Beyond the single gene: Integrating genomic selection and genome editing for the improvement of polygenic traits in crop plants

Abstract

Polygenic traits such as yield, drought tolerance, water-use efficiency, and nutritional quality are central to crop improvement but remain challenging targets because they are controlled by numerous loci and influenced by complex genotype-by-environment (G×E) interactions. These characteristics limit the effectiveness of single-gene approaches and highlight the need for integrated breeding strategies. This review examines the complementary roles of genomic selection (GS) and genome editing (GE) for the improvement of complex traits in crop plants. The genetic architecture of polygenic traits, the principles underlying genomic prediction, and recent advances in CRISPR-based genome editing are critically evaluated. Building on current knowledge, five integration strategies are discussed: GWAS-guided target prioritization, favorable allele deployment with polygenic background optimization, SpeedGS-assisted breeding, regulatory network editing, and environment-informed genome editing. The review also examines key challenges associated with GS–GE integration, including causal variant identification, epistasis, pleiotropy, genotype-by-environment interactions, transformation efficiency, and regulatory considerations. Finally, emerging developments in machine learning, multi-omics, and high-throughput phenotyping are highlighted as enabling technologies for future breeding programs. Overall, the integration of GS and GE is presented as a promising framework for accelerating genetic gain and improving complex polygenic traits in crops.