Association analyses of host genetics, root-colonizing microbes, and plant phenotypes under different nitrogen conditions in maize

Abstract

The root-associated microbiome (rhizobiome) affects plant health, stress tolerance, and nutrient use efficiency. However, it remains unclear to what extent the composition of the rhizobiome is governed by intraspecific variation in host plant genetics in the field and the degree to which host plant selection can reshape the composition of the rhizobiome. Here we quantify the rhizosphere microbial communities associated with a replicated diversity panel of 230 maize (Zea mays L.) genotypes grown in agronomically relevant conditions under high N (+N) and low N (-N) treatments. We analyze the maize rhizobiome in terms of 150 abundant and consistently reproducible microbial groups and we show that the abundance of many root-associated microbes is explainable by natural genetic variation in the host plant, with a greater proportion of microbial variance attributable to plant genetic variation in -N conditions. Population genetic approaches identify signatures of purifying selection in the maize genome associated with the abundance of several groups of microbes in the maize rhizobiome. Genome-wide association study was conducted using the abundance of microbial groups as rhizobiome traits, and identified n = 622 plant loci that are linked to the abundance of n = 104 microbial groups in the maize rhizosphere. In 62/104 cases, which is more than expected by chance, the abundance of these same microbial groups was correlated with variation in plant vigor indicators derived from high throughput phenotyping of the same field experiment. We provide comprehensive datasets about the three-way interaction of host genetics, microbe abundance, and plant performance under two N treatments to facilitate targeted experiments towards harnessing the full potential of root-associated microbial symbionts in maize production.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Michael A Meier

    Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Gen Xu

    Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Martha G Lopez-Guerrero

    Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Guangyong Li

    Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Christine Smith

    Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Brandi Sigmon

    Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Joshua R Herr

    Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3425-292X
  8. James R Alfano

    Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Yufeng Ge

    Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. James C Schnable

    Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, United States
    For correspondence
    schnable@unl.edu
    Competing interests
    The authors declare that no competing interests exist.
  11. Jinliang Yang

    Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, United States
    For correspondence
    jinliang.yang@unl.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0999-3518

Funding

National Science Foundation (Cooperative Agreement OIA-1557417)

  • Jinliang Yang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Meier et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Michael A Meier
  2. Gen Xu
  3. Martha G Lopez-Guerrero
  4. Guangyong Li
  5. Christine Smith
  6. Brandi Sigmon
  7. Joshua R Herr
  8. James R Alfano
  9. Yufeng Ge
  10. James C Schnable
  11. Jinliang Yang
(2022)
Association analyses of host genetics, root-colonizing microbes, and plant phenotypes under different nitrogen conditions in maize
eLife 11:e75790.
https://doi.org/10.7554/eLife.75790

Share this article

https://doi.org/10.7554/eLife.75790

Further reading

    1. Genetics and Genomics
    Jorge Blanco Mendana, Margaret Donovan ... Daryl M Gohl
    Tools and Resources

    Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression and cellular heterogeneity within tissues and have enabled the construction of transcriptomic cell atlases. However, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM enables positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that TaG-EM barcodes can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to multiplex and reliably annotate single-cell transcriptomic experiments.

    1. Cell Biology
    2. Genetics and Genomics
    Adam D Longhurst, Kyle Wang ... David P Toczyski
    Tools and Resources

    Progression through the G1 phase of the cell cycle is the most highly regulated step in cellular division. We employed a chemogenetic approach to discover novel cellular networks that regulate cell cycle progression. This approach uncovered functional clusters of genes that altered sensitivity of cells to inhibitors of the G1/S transition. Mutation of components of the Polycomb Repressor Complex 2 rescued proliferation inhibition caused by the CDK4/6 inhibitor palbociclib, but not to inhibitors of S phase or mitosis. In addition to its core catalytic subunits, mutation of the PRC2.1 accessory protein MTF2, but not the PRC2.2 protein JARID2, rendered cells resistant to palbociclib treatment. We found that PRC2.1 (MTF2), but not PRC2.2 (JARID2), was critical for promoting H3K27me3 deposition at CpG islands genome-wide and in promoters. This included the CpG islands in the promoter of the CDK4/6 cyclins CCND1 and CCND2, and loss of MTF2 lead to upregulation of both CCND1 and CCND2. Our results demonstrate a role for PRC2.1, but not PRC2.2, in antagonizing G1 progression in a diversity of cell linages, including chronic myeloid leukemia (CML), breast cancer, and immortalized cell lines.