Abstract

High-throughput DNA sequencing allows efficient discovery of thousands of single nucleotide polymorphisms (SNPs) in non-model species. Population genetic theory predicts that this large number of independent markers should provide detailed insights into the population structure, even when only a few individuals are sampled. Still, sampling design can have a strong impact on such inferences. Here, we use simulations and empirical SNP data to investigate the impacts of sampling design on estimating genetic differentiation among populations that represent three species of Galapagos giant tortoises (Chelonoidis spp.). Though microsatellite and mitochondrial DNA analyses have supported the distinctiveness of these species, a recent study called into question how well these markers matched with data from genomic SNPs, thereby questioning decades of studies in non-model organisms. Using >20,000 genome-wide SNPs from 30 individuals from three Galapagos giant tortoise species, we find distinct structure that matches the relationships described by the traditional genetic markers. Furthermore, we confirm that accurate estimates of genetic differentiation in highly structured natural populations can be obtained using thousands of SNPs and 2-5 individuals, or hundreds of SNPs and 10 individuals, but only if the units of analysis are delineated in a way that is consistent with evolutionary history. We show that the lack of structure in the recent SNP-based study was likely due to unnatural grouping of individuals and erroneous genotype filtering. Our study demonstrates that genomic data enable patterns of differentiation among populations to be elucidated even with few samples per population, and underscores the importance of sampling design. These results have specific implications for studies of population structure in endangered species and subsequent management decisions.

Details

Title
Theory, practice, and conservation in the age of genomics: the Gal��pagos giant tortoise as a case study
Author
Gaughran, Stephen J; Quinzin, Maud C; Miller, Joshua M; Garrick, Ryan C; Edwards, Danielle L; Russello, Michael A; Poulakakis, Nikos; Ciofi, Claudio; Beheregaray, Luciano B; Caccone, Adalgisa
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2017
Publication date
Sep 12, 2017
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
2069685581
Copyright
�� 2017. This article is published under http://creativecommons.org/licenses/by-nd/4.0/ (���the License���). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.