Mapping QTLs associated with salt tolerance indices in sunflower (Helianthus annuus L.) genome

Salinity is one of the most important abiotic stresses that has a negative effect on the growth and productivity of plants cultivated around the world by reducing soil fertility. Unfortunately, due to inefficient irrigation management of agricultural fields, high exploitation of agricultural soil and rising ground-water levels, the area affected by soil salinity is increasing every year. For utility of lands affected by salinity or using salty water resources, identification and selection of salt tolerant genotypes are important. Sunflower botanically is a dicotyledonous, annual, monoicous plant from North America. The plant is often cultivated for its edible oil. Different criteria are proposed for selecting genotypes on the basis of their appearance in stress or non-stress environments. In general, a criterion is considered as the best index for determining drought tolerance genotypes when it is highly correlated with plant performance in both normal and stress conditions. In such a case this index is able to identify genotypes with high performance in both environments. Since for calculating tolerance indices need to evaluate genotypes in both normal and stress conditions; by identifying molecular markers associated with tolerance indices, it will be possible to select tolerant genotypes in normal conditions at seedling stage. The aim of this research is to identify molecular markers associated with salt tolerance indices in order to use them in sunflowers salt tolerance breeding programs.
In this study, 59 recombinant inbred lines (F9) of sunflower coming from the cross between PAC2 (maternal) × RHA266 (paternal) accompanied with their parental lines were evaluated in both normal and salt stress conditions. The factorial experiment was conducted in completely randomized design with three replications in Urmia University. Several tolerance indices including mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), stress tolerance index (STI), yield stability index (YSI) and tolerance index (TOL) were calculated based on yield performance under normal and salt stress conditions. In order to identify molecular markers associated with salt tolerance indices, a genetic linkage map including 210 SSR and 11 SNP markers on 17 linkages groups with average distance of 7.44 CM between marker pairs were used. Identification of QTLs linked to tolerance indices was performed by QGene software via composite interval mapping method (CIM).
Considering simple correlation results, high correlation was observed between yield under normal and salinity conditions with mean productivity, geometric mean productivity and harmonic mean. So, these indices are introduced as the most appropriate measures to identify sunflower lines tolerant to salinity stress. Based on three dimensional plots constructed by yield in normal and salt stress conditions and each one of appropriate indicators (GMP, MP and HM), lines such as C86, C61, C142, C134a, C62, C70a, LR1, C153, C108, C6, C106, C98b and C148 are considered as salt tolerant lines. In QTL analysis, totally 5 QTLs was identified significantly associated with salt tolerance indices. The results indicate co-localization of the identified QTLs for GMP, MP and HM in linkage group 14 with QTL identified for grain yield under salt stress conditions.
The results support the phenotypic correlations observed between grain yield and salt tolerance indices. After validation and fine mapping of genomic regions associated with salt tolerance indices, they can be used for MAS (marker-assisted selection) in sunflower breeding programs. This leads to increase the efficiency of traditional breeding methods.