Identification of conserved drought-adaptive genes using a cross-species meta-analysis approach

Abstract

Background: Drought is the major environmental stress threatening crop-plant productivity worldwide. Identification of new genes and metabolic pathways involved in plant adaptation to progressive drought stress at the reproductive stage is of great interest for agricultural research.

Results: We developed a novel Cross-Species meta-Analysis of progressive Drought stress at the reproductive stage (CSA:Drought) to identify key drought adaptive genes and mechanisms and to test their evolutionary conservation. Empirically defined filtering criteria were used to facilitate a robust integration of 17 deposited microarray experiments (148 arrays) of Arabidopsis, rice, wheat and barley. By prioritizing consistency over intensity, our approach was able to identify 225 differentially expressed genes shared across studies and taxa. Gene ontology enrichment and pathway analyses classified the shared genes into functional categories involved predominantly in metabolic processes (e.g. amino acid and carbohydrate metabolism), regulatory function (e.g. protein degradation and transcription) and response to stimulus. We further investigated drought related cis-acting elements in the shared gene promoters, and the evolutionary conservation of shared genes. The universal nature of the identified drought-adaptive genes was further validated in a fifth species, Brachypodium distachyon that was not included in the meta-analysis. qPCR analysis of 27, randomly selected, shared orthologs showed similar expression pattern as was found by the CSA:Drought.In accordance, morpho-physiological characterization of progressive drought stress, in B. distachyon, highlighted the key role of osmotic adjustment as evolutionary conserved drought-adaptive mechanism.

Conclusions: Our CSA:Drought strategy highlights major drought-adaptive genes and metabolic pathways that were only partially, if at all, reported in the original studies included in the meta-analysis. These genes include a group of unclassified genes that could be involved in novel drought adaptation mechanisms. The identified shared genes can provide a useful resource for subsequent research to better understand the mechanisms involved in drought adaptation across-species and can serve as a potential set of molecular biomarkers for progressive drought experiments.

Figure 1

A schematic overview of the Cross-Species meta-Analysis of progressive Drought stress at the reproductive stage (CSA:Drought) approach. Following selection of relevant microarray drought stress studies, raw data, from each species, was integrated into separate datasets using rank product analysis. This statistical method generated lists of up- and down-regulated genes based on their expression (i.e. rank) across the individual experiments within each species. Significantly differentially expressed genes (DEGs), were used for intra-species analysis to retrieve enriched gene ontology (GO) terms and to classify genes into functional pathways. Next, DEGs within each species were transformed to rice orthologs and the penalized Fisher method was used to combine P-value distributions across species meta-analysis. Finally, the shared drought-adaptive DEGs were characterized and their universal nature was validated in a fifth species that was not included in the meta-analysis.

Figure 2

Within species microarray meta-analysis. (A) Expression profiles of significantly differentially expressed genes in each species based on the rank product analysis. Length of heatmap is proportional to number of probe-sets. Unique and common (B) up- and (C) down-regulated gene ontology biological processes (FDR ≤ 0.05) based on significantly differentially expressed genes within each species. Unique and common (D) up- and (E) down-regulated orthologs (FDR ≤ 0.05).

Figure 3

Functional classification of shared drought-adaptive DEGs based on MapMan and BLAST2GO annotations.

Figure 4

Conservation analysis. (A) Hierarchal clustering of pair-wise distance matrix based on expression profile of orthologs in each species. Bootstrap scores supporting the consensus tree (percentage) are indicated at each node. (B) Sequence conservation of shared DEGs versus species-specific DEGs. For each species, the bit score, obtained from the permutated blastn analysis, was compared between shared DEGs and species-specific DEGs. Bold horizontal bars indicate the average, boxes indicate the upper and lower 0.25 quartile, dashed bars indicate the max/min scores (excluding extremes), circles indicate the extremes, and notch overlaps indicate non-significant differences (P ≤ 0.05).

Figure 5

Brachypodium distachyon as a case study to validate the shared DEGs detected by CSA:Drought. (A) Plants grown under control and drought conditions. (B) Spike morphology, (C) Roots biomass, (D) Culm length, (E) Total biomass, (F) Spike weight, (G) Transformed chlorophyll absorbance in reflectance (TCAR) index, (H) Osmotic potential, and (I) Relative water content (RWC) under control and drought conditions. Values are mean ± SD (n = 5). *, ** and *** indicate significant differences between treatments at P ≤ 0.05, 0.01 and 0.001, respectively.

Figure 6

Heat-map of selected drought-adaptive genes detected by CSA:Drought and validated by qPCR analysis in Brachypodium distachyon. Red and blue represent high and low relative expression when compared to the mean value of expression across all samples, respectively. Scale is log₂ of mean expression value. qPCR values, representing mean ± SD (n = 6), were calculated and normalized using Glyceraldehyde 3-phosphate dehydrogenase and S-adenosylmethionine decarboxylase as internal controls and presented as fold-change (P ≤ 0.05). (A) Carbohydrate metabolism: GBSS1, Granule-bound starch synthase 1; BAM1, β-Amylase 1; TPP, Trehalose-6-phosphate phosphatase; INV-E, Alkaline/neutral invertase E; HXK1, Hexokinase 1; GOLS1, Galactinol synthase 1. (B) Amino acid metabolism: HGO, Homogentisate 1,2-dioxygenase; P5CS1, Delta1-pyrroline-5-carboxylate synthetase; DAHPS, 3-Deoxy-D-arabino-heptulosonate 7-phosphate synthase; AK1, Aspartate kinase 1. (C) Protein degradation: ERD1, Early responsive to dehydration 1; SCPL49, Serine carboxypeptidase-like 49. (D) Hormone metabolism and transcription factors: ABF4, ABRE binding factor 4; SnRK2.4, SNF1-related kinase 2.4; GA20ox2, Gibberellin 20 oxidase 2; NAC1, NAC domain containing protein 1. (E) Unknown and unclassified: LEA3, Late embryogenesis abundant protein, group 3. ^§ indicates significant differences of qPCR analysis at P ≤ 0.1. Fold change values and statistical analysis for each gene can be found in Additional file 13: Figure S6.