Brassinosteroid insensitive 1 (BRI1) is a multidomain plant leucine-rich repeat receptor-like kinase (LRR-RLK), belongs to the LRR X subfamily. BRI1 perceives plant hormone brassinosteroids (BRs) through its extracellular domain that constitutes of LRRs interrupted by a 70 amino acid residue island domain (ID), which activates the kinase domain (KD) in its intracellular domain to trigger BR response. Thus, the KD and the ID of BRI1 are highly conserved and greatly contribute to BR functions. In fact, most bri1 mutants are clustered in or surrounded around the ID and the KD. However, the role of the less conserved LRR domains, particularly the first few LRRs after the signal peptide, is elusive. Here, we report the identification of a loss-of-function mutant bri1-235 that carries a mutation in the less conserved fourth LRR of BRI1 extracellular domain in Arabidopsis. This mutant had a base alteration from C to T, resulting in an amino acid substitution from serine to phenylalanine at the 156th position of BRI1. Compared with the wild-type plants, bri1-235 exhibited round leaves, prolonged life span, shorter stature, and approximately normal fertility under light conditions. The bri1-235 mutant was less sensitive to exogenous brassinolide under normal conditions. Importantly, both wild-type BRI1 expression and a sbi1 mutant that activates BRI1 rescued bri1-235 and resembled the wild type. Furthermore, bri1-235 protein was localized in endoplasmic reticulum rather than plasma membrane, suggestive of a cause for reducing BR sensitive in bri1-235 . Taken together, our findings provide an insight into the role of the less conserved LRRs of BRI1, shedding light on the role of LRRs in a variety of LRR-RLKs that control numerous processes of plant growth, development, and stress response.

Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large‐scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change.

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