Nuclear orthologs derived from whole genome sequencing indicate cryptic diversity in the Bemisia tabaci (Insecta: Aleyrodidae) complex of whiteflies

Robert S. de Moya, Judith K. Brown, Andrew D. Sweet, Kimberly K. Kimberly, Jorge R. Paredes-Montero, Robert M. Waterhouse, Kevin P. Johnson

Research output: Contribution to journalArticlepeer-review

Abstract

The Bemisia tabaci complex of whiteflies contains globally important pests thought to contain cryptic species corresponding to geographically structured phylogenetic clades. Although mostly morphologically indistinguishable, differences have been shown to exist among populations in behavior, plant virus vector capacity, ability to hybridize, and DNA sequence divergence. These differences allow for certain populations to become invasive and cause great economic damage in a monoculture setting. Although high mitochondrial DNA divergences have been reported between putative conspecifics of the B. tabaci species complex, there is limited data that exists across the whole genome for this group. Using data from 2184 orthologs obtained from whole genome sequencing (Illumina), a phylogenetic analysis using maximum likelihood and coalescent methodologies was completed on ten individuals of the B. tabaci complex. In addition, automatic barcode gap discovery methods were employed, and results suggest the existence of five species. Although the divergences of the mitochondrial cytochrome oxidase I gene are high among members of this complex, nuclear divergences are much lower in comparison. Single-copy orthologs from whole genome sequencing demonstrate divergent population structures among members of the B. tabaci complex and the sequences provide an important resource to aid in future genomic studies of the group.

Original languageEnglish (US)
Article number151
JournalDiversity
Volume11
Issue number9
DOIs
StatePublished - Sep 1 2019

Keywords

  • Cryptic species
  • Hemiptera
  • Pests
  • Phylogenomics
  • Read-mapping

ASJC Scopus subject areas

  • Ecology
  • Ecological Modeling
  • Agricultural and Biological Sciences (miscellaneous)
  • Nature and Landscape Conservation

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