Development of new quantitative physiological and molecular breeding parameters based on the sugar beet vernalization intensity model.

Abstract

Sugar-beet crops, Beta vulgaris spp. vulgaris (L), suffer from premature bolting and flowering as a consequence of prolonged exposure to cold conditions (vernalization). This reduces crop yield and quality and could be avoided if bolting-resistant varieties were available. Traditionally, development of bolting-resistant varieties has relied on selection against the annual growth habit associated with the bolting gene B. However, this has failed to deliver crops that can be reliably sown in early spring or grown over winter without the risk of bolting. New breeding targets and selection strategies are required and have become tractable with the recent development of the vernalization-intensity model. This model uses parameters for the intensity and duration of vernalization (vernalization hours) to predict bolting responses and discriminates between varieties by the minimum number of vernalization hours needed to induce bolting (vernalization requirement (VR)) and by the increase in bolting incidence for each extra vernalizing hour once the VR has been satisfied (bolting sensitivity (BS)). Since the vernalization-intensity model was developed from variety-assessment trials data, the present work sought to refine and test it through controlled environment (CE) experiments in which seven sugar-beet varieties were exposed to differing levels of accurately defined vernalization treatments and scored for bolting rates to determine their VR and BS values. The results confirmed and improved the model and showed that VR, not BS, has more potential for developing bolting resistant varieties. It was also observed that there exist in current varieties, the genetic potential to breed for higher VR. Further experiments assessed the correlation of attainment of VR with changes in gene expression and shoot apical meristem (SAM) morphology to identify potential markers for this trait. It was found that the time when VR is attained correlates with up-regulation of gibberellin biosynthetic genes and floral transcription factors in leaf and shoot apices; most prominently, GIBBERELLIN 20-OXIDASE 2 (BvGA20ox2) and FLOWERING LOCUS T 2 (BvFT2). To integrate the results with weather data, temperature records for the past 47 years from the Broom's Barn weather station were used to develop a tool for predicting accumulated vernalization hours based on sowing date. The results, together with data from the CE experiments, were used to establish VR-breeding targets for bolting-resistant varieties for spring- and autumn-sown sugar-beet crops. The present paper shows that integration of weather, VR and genetic data provide useful tools to aid both cultivation and breeding selection. For growers, it provides a weather data tool to assist with the selection of suitable sowing dates. For breeders, it provides the first identification of molecular genetic factors that correlate with VR and the physiological changes associated with vernalization responses in sugar beet. The results suggest that gene-expression profiles can be developed into tools for quantifying bolting resistance in beet, thereby providing a cost-effective, high-throughput and simple method for breeders to apply the vernalization-intensity model.