Global population structure and adaptive evolution of aflatoxin-producing fungi

Geromy G. Moore, Rodrigo A. Olarte, Bruce W. Horn, Jacalyn L. Elliott, Rakhi Singh, Carolyn J. O'Neal, Ignazio Carbone

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

Aflatoxins produced by several species in Aspergillus section Flavi are a significant problem in agriculture and a continuous threat to human health. To provide insights into the biology and global population structure of species in section Flavi, a total of 1,304 isolates were sampled across six species (A. flavus, A. parasiticus, A. nomius, A. caelatus, A. tamarii, and A. alliaceus) from single fields in major peanut-growing regions in Georgia (USA), Australia, Argentina, India, and Benin (Africa). We inferred maximum-likelihood phylogenies for six loci, both combined and separately, including two aflatoxin cluster regions (aflM/alfN and aflW/aflX) and four noncluster regions (amdS, trpC, mfs and MAT), to examine population structure and history. We also employed principal component and STRUCTURE analysis to identify genetic clusters and their associations with six different categories (geography, species, precipitation, temperature, aflatoxin chemotype profile, and mating type). Overall, seven distinct genetic clusters were inferred, some of which were more strongly structured by G chemotype diversity than geography. Populations of A. flavus S in Benin were genetically distinct from all other section Flavi species for the loci examined, which suggests genetic isolation. Evidence of trans-speciation within two noncluster regions, whereby A. flavus SBG strains from Australia share haplotypes with either A. flavus or A. parasiticus, was observed. Finally, while clay soil and precipitation may influence species richness in Aspergillus section Flavi, other region-specific environmental and genetic parameters must also be considered.

Original languageEnglish (US)
JournalEcology and Evolution
DOIs
StateAccepted/In press - 2017

Keywords

  • Aspergillus
  • Balancing selection
  • Maximum likelihood
  • Multilocus sequence typing
  • Principal component analysis

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