Outlook for Implementation of Genomics-Based Selection in Public Cotton Breeding Programs.

Area of Science:

• Agricultural Science
• Genetics
• Plant Breeding

Background:

• Quantitative genetics has mapped cotton loci, but alleles are often population/environment-specific, limiting their use in traditional breeding.
• Genomics-based selection offers potential for improving cotton breeding within closed gene pools.

Purpose of the Study:

• To assess the feasibility of genomics-based selection in historical Upland cotton lines.
• To identify genetic loci associated with fiber quality, seed composition, and yield traits.
• To evaluate genomic prediction models and the impact of genome-wide association study (GWAS) hits on prediction accuracy.

Main Methods:

• Utilized genotypic and phenotypic data from 80 historical Upland cotton lines.
• Performed genome-wide association study (GWAS) for 20 traits across 14 field trials.
• Explored genomic prediction and incorporated GWAS hits into prediction models.

Main Results:

• Genomic selection for fiber quality traits is immediately applicable in cotton breeding programs.
• Prediction ability for other traits is lower but correlates with heritability.
• Consistently detected GWAS hits can enhance prediction accuracy when significance thresholds are carefully chosen.

Conclusions:

• Genomic selection holds significant promise for accelerating Upland cotton (Gossypium hirsutum L.) improvement.
• Integrating GWAS findings into genomic prediction models can boost accuracy for key traits.
• A collaborative, community-based approach is essential for advancing US public-sector cotton breeding into the genomics era.