Population genomics and comparisons of selective signatures in two invasions of melon fly, Bactrocera cucurbitae (Diptera: Tephritidae)

Julian R. Dupuis, Sheina B. Sim, Michael San Jose, Luc Leblanc, M. Aftab Hoassain, Daniel Rubinoff, Scott M. Geib

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Population genetics is a powerful tool for invasion biology and pest management, and useful for a range of questions from tracing invasion pathways to informing management decisions with inference of population demographics. Genomics greatly increases the resolution of population-scale analyses, yet outside of model species with extensive genomic resources, few studies have used population genomics in invasion biology. We use genome-wide single nucleotide polymorphisms (SNPs) to investigate population genomic structure with samples from across the range of melon fly, Bactrocera cucurbitae (Coquillett, 1849), a highly polyphagous pest of commercial produce. We then make use of a chromosome-scale genome assembly and gene set to compare signatures of selection across the melon fly’s genome, both across our sampling as a whole and in the context of two independent, established introductions. Using multiple approaches, we find support for six genetic clusters across melon fly’s distribution. Some of these agree with previously identified genetic clusters using microsatellites, but consensus of clusters in mainland and oceanic southeast Asia is confounded by variable sampling between studies. We find few adaptive signatures across the genome, and virtually no unique signatures when comparing the two independent introductions, which suggests that similar management strategies are appropriate across melon fly’s range. This is the first use of genome-wide data to characterize population structure in tephritid fruit fly pests, and our SNP dataset provides a foundation for objective and cost-effective genotyping of previously collected melon fly specimens. Future research needs to focus on truly comprehensive sampling across melon fly’s range to overcome the historic variability of range-wide estimates of population structure for this pest.

Original languageEnglish
Pages (from-to)1211-1228
Number of pages18
JournalBiological Invasions
Issue number5
StatePublished - May 1 2018

Bibliographical note

Funding Information:
Acknowledgements ddRAD library preparation was performed at the USDA-ARS Daniel K. Inouye US PBARC Genomics facility by Nicole Yoneishi and sequencing was conducted at the Vincent J. Coates Genomics Sequencing Laboratory at University of California at Berkeley, supported by National Institutes of Health S10 Instrumentation Grants S10RR029668 and S10RR027303. Funding for this project was provided by United States Department of Ariculture (USDA) Animal and Plant Health Inspection Service (APHIS) Farm Bill Section 10007 Projects ‘‘Diagnostic Resources to Support Fruit Fly Exclusion and Eradication, 2012–2014’’ and ‘‘Genomic approaches to fruit fly exclusion and pathway analysis, 2015–2016’’ to USDA-APHIS, USDA-ARS and UH Manoa (Projects 3.0251.02 and 3.01251.03 (FY 2014), 3.0256.01 and 3.0256.02 (FY 2015), and 3.0392.02 and 3.0392.03 (FY 2016)). We thank Boyd Mori and Forest Bremer for technical assistance. For help with facilitating permits and field collections, we thank Po-Yung Lai (UH-CTAHR), Yuchi Lin (National Normal University, Taiwan China), Johannes Ketellar (Chief Technical Advisor, FAO Inter-Country Programme for IPM), Prabhat Kumar (Asian Institute of Technology, Thailand), Chi-Yeh Chien (Thai Royal Project Foundation), Lira Chea (FAO-IPM Cambodia), Ajay Markanday (FAO-IPM Cambodia) Thongsavanh Taipangnavong (FAO-IPM, Laos) and Vornthalom Chanthavong (FAO-IPM, Laos) Yu-Feng Hsu (National Normal University, Taiwan China). We also thank Kemo Badji, Bishnu Bhandari, Elaida Fiegalan, Uyen Freitas, Will Haines, David Haymer, Chia-Lung Huang, Shakil Ahmed Khan, Ron Mau, Thai Hong Pham, N. Pierce, Steve Souder, Tiara Stark, and Steve Tam for assistance in collecting specimens. Artwork was created using R (R Core Team 2016) and Inkscape v0.91 (The Inkscape Team 2017). USDA is an equal opportunity employer.

Publisher Copyright:
© 2017, Springer International Publishing AG, part of Springer Nature (outside the USA).


  • Adaptive signatures
  • Invasive pest
  • Outlier loci
  • Population genetics
  • ddRAD

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology


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