A large-scale survey of the Iberian honey bee (Apis mellifera iberiensis) diversity patterns, using sequence data of the tRNA leu-cox2 mitochondrial DNA (mtDNA) region, demonstrates that earlier studies based on the Dra I test missed significant components of genetic variation. Based on results from this survey, existing haplotype names were revised and updated following a nomenclature system established earlier and extended herein for the intergenic region. A more complete picture of the complex diversity patterns of IHBs is revealed that includes 164 novel haplotypes, 113 belonging to lineage A and 51 to lineage M and within lineage A and 69 novel haplotypes that belong to sub-lineage A I , 13 to A II , and 31 to A III. Within lineage M, two novel haplotypes show a striking architecture with features of lineages A and M, which based on sequence comparisons and relationships among haplotypes are seemingly ancestral. These data expand our knowledge of the complex architecture of the tRNA leu-cox2 intergenic region in Apis mellifera and re-emphasizes the importance of Iberia as a source of honey bee mtDNA diversity. Iberian honey bee / Apis mellifera intermissa / ancestral haplotype M / Dra I test

In a scenario of worldwide honey bee decline, assessing colony strength is becoming increasingly important for sustainable beekeeping. Temporal counts of number of comb cells with brood and food reserves offers researchers data for multiple applications, such as modelling colony dynamics, and beekeepers information on colony strength, an indicator of colony health and honey yield. Counting cells manually in comb images is labour intensive, tedious, and prone to error. Herein, we developed a free software, named DeepBee©, capable of automatically detecting cells in comb images and classifying their contents into seven classes. By distinguishing cells occupied by eggs, larvae, capped brood, pollen, nectar, honey, and other, DeepBee© allows an unprecedented level of accuracy in cell classification. Using Circle Hough Transform and the semantic segmentation technique, we obtained a cell detection rate of 98.7%, which is 16.2% higher than the best result found in the literature. For classification of comb cells, we trained and evaluated thirteen different convolutional neural network (CNN) architectures, including: DenseNet (121, 169 and 201); InceptionResNetV2; InceptionV3; MobileNet; MobileNetV2; NasNet; NasNetMobile; ResNet50; VGG (16 and 19) and Xception. MobileNet revealed to be the best compromise between training cost, with~9 s for processing all cells in a comb image, and accuracy, with an F1-Score of 94.3%. We show the technical details to build a complete pipeline for classifying and counting comb cells and we made the CNN models, source code, and datasets publicly available. With this effort, we hope to have expanded the frontier of apicultural precision analysis by providing a tool with high performance and source codes to foster improvement by third parties (https://github.com/AvsThiago/DeepBeesource).

Wing geometric morphometrics has been applied to honey bees (Apis mellifera) in identification of evolutionary lineages or subspecies and, to a lesser extent, in assessing genetic structure within subspecies. Due to bias in the production of sterile females (workers) in a colony, most studies have used workers leaving the males (drones) as a neglected group. However, considering their importance as reproductive individuals, the use of drones should be incorporated in these analyses in order to better understand diversity patterns and underlying evolutionary processes. Here, we assessed the usefulness of drone wings, as well as the power of wing geometric morphometrics, in capturing the signature of complex evolutionary processes by examining wing shape data, integrated with geographical information, from 711 colonies sampled across the entire distributional range of Apis mellifera iberiensis in Iberia. We compared the genetic patterns reconstructed from spatially-explicit shape variation extracted from wings of both sexes with that previously reported using 383 genome-wide SNPs (single nucleotide polymorphisms). Our results indicate that the spatial structure retrieved from wings of drones and workers was similar (r = 0.93) and congruent with that inferred from SNPs (r = 0.90 for drones; r = 0.87 for workers), corroborating the clinal pattern that has been described for A. m. iberiensis using other genetic markers. In addition to showing that drone wings carry valuable genetic information, this study highlights the capability of wing geometric morphometrics in capturing complex genetic patterns, offering a reliable and low-cost alternative for preliminary estimation of population structure.

Dioecy, the separation of reproductive organs on different individuals, has evolved repeatedly in different plant families. Several evolutionary paths to dioecy have been suggested, but the mechanisms behind sex determination is not well understood. The diploid dioecious Amaranthus palmeri represents a well-suited model system to study sex determination in plants. Despite the agricultural importance of the species, the genetic control and evolutionary state of dioecy in A. palmeri is currently unknown. Early cytogenetic experiments did not identify heteromorphic chromosomes. Here, we used whole-genome sequencing of male and female pools from 2 independent populations to elucidate the genetic control of dioecy in A. palmeri. Read alignment to a close monoecious relative and allele frequency comparisons between male and female pools did not reveal significant sex-linked genes. Consequently, we employed an alignment-free k-mer comparison which enabled us to identify a large number of male-specific k-mers. We assembled male-specific contigs comprising a total of almost 2 Mb sequence, proposing a XY sex-determination system in the species. We were able to identify the potential Y chromosome in the A. palmeri draft genome sequence as 90% of our male-specific sequence aligned to a single scaffold. Based on our findings, we suggest an intermediate evolutionary state of dioecy with a young Y chromosome in A. palmeri. Our findings give insight into the evolution of sex chromosomes in plants and may help to develop sustainable strategies for weed management.

In this study, honey bees from the Macaronesian archipelago of the Azores were extensively surveyed to unveil diversity patterns. A total of 638 colonies were analyzed over two time periods using mtDNA and wing geometric morphometrics. The genetic composition revealed to be heterogeneous and related to historical and contemporary human-mediated introductions. The close relationship of Azorean populations with those from northern Portugal supports historical introductions by Portuguese settlers. The African sublineage A III prevailed on five islands, contrasting with three islands where C haplotypes were dominant. On Pico and Graciosa, C haplotypes are due to recent imports of commercial queens. On Faial, the sudden replacement of A III by C haplotypes coincided with arrival of Varroa destructor. This study deepens the current understanding of Macaronesian honey bees, suggesting that they are variants of the Iberian honey bee with differential levels of Cderived introgression. Iberian honey bee / tRNA leu-cox2 intergenic region / wing geometric morphometrics / DraI test