Tomato Genotype-specific Biomarkers under Salinity Stress

Monday, July 22, 2013
Desert Ballroom: Salons 7-8 (Desert Springs J.W Marriott Resort )
Monther Sadder , King Saud University, Riyadh, Saudi Arabia
Abdulla A. Alsadon , King Saud University, Riyadh 11451, Saudi Arabia
Mahmouad Wahb-Allah , King Saud University, Riyadh, Saudi Arabia
Salinity stress is increasing becoming an important research domain. The development of improved salt tolerant crops is urgently needed to face limitation in water resources, salinity accumulation in irrigated soils, and agricultural expansion to marginal areas. In this study, the expression profiles were investigated for three advanced tomato lines (salinity susceptible genotype L46, salinity tolerant genotype L56, and salinity intermediate genotype L66) and one salinity tolerant genotype as reference (BL 1076). The generated data were analyzed in a way to pinpoint genotype-specific biomarkers. Genotype L56 revealed prominent over-expression of major unique gene cluster over other genotypes under salinity stress, which include AP2 erf domain-containing transcription factor (Pti5), NAC domain protein, calmodulin binding, and osmotin-like protein with 422.6, 59.7, 45.8, and 45.1 fold, respectively. The LesAffx.70722.1.S1 (type-a response regulator) was found to be expressed mainly in root and hypocotyl, while Les.4483.1.S1 (NAC domain protein) was found to be expressed mainly in cotyledon and fruit. Two tomato responsive genes were found to be unique based on phylogenetic analysis. The tomato genes encoding xyloglucan endotransglucosylase-hydrolase XTH3 and salt responsive protein 1 did not cluster with any formed clade of related plant homologs. The revealed salinity stress biomarkers can be either beneficial or damaging to the stressed  plant. Beneficial biomarkers are desired as they are part of tolerance mechanism against the salinity stress. The damaging biomarkers are undesired as they accelerate plant senesces and reduce growth. Both biomarkers can be implemented in the breeding program, where one can select for the beneficial over the damaging ones. Thereafter, the beneficial biomarkers can be combined in one line by crossing and further selection.