Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, 318000 Taizhou, China; IRD, IPME, 911 Avenue Agropolis, BP 64501, 34394, Montpellier, France.
Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, 318000 Taizhou, China; AMAP, IRD, CNRS, CIRAD, INRA, Université de Montpellier, 34398 Montpellier Cedex 05, France.
Trends Plant Sci. 2020 Oct;25(10):1017-1029. doi: 10.1016/j.tplants.2020.04.015. Epub 2020 May 25.
It is generally accepted that plants locally influence the composition and activity of their rhizosphere microbiome, and that rhizosphere community assembly further involves a hierarchy of constraints with varying strengths across spatial and temporal scales. However, our knowledge of rhizosphere microbiomes is largely based on single-location and time-point studies. Consequently, it remains difficult to predict patterns at large landscape scales, and we lack a clear understanding of how the rhizosphere microbiome forms and is maintained by drivers beyond the influence of the plant. By synthesizing recent literature and collating data on rhizosphere microbiomes, we point out the opportunities and challenges offered by advances in molecular biology, bioinformatics, and data availability. Specifically, we highlight the use of exact sequence variants, coupled with existing and newly generated data to decipher the rules of rhizosphere community assembly across large spatial and taxonomic scales.
人们普遍认为，植物会对其根际微生物组的组成和活性产生局部影响，而根际群落的组装进一步涉及到一个层次结构的约束，其强度在空间和时间尺度上有所不同。然而，我们对根际微生物组的了解在很大程度上是基于单点和时间点的研究。因此，很难预测大景观尺度上的模式，我们也不清楚根际微生物组是如何通过植物以外的驱动因素形成和维持的。通过综合最近的文献和整理根际微生物组的数据，我们指出了分子生物学、生物信息学和数据可用性方面的进展所带来的机遇和挑战。具体来说，我们强调使用精确的序列变体，结合现有的和新生成的数据来破译根际群落组装的规则，跨越大的空间和分类尺度。
