Title
SNPs selected by information content outperform randomly selected microsatellite loci for delineating genetic identification and introgression in the endangered dark European honeybee (Apis mellifera mellifera)
Date Issued
01 July 2017
Access level
metadata only access
Resource Type
journal article
Author(s)
Muñoz I.
Henriques D.
Jara L.
Johnston J.S.
De La Rúa P.
Pinto M.A.
Instituto Politécnico de Bragança
Publisher(s)
Blackwell Publishing Ltd
Abstract
The honeybee (Apis mellifera) has been threatened by multiple factors including pests and pathogens, pesticides and loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the genetic integrity of the native A. m. mellifera (M-lineage) is endangered due to trading and intensive queen breeding with commercial subspecies of eastern European ancestry (C-lineage). Effective conservation actions require reliable molecular tools to identify pure-bred A. m. mellifera colonies. Microsatellites have been preferred for identification of A. m. mellifera stocks across conservation centres. However, owing to high throughput, easy transferability between laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolving power of a widely utilized microsatellite set to detect structure and introgression with that of different sets that combine a variable number of SNPs selected for their information content and genomic proximity to the microsatellite loci. Contrary to every SNP data set, microsatellites did not discriminate between the two lineages in the PCA space. Mean introgression proportions were identical across the two marker types, although at the individual level, microsatellites' performance was relatively poor at the upper range of Q-values, a result reflected by their lower precision. Our results suggest that SNPs are more accurate and powerful than microsatellites for identification of A. m. mellifera colonies, especially when they are selected by information content.
Start page
783
End page
795
Volume
17
Issue
4
Language
English
OCDE Knowledge area
Ecología Genética, Herencia Bioquímica, Biología molecular
Scopus EID
2-s2.0-85007232634
PubMed ID
Source
Molecular Ecology Resources
ISSN of the container
1755098X
Sponsor(s)
We are deeply grateful to Andrew Abrahams, Bjørn Dahle, Gabriele Soland, Gilles Fert, Lionel Garnery, Norman Carreck, Per Kryger, Raffaele Dall'Olio and Romee Van der Zee for providing honeybee samples. DNA extractions and SNP genotyping were performed by Colette Abbey, with support from the TAMU Institute of Genomic Science and Society. An earlier version of the manuscript was improved by the constructive comments made by three anonymous reviewers. IM was supported by two postdoctoral fellowships from the Fundación Seneca (19149/PD/13-N) and from the University of Murcia (R-1017/2015). JC-G and DH were supported by PhD Scholarships (SFRH/BD/68682/2010 and SFRH/BD/84195/2012, respectively) from the Portuguese Science Foundation (FCT). MAP and PDLR are members of and receive support from the COST Action FA1307 (SUPER-B). Financial support for this research was provided by the project of Regional Excellence 19908-GERM-15 of the Fundación Seneca (Gobierno Regional de Murcia, Spain) to PDLR and by FCT and COMPETE/QREN/EU through the project PTDC/BIA-BEC/099640/2008 and the 2013-2014 BiodivERsA/FACCE-JPI joint call for research proposals (138573 - BiodivERsA/0002/2014) to MAP.
Sources of information: Directorio de Producción Científica Scopus