Biology subjects

de Miranda, J. R.

Publications and source records attributed to de Miranda, J. R..

4 recordsLinked to original sources

bioRxiv2026

Genetic determinants of intraspecific variation in crossover frequencies in the honeybee, Apis mellifera

Meiotic recombination facilitates natural selection and is necessary for correct chromosomal segregation in most sexually reproducing species. Crossover rates vary greatly both within and among species, but the determinants of this variation are not fully understood. The honeybee Apis mellifera has extremely high recombination rates. Honeybee males (drones) are haploid, which enables the distribution of crossovers to be directly estimated from the progeny of a single reproductive female (queen). Here we map crossover events in the honeybee using whole genome sequencing of 1509 drone progeny of 184 queens. This allows us to assay intra-specific variation in recombination rate and its genetic and non-genetic determinants. We estimate the average crossover rate as 23 cM/Mb, with between 22 and 88 crossovers events detected in individual offspring. We estimate 28% of this variation is additive heritable variation among queens. There is no effect of queen age or genetic background on crossover rate. A genome-wide association study identifies variation in the gene mlh1 as associated with mean crossover rate. We estimate that variation in the gene is associated with a 10% difference in crossover rate between the two homozygous genotypes at the most significant SNP. This gene has a well-established role in recombination and variation in the gene could affect crossover rates by affecting resolution of Holliday junctions as crossovers. This is the first gene discovered to be associated with recombination rate variation in an insect. Adaptive evolution of this gene could potentially underlie the extremely high recombination rates in honeybees.

genomics↗

bioRxiv2024

Sequence-based genome-wide association studies reveal the polygenic architecture of Varroa destructor resistance in Western honey bees Apis mellifera

Honey bees, Apis mellifera, have experienced the full impacts of globalisation, including the recent invasion by the parasitic mite Varroa destructor which has become one of the main causes of colony losses worldwide. Despite its lethal effects, some colonies have developed defence strategies conferring colony resistance and, assuming non-null heritability, selective breeding of naturally resistant bees could be a sustainable way to fight infestations. Here we report on the largest genome-wide association study performed on honey bees to understand the genetic basis of multiple phenotypes linked to varroa resistance. This study was performed on whole genome sequencing of more than 1,500 colonies belonging to different ancestries and combined in a meta-analysis. Results show that varroa resistance is polygenic. A total of 60 genetic markers were identified as having a significant impact in at least one of the tested populations pinpointing several regions of the honey bee genome. Our results also support strategies for genomic selection in honey bee breeding.

genetics↗

bioRxiv2022

Dynamics in vertical transmission of viruses in naturally selected and traditionally managed honey bee colonies across Europe

The suppressed in-ovo virus infection trait (SOV) was the first trait applied in honey bee breeding programs aimed to increase resilience to virus infections, a major threat for colony survival. By screening drone eggs for viruses, the SOV trait scores the antiviral resistance of queens and its implications for vertical transmission. In this study, queens from both naturally surviving and traditionally managed colonies from across Europe were screened using a two-fold improved SOV phenotyping protocol. First, a gel-based RT-PCR was replaced by a RT-qPCR. This not only allowed quantification of the infection load but also increased the test sensitivity. Second, a genotype specific primer set was replaced by a primer set that covered all known deformed wing virus (DWV) genotypes, which resulted in higher virus loads and fewer false negative results. It was demonstrated that incidences of vertical transmission of DWV were more frequent in naturally surviving populations than in traditionally managed colonies, although the virus load in the eggs remained the same. Dynamics in vertical transmission were further emphasized when comparing virus infections with queen age. Interestingly, older queens showed significantly lower infection loads of DWV in both traditionally managed and naturally surviving colonies, as well as reduced DWV infection frequencies in traditionally managed colonies when compared with younger queens. Seasonal variation in vertical transmission was found with lower infection frequencies in spring compared to summer for DWV and black queen cell virus. Together, these patterns in vertical transmission suggest an adaptive antiviral response of queens aimed at reducing vertical transmission over time.

ecology↗

bioRxiv2018

Characterisation of the UK honey bee (Apis mellifera) metagenome.

The European honey bee (Apis mellifera) plays a major role in pollination and food production, but is under threat from emerging pathogens and agro-environmental insults. As with other organisms, honey bee health is a complex product of environment, host genetics and associated microbes (commensal, opportunistic and pathogenic). Improved understanding of bee genetics and their molecular ecology can help manage modern challenges to bee health and production. Sampling bee and cobiont genomes, we characterised the metagenome of 19 honey bee colonies across Britain. Low heterozygosity was observed in bees from many Scottish colonies, sharing high similarity to the native dark bee, A. mellifera mellifera. Apiaries exhibited high diversity in the composition and relative abundance of individual microbiome taxa. Most non-bee sequences derived from known honey bee commensal bacteria or known pathogens, e.g. Lotmaria passim (Trypanosomatidae), and Nosema spp. (Microsporidia). However, DNA was also detected from numerous additional bacterial, plant (food source), protozoan and metazoan organisms. To classify sequences from cobionts lacking genomic information, we developed a novel network analysis approach clustering orphan contigs, allowing the identification of a pathogenic gregarine. Our analyses demonstrate the power of high-throughput, directed metagenomics in agroecosystems identifying potential threats to honey bees present in their microbiota.

genomics↗