Epistasis and pleiotropy-induced variation for plant breeding

Area of Science:

• Genetics
• Plant Breeding
• Genomics

Background:

• Epistasis involves nonallelic gene interactions affecting phenotypes, complicating genetic parameter estimation.
• Pleiotropy, where one gene influences multiple traits, offers functional specificity but challenges gene discovery.
• Understanding these interactions is crucial for dissecting complex traits and improving crop breeding.

Purpose of the Study:

• To overview emerging approaches for exploiting epistatic and pleiotropic interactions in plant breeding.
• To explore how modelling higher-order interactions can enhance crop productivity and stress tolerance.
• To discuss the role of artificial intelligence and large-scale data in analyzing these genetic phenomena.

Main Methods:

• Reviewing advances in statistical models, software, and genomic research.
• Analyzing epistatic interactions and pleiotropic quantitative trait loci.
• Integrating genotype × environment interactions into genomic selection models.

Main Results:

• Partitioning epistatic effects enables accurate genetic parameter estimation.
• Overcoming pleiotropy-based trade-offs can aid breeding for complex traits.
• New paths for increasing crop productivity and stress tolerance are emerging.

Conclusions:

• Exploiting positive epistatic and pleiotropic interactions offers significant potential for next-generation crop cultivars.
• Artificial intelligence and large-scale genomics/phenomics data are vital for dissecting complex genetic interactions.
• Addressing missing heritability through understanding these interactions is a key future direction.