Lan Zhou , Long Jiang

College of Agriculture, Jilin Agricultural Science and Technology University, Jilin, 132101, Jilin, China
Author    Correspondence author
Maize Genomics and Genetics, 2024, Vol. 15, No. 3   doi: 10.5376/mgg.2024.15.0012
Received: 31 Mar., 2024    Accepted: 06 May, 2024    Published: 22 May, 2024

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Zhou L., and Jiang L., 2024, Genomics-assisted breeding in maize: techniques and outcomes, Maize Genomics and Genetics, 15(3): 111-122 (doi: 10.5376/mgg.2024.15.0012)

Genomics-assisted breeding (GAB) has revolutionized maize breeding by integrating advanced genomic techniques to enhance crop improvement. This study reviews the various techniques and outcomes of GAB in maize, focusing on the integration of genomic selection, genome optimization, and marker-assisted selection. Genomic selection leverages genome-wide marker data to predict breeding values, thereby increasing genetic gains with fewer breeding cycles. Genome optimization, incorporating doubled haploid production and computational simulations, aims to design optimized genomes for maximum genetic gain. Marker-assisted selection, facilitated by high-throughput genotyping platforms, provides cost-effective and efficient genotyping solutions. The outcomes of these techniques include the development of disease-resistant, climate-smart, and high-yielding maize cultivars. The integration of these genomic tools has transformed maize breeding from an empirical art to a data-driven science, promising significant advancements in crop productivity and sustainability.

Maize; Genomics-assisted breeding; Genomic selection; Genome optimization; Marker-assisted selection