Multi-scale and multi-site resampling of study area in spatial genetics: implications for flying insect species

UR633 Zoologie Forestière, INRA, Orléans, France
UMR CBGP (INRA/IRD/Cirad/Montpellier SupAgro), Cirad, Montpellier, France
UMR CBGP (INRA/IRD/Cirad/Montpellier SupAgro), INRA, Montpellier, France
Sustainable Forest Management Res Inst, Universidad de Valladolid, Palencia, Spain
Instituto Nacional de Investigacao Agraria e Veterinaria, INIAV, Oeiras, Portugal
DOI
10.7287/peerj.preprints.2968v1
Subject Areas
Entomology, Environmental Sciences, Molecular Biology
Keywords
insect dispersal, gene flow, landscape genetics, Monochamus galloprovincialis, Iberian Peninsula
Copyright
© 2017 Haran et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Haran JM, Rossi J, Pajares J, Bonifacio L, Naves P, Roques A, Roux G. 2017. Multi-scale and multi-site resampling of study area in spatial genetics: implications for flying insect species. PeerJ Preprints 5:e2968v1

Abstract

The use of multiple sampling areas in landscape genetic analysis has been recognized as a useful way to generalize the patterns of environmental effects on gene flow. It allows reducing the variability of inference, accounting for multiple scales and locations of study areas. Although several reviews have stressed the importance of this point, few studies have considered multiple sampling areas in analysis and formally tested their effects on inference. In this study, we present a method for resampling of study areas at multiple scales and multiple locations (sliding windows) to track the variation of inference in spatial genetics. We explored the effects of environmental features on gene flow of a flying long-horned beetle (Monochamus galloprovincialis) in 3*104 study areas ranging in scale from 220 to 1000 km and spread over 132 locations among the Iberian Peninsula. We show that there were no general or recurrent effects of environmental features detected among scales and locations, independent of variation in environmental features. Detection of environmental features on gene flow generally increased with an increasing scale of study, and was variable between locations. The resampling method presented here provides the opportunity to explore the effects of environmental features on gene flow of organisms in their whole extent and to conclude about general landscape effects on the dispersal of organisms, while keeping sampling effort to a reasonable level.

Author Comment

This is a submission to PeerJ for review.

Supplemental Information

Distribution of sampling sites in the Iberian Peninsula

Black dots refer to populations of size > 19 individuals. Green background refers to elevation (from pale to dark green: low to high elevation).

DOI: 10.7287/peerj.preprints.2968v1/supp-1

Number of individuals in sampling areas across spatial scal

Mean: black; +/- SD: grey

DOI: 10.7287/peerj.preprints.2968v1/supp-2

Evolution of DeltaK among an increasing number of K (2 -20)

DOI: 10.7287/peerj.preprints.2968v1/supp-3

Sampling details of the 132 demes

(Long. and Lat. refer to geographic coordinates of sampling sites; N. is the number of individuals of demes; A. mean allelic richness; AR. corrected allelic richness, accounting to variation in deme size; Fis. Fis estimate of deme, computed without Mon01 and Mon 27).

DOI: 10.7287/peerj.preprints.2968v1/supp-4

Details of primer sequence and genotyping

Multiplexed PCR were performed in a 10 µL reaction volume using 25 ng of genomic DNA, 0.4 U of DreamTaq DNA Polymerase (Thermo Scientific®), 0.75 µL Dream Taq Green Buffer (including 20 mM MgCl2, Thermo Scientific®), 1 µM Betaine, 0.24 µL dNTP (10 µM) and deionized H2O. PCR amplifications were run on a Veriti® 96 well fast Thermal cycler (Applied Biosystems®) using the following settings: a first denaturation step at 95 °C during 10 min; 40 cycles of denaturation (30 s at 95 °C), hybridization (30 s at 55 °C) and elongation (1 min at 72 °C), and a final elongation step at 72 °C during 10 min. One µL of PCR products were denatured within a mix of 10 µL of formamide and 0.3 µL of 600 Liz marker before being run on an ABI PRISM 3500 sequencer (Life Technologies®). Genotypes were read using the software GENEMAPPER V 4.1 (Applied Biosystems®).

DOI: 10.7287/peerj.preprints.2968v1/supp-5

Sampling locations and microsatellite genotypes

DOI: 10.7287/peerj.preprints.2968v1/supp-6