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Biology subjects

Eynard, S.

Publications and source records attributed to Eynard, S..

2 recordsLinked to original sources

Inferring long-term and short-term determinants of genetic diversity in honey bees: Beekeeping impact and conservation strategies

Bees are vital pollinators in natural and agricultural landscapes around the globe, playing a key role in maintaining flowering plant biodiversity and ensuring food security. Among the honey bee species, the Western honey bee (Apis mellifera) is particularly significant, not only for its extensive crop pollination services but also for producing economically valuable products such as honey. Here, we analyzed whole-genome sequence data from four Apis species to explore how honey bee evolution has shaped current diversity patterns. Using Approximate Bayesian Computation, we first reconstructed the demographic history of A. mellifera in Europe, finding support for postglacial secondary contacts, therefore predating human-mediated transfers linked to modern beekeeping. However, our analysis of recent demographic changes then reveals significant bottlenecks due to beekeeping practices, which have notably affected genetic diversity. Black honey bee populations from conservatories, particularly those on islands, exhibit considerable genetic loss, raising concerns about the long-term effectiveness of current conservation strategies. Additionally, we observed a high degree of conservation in the genomic landscapes of nucleotide diversity across the four species, despite a divergence gradient spanning over 15 million years, consistent with a long-term conservation of the recombination landscapes. Taken together, our results provide the most comprehensive assessment of diversity patterns in honey bees to date and offer insights into the optimal management of resources to ensure the long-term persistence of honey bees and their invaluable pollination services.

evolutionary biology↗

Empowering bioinformatics communities with Nextflow and nf-core

Standardised analysis pipelines are an important part of FAIR bioinformatics research. Over the last decade, there has been a notable shift from point-and-click pipeline solutions such as Galaxy towards command-line solutions such as Nextflow and Snakemake. We report on recent developments in the nf-core and Nextflow frameworks that have led to widespread adoption across many scientific communities. We describe how adopting nf-core standards enables faster development, improved interoperability, and collaboration with the >8,000 members of the nf-core community. The recent development of Nextflow Domain-Specific Language 2 (DSL2) allows pipeline components to be shared and combined across projects. The nf-core community has harnessed this with a library of modules and subworkflows that can be integrated into any Nextflow pipeline, enabling research communities to progressively transition to nf-core best practices. We present a case study of nf-core adoption by six European research consortia, grouped under the EuroFAANG umbrella and dedicated to farmed animal genomics. We believe that the process outlined in this report can inspire many large consortia to seek harmonisation of their data analysis procedures.

bioinformatics↗