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转录组增强型水稻籽粒代谢模型将组氨酸水平确定为籽粒垩白的一个标志物。

Transcriptome enhanced rice grain metabolic model identifies histidine level as a marker for grain chalkiness.

作者信息

Chowdhury Niaz Bahar, Chandran Anil Kumar Nalini, Walia Harkamal, Saha Rajib

机构信息

Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, 1600 Vine Street, Lincoln, NE, 68505, USA.

Department of Agronomy and Horticulture, University of Nebraska- Lincoln, 1600 Vine Street, Lincoln, NE, 68505, USA.

出版信息

Sci Rep. 2025 May 12;15(1):16432. doi: 10.1038/s41598-025-00504-6.

Abstract

Rising temperatures due to global warming can negatively impact rice grain quality and yield. This study investigates the effects of increased warmer night temperatures (WNT), a consequence of global warming, on the quality of rice kernel, particularly grain chalkiness. By integrating computational and experimental approaches, we used a rice grain metabolic network to discover the metabolic factors of chalkiness. For this, we reconstructed the rice grain genome-scale metabolic model (GSM), iOSA3474-G and incorporated transcriptomics data from three different times of the day (dawn, dawn 7 h, and dusk) for both control and WNT conditions with iOSA3474-G. Three distinct growth phases: anoxia, normoxia, and hyperoxia, were identified in rice kernels from the GSMs, highlighting the grain-filling pattern under varying oxygen levels. We predicted excess flux through histidine contributing to the biomass as a marker of normoxia, during which kernel chalkiness occurs. Moreover, similarly, we proposed tyrosine as a marker for the hyperoxic growth phase. We also proposed a potential link between monodehydroascorbate reductase, an enzyme with evolutionary significance dating back to the carboniferous era, in regulating the hyperoxic growth phase. Metabolic bottleneck analysis identified nucleoside diphosphate kinase as a central regulator of metabolic flux under different conditions. These findings provide targeted insights into the complex metabolic network governing rice grain chalkiness under WNT conditions. Integration of GSM and transcriptomics data, enhanced our understanding of the intricate relationship between environmental factors, metabolic processes, and grain quality and also offer markers that can be useful to develop rice with improved resilience.

摘要

全球变暖导致的气温上升会对稻米品质和产量产生负面影响。本研究调查了全球变暖导致的夜间气温升高(WNT)对水稻籽粒品质,特别是籽粒垩白的影响。通过整合计算和实验方法,我们利用水稻籽粒代谢网络来发现垩白的代谢因子。为此,我们重建了水稻籽粒基因组规模代谢模型(GSM)iOSA3474-G,并将对照和WNT条件下一天中三个不同时间(黎明、黎明后7小时和黄昏)的转录组学数据与iOSA3474-G整合。从GSM中确定了水稻籽粒的三个不同生长阶段:缺氧、常氧和高氧,突出了不同氧水平下的灌浆模式。我们预测通过组氨酸的过量通量有助于生物量,作为常氧的一个标志,在此期间籽粒会出现垩白。此外,同样地,我们提出酪氨酸作为高氧生长阶段的一个标志。我们还提出了单脱氢抗坏血酸还原酶(一种可追溯到石炭纪具有进化意义的酶)在调节高氧生长阶段之间的潜在联系。代谢瓶颈分析确定核苷二磷酸激酶是不同条件下代谢通量的中心调节因子。这些发现为WNT条件下控制水稻籽粒垩白的复杂代谢网络提供了有针对性的见解。GSM和转录组学数据的整合,增强了我们对环境因素、代谢过程和籽粒品质之间复杂关系的理解,也提供了有助于培育具有更强抗逆性水稻的标记。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1213/12069599/45a3b8248957/41598_2025_504_Fig1_HTML.jpg

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