Abstract：
Long-term continuous cropping of soybean can generate the development of disease-suppressive soils. However, whether the changes in microbial communities, especially for archaea, contribute to controlling soil sickness and improving crop yields remains poorly understood. Here, real-time PCR and high-throughput sequencing were employed to investigate the changes in soil archaeal communities in both bulk and rhizosphere soils under four cropping systems, including the continuous cropping of soybeans for a short-term of 3 and 5 years (CC3 and CC5, respectively) and for a long-term of 13 years (CC13), as well as a soybean-maize rotation for 5 years (CR5). The results showed that CC13 and CR5 significantly increased archaeal abundance, reduced the alpha-diversity of archaeal communities, and changed soil archaeal community structures compared to CC3 and CC5. Microbial co-occurrence network analysis revealed that CC13 led to the higher resistant microbial community and lower the relative abundance of potential plant pathogens in the network compared to CC3 and CC5. Correlation analysis showed that the microbial resistance index was negatively correlated with the relative abundance of potential plant pathogens and positively correlated with soybean yields in both bulk and rhizosphere soils. Intriguingly, the random forest (RF) analysis showed that archaea contributed the most to soil microbial resistance even though they were not at the core positions of the network. Overall, structural equation models (SEMs) revealed that high resistant microbial community could directly or indirectly improved soybean yields by regulating the relative abundance of plant pathogens and the soil nutrients, suggesting that the regulation of soil microbial taxa may play an important role in maintaining agricultural productivity under continuous cropping of soybean.
摘要：
大豆的长期连作可以产生病害抑制土壤的发育。然而,微生物群落的变化，尤其是古细菌,对控制土壤病和提高作物产量的贡献仍然知之甚少。这里,采用实时PCR和高通量测序技术研究了四种种植系统下散装和根际土壤中土壤古细菌群落的变化，包括短期3年和5年（分别为CC3和CC5）和长期13年（CC13）的大豆连续种植，以及大豆-玉米轮作5年（CR5）。结果表明，CC13和CR5显著增加了古细菌的丰度，减少了考古群落的阿尔法多样性，与CC3和CC5相比，改变了土壤古细菌群落结构。微生物共生网络分析显示，与CC3和CC5相比，CC13导致较高的抗性微生物群落，并降低了网络中潜在植物病原体的相对丰度。相关分析表明，微生物抗性指数与潜在植物病原菌的相对丰度呈负相关，与大豆产量呈正相关。有趣的是，随机森林（RF）分析表明，古细菌对土壤微生物抗性的贡献最大，即使它们不在网络的核心位置。总的来说,结构方程模型（SEM）表明，高抗性微生物群落可以通过调节植物病原体和土壤养分的相对丰度来直接或间接提高大豆产量，表明土壤微生物类群的调控可能在大豆连作条件下维持农业生产力方面发挥重要作用。
