Genome-wide identification of phosphate-deficiency-responsive genes in soybean roots by high-throughput sequencing

Abstract

Soybean is an important food crop as well as a promising energy source. Because soybean is self-sufficient in nitrogen, phosphorus, in the orthophosphate form (Pi), becomes the most limiting macronutrient affecting the growth and productivity of soybean, especially in acidic and alkaline soils. It has been documented that plants have developed a series of physiological and biochemical strategies to adapt to Pi deficiency, but the mechanistic details of soybean response to Pi deficiency, especially those at the molecular level, are largely unknown. In this study, we aim to understand how soybean plants respond to Pi deficiency in soils by identifying and analysing Pi-responsive genes in the roots of soybean at the whole-genome scale. The transcriptome in soybean roots under Pi-deficiency was analyzed using the Illumina’s digital gene expression (DGE) high-throughput sequencing platforms, and the expression profiles of arbitrarily selected Pi-responsive genes identified in the current research were validated by quantitative RT-PCR. A total of 1612 genes were found to be differentially expressed in soybean roots after Pi deficiency for seven days; 727 genes were up-regulated, and 885 genes were down-regulated. Gene ontology (GO) enrichment analysis showed that 17 GO terms of biological processes were significantly enriched including photosynthesis, iron ion transport, dUTP metabolism, cell wall organization, fatty acid metabolism and stress responses. Genes possibly involved in regulating Pi homeostasis, nutrient uptake and transport, homeostasis control of reactive oxygen species, calcium signaling, hormonal signaling and gene transcription were included in the differentially expressed genes. Quantitative RT-PCR was used to analyze the expression of 30 arbitrarily selected genes and 29 of them were confirmed to exhibit similar differential expression patterns under Pi deficiency as revealed by the high throughput DGE sequencing. These results provide useful information for identifying and characterizing important components in the Pi signaling network in soybean and enhance understanding of the molecular mechanisms by which plants adapt to low Pi stress.