Abstract
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;never-theless,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-Dwarf 1(SD1),en-coding GA20-oxidase for gibberellin(GA)bio-synthesis.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 tran-scription,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 pro-mote rice seedling ME and emergence.The an-cient traits of long mesocotyl and strong emer-gence ability in wild rice and landrace were gradually lost in company with the Green Revo-lution 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.Fur-thermore,the ectopic and high expression of ME1 driven by mesocotyl-specific promoters re-sulted in rice plants that could be direct-seeded without obvious plant architecture or yield pen-alties.Collectively,we reveal the molecular mechanism of rice ME,and provide useful in-formation for breeding new Green Revolution varieties with long mesocotyl suitable for direct-seeding practice.
基金项目
National Natural Science Foundation of China(32188102)
National Natural Science Foundation of China(32101763)
Zhejiang Provincial Science and Technology Project(2020R51007)
Key Research and Development Program of Zhejiang province(2022C02011)
Innovation Program of Chinese Academy of Agricultural Sciences(CAAS-CACB-202402)
万方数据