Agroécologie laboratory, Université Bourgogne Franche-Comté, AgroSup Dijon, INRAE, Université Bourgogne, Dijon, France.
Section of Microbiology, University of Copenhagen, Copenhagen, Denmark.
Ecol Lett. 2022 Jan;25(1):189-201. doi: 10.1111/ele.13916. Epub 2021 Nov 8.
Artificial selection of microbiota opens new avenues for improving plants. However, reported results lack consistency. We hypothesised that the success in artificial selection of microbiota depends on the stabilisation of community structure. In a ten-generation experiment involving 1,800 plants, we selected rhizosphere microbiota of Brachypodium distachyon associated with high or low leaf greenness, a proxy of plant performance. The microbiota structure showed strong fluctuations during an initial transitory phase, with no detectable leaf greenness heritability. After five generations, the microbiota structure stabilised, concomitantly with heritability in leaf greenness. Selection, initially ineffective, did successfully alter the selected property as intended, especially for high selection. We show a remarkable correlation between the variability in plant traits and selected microbiota structures, revealing two distinct sub-communities associated with high or low leaf greenness, whose abundance was significantly steered by directional selection. Understanding microbiota structure stabilisation will improve the reliability of artificial microbiota selection.
人工选择微生物组为改善植物开辟了新途径。然而,报道的结果缺乏一致性。我们假设人工选择微生物组的成功取决于群落结构的稳定化。在一项涉及 1800 株植物的十代实验中,我们选择了与叶片绿色度(植物表现的替代指标)高低相关的拟南芥根际微生物组。在初始过渡阶段,微生物组结构表现出强烈的波动,叶片绿色度的遗传力无法检测到。经过五代后,微生物组结构稳定,同时叶片绿色度的遗传力也稳定下来。最初无效的选择确实成功地按照预期改变了所选性状,特别是在高选择强度下。我们展示了植物性状变异和所选微生物组结构之间的显著相关性,揭示了与叶片绿色度高低相关的两个不同的亚群落,它们的丰度显著受到定向选择的影响。了解微生物组结构的稳定化将提高人工微生物组选择的可靠性。