Plant-specific GRAS transcription factors play important roles in regulating growth, development, and stress responses. Castor beans (Ricinus communis) are important non-edible oilseed plants, cultivated worldwide for its seed oils and its adaptability to growth conditions. In this study, we identified and characterized a total of 48 GRAS genes based on the castor bean genome. Combined with phylogenetic analysis, the castor bean GRAS members were divided into 13 distinct groups. Functional divergence analysis revealed the presence of mostly Type-I functional divergence. The gene structures and conserved motifs, both within and outside the GRAS domain, were characterized. Gene expression analysis, performed in various tissues and under a range of abiotic stress conditions, uncovered the potential functions of GRAS members in regulating plant growth development and stress responses. The results obtained from this study provide valuable information toward understanding the potential molecular mechanisms of GRAS proteins in castor beans. These findings also serve as a resource for identifying the genes that allow castor beans to grow in stressful conditions and to enable further breeding and genetic improvements in agriculture.

Global localization is essential for robot navigation, of which the first step is to retrieve a query from the map database. This problem is called place recognition. In recent years, LiDAR scan based place recognition has drawn attention as it is robust against the environmental change. In this paper, we propose a LiDAR-based place recognition method, named Differentiable Scan Context with Orientation (DiSCO), which simultaneously finds the scan at a similar place and estimates their relative orientation. The orientation can further be used as the initial value for the down-stream local optimal metric pose estimation, improving the pose estimation especially when a large orientation between the current scan and retrieved scan exists. Our key idea is to transform the feature learning into the frequency domain. We utilize the magnitude of the spectrum as the place signature, which is theoretically rotation-invariant. In addition, based on the differentiable phase correlation, we can efficiently estimate the global optimal relative orientation using the spectrum. With such structural constraints, the network can be learned in an end-to-end manner, and the backbone is fully shared by the two tasks, achieving interpretability and light weight. Finally, DiSCO is validated on the NCLT and Oxford datasets with long-term outdoor conditions, showing better performance than the compared methods. 1

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Isoprenoids are among the largest and most chemically diverse classes of organic compounds in nature and are involved in the processes of photosynthesis, respiration, growth, development, and plant responses to stress. The basic building block units for isoprenoid synthesis—isopentenyl diphosphate and its isomer dimethylallyl diphosphate—are generated by the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways. Here, we summarize recent advances on the roles of the MEP and MVA pathways in plant growth, development and stress responses, and attempt to define the underlying gene networks that orchestrate the MEP and MVA pathways in response to developmental or environmental cues. Through phylogenomic analysis, we also provide a new perspective on the evolution of the plant isoprenoid pathway. We conclude that the presence of the MVA pathway in plants may be associated with the transition from aquatic to subaerial and terrestrial environments, as lineages for its core components are absent in green algae. The emergence of the MVA pathway has acted as a key evolutionary event in plants that facilitated land colonization and subsequent embryo development, as well as adaptation to new and varied environments.