OsNF-YB7 inactivates OsGLK1 to inhibit chlorophyll biosynthesis in rice embryo.

As a master regulator of seed development, Leafy Cotyledon 1 (LEC1) promotes chlorophyll (Chl) biosynthesis in Arabidopsis, but the mechanism underlying this remains poorly understood. Here, we found that loss of function of OsNF-YB7, a LEC1 homolog of rice, leads to chlorophyllous embryo, indicating that OsNF-YB7 plays an opposite role in Chl biosynthesis in rice compared with that in Arabidopsis. OsNF-YB7 regulates the expression of a group of genes responsible for Chl biosynthesis and photosynthesis by directly binding to their promoters. In addition, OsNF-YB7 interacts with Golden 2-Like 1 (OsGLK1) to inhibit the transactivation activity of OsGLK1, a key regulator of Chl biosynthesis. Moreover, OsNF-YB7 can directly repress OsGLK1 expression by recognizing its promoter in vivo, indicating the involvement of OsNF-YB7 in multiple regulatory layers of Chl biosynthesis in rice embryo. We propose that OsNF-YB7 functions as a transcriptional repressor to regulate Chl biosynthesis in rice embryo.

Effect of agricultural soil wind erosion on urban PM2.5 concentrations simulated by WRF-Chem and WEPS: A case study in Kaifeng, China.

Dust emission induced by agricultural soil wind erosion is one of the main sources of atmospheric particulate matter (PM) in dryland areas. However, most current air quality models do not consider this emission source, resulting in large uncertainties in PM simulations. Here we estimated the agricultural PM2.5 (particulate matter with an aerodynamic diameter <2.5 µm) emission around Kaifeng, a prefecture-level city in central China, using the Wind Erosion Prediction System (WEPS), with the MEIC (Multi-resolution Emission Inventory for China) as an anthropogenic emission source. We then plugged these estimates into the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an air pollution episode in Kaifeng, China. Results showed that the addition of agricultural soil PM2.5 emissions significantly improved the ability of WRF-Chem to accurately simulate PM2.5 concentrations. The PM2.5 concentration mean bias and correlation coefficient of not considered and considered agricultural dust emission were -72.35 µg m-|3 and 3.31 µg m-|3 and 0.3 and 0.58, respectively. The PM2.5 emitted by the agricultural soil wind erosion contributed around 37.79% of the PM2.5 in the Kaifeng municipal district during this pollution episode. This study confirmed that the dust emission caused by agricultural soil wind erosion can significantly impact urban PM2.5 concentrations which surrounded by large areas of farmland, and also indicated that coupling dust emissions from farmland with anthropogenic air pollutant emissions can improve the accuracy of air quality models.