Genome-wide developed microsatellites reveal a weak population differentiation in the hoverfly Eupeodes corollae (Diptera: Syrphidae) across China


Autoři: Mengjia Liu aff001;  Xiaoqiang Wang aff001;  Ling Ma aff002;  Lijun Cao aff002;  Hongling Liu aff003;  Deqiang Pu aff001;  Shujun Wei aff002
Působiště autorů: Industrial Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, China aff001;  Institute of Plant and Environmental Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China aff002;  Institute of Plant Protection, Sichuan Academy of Agricultural Sciences, Chengdu, China aff003
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0215888

Souhrn

The hoverfly, Eupeodes corollae, is a worldwide natural enemy of aphids and a plant pollinator. To provide insights into the biology of this species, we examined its population genetic structure by obtaining 1.15-GB random genomic sequences using next-generation sequencing and developing genome-wide microsatellite markers. A total of 79,138 microsatellite loci were initially isolated from the genomic sequences; after strict selection and further testing of 40 primer pairs in eight individuals, 24 polymorphic microsatellites with high amplification rates were developed. These microsatellites were used to examine the population genetic structure of 96 individuals from four field populations collected across southern to northern China. The number of alleles per locus ranged from 5 to 13 with an average of 8.75; the observed and expected heterozygosity varied from 0.235 to 0.768 and from 0.333 to 0.785, respectively. Population genetic structure analysis showed weak genetic differentiation among the four geographical populations of E. corollae, suggesting a high rate of gene flow reflecting likely widespread migration of E. corollae in China.

Klíčová slova:

Genetic loci – Genomic library construction – Genomics – China – Invertebrate genomics – Population genetics – Microsatellite loci – Structural genomics


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