Data from: Effective population sizes of a major vector of human diseases, Aedes aegypti

The effective population size (Ne) is a fundamental parameter in population genetics that determines the relative strength of selection and random genetic drift, the effect of migration, levels of inbreeding, and linkage disequilibrium. In many cases where it has been estimated in animals, Ne is on the order of 10-20% of the census size. In this study, we use 12 microsatellite markers and 14,888 single nucleotide polymorphisms (SNPs) to empirically estimate Ne in Aedes aegypti, the major vector of yellow fever, dengue, chikungunya, and Zika viruses. We used the method of temporal sampling to estimate Ne on a global dataset made up of 46 samples of Ae. aegypti that included multiple time points from 17 widely distributed geographic localities. Our Ne estimates for Ae. aegypti fell within a broad range (~25-3,000), and averaged between 400 and 600 across all localities and time points sampled. Adult census size (Nc) estimates for this species range between one and five thousand, so the Ne/Nc ratio is about the same as for most animals. These Ne values are lower than estimates available for other insects and have important implications for the design of genetic control strategies to reduce the impact of this species of mosquito on human health.Ae.aegypti_Ne_genepop_filesAedes aegypti microsatellite alleles and SNP-chip genotypes from a worldwide sample of populations in "genepop" format, used in estimates of Ne for this paper. Details of the "genepop" format can be found at http://genepop.curtin.edu.au. For the microsatellite genotyping, we used the protocol described in (Brown et al, 2011) for 12 loci; A1, B2, B3, A9, AC2, CT2, AG2, AC4, AC1, AC5, AG1, and AG4. Briefly, amplifications were performed using standard PCR protocol (35 cycles at 54˚C) with fluorescently labeled M13 primers (6-FAM and HEX) in 10.0 μl reaction volumes using the Type-it Microsatellite PCR Master Mix (Qiagen), then diluted, multiplexed, and submitted for fragment analysis with GS 500 ROX internal size standard (Applied Biosystems, Foster City, CA, USA) on an Applied Biosystems 3730xl DNA Genetic Analyzer at the DNA Analysis Facility on Science Hill at Yale. Alleles were scored using GeneMapper v4.0 (Applied Biosystems). For the SNP-chip genotyping, 167 samples were analyzed on the Axiom_aegypti1 SNP-chip (Evans et al, 2015) at the Functional Genomics Core at University of North Carolina, Chapel Hill, using manufacturer protocols. Raw data were processed and converted into genotype calls following Evans et al. (2015) using Genotyping Console v4.2 (Affymetrix, Santa Clara, CA, USA) and SNPolisher v1.4 (Affymetrix) in the R environment with the call threshold set to 95%. SNPs were pruned to remove any linked SNPs in PLINK v1.7 (Purcell et al, 2007) with the command "--indep 100 10 2", which recursively removed SNPs within a sliding window of 100 SNPs wide, shifting 10 SNPs per step, with a variance inflation factor (i.e. VIF) threshold of 2