Maxime de Ronne

This study identifies sex-specific ethylene-responsive genes driving floral sex plasticity in Cannabis through multi-omic analysis of hormonally induced sex change.

This study performs GWAS on drug-type Cannabis to identify genetic markers associated with agronomic and morphological traits using HD-GBS and statistical methods.

This study compares k-mer-based GWAS with conventional SNP/indel-based GWAS in soybean, finding k-mer-based methods more effective at identifying causal variants and candidate genes for specific traits.

SNPLift converts genetic variant coordinates between genome assemblies efficiently, achieving high accuracy across multiple species.