Hélène Muranty

This study identifies and validates five QTLs associated with apple scab resistance using transcriptomic data and high-resolution genotyping in a biparental population.

WISER improves breeding value estimation by addressing population structure and genotype-environment confounding through spectral whitening, outperforming LS-means and BLUP across multiple species and traits.

WISER improves phenotype estimation in omics studies by correcting population structure, outperforming LS and BLUP across multiple species and datasets.

This study applies statistical and deep learning models to multi-environmental genomic prediction in apple, showing improved predictive ability for certain traits.

This study examines the genetic architecture and genomic prediction accuracy of 30 apple quantitative traits across six European locations, identifying novel associations and demonstrating the impact of genotype by environment interactions.

This study combines genetic resources and elite material populations to improve genomic prediction accuracy in apple breeding by optimizing training set composition and population integration.

This paper integrates Infinium and Axiom SNP array data in apple, identifies compatible SNPs, and highlights challenges in data integration.

This paper uses genomic selection to predict apple fruit texture traits, achieving high accuracy by optimizing the training set size and composition.