Transcriptome profiling revealed diverse gene expression patterns in poplar (Populus × euramericana) under different planting densities

• DOI: 10.1371/journal.pone.0217066
• Publication Date: 2019-05-29T17:31:01Z
• Authors: Kun Ning; Changjun Ding; Qinjun Huang; Weixi Zhang; Chengchao Yang; Dejun Liang; Ruting Fan; Xiaohua Su
• Keywords: Population Density; 0301 basic medicine; 2. Zero hunger; Science; Gene Expression Profiling; Q; R; 15. Life on land; 03 medical and health sciences; Populus; Gene Expression Regulation, Plant; Medicine; Transcriptome; Research Article; Plant Proteins

Certain plant genotypes can achieve optimal growth under appropriate environmental conditions. Under high planting density conditions, plants undergo competition for uptake and utilization of light and nutrients. However, the relationship between whole-genome expression patterns and the planting density in perennial woody plants remains unknown. In this study, whole-genome RNA sequencing of poplar (Populus × euramericana) was carried out at three different sampling heights to determine gene expression patterns under high (HD) and low (LD) planting densities. As a result, 4,004 differentially expressed genes (DEGs) were detected between HD and LD, of which 2,300, 701, and 1,003 were detected at the three positions, upper, middle and bottom, respectively. Function annotation results further revealed that a large number of the DEGs were involved in distinct biological functions. There were significant changes in the expression of metabolism-related and stimulus-related genes in response to planting density. There were 37 DEGs that were found at all three positions and were subsequently screened. Several DEGs related to plant light responses and photosynthesis were observed at different positions. Meanwhile, numbers of genes related to auxin/indole-3-acetic acid, and carbon and nitrogen metabolism were also revealed, displaying overall trends of upregulation under HD. These findings provide a basis for identifying candidate genes related to planting density and could increase our molecular understanding of the effect of planting density on gene expression.