Comprehensive transcriptome profiling of soybean leaves in response to simulated acid rain

Abstract

As a source of edible oil and protein, soybean is a major globally important economic crop; Improving its production has been an important objective of soybean breeding. Acid rain has been shown to influence soybean growth and productivity, with consequent adverse impacts on its production for use by human populations. In this study, RNA sequencing technology was utilized to examine changes in gene expression when soybean was exposed to simulated acid rain (SAR). We sampled soybean leaves at five time intervals (0, 6, 30, 54, 78, and 102 h), and built the cDNA library. In total, 54,175 expression genes were found, including 2016 genes with differential expression. A total of 416 genes were considered, as they were closely related to the response to SAR. Genes related to the regulation of sulfur and nitrogen metabolism, carbohydrate metabolism, photosynthesis, and reactive oxygen species were among those differentially expressed in response to SAR. In this study, we examined the response mechanisms of soybean under SAR exposure. Our findings will improve our understanding of the molecular mechanisms employed by soybean in responding to abiotic stress, and therefore provides important information in developing soybean breeding to improve tolerance to these stresses.