Dogantzis Kathleen A, Patel Harshilkumar, Rose Stephen, Conflitti Ida M, Dey Alivia, Tiwari Tanushree, Chapman Nadine C, Kadri Samir M, Patch Harland M, Muli Elliud M, Alqarni Abdulaziz S, Allsopp Michael H, Zayed Amro
Department of Biology York University Toronto Ontario Canada.
Behaviour, Ecology and Evolution Laboratory, School of Life and Environmental Sciences University of Sydney Sydney Australia.
Ecol Evol. 2024 Nov 17;14(11):e70554. doi: 10.1002/ece3.70554. eCollection 2024 Nov.
Hybrid populations of Africanized honey bees (-hybrids), notable for their defensive behaviour, have spread rapidly throughout South and North America since their unintentional introduction. Although their migration has slowed, the large-scale trade and movement of honey bee queens and colonies raise concern over the accidental importation of -hybrids to previously unoccupied areas. Therefore, developing an accurate and robust assay to detect -hybrids is an important first step toward mitigating risk. Here, we used an extensive population genomic dataset to assess the genomic composition of native populations and patterns of genetic admixture in North and South American commercial honey bees. We used this dataset to develop a SNP assay, where 80 markers, combined with machine learning classification, can accurately differentiate between -hybrids and non--hybrid commercial colonies. The assay was validated on 1263 individuals from colonies located in Canada, the United States, Australia and Brazil. Notably, we demonstrate that using a reduced SNP set of as few as 10 loci can still provide accurate results.
非洲化蜜蜂的杂交种群(简称“杂交种”)以其防御行为而闻名,自无意间被引入以来,已在南美洲和北美洲迅速扩散。尽管它们的迁移速度有所减缓,但蜜蜂蜂王和蜂群的大规模贸易和移动引发了人们对杂交种意外引入此前未受影响地区的担忧。因此,开发一种准确且可靠的检测方法来检测杂交种是降低风险的重要第一步。在此,我们使用了一个广泛的种群基因组数据集来评估北美和南美商业蜜蜂的本地种群基因组组成以及基因混合模式。我们利用该数据集开发了一种单核苷酸多态性(SNP)检测方法,其中80个标记与机器学习分类相结合,能够准确区分杂交种和非杂交种商业蜂群。该检测方法在来自加拿大、美国、澳大利亚和巴西的1263个蜂群个体上得到了验证。值得注意的是,我们证明使用少至10个位点的简化SNP集仍能提供准确的结果。