Monosaccharide transporter OsMST6 is activated by transcription factor OsERF120 to enhance chilling tolerance in rice seedlings

Chilling stress caused by extreme weather is threatening global rice (Oryza sativa L.) production. Identifying components of the signal transduction pathways underlying chilling tolerance in rice would advance molecular breeding. Here, we report that OsMST6, which encodes a monosaccharide transporter, positively regulates the chilling tolerance of rice seedlings. The mst6 mutants showed hypersensitivity to chilling, while the OsMST6 overexpression lines were tolerant. During chilling stress, OsMST6 transported more glucose into cells to modulate sugar and ABA signal pathways. We showed that the transcription factor OsERF120 could bind to the DRE/CRT element of the OsMST6 promoter and activate the expression of OsMST6 to positively regulate chilling tolerance. Genetically, OsERF120 was functionally dependent on OsMST6 when promoting chilling tolerance. In summary, OsERF120 and OsMST6 form a new downstream chilling regulatory pathway in rice in response to chilling stress, providing valuable findings for molecular breeding aimed at achieving global food security.

The stored data is the analysis results of transcriptome data from ZH11 and mst6-1 after 0 hours and 4 hours of chilling treatment. These data form the basis for the transcriptome data visualization in the article.

Methods
The 14-day-old rice seedlings of ZH11 and mst6-1, incubated in the greenhouse with 28 °C/25 °C (10 h day/14 h night) cycles in Kimura B nutrient solution, were treated for 0 h and 4 h at 4 °C, and the whole seedlings were sampled for transcriptome sequencing with three biological replicates. 

RNA-seq was performed at Anoroad Genome (Beijing, China). Clean reads were mapped referring to the rice genome (Oryza sativa IRGSP-1.0.38), using HISAT2 (Sirén et al., 2014) with default parameters. The significant differentially expressed genes were determined using DESeq2 with |Fold change| ≥2, adjusted P value <0.05. Gene ontology (GO) analysis was performed using DAVID.