Comparison of Leaf Sheath Transcriptome Profiles with Physiological Traits of Bread Wheat Cultivars under Salinity Stress

Abstract

Salinity stress has significant negative effects on plant biomass production and crop yield. Salinity tolerance is controlled by complex systems of gene expression and ion transport. The relationship between specific features of mild salinity stress adaptation and gene expression was analyzed using four commercial varieties of bread wheat (Triticum aestivum) that have different levels of salinity tolerance. The high-throughput phenotyping system in The Plant Accelerator at the Australian Plant Phenomics Facility revealed variation in shoot relative growth rate and salinity tolerance among the four cultivars. Comparative analysis of gene expression in the leaf sheaths identified genes whose functions are potentially linked to shoot biomass development and salinity tolerance. Early responses to mild salinity stress through changes in gene expression have an influence on the acquisition of stress tolerance and improvement in biomass accumulation during the early "osmotic" phase of salinity stress. In addition, results revealed transcript profiles for the wheat cultivars that were different from those of usual stress-inducible genes, but were related to those of plant growth. These findings suggest that, in the process of breeding, selection of specific traits with various salinity stress-inducible genes in commercial bread wheat has led to adaptation to mild salinity conditions.

Fig 1. Sequential monitoring of shoot biomass under conditions of salinity stress.

Quantification of growth through time under conditions of salinity stress of (A) Berkut (blue diamonds, SE, n = 6), (B) Krichauff (orange triangles, SE, n = 6,), (C) Gladius (green squares, SE, n = 4) or (D) Drysdale (red circles, SE, n = 4). Cultivars were treated with RO water (open symbols) or 100 mM NaCl (filled symbols) at the emergence of the fourth leaf (vertical line indicates day 0 or day of treatment). Projected shoot area (pixels) was determined by image analysis from digital images taken with RGB cameras. Exponential curves were fitted to data from day 0 to day 7 after treatment (rectangle within graphs A to D) to calculate relative growth rates for (E) Berkut, (F) Krichauff, (G) Gladius and (H) Drysdale seedlings under control and saline conditions.

Fig 2. Relative growth rates (RGRs) of seedlings of Berkut, Krichauff, Gladius and Drysdale over 0 to 7 days grown with no added NaCl (circles) or treated with 100 mM NaCl (triangles).

(SE, n = 6 for Berkut and Krichauff, n = 4 for Gladius and Drysdale). RGRs of treated plants were significantly difference to RGRs of control plants (2 way ANOVA, p = 0.025).

Fig 3. Gene expression pattern for the four cultivars under control conditions.

(A) Venn diagrams showing a five-fold or greater difference in expression with all possible regressions during the first 3 days of growth under control conditions compared with the starting point (day 0) of the experiments. (B) Heat maps indicating intensity of gene expression in Berkut. Log FC = log₂ (the signal intensity under saline conditions / the signal intensity under control conditions). (C) Analysis of the gene ontology of 39 genes upregulated only in Berkut under control conditions. Functional categorizations by annotation were shown as gene ontology of biological process.

Fig 4. Venn diagram analyses of genes regulated in all four cultivars under salinity conditions (100 mM NaCl).

(A–C) Venn diagrams showing a five-fold or greater difference in expression at 1 (A), 2 (B) or 3 (C) days after NaCl treatment. Red numeric characters show the number of upregulated genes. Blue numeric characters show the number of downregulated genes.

Fig 5. Gene expression pattern for four cultivars under conditions of salinity stress.

(A) Venn diagrams showing a five-fold or greater difference in expression with all possible regressions under saline conditions (100 mM NaCl). Red numeric characters show the number of upregulated genes. Blue numeric characters show the number of downregulated genes. (B) Analysis of the gene ontology of 48 genes increased only in Krichauff under saline conditions. Functional categorizations by annotation were shown as gene ontology of biological process. (C) Analysis of the gene ontology of 21 genes increased only in Drysdale under saline conditions.

Fig 6. Comparative analysis of gene expression among regulated genes in Berkut under control conditions, in Krichauff under saline conditions and in Drysdale under saline conditions (100 mM NaCl).

(A) Venn diagrams show the comparative analysis of upregulated gene expression associated with each specific physiological trait. (B) Venn diagrams show the comparative analysis of downregulated gene expression associated with each specific physiological trait.