Genome-Wide Identification and Characterization of the Soybean DEAD-Box Gene Family and Expression Response to Rhizobia

Abstract

DEAD-box proteins are a large family of RNA helicases that play important roles in almost all cellular RNA processes in model plants. However, little is known about this family of proteins in crops such as soybean. Here, we identified 80 DEAD-box family genes in the Glycine max (soybean) genome. These DEAD-box genes were distributed on 19 chromosomes, and some genes were clustered together. The majority of DEAD-box family proteins were highly conserved in Arabidopsis and soybean, but Glyma.08G231300 and Glyma.14G115100 were specific to soybean. The promoters of these DEAD-box genes share cis-acting elements involved in plant responses to MeJA, salicylic acid (SA), low temperature and biotic as well as abiotic stresses; interestingly, half of the genes contain nodulation-related cis elements in their promoters. Microarray data analysis revealed that the DEAD-box genes were differentially expressed in the root and nodule. Notably, 31 genes were induced by rhizobia and/or were highly expressed in the nodule. Real-time quantitative PCR analysis validated the expression patterns of some DEAD-box genes, and among them, Glyma.08G231300 and Glyma.14G115100 were induced by rhizobia in root hair. Thus, we provide a comprehensive view of the DEAD-box family genes in soybean and highlight the crucial role of these genes in symbiotic nodulation.

Keywords: DEAD-box RNA helicases; Glycine max; nodulation; phylogenetic analysis; rhizobia.

Figure 1

The chromosome distribution of the DDX genes.

Figure 2

Phylogenetic tree of DDX proteins in Arabidopsis thaliana and soybean. Tree constructed with 1000 bootstrap replications. DDX proteins from Arabidopsis and soybean distinguished using blue and red, respectively. Proteins from different clusters (I–XV) were indicated with different color zones. Green stars at XIV indicate the soybean-specific DDX proteins.

Figure 3

The structures and motif compositions of DDX genes and proteins. (A) Phylogenetic tree and classification of DDX proteins was constructed by MEGA. (B) Gene structures of DDX genes. The yellow boxes, black lines and blue boxes represent the CDS, intron and upstream/downstream. (C) Twelve conserved motif compositions of DDX proteins were identified using MEME. Each color represents a specific motif.

Figure 4

Predicted cis elements in the promoter regions of DDX genes. (A) Predicted cis elements of all DDX genes. (B) Predicted nodule-specific cis elements of 49 DDX genes. (C) Predicted cis elements of two soybean specific DDX genes. The scale bars at the bottom indicate the lengths of the promoter sequences. Color boxes indicate cis elements in the promoter regions.

Figure 5

Expression analysis of DDX genes in the root and nodule, and their response to rhizobium. A heat map with clustering was created based on the RPKM value of 80 DDX genes of soybean. (A) Expression patterns of DDX genes in the root and nodule. (B) Expression patterns of DDX genes’ response to rhizobium in root hair at 12 and 24 h after inoculation (HAI). The colored scale varies from green to red, which indicates low or high levels of gene expression. Root hair 12 HAImock/Root hair 24 HAImock and Root hair 12 HAI/Root hair 24 HAI indicate root hairs at 12 h/24 h after inoculation without and with rhizobia, respectively.

Figure 6

Expression profiles of DDX genes in the root and nodule, and their response to rhizobium. (A) Expression patterns of selected DDX genes in the root and nodule were examined by a qPCR assay. (B) Expression patterns of selected DDX genes in response to rhizobium in root hair were examined by a qPCR assay at 24 HAI. Data were the most representative of three biological replicates. The GmELF1b gene was used as an internal control. Root hair 24 HAImock and Root hair 24 HAI indicate root hairs at 24 h after inoculation without and with rhizobia, respectively. A Student’s t-test tested the significance of the difference between two groups. * p < 0.05. ** p < 0.01. *** p < 0.001.