bioRxivPlant BiologyPreprint
Cover crop microbiomes affect legume cash crop growth but not consistently through enriching nitrogen-fixing rhizobia
Kayla M. ClouseiD, Elizabeth Leslie PaillaniD, Cody L. DePewiD, Jennifer E. HarrisiD, Agustin Jason, Kelsey Mercurio, Andy SwartleyiD, Ellen BinghamiD, Liana T. BurghardtiD
Abstract
Harnessing plant-microbe interactions offers a promising path to reduce chemical inputs and enhance crop resilience in agricultural systems. However, microbial inoculants often fail to persist or function consistently across soils, which limits their broad utility. Here, we explore whether legume cover crops can be used to create microbial legacies that improve nodulation and nitrogen fixation in downstream legume cash crops. In a greenhouse experiment, we inoculated four cash crops with rhizosphere and nodule microbiomes derived from different legume cover crops, then used 16S rRNA and nifH amplicon sequencing to profile bacterial and diazotroph communities, respectively. Host identity shaped cover crop rhizosphere and nodule microbial communities, and specific taxa within these communities predicted nodulation and growth in some cash crops. Host specificity varied widely across cash crops, with alfalfa narrowly dependent on a specific symbiont and common bean and fava bean forming more permissive, taxonomically diverse nodule communities. Increased nodulation did not consistently improve biomass, and outcomes in some cash crops depended on more than symbiont compatibility alone. In particular, common bean growth was predicted by both rhizobial and non-rhizobial taxa, while soybean nodulation was shaped by its compatible symbiont as well as a mismatched rhizobial taxon associated with other hosts. Together, these results suggest that cover crops can shape cash crop microbiomes and productivity in host-specific ways, requiring precise symbiont matching in selective hosts but offering more flexible, multi-taxon management opportunities in permissive hosts.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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