Numero del progetto: 26.29.14.04.01_OptiGenSel

Selezione genomica: algoritmi e strategie avanzati per la selezione vegetale e animale

Predicting plant and animal traits based on genomic information allows for the precise and efficient selection of superior individuals in breeding. This project aims to implement advanced predictive breeding strategies to improve the accuracy of trait prediction in crops and livestock, focusing on key characteristics such as yield, quality, disease resistance, climate adaptation, and reduced methane emissions. In close collaboration with breeders, the project will deliver practical, science-driven computational solutions that make breeding more efficient. The outcomes can help improve characteristics of crops and livestock, ensuring the long-term sustainability of agricultural production.

Cognome, Nome Sede
Jung Michaela Wädenswil
Neuditschko Markus Posieux
Wüst Samuel Wädenswil

Neuditschko M.
GENIUS: Genotype-informed unbiased selection of individuals for efficient phenotyping.
In: 77th EAAP Annual Meeting. 7 September, Ed. German Society for Animal Production (DGfZ), Hamburg (DE). 2026, 1186.

Neuditschko M.
TRACE: A novel approach to detect genomic regions under selection in populations.
In: World Congress on Genetics Applied to Livestock Production. 12 July, Ed. American Society of Animal Science (ASAS), Madison (US). 2026.

Zuffa F., Jung M., Yates S., Quesada-Traver C., López M.-E., Broggini G., Patocchi A., Studer B., Dow G.
Candidate genes with antagonistic roles in stomatal development are associated with population-wide variation in apple.
Horticulture Research, 13, (10), 2026, Articolo uhag285.