QTL mapping for root yield and leaf traits in sugar beet (Beta vulgaris L.) under drought stress condition

Drought stress is one of the most important environmental factors limiting sugar beet production in arid and semi-arid regions of the world including Iran. Development of drought tolerant varieties is a sustainable approach to mitigate the effect of this limitation. To develop drought tolerant varieties, it is necessary to understand the genetic basis and to map the genomic positions (QTLs) of the traits associated with drought tolerance. To identify the genomic regions of root yield and some leaf traits such as leaf number, leaf chlorophyll content, specific leaf weight, percent green crop cover, carbon isotope discrimination (Δ), leaf succulence index, leaf wilt score and leaf scenecense score, 142 F2:3 families derived from crosses between two parental lines (R49 as tolerant and S501 as sensitive) were studied using simple lattice design under non-stress and water-deficit stress conditions at Kamalabad Research Station, Karaj, Iran, in 2010. Linkage analysis was carried out using 759 simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers with a minimum LOD value of 2.5. Eighteen QTLs were identified in the two moisture regime environments. The highest number of QTLs was found on chromosomes 4 and 6 indicating that these chromosomes play an important role in genetic control of the traits studied. In non-stress condition, one QTL was found for specific leaf weight and leaf succulence index, two QTLs for root yield and five QTLs for Δ. In stress condition, one QTL was identified for root yield, leaf number, leaf chlorophyll content, leaf succulence index and leaf scenecense score, and two QTLs for Δ and leaf wilt score. The proportion of variance explained by each QTL ranged from 10.63 to 25.70% in non-stress and from 9.12 to 21.78% in stress conditions, respectively. In stress condition, the QTL of root yield was co-located with that of leaf scenecense score. Makers tightly linked with the major QTLs, especially the QTLs of root yield (qRY4s), leaf scenecense (qSen4s) and leaf wilt (qWilt4s), which could be exploited in marker-assisted selection programs for selection of superior drought tolerant lines and transfer of desirable alleles into improved varieties.