Grain size is one of the key agronomic traits that determine grain yield in crops. However, the mechanisms underlying grain size control in crops remain elusive. Here we demonstrate that the OsMKKK10-OsMKK4-OsMAPK6 signaling pathway positively regulates grain size and weight in rice. In rice, loss of OsMKKK10 function results in small and light grains, short panicles, and semi-dwarf plants, while overexpression of constitutively active OsMKKK10 (CA-OsMKKK10) results in large and heavy grains, long panicles, and tall plants. OsMKKK10 interacts with and phosphorylates OsMKK4. We identified an OsMKK4 gain-of-function mutant (large11-1D) that produces large and heavy grains. OsMKK4 encoded by the large11-1D allele has stronger kinase activity than OsMKK4. Plants overexpressing a constitutively active form of OsMKK4 (OsMKK4-DD) also produce large grains. Further biochemical and genetic analyses revealed that OsMKKK10, OsMKK4, and OsMAPK6 function in a common pathway to control grain size. Taken together, our study establishes an important genetic and molecular framework for OsMKKK10-OsMKK4-OsMAPK6 cascade-mediated control of grain size and weight in rice.

With global warming and climate change, breeding crop plants tolerant to high-temperature stress is of immense significance. tRNA 2-thiolation is a highly conserved form of tRNA modification among living organisms. Here, we report the identification of SLG1 (Slender Guy 1), which encodes the cytosolic tRNA 2-thiolation protein 2 (RCTU2) in rice. SLG1 plays a key role in the response of rice plants to high-temperature stress at both seedling and reproductive stages. Dysfunction of SLG1 results in plants with thermosensitive phenotype, while overexpression of SLG1 enhances the tolerance of plants to high temperature. SLG1 is differentiated between the two Asian cultivated rice subspecies, indica and japonica, and the variations at both promoter and coding regions lead to an increased level of thiolated tRNA and enhanced thermotolerance of indica rice varieties. Our results demonstrate that the allelic differentiation of SLG1 confers indica rice to high-temperature tolerance, and tRNA thiolation pathway might be a potential target in the next generation rice breeding for the warming globe.

Panicle size and grain number are important agronomic traits and influence grain yield in rice (Oryza sativa), but the molecular and genetic mechanisms underlying panicle size and grain number control remain largely unknown in crops. Here we report that LARGE2 encodes a HECT-domain E3 ubiquitin ligase OsUPL2 and regulates panicle size and grain number in rice. The loss of function large2 mutants produce large panicles with increased grain number, wide grains and leaves, and thick culms. LARGE2 regulates panicle size and grain number by repressing meristematic activity. LARGE2 is highly expressed in young panicles and grains. Biochemical analyses show that LARGE2 physically associates with ABERRANT PANICLE ORGANIZATION1 (APO1) and APO2, two positive regulators of panicle size and grain number, and modulates their stabilities. Genetic analyses support that LARGE2 functions with APO1 and APO2 in a common pathway to regulate panicle size and grain number. These findings reveal a novel genetic and molecular mechanism of the LARGE2-APO1/APO2 module-mediated control of panicle size and grain number in rice, suggesting that this module is a promising target for improving panicle size and grain number in crops.

Abstract:Simulating future land use/cover changes is of great importance for urban planners and decision-makers, especially in metropolitan areas, to maintain a sustainable environment. This study examines the changes in land use/cover in the Tokyo metropolitan area (TMA) from 2007 to 2017 as a first step in using supervised classification. Second, based on the map results, we predicted the expected patterns of change in 2027 and 2037 by employing a hybrid model composed of cellular automata and the Markov model. The next step was to decide the model inputs consisting of the modeling variables affecting the distribution of land use/cover in the study area, for instance distance to central business district (CBD) and distance to railways, in addition to the classified maps of 2007 and 2017. Finally, we considered three scenarios for simulating land use/cover changes: spontaneous, sub-region development, and green space improvement. Simulation results show varied patterns of change according to the different scenarios. The sub-region development scenario is the most promising because it balances between urban areas, resources, and green spaces. This study provides significant insight for planners about change trends in the TMA and future challenges that might be encountered to maintain a sustainable region.

