Embracing Native Diversity to Enhance the Maximum Quantum Efficiency of Photosystem II in Maize

Sebastian Urzinger,Viktoriya Avramova,Monika Frey,Claude Urbany,Daniela Scheuermann,Thomas Presterl, Stefan Reuscher,Karin Ernst,Manfred Mayer,Caroline Marcon,Frank Hochholdinger,Sarah Brajkovic,Bernardo Ordas,Peter Westhoff,Milena Ouzunova,Chris-Carolin Schoen

PLANT PHYSIOLOGY（2025）

Tech Univ Munich | KWS SAAT SE & Co KGaA | Heinrich Heine Univ Dusseldorf | Univ Bonn | CSIC

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Abstract

The sustainability of maize cultivation would benefit tremendously from early sowing, but is hampered by low temperatures during early development in temperate climates. We show that allelic variation within the gene encoding subunit M of the NADH-dehydrogenase-like (NDH) complex (ndhm1) in a European maize landrace affects several quantitative traits that are relevant during early development in cold climates through NDH-mediated cyclic electron transport around photosystem I, a process crucial for photosynthesis and photoprotection. Beginning with a genome-wide association study for maximum potential quantum yield of photosystem II in dark-adapted leaves (Fv/Fm), we capitalized on the large phenotypic effects of a hAT transposon insertion in ndhm1 on multiple quantitative traits (early plant height [EPH], Fv/Fm, chlorophyll content, and cold tolerance) caused by the reduced protein levels of NDHM and associated NDH components. Analysis of the ndhm1 native allelic series revealed a rare allele of ndhm1 that is associated with small albeit significant improvements of Fv/Fm, photosystem II efficiency in light-adapted leaves (Phi PSII), and EPH compared with common alleles. Our work showcases the extraction of favorable alleles from locally adapted landraces, offering an efficient strategy for broadening the genetic variation of elite germplasm by breeding or genome editing. A European maize landrace harbors favorable allelic diversity in a gene encoding a subunit of the NADH-dehydrogenase-like complex, which can be harnessed to improve quantitative traits in maize.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
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