Nonlinear genomic selection index accelerates multi-trait crop improvement.

ABSTRACT: Linear phenotypic and genomic selection indices assume additivity and linearity, limiting their ability to exploit nonlinear trait relationships. Here, we introduce the Quadratic Genomic Selection Index (QGSI), a genomic extension of the quadratic phenotypic selection index (QPSI) that integrates genomic estimated breeding values (GEBVs) within a unified quadratic framework. QGSI combines additive, squared, and cross-product terms of GEBVs, enabling phenotype-free, rapid-cycle multi-trait selection while capturing genome-wide nonlinear relationships. We evaluate QGSI using two genomic prediction strategies: (i) a maximum-likelihood additive genomic model, and (ii) a nonlinear multi-trait Gaussian kernel model that accommodates epistatic signals. Using 10 simulated maize selection cycles an

SUBMITTER: Jesus Ceron-Rojas J 

PROVIDER: S-EPMC12932720 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature