gavery & Roberts, 2010)Predicted degree of DNA methylation
  • 14. Measured degree of DNA methylation (Roberts & Gavery, 2011) Enrichment level in MBD library Part 1: Results CpG O/E (Gavery & Roberts, 2010)Predicted degree of DNA methylation
  • 15. Measured degree of DNA methylation (Roberts & Gavery, 2011) Enrichment level in MBD library Part 1: Results CpG O/E (Gavery & Roberts, 2010)Predicted degree of DNA methylation
  • 16. Part 2
  • 17. Part 2 Approach  High-throughput bisulfite sequencing:  Gill tissue  Additional resources:  RNA-seq data: gill tissue (Zhang et al, 2012) genomic DNA
  • 18. Part 2 Approach  High-throughput bisulfite sequencing:  Gill tissue  Additional resources:  RNA-seq data: gill tissue (Zhang et al, 2012) genomic DNA
  • 19. Part 2: Results >250,000 CG dinucleotides
  • 20. Part 2: Results 0bp 200,000bp CG genes exons ex %methylation100%0% scaffold 86 (Galaxy Trackster)
  • 21. Part 2: Results 0bp 200,000bp CG genes exons ex %methylation100%0% scaffold 86 (Galaxy Trackster)
  • 22. Part 2: Results 0bp 200,000bp CG genes exons ex %methylation100%0% scaffold 86 (Galaxy Trackster)
  • 23. Part 2: Results 0bp 200,000bp CG genes exons ex %methylation100%0% scaffold 86 (Galaxy Trackster)
  • 24. Part 2: Results Distribution in genomic elements
  • 25. Part 2: Results Distribution in genomic elements exon 17% unannotated 48% intron 35%
  • 26. Part 2: Results Relationship with expression
  • 27. Part 2: Results Relationship with expression DNA methylation/gene Gene expression (Deciles) RNA-Seq data (Zhang et al., 2012)
  • 28. Part 3
  • 29. Part 3 Approach:  High-throughput bisulfite sequencing:  Gill tissue
  • 30. Part 3 Approach:  High-throughput bisulfite sequencing:  Gill tissue  Male gamete (sperm) tissue
  • 31. 0bp Part 3: Results 6,000bpCGgenes%methylation: gill%methylation: sperm
  • 32. 0bp Part 3: Results 6,000bpCGgenes%methylation: gill%methylation: sperm
  • 33. 0bp Part 3: Results 6,000bpCGgenes%methylation: gill%methylation: sperm
  • 34. Part 3: Results Identify differentially methylated regions (DMR)
  • 35. Part 3: Results Identify differentially methylated regions (DMR)  100bp windows  DMR >75% difference between tissues
  • 36. Part 3: Results >200,000 regions were evaluated
  • 37. Part 3: Results >200,000 regions were evaluated DMR 7% methylation same across tissues 93%
  • 38. Part 3: Results >200,000 regions were evaluated  half of DMR in gene DMR bodies 7%  genes with DMR had significantly less methylation methylation same across tissues 93%
  • 39. Summary
  • 40. Summary methylated unmethylated
  • 41. Summary methylated unmethylatedGene function:
  • 42. Summary methylated unmethylatedGene function: housekeeping inducible
  • 43. Summary methylated unmethylatedGene function: housekeeping inducible Expression:
  • 44. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high low
  • 45. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high lowTissue specific methylation:
  • 46. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high lowTissue specific conserved tissue specific methylation: across tissues
  • 47. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high lowTissue specific conserved tissue specific methylation: across tissues Role of methylation in introns:
  • 48. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high lowTissue specific conserved tissue specific methylation: across tissues Role of methylation unknown in introns:
  • 49. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high lowTissue specific conserved tissue specific methylation: across tissues Role of methylation unknown in introns:Role of methylation in inter-genic regions:
  • 50. Summary methylated unmethylatedGene function: housekeeping inducible Expression: high lowTissue specific conserved tissue specific methylation: across tissues Role of methylation unknown in introns:Role of methylation in unknown inter-genic regions:
  • 51. Next Steps
  • 52. Next Steps Explore relationships between DNA methylation and alternative splicing Annotate intergenic regions of the C. gigas genome EPIGENOME (DNA methylation) GENES (DNA)
  • 53. Conclusions EPIGENOME (DNA methylation) GENES (DNA)
  • 54. Conclusions color disease resistance growth TRAITS temperature pathogens nutrition EPIGENOME (DNA methylation) GENES (DNA) ENVIRONMENT
  • 55. Acknowledgements  Roberts Lab: Samuel White Caroline Storer Emma Timmins-Schiffman Claire Ellis Lisa Crosson  Taylor Shellfish: Jonathan Davis Molly Jackson email: mgavery@uw.edu website: students.washington.edu/mgavery