Validation of DNA marker-assisted selection for forage biomass productivity under deficit irrigation in alfalfa

Abstract

Drought and limited irrigation resources threaten agricultural sustainability in many regions of the world. Application of genomic-based breeding strategies may benefit crop variety development for these environments. Here, we provide a first report on the effect of deploying DNA marker-assisted selection (MAS) for the drought resilience quantitative trait in alfalfa (Medicago sativa L.). The goals of this study were to validate the effect of several quantitative trait loci (QTL) associated with alfalfa forage and crown-root (CR) biomass during drought and to determine their potential to improve forage yield of elite germplasm under water-limited conditions. Marker assisted selection was employed to introgress favorable or unfavorable DNA marker alleles affiliated with 10 biomass QTL into three elite backgrounds. Thirty-two populations were developed and evaluated for forage productivity over 3 yr under continuous deficit irrigation management in New Mexico, USA. Significant yield differences (ranging from -13 to 26%) were detected among some MAS-derived populations in all three elite backgrounds. Application of QTL MAS generally resulted in expected phenotypic responses within an elite genetic background that was similar to that in which the QTL were originally identified. However, relative performance of the populations varied substantially across the three genetic backgrounds. These outcomes indicate that QTL MAS can significantly affect forage productivity of elite alfalfa germplasm in drought-stressed environments. However, if biomass QTL are detected in donor germplasm that is genetically dissimilar to targeted elite populations, characterization of donor alleles may be warranted within elite backgrounds of interest to confirm their phenotypic effects prior to implementing MAS-based breeding.

Description
Keywords
water-use efficiency, drought tolerance, yield, registration, improvement, germplasm, genomics, carbon
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