RT Journal Article
T1 High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool
A1 Henriques, Dora
A1 Browne, Keith
A1 Barnett, Mark
A1 Parejo, Melanie
A1 Kryger, Per
A1 Freeman, Tom
A1 Muñoz Gabaldón, Irene
A1 Garnery, Lionel
A1 Highet, Fiona
A1 Jonhston, Spencer
A1 McCormack, Grace
A1 Pinto, Alice
AB The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.
PB Nature Research
SN 2045-2322
YR 2018
FD 2018
LK https://hdl.handle.net/20.500.14352/97378
UL https://hdl.handle.net/20.500.14352/97378
LA eng
NO Henriques, D., Browne, K.A., Barnett, M.W. et al. High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool. Sci Rep 8, 8552 (2018). https://doi.org/10.1038/s41598-018-26932-1
NO José Rufino provided computational resources at the Polytechnic Institute of Bragança, Portugal. DH was supported by a PhD scholarship (SFRH/BD/84195/2012) from the Portuguese Science Foundation (FCT). KAB receives a PhD fellowship from the Irish Research Council. MP was supported by the Swiss Federal Office for Agriculture FOAG and the Fondation Sur-la-Croix, Basel. IM was supported by Saavedra Fajardo fellowship from the Fundación Séneca (20036/SF/16). MAP is a member of and receives support from the COST Action FA1307 (SUPER-B). Funding for genotyping of Irish honeybees was gratefully received from the Eva Crane Trust, the Native Irish Honeybee Society and the Department of Agriculture, Food and the Marine (16/GR/09). MB and TCF are funded by an Institute Strategic Grant from the Biotechnology and Biological Sciences Research Council (BBSRC) (BB/JO1446X/1). Financial support for this research was provided to MAP and LG by 2013–2014 BiodivERsA/FACCE-JPI joint call for research proposals, with the national funders FCT (Portugal), “Agence Nationale de la Recherche” (France), and “Ministério de Economia y Competividade” (Spain).
NO Polytechnic Institute of Bragança
NO Ministerio de Economía y Competitividad (España)
NO Biotechnology and Biological Sciences Research Council
NO Agence Nationale de la Recherche (France)
NO Ministerio de Economía y Competitividad (España)
DS Docta Complutense
RD 20 abr 2025