Genome-wide association study for antibody response to Mycobacterium avium ssp. paratubeculosis in goats.

Mycobacterium avium ssp. paratuberculosis (MAP), causes Johne's disease (JD), or paratuberculosis, a chronic enteritis of ruminants, which in goats is characterized by ileal lesions. The work described here is a case-control association study using the Illumina Caprine SNP50 BeadChip to unravel the genes involved in susceptibility of goats to JD. Goats in herds with a high occurrence of Johne's disease were classified as healthy or infected based on the level of serum antibodies against MAP, and 331 animals were selected for the association study. Goats belonged to the Jonica (157) and Siriana breeds (174). Whole-genome association analysis identified one region suggestive of significance associated with an antibody response to MAP on chromosome 7 (p-value = 1.23 × 10-5 ). These results provide evidence for genetic loci involved in the antibody response to MAP in goats.

Analysis of Complementary Sex-Determiner (csd) Allele Diversity in Different Honeybee Subspecies from Italy Based on NGS Data.

Sexual regulation in Apis mellifera is controlled by the complementary sex-determiner (csd) gene: females (queens and workers) are heterozygous at this locus and males (drones) are hemizygous. When homozygous diploid drones develop, they are eaten by worker bees. High csd allelic diversity in honeybee populations is a priority for colony survival. The focus of this study is to investigate csd variability in the genomic sequence of the hypervariable region (HVR) of the csd gene in honeybee subspecies sampled in Italy. During the summer of 2017 and 2018, worker bees belonging to 125 colonies were sampled. The honeybees belonged to seven different A. mellifera subspecies: A. m. ligustica, A. m. sicula, A. m cecropia, A. m. carnica, A. m. mellifera, Buckfast and hybrid Carnica. Illumina genomic resequencing of all samples was performed and used for the characterization of global variability among colonies. In this work, a pipeline using existing resequencing data to explore the csd gene allelic variants present in the subspecies collection, based on de novo assembly of sequences falling within the HVR region, is described. On the whole, 138 allelic sequences were successfully reconstructed. Among these, 88 different alleles were identified, 68 of which match with csd alleles present in the NCBI GenBank database.

Automated image analysis to assess hygienic behaviour of honeybees.

Focus of this study is to design an automated image processing pipeline for handling uncontrolled acquisition conditions of images acquired in the field. The pipeline has been tested on the automated identification and count of uncapped brood cells in honeybee (Apis Mellifera) comb images to reduce the workload of beekeepers during the study of the hygienic behavior of honeybee colonies. The images used to develop and test the model were acquired by beekeepers on different days and hours in summer 2020 and under uncontrolled conditions. This resulted in images differing for background noise, illumination, color, comb tilts, scaling, and comb sizes. All the available 127 images were manually cropped to approximately include the comb area. To obtain an unbiased evaluation, the cropped images were randomly split into a training image set (50 images), which was used to develop and tune the proposed model, and a test image set (77 images), which was solely used to test the model. To reduce the effects of varied illuminations or exposures, three image enhancement algorithms were tested and compared followed by the Hough Transform, which allowed identifying individual cells to be automatically counted. All the algorithm parameters were automatically chosen on the training set by grid search. When applied to the 77 test images the model obtained a correlation of 0.819 between the automated counts and the experts' counts. To provide an assessment of our model with publicly available images acquired by a different equipment and under different acquisition conditions, we randomly extracted 100 images from a comb image dataset made available by a recent literature work. Though it has been acquired under controlled exposure, the images in this new set have varied illuminations; anyhow, our pipeline obtains a correlation between automatic and manual counts equal to 0.997. In conclusion, our tests on the automatic count of uncapped honey bee comb cells acquired in the field and on images extracted from a publicly available dataset suggest that the hereby generated pipeline successfully handles varied noise artifacts, illumination, and exposure conditions, therefore allowing to generalize our method to different acquisition settings. Results further improve when the acquisition conditions are controlled.