Accelerating genetic gain through integrated genomic selection in crop plants

Area of Science:

• Agricultural Science
• Genetics
• Plant Breeding

Background:

• Projected 70% rise in agricultural output by 2050 is challenged by climate change and population growth.
• Traditional breeding methods struggle with complex polygenic traits crucial for crop improvement.

Purpose of the Study:

• To review the framework, evolution, and integration of Genomic Selection (GS).
• To highlight GS's potential in developing climate-resilient, high-yielding cultivars for global food security.

Main Methods:

• Genomic selection (GS) leverages genome-wide markers for accurate prediction of breeding values.
• Integration of GS with high-throughput genotyping, phenomics, multi-omics, and machine learning.

Main Results:

• GS captures cumulative effects of numerous small-effect loci, enabling faster genetic gains for complex traits.
• GS enhances selection accuracy and shortens breeding cycles compared to traditional methods.

Conclusions:

• Genomic selection represents a paradigm shift in crop improvement strategies.
• GS integration is crucial for sustainable agriculture and ensuring global food security under climate uncertainty.