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您的检索式：作者名="Subramanian Sankaranarayanan"
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| 1 | Stigma Receptivity Is Controlled by Functionally Redundant MAPK Pathway Components in Arabidopsis显示文摘In angiosperms,the process of pollination relies on species-specific interaction and signaling between the male(pollen)and female(pistil)counterparts where the interplay between several pollen and stigma proteins decides the fate of the pollen.In Brassicaceae,the dry stigmatic papillary cells control pollen germination by releasing resources only to compatible pollen thereby allowing pollen to hydrate and germinate.Despite the identification of a number of stigmatic proteins that facilitate pollination responses,the signaling mechanisms that regulate functions of these proteins have remained unknown.Here,we show that,in Arabidopsis,an extremely functionally redundant mitogen-activated protein kinase(MAPK)cascade is required for maintaining stigma receptivity to accept compatible pollen.Our genetic analyses demonstrate that in stigmas,five MAPK kinases(MKKs),MKK1/2/3/7/9 are required to transmit upstream signals to two MPKs,MPK3/4,to mediate compatible pollination.Compromised functions of these five MKKs in the quintuple mutant(mkk1/2/3RNAi/mkk7/9)phenocopied pollination defects observed in the m pk4RNAi/m pk3 double mutant.We further show that this MAPK nexus converges on Exo70A1,a previously identified stigma receptivity factor essential for pollination.Given that pollination is the crucial initial step during plant reproduction,understanding the mechanisms that govern successful pollination could lead to development of strategies to improve crop yield. | Muhammad Jamshed Subramanian Sankaranarayanan Kumar Abhinandan Marcus A.Samuel | 2020 | Molecular Plant2020，13，11： | 3 |
| 2 | AutoPhaseNN:unsupervised physics-aware deep learning of 3D nanoscale Bragg coherent diffraction imaging显示文摘The problem of phase retrieval underlies various imaging methods from astronomy to nanoscale imaging.Traditional phase retrieval methods are iterative and are therefore computationally expensive.Deep learning(DL)models have been developed to either provide learned priors or completely replace phase retrieval.However,such models require vast amounts of labeled data,which can only be obtained through simulation or performing computationally prohibitive phase retrieval on experimental datasets.Using 3D X-ray Bragg coherent diffraction imaging(BCDI)as a representative technique,we demonstrate AutoPhaseNN,a DL-based approach which learns to solve the phase problem without labeled data.By incorporating the imaging physics into the DL model during training,AutoPhaseNN learns to invert 3D BCDI data in a single shot without ever being shown real space images.Once trained,AutoPhaseNN can be effectively used in the 3D BCDI data inversion about 100×faster than iterative phase retrieval methods while providing comparable image quality. | Yudong Yao Henry Chan Subramanian Sankaranarayanan Prasanna Balaprakash Ross J.Harder Mathew J.Cherukara | 2022 | npj Computational Materials2022，，1： | 1 |
| 3 | Deciphering the Stigmatic Transcriptional Landscape of Compatible and Self-Incompatible Pollinations in Brassica napus Reveals a Rapid Stigma Senescence Response Following Compatible Pollination显示文摘 | Subramanian Sankaranarayanan Muhammad Jamshed Srijani Deb Kate Chatfield-Reed Eun-Joo Gina Kwon Gordon Chua Marcus A. Samuel | 2013 | Molecular Plant2013，6，6： | 1 |
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