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Jasmonates (JAs) regulate plant growth and defense responses. On perception of bioactive JAs, the JA receptor CORONATINE INSENSITIVE1 (COI1) recruits JA ZIM-domain (JAZ) proteins for degradation, and JAZ-targeted transcription factors are released to regulate JA responses. The subgroup IIId bHLH transcriptional factors, including bHLH17, bHLH13, bHLH3, and bHLH14, interact with JAZs and repress JA responses. In this study, we show that IIId bHLH factors form dimers via the C-terminus in yeast. N-terminus of bHLH13 is essential for its transcriptional repression function. bHLH13 overexpression inhibits Arabidopsis resistance to the necrotrophic fungi Botrytis cinerea and defense against the insect Spodoptera exigua . COI1 mutation disrupts the oversensitivity of the quadruple mutant bhlh3 bhlh13 bhlh14 bhlh17 in various JA responses, including anthocyanin accumulation, root growth inhibition, and defense against B cinerea and S exigua . Disruption of the TTG1/bHLH/MYB complex blocks anthocyanin accumulation of bhlh3 bhlh13 bhlh14 bhlh17 , whereas abolishment of MYC2 attenuates JA-inhibitory root growth of bhlh3 bhlh13 bhlh14 bhlh17 . These results genetically demonstrate that IIId bHLH factors function downstream of COI1 to inhibit distinctive JA responses via antagonizing different transcriptional activators.

In order to realize intelligent and autonomous navigation, a bio-inspired method of autonomous positioning using spatial association based on place cells firing is proposed. First, a vision sensor is used to get the landmarks in the environment and the distances between the agent and the different landmarks so as to construct an internal map of place cells. Then, we build a relationship between the distances and the activities of place cells using a radial basis function neural network, and further achieve the memory and association of spatial locations by comparing the activities of all place cells. Finally, we also provide a detailed analysis on the feasibility of this method for autonomous positioning and how the involved parameters in the model have an influence on the performance of positioning. The result of simulation shows that the method presented is effective and feasible for autonomous positioning.