No abstract

Alkaline salt stress adversely affects rice growth, productivity and grain quality. However, the mechanism underlying this process remains elusive. We characterized here an alkaline tolerant mutant, alt1 in rice. Map-based cloning revealed that alt1 harbors a mutation in a chromatin remodeling ATPase gene. ALT1-RNAi transgenic plants under different genetic background mimicked the alt1 phenotype, exhibiting tolerance to alkaline stress in a transcript dosage-dependent manner. The predicted ALT1 protein belonged to the Ris1 subgroup of the Snf2 family and was localized in the nucleus, and transcription of ALT1 was transiently suppressed after alkaline treatment. Although the absorption of several metal ions maintained well in the mutant under alkaline stress, expression level of the genes involved in metal ions homeostasis was not altered in the alt1 mutant. Classification of differentially expressed abiotic stress related genes, as revealed by microarray analysis, found that the majority (50/78) were involved in ROS production, ROS scavenging, and DNA repair. This finding was further confirmed by that alt1 exhibited lower levels of H2O2 under alkaline stress and tolerance to methyl viologen treatment. Taken together, these results suggest that ALT1 negatively functions in alkaline tolerance mainly through the defense against oxidative damage, and provide a potential two-step strategy for improving the tolerance of rice plants to alkaline stress.

Rapid urbanization is one of the most concerning issues in the 21st century because of its significant impacts on various fields, including agriculture, forestry, ecology, and climate. The urban heat island (UHI) phenomenon, highly related to the rapid urbanization, has attracted considerable attention from both academic scholars and governmental policymakers because of its direct influence on citizens’ daily life. Land surface temperature (LST) is a widely used indicator to assess the intensity of UHI significantly affected by the local land use/cover (LULC). In this study, we used the Landsat time-series data to derive the LULC composition and LST distribution maps of Nanjing in 2000, 2014, and 2018. A correlation analysis was carried out to check the relationship between LST and the density of each class of LULC. We found out that cropland and forest in Nanjing are helping to cool the city with different degrees of cooling effects depending on the location and LULC composition. Then, a Cellar Automata (CA)-Markov model was applied to predict the LULC conditions of Nanjing in 2030 and 2050. Based on the simulated LULC maps and the relationship between LST and LULC, we delineated high- and moderate-LST related risk areas in the city of Nanjing. Our findings are valuable for the local government to reorganize the future development zones in a way to control the urban climate environment and to keep a healthy social life within the city.

Forecasting landscape changes is vital for developing and implementing sustainable urban planning. Presently, apart from lowland coastal cities, mountain cities (i.e., hill stations) are also facing the negative impacts of rapid urbanization due to their economic and social importance. However, few studies are addressing urban landscape changes in hill stations in Asia. This study aims to examine and forecast landscape changes in the rapidly urbanizing hill station of Nuwara Eliya, Sri Lanka. Landsat data and geospatial techniques including support vector machines, urban–rural gradient, and statistical analysis were used to map and examine the land use/land cover (LULC) change in Nuwara Eliya during the 1996–2006 and 2006–2017 periods. The multilayer perceptron neural network-Markov model was applied to simulate future LULC changes for 2027 and 2037. The results show that Nuwara Eliya has been directly affected by rapid urban development. During the past 21 years (1996–2017), built-up areas increased by 1791 ha while agricultural land declined by 1919 ha due to augmented urban development pressure. The pressure of urban development on forest land has been relatively low, mainly due to strict conservation government policies. The results further show that the observed landscape changes will continue in a similar pattern in the future, confirming a significant increase and decrease of built-up and agricultural land, respectively, from 2017 to 2037. The changes in agricultural land exhibit a strong negative relationship with the changes in built-up land along the urban–rural gradient (R2 were 0.86 in 1996–2006, and 0.93 in 2006–2017, respectively). The observed LULC changes could negatively affect the production of unique upcountry agricultural products such as exotic vegetables, fruits, cut flowers, and world-famous Ceylon tea. Further, unplanned development could cause several environmental issues. The study is important for understanding future LULC changes and suggesting necessary remedial measures to minimize possible undesirable environmental and socioeconomic impacts.