An orchestrated ethylene-gibberellin signaling cascade contributes to mesocotyl elongation and emergence of rice direct seeding.

A mechanized direct seeding of rice with less labor and water usage, has been widely adopted. However, this approach requires varieties that exhibit uniform seedling emergence. Mesocotyl elongation (ME) offers the main drive of fast emergence of rice seedlings from soils; nevertheless, its genetic basis remains unknown. Here, we identify a major rice quantitative trait locus Mesocotyl Elongation1 (qME1), an allele of the Green Revolution gene Semi-Dwarf1 (SD1), encoding GA20-oxidase for gibberellin (GA) biosynthesis. ME1 expression is strongly induced by soil depth and ethylene. When rice grains are direct-seeded in soils, the ethylene core signaling factor OsEIL1 directly promotes ME1 transcription, accelerating bioactive GA biosynthesis. The GAs further degrade the DELLA protein SLENDER RICE 1 (SLR1), alleviating its inhibition of rice PHYTOCHROME-INTERACTING FACTOR-LIKE13 (OsPIL13) to activate the downstream expansion gene OsEXPA4 and ultimately promote rice seedling ME and emergence. The ancient traits of long mesocotyl and strong emergence ability in wild rice and landrace were gradually lost in company with the Green Revolution dwarf breeding process, and an elite ME1-R allele (D349H) is found in some modern Geng varieties (long mesocotyl lengths) in northern China, which can be used in the direct seeding and dwarf breeding of Geng varieties. Furthermore, the ectopic and high expression of ME1 driven by mesocotyl-specific promoters resulted in rice plants that could be direct-seeded without obvious plant architecture or yield penalties. Collectively, we reveal the molecular mechanism of rice ME, and provide useful information for breeding new Green Revolution varieties with long mesocotyl suitable for direct-seeding practice.

Localizing epileptogenic zones with high-frequency oscillations and directed connectivity.

PURPOSE: Precise localization of the epileptogenic zone (EZ) is essential for epilepsy surgery. Existing methods often fail to detect slow onset patterns or similar neural activities presented in the recorded signals. To address this issue, we propose a new measure to quantify epileptogenicity, i.e., the connectivity high-frequency epileptogenicity index (cHFEI). METHODS: The cHFEI method combines directed connectivity and high-frequency oscillations (HFOs) to measure the epileptogenicity of regions involved in a brain network. By applying this method to stereoelectroencephalography (SEEG) recordings of 49 seizures in 20 patients, we calculated the accuracy, sensitivity, and precision with a visually identified epileptogenic zone as a reference. The performance was evaluated by the confusion matrix and the area under the receiver operating characteristic (ROC) curve. RESULTS: Epileptic network estimation based on cHFEI successfully distinguished brain regions involved in seizure onset from the propagation network. Moreover, cHFEI outperformed other existing detection methods in the estimation of EZs in all patients, with an average area under the ROC curve of 0.88 and an accuracy of 0.85. CONCLUSIONS: cHFEI can characterize EZ in a robust manner despite various seizure onset patterns and has potential application in epilepsy therapy.