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Objective
• Withering syndrome is a fatal disease of abalone
  caused by a rickettsial bacterium (WS-RLO)

• WS-RLO transmission experiments demonstrate
  progeny from disease selected populations are more
  resistant to WS-RLO than naïve populations

• GOAL: Characterize and compare the transcriptomes
  of WS-resistant and naïve abalone to elucidate
  mechanisms associated with increased disease
  tolerance
Approach

1. WS-Resistant   2. WS-Resistant         3. Naïve   4. Naïve
    Exposed           Control             Exposed    Control


                        De novo assemble &
                             annotate



                          RNA-Seq & DESeq


                    Galaxy – join annotation & GO


                    Enrichment Analysis - DAVID


                        Visualize data - REVIGO
Discovery: QC
            Losing large # of reads after
            trimming – trim on length only

            Working – RNA-Seq using
            trimmed and untrimmed files

            Assessing different RNA-Seq
            software – CLC vs Tophat


            Working – Annotating 3
            assemblies (blastx)
Discovery
(enrichment only on 2
naïve libraries)




                           EXPOSED
Less DEG in naïve WS-
RLO exposed animals

Shift from homeostatic
processes to catabolic
processes
(autophagy, cytolysis, a
ntioxidants)

Consistent with
characteristics of
withering syndrome so
                           CONTROL




pretty cool 


Next Step
Pick “best” assembly &
RNA-Seq for DESeq and
enrichment analysis on
all 4 libraries

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546project

  • 1. Objective • Withering syndrome is a fatal disease of abalone caused by a rickettsial bacterium (WS-RLO) • WS-RLO transmission experiments demonstrate progeny from disease selected populations are more resistant to WS-RLO than naïve populations • GOAL: Characterize and compare the transcriptomes of WS-resistant and naïve abalone to elucidate mechanisms associated with increased disease tolerance
  • 2. Approach 1. WS-Resistant 2. WS-Resistant 3. Naïve 4. Naïve Exposed Control Exposed Control De novo assemble & annotate RNA-Seq & DESeq Galaxy – join annotation & GO Enrichment Analysis - DAVID Visualize data - REVIGO
  • 3. Discovery: QC Losing large # of reads after trimming – trim on length only Working – RNA-Seq using trimmed and untrimmed files Assessing different RNA-Seq software – CLC vs Tophat Working – Annotating 3 assemblies (blastx)
  • 4. Discovery (enrichment only on 2 naïve libraries) EXPOSED Less DEG in naïve WS- RLO exposed animals Shift from homeostatic processes to catabolic processes (autophagy, cytolysis, a ntioxidants) Consistent with characteristics of withering syndrome so CONTROL pretty cool  Next Step Pick “best” assembly & RNA-Seq for DESeq and enrichment analysis on all 4 libraries