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    甜玉米种子老化进程中ROS积累、存储mRNA降解及标志物筛选研究

    Study on ROS accumulation, stored mRNA degradation, and molecular marker selection during the aging process of sweet corn seeds

      摘要
    • 摘要:
      目的 解析甜玉米Zea mays L. saccharata Sturt种子老化进程中存储mRNA降解、活性氧(Reactive oxygen species，ROS)积累与种子活力衰退的关系，筛选监测种子老化的分子标志物，为建立基于存储mRNA和ROS的种子质量评估体系提供理论依据。
      方法 以甜玉米品种‘农甜99’和‘农甜20’为材料，进行人工加速老化处理(0~21 d)，结合RT-qPCR技术测定Zm00001d003301、Zm00001d046591和Zm00001d009990等基因存储mRNA的ΔΔCt，同步检测ROS荧光强度及种子活力指标，通过回归分析解析二者与老化时间和种子活力的相关性。
      结果 经过21 d老化后，‘农甜99’发芽率、发芽势、发芽指数和活力指数显著下降100%(P<0.05)；‘农甜20’分别显著下降91.8%、100.0%、95.3%和99.4%(P<0.05)。方差分析表明，品种差异造成了两品种种子活力的差异(P<0.000 1)，‘农甜20’的耐老化能力更强。ROS相对荧光强度和ΔΔCt与种子活力指标均呈显著负相关，其相关系数分别为r = −0.97 ~ −0.83(P<0.01)和r = −0.96 ~ −0.72(P<0.05)，ROS相对荧光强度与老化时间所构建的回归模型的决定系数较高，R2 = 0.978 ~ 0.997。存储mRNA的ΔΔCt与老化时间符合一元二次回归模型(R2=0.969 ~ 0.983)，峰值出现在老化中期(15—18 d)。ΔΔCt与种子活力指标所构建的逐步回归模型的决定系数为R2 = 0.514 ~ 0.956，双基因组合可提升回归模型精度。
      结论 存储mRNA降解与ROS积累是甜玉米种子老化的核心机制。存储mRNA降解呈非线性动态，前期加速降解，后期降解减缓，而ROS积累呈线性增长，二者联合使用可覆盖全老化进程监测。该研究为甜玉米种子老化的分子标志物筛选及动态监测提供了新见解。

       

      Abstract:
      Objective To investigate the relationships between stored mRNA degradation, reactive oxygen species (ROS) accumulation, and the decline of seed viability during the aging of sweet corn (Zea mays L. saccharata Sturt) seeds, and identify molecular markers for monitoring seed aging, thereby providing a theoretical basis for establishing a seed quality evaluation model based on stored mRNAs and ROS.
      Method Two sweet corn varieties, ‘Nongtian 99’ and ‘Nongtian 20’, were subjected to artificial accelerated aging treatment (0–21 days). The ΔΔCt of stored mRNAs for Zm00001d003301, Zm00001d046591 and Zm00001d009990 genes were measured using RT-qPCR, while ROS fluorescence intensity and seed vigor indices were determined simultaneously. Regression analysis was employed to evaluate the correlations of these two parameters with aging time and seed vigor.
      Result After 21 days of aging, the germination rate, germination potential, germination index, and vigor index of ‘Nongtian 99’ decreased significantly by 100% (P<0.05). For ‘Nongtian 20’, the corresponding indices decreased significantly by 91.8%, 100.0%, 95.3%, and 99.4% (P<0.05), respectively. Analysis of variance indicated significant variety difference in seed aging tolerance (P<0.0001), with ‘Nongtian 20’ exhibiting greater aging resistance. Both ROS relative fluorescence intensity and ΔΔCt showed significant negative correlations with seed vigor indices (r = −0.97 to −0.83, P<0.01; r = −0.96 to −0.72, P<0.05). The regression models between ROS relative fluorescence intensity and aging time yielded high coefficients of determination (R2 = 0.978–0.997). Stored mRNA ΔΔCt followed a quadratic regression model with aging time (R2 = 0.969–0.983), peaking at mid-aging stage (15–18 days). Stepwise regression models incorporating ΔΔCt and seed vigor indices achieved R2 of 0.514–0.956, and combining two genes improved model accuracy.
      Conclusion Stored mRNA degradation and ROS accumulation are core mechanisms in sweet corn seed aging. Stored mRNA degradation follows a nonlinear dynamic, accelerating initially and slowing later, whereas ROS accumulation increases linearly. Their combined use enables comprehensive monitoring across the entire aging process. This study provides new insights into molecular marker screen and dynamic monitoring for sweet corn seed aging.

       

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