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Improving our understanding of Aspergillus fumigatus. Project Overview. Aspergillus fumigatus. RNA- Seq. WGS. SNP calling. Statistical analysis. Network analysis. Why sequence Aspergillus fumigatus ? . Allergic aspergillosis – associated with asthma Invasive aspergillosis

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project overview
Project Overview

Aspergillusfumigatus

  • RNA-Seq
  • WGS
  • SNP calling
  • Statistical analysis
  • Network analysis
why sequence aspergillus fumigatus
Why sequence Aspergillus fumigatus?
  • Allergic aspergillosis – associated with asthma
  • Invasive aspergillosis
    • > 40% hospital acquired ?
    • Very high mortality rate (50–90%) in treated patients
    • No effective drugs, vaccines or diagnostics
    • Emerging drug resistance: 10%-50%

Bueid et al., 2010

Invasive aspergillosis

two additional reference genomes
Two additional reference genomes

Mitochodrial genetic diversity

  • AF10 and AF210 – chosen because they are different from Af293 and Af1163
  • Unique MLST types
    • Af10: Clinical isolate from immunosuppressed patient in LA; fully susceptible to azoles and amphothericin B
    • Af210: Nosocomial infection in Manchester; MLST identical to ICU environmental strain and 5 other clinical samples
  • Sequencing completed; annotation pending
  • Mitochondria compared for 11 Aspergillusand Penicilliumgenomes

Joardar, submitted

novel drug resistance mechanisms snp calling clustering and association
Novel drug resistance mechanisms:SNP calling, clustering, and association

*sequential resistant isolates TBS

SNP density along the 8 Afu293 chromosomes show a subtelomere bias

SNP/10Kb

50 loci show extreme allelic variability between strains
>50 loci show extreme allelic variability between strains
  • Greater than 15 SNPs/Kb
  • Several involved in vegetative incompatibility

HET locus AFUB_017990

GBrowse2

significant variability is also present in drug resistance genes
Significant variability is also present in drug resistance genes
  • Cyp51A: 10-12 SNPs
  • Mdr1/AtrD ABC transporter: 2-8 SNPs

cyp51A asn2

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annotation improvement with rnaseq
Annotation improvement with RNAseq

630 updates so far

  • Use sequence reads to validate and/or modify existing gene models
  • Update categories
    • Gene extension
    • Gene mergers
    • UTRs
    • Alternative Isoforms
    • Novel genes
    • Exon boundary adjustments
    • Validation of hypotheticals
rna seq reveals alternative isoforms in a transcription factor linked to hypoxia
RNA-Seq reveals alternative isoforms in a transcription factor linked to hypoxia

AFUB_018340

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rna seq expression profiling of host pathogen interactions
RNA-Seqexpression profiling of host-pathogen interactions
  • Fungusexposed vs. non-exposed to NK cells
    • 171 genes
    • 63 genes
  • Human NK cells exposed to fungus
    • 503 genes
    • 518 genes
  • => Pathway enrichment and network analysis
    • Key drivers of the transcriptional changes
    • Targets for immuno-modulation therapy
outbreak investigation
Outbreak Investigation
  • Current methodology depends on analysis of short tandem repeats at 6 loci in the genome
  • However, there are no high-confidence global SNP markers for outbreak investigation
  • Sequenced “clonal” strains from two different outbreaks to understand variability
    • Identify novel SNPs to be used as markers
    • Technology is complementary to currently used typing schemes
future directions
Future directions
  • Integration of omics data for drug resistant isolates
    • => Drug resistance and diagnostic arrays
  • Additional genotyping markers
    • Ribosomal monomers
    • Mitochondrial genomes
    • HET genes
    • => Geographic variation and disease phenotypes
  • RNA-Seqsoftware evaluation tool
  • Sequencing of a highly virulent species A. tanneri
  • Development of a system for genetic analysis of A. fumigatus
    • Sequencing of “supermaters”
    • Testing drug resistance SNPs
acknowledgements
Acknowledgements
  • J. Craig Venter Institute
    • Informatics
      • Natalie FedorovaAbrams
      • Suman Pakala
      • Vinita Joardar
      • NikhatZafar
      • Suchitra Pakala
      • PratapVenepally
      • VenkiMoktali
      • Culture & sample prep
      • Stephanie Maunoud
      • Yan Yu
      • Tatiana Slepushkina
      • Ashlee Dravis
    • IFX, IT, Sequencing Core
  • GSCID directors at JCVI
    • Bill Nierman
    • Karen Nelson
  • Funding: NIAID/NIH
  • Outside collaborators
  • U. of Manchester: David Denning
  • NIAID/NIH: June Kwon-Chung
  • CDC: Arun Balajee
  • U. of Montana: Robb Cramer
  • U. of Georgia: Michelle Momany
  • U. of Tuebingen: JuergenLoeffler
  • U. of Wisconsin: Nancy Keller
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