A SNP assay for assessing diversity in immune genes in the honey bee (Apis mellifera L.)

Abstract

With a growing number of parasites and pathogens experiencing large-scale range expansions, monitoring diversity in immune genes of host populations has never been so important because it can inform on the adaptive potential to resist the invaders. Population surveys of immune genes are becoming common in many organisms, yet they are missing in the honey bee (Apis mellifera L.), a key managed pollinator species that has been severely affected by biological invasions. To fill the gap, here we identified single nucleotide polymorphisms (SNPs) in a wide range of honey bee immune genes and developed a medium-density assay targeting a subset of these genes. Using a discovery panel of 123 whole-genomes, representing seven A. mellifera subspecies and three evolutionary lineages, 180 immune genes were scanned for SNPs in exons, introns (< 4 bp from exons), 3' and 5´UTR, and < 1 kb upstream of the transcription start site. After application of multiple filtering criteria and validation, the final medium-density assay combines 91 quality-proved functional SNPs marking 89 innate immune genes and these can be readily typed using the high-sample-throughput iPLEX MassARRAY system. This medium-density-SNP assay was applied to 156 samples from four countries and the admixture analysis clustered the samples according to their lineage and subspecies, suggesting that honey bee ancestry can be delineated from functional variation. In addition to allowing analysis of immunogenetic variation, this newly-developed SNP assay can be used for inferring genetic structure and admixture in the honey bee. ; We are deeply indebted to Frank Aguiar, Luís Silva, Edgardo Melo, João Martins, João Melo, Manuel Moura, Manuel Viveiros, and Ricardo Sousa from "Direção Regional da Agricultura e Desenvolvimento Rural dos Açores" (Portugal), and to Laura Garreau, Laurent Maugis, Pascale Sauvage and Jacques Kermagoret, from "Association Conservatoire de l'Abeille Noir Bretonne" (France), for sampling the apiaries in São Miguel, Santa Maria, and Ouessant islands. Genotyping was outsourced to the Epigenetics and Genotyping laboratory, Central Unit for Research in Medicine (UCIM), University of Valencia, Spain. Data analyses were performed using computational resources at the Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança. Ana Rita Lopes is supported by a PhD scholarship (SFRH/BD/143627/2019) from the Foundation for Science and Technology (FCT), Portugal. FCT provided financial support by national funds (FCT/MCTES) to CIMO (UIDB/00690/2020).This research was funded through the projects BEEHAPPY (POCI-01-0145- FEDER-029871, FCT and COMPETE/QREN/EU) and BEEHEAL. BEEHEAL was funded by the ARIMNet2 2016 Call by the following agencies: INIA (Spain), MOARD (Israel), ANR (France) and FCT (Portugal). ARIMNet2 (ERA-NET) received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 618127. ; info:eu-repo/semantics/publishedVersion