Genomic Selection for Pea Grain Yield and Protein Content in Italian Environments for Target and Non-Target Genetic...

Area of Science:

• Agricultural Science
• Plant Breeding
• Genomics

Background:

• Sustainable European agriculture requires improved pea cultivars for higher yields and protein content.
• Genomic selection (GS) offers a potential tool for accelerating breeding programs.

Purpose of the Study:

• To evaluate the predictive ability of genomic selection (GS) for grain yield, protein content, and protein yield in peas.
• To assess GS performance across different genetic bases (target and non-target).

Main Methods:

• Developed GS models using 5537 SNPs from 276 lines across three Recombinant Inbred Line (RIL) populations in Italian environments.
• Validated models on 108 independent lines from five RIL populations with varying genetic relatedness to the training set.
• Conducted a genome-wide association study (GWAS) with 18,674 SNPs to understand trait control.

Main Results:

• GS demonstrated intermediate to high predictive ability (0.359-0.675) for all traits within the target genetic base.
• Predictive ability was modest for protein content but poor for yield and protein yield in non-target genetic bases.
• Genome-wide association study indicated polygenic control for protein content and grain yield, with environment-dependent QTLs for yield.

Conclusions:

• Genomic selection is a valuable tool for predicting grain yield and protein content in peas within a related genetic base.
• GS shows potential for protein content prediction in non-target genetic bases, but less so for yield.
• No negative correlation was observed between grain yield and protein content in this study.