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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #358209

Research Project: Improving Crop Efficiency Using Genomic Diversity and Computational Modeling

Location: Plant, Soil and Nutrition Research

Title: Quantitative genetic analysis of the maize leaf microbiome

Author
item Wallace, Jason - University Of Georgia
item Kremling, Karl - Cornell University - New York
item Buckler, Edward - Ed

Submitted to: bioRxiv
Publication Type: Review Article
Publication Acceptance Date: 2/1/2018
Publication Date: 2/20/2018
Citation: Wallace, J., Kremling, K., Buckler Iv, E.S. 2018. Quantitative genetic analysis of the maize leaf microbiome. bioRxiv. 268532. doi: https://doi.org/10.1101/268532
DOI: https://doi.org/10.1101/268532

Interpretive Summary:

Technical Abstract: The degree to which an organism can affect its associated microbial communities ("microbiome") varies by organism and habitat, and in many cases is unknown. We address this question by analyzing the metabolically active bacteria of the maize phyllosphere across 300 diverse maize lines growing in a common environment. We performed comprehensive heritability analysis for 49 community diversity metrics, 380 bacterial clades (individual operational taxonomic units and higher-level groupings), and 9042 predicted metagenomic functions. We find that only a few few bacterial clades (5) and diversity metrics (2) are significantly heritable, while a much larger number of metabolic functions (200) are. Many of these associations appear to be driven by the amount of Methylobacteria present in each sample, and we find significant enrichment for traits relating to short-chain carbon metabolism, secretion, and nitrotoluene degradation. Genome-wide association analysis identifies a small number of associated loci for these heritable traits, including two loci (on maize chromosomes 7 and 10) that affect a large number of traits even after correcting for correlations among traits. This work is among the most comprehensive analyses of the maize phyllosphere to date. Our results indicate that while most of the maize phyllosphere composition is driven by environmental factors and/or stochastic founder events, a subset of bacterial taxa and metabolic functions is nonetheless significantly impacted by host plant genetics. Additional work will be needed to identify the exact nature of these interactions and what effects they may have on the phenotype of host plants.