Salt tolerance involved candidate genes in rice: an integrative meta-analysis approach

Abstract

Background: Salinity, as one of the main abiotic stresses, critically threatens growth and fertility of main food crops including rice in the world. To get insight into the molecular mechanisms by which tolerant genotypes responds to the salinity stress, we propose an integrative meta-analysis approach to find the key genes involved in salinity tolerance. Herein, a genome-wide meta-analysis, using microarray and RNA-seq data was conducted which resulted in the identification of differentially expressed genes (DEGs) under salinity stress at tolerant rice genotypes. DEGs were then confirmed by meta-QTL analysis and literature review.

Results: A total of 3449 DEGs were detected in 46 meta-QTL positions, among which 1286, 86, 1729 and 348 DEGs were observed in root, shoot, seedling, and leaves tissues, respectively. Moreover, functional annotation of DEGs located in the meta-QTLs suggested some involved biological processes (e.g., ion transport, regulation of transcription, cell wall organization and modification as well as response to stress) and molecular function terms (e.g., transporter activity, transcription factor activity and oxidoreductase activity). Remarkably, 23 potential candidate genes were detected in Saltol and hotspot-regions overlying original QTLs for both yield components and ion homeostasis traits; among which, there were many unreported salinity-responsive genes. Some promising candidate genes were detected such as pectinesterase, peroxidase, transcription regulator, high-affinity potassium transporter, cell wall organization, protein serine/threonine phosphatase, and CBS domain cotaining protein.

Conclusions: The obtained results indicated that, the salt tolerant genotypes use qualified mechanisms particularly in sensing and signalling of the salt stress, regulation of transcription, ionic homeostasis, and Reactive Oxygen Species (ROS) scavenging in response to the salt stress.

Keywords: Meta- analysis; Microarray; Oryza sativa; QTLs; RNA-seq; Salinity stress.

Fig. 1

Meta-QTL positions for traits associated with the salt tolerance (Table S1) on 12 chromosomes of rice. Vertical lines on the left of the chromosomes show the confidence interval of each QTL. Marker names and positions (in cM on the consensus map) are indicated on the left. The colors indicate Meta-QTL positions for traits associated with the salt tolerance

Fig. 2

The results of comparison between differentially expressed genes under salt stress conditions in the tolerant genotypes revealed by RNA-Seq and microarray data analysis, or through literature review in (a) root, (b) shoot, (c) seedling and (d) leaves

Fig. 3

The number of differentially expressed genes identified by RNA-Seq and microarray data analysis, or through literature review, which are located on the meta-QTL positions in each tissue (roots, shoots, seedlings, and leaves)

Fig. 4

Flowchart showing different steps of meta-analysis pipeline used to identify the promising candidate genes involved in the salinity tolerance. The differentially expressed genes detected by more than one approach called common genes in this manuscript. To find the potential candidate genes, the common genes were sought in the salinity tolerance associated meta-QTLs regions. The potential candidate genes that were located on hotspot-regions overlying original QTLs for both yield components and ion homeostasis traits were assumed as promising candidate genes

Fig. 5

Validation of selected genes using qRT-PCR in root and shoot tissues of FL478 (tolerant genotype). Bar graphs depict the relative transcript abundance of the selected potential candidate genes in FL478 under different conditions. Data points are represented as log2 fold change values

Fig. 6

The schematic representation of the molecular response to salt stress in the tolerant genotypes. Some candidates are depicted, whose coding gene was differentially expressed under the salt stress conditions located on the meta-QTLs