Broeckx, B. J. G. | bioRxiv Science

bioRxiv2026

A Putative Single-Locus Determinant of the Suppressed In Ovo Virus Infection (SOV) Trait in Apis mellifera

Today, the deformed wing virus (DWV) can be considered as one of the major causes of global elevated western honey bee colony losses (Apis mellifera). Virus transmission may occur horizontally between individuals of the same generation, but also vertically from parents to offspring. The recently defined heritable suppressed in ovo virus infection (SOV) trait describes the absence of viruses in pooled drone eggs of a queen, associated with significant lower DWV prevalence and viral loads in the subsequent developmental offspring stages. By definition, the trait reflects the absence of vertical virus transmission from SOV-positive (SOV+) queens themselves to their offspring. However, the genetic basis influencing this heritable virus resilience has not been identified yet. In this study, we aimed to identify SOV-associated genetic marker(s) or loci in the honey bee genome through genome-wide variant comparison of 44 DWV-positive and 44 DWV-negative drone pupae descendent from an artificially created hybrid SOV+/SOV- colony. After whole genome sequencing (WGS), variant calling, and genotype-phenotype association analysis by means of single marker tests and elastic net regression, one variant in a locus of 241.246 bp on chromosome 7 that contained 17 other highly SOV-associated variants classified 68,2% of the drone phenotypes correctly. These results may support the potential application of marker-assisted selection (MAS) strategies targeting reduced vertical virus transmission in honey bees.

genomics↗

bioRxiv2024

Variant classification guidelines for animals to objectively evaluate genetic variant pathogenicity

Assessing the pathogenicity of a disease-associated variant in animals accurately is vital, both on a population and individual scale. At the population level, breeding decisions based on invalid DNA tests can lead to the incorrect exclusion of animals and compromise the long- term health of a population, and at the level of the individual animal, lead to incorrect treatment and even life-ending decisions. Criteria to determine pathogenicity are not standardized, hence no guidelines for animal variants are available. Here, we developed and optimized the animal variant classification guidelines, based on those developed for humans by The American College of Medical Genetics and Genomics, and demonstrated a superior classification in animals. We described methods to develop datasets for benchmarking the criteria and identified the most optimal in silico variant effect predictor tools. As the reproducibility was high, we classified 72 known disease-associated variants in cats and 40 other disease-associated variants in eight additional species.

genetics↗