Water Stress Tolerance, Genomic Selection and Identification of Genomic Regions in a MAGIC Population of Eggplant

Abstract

Horticultural crops are increasingly affected by water stress due to climate change, making the development of stress-tolerant varieties an urgent need. In this study, we evaluated a set of 184 Multi-parent Advanced Generation Inter-Cross (MAGIC) eggplant lines under water stress conditions, consisting of irrigation at 30% of field capacity. After 21 days of stress, we assessed traits related to growth, water content, plant pigments, and proline content. The MAGIC population displayed a high variability for water stress tolerance, as transgressive lines over parental values were found for most of the traits. Key traits associated with water stress tolerance were identified, including increased root growth and elevated proline, and flavonoid content. Genome-Wide Association Study (GWAS) analysis allowed identification of three genomic regions associated with total dry weight, water content and flavonoids, traits that contribute significantly to stress tolerance. Additionally, a linear genomic selection index was constructed based on total dry weight, dry weight increase during the stress period, root dry weight, water content, and proline content to identify water stress-tolerant and susceptible lines. The models predictive ability was calculated, and the value of the selection index was predicted for 141 unevaluated MAGIC lines, with prediction accuracy for the index traits ranging from 0.11 to 0.53. This study presents a comprehensive analysis, identifying critical traits, genomic regions and lines with genetic potential, providing valuable information for future breeding programmes to improve water stress tolerance in eggplant.