Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Quantitative Genetic Analysis of the Maize Leaf Microbiome

View ORCID ProfileJason G. Wallace, Karl A. Kremling, View ORCID ProfileEdward S. Buckler
doi: https://doi.org/10.1101/268532
Jason G. Wallace
1Department of Crop & Soil Sciences, University of Georgia, Athens, Georgia, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jason G. Wallace
Karl A. Kremling
2Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Edward S. Buckler
3United States Department of Agriculture – Agricultural Research Service, Ithaca, New York, USA
4Institute for Genomic Diversity, Cornell University, Ithaca, New York, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Edward S. Buckler
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

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.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted February 20, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Quantitative Genetic Analysis of the Maize Leaf Microbiome
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Quantitative Genetic Analysis of the Maize Leaf Microbiome
Jason G. Wallace, Karl A. Kremling, Edward S. Buckler
bioRxiv 268532; doi: https://doi.org/10.1101/268532
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Quantitative Genetic Analysis of the Maize Leaf Microbiome
Jason G. Wallace, Karl A. Kremling, Edward S. Buckler
bioRxiv 268532; doi: https://doi.org/10.1101/268532

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genetics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4222)
  • Biochemistry (9095)
  • Bioengineering (6734)
  • Bioinformatics (23916)
  • Biophysics (12066)
  • Cancer Biology (9484)
  • Cell Biology (13722)
  • Clinical Trials (138)
  • Developmental Biology (7614)
  • Ecology (11645)
  • Epidemiology (2066)
  • Evolutionary Biology (15460)
  • Genetics (10611)
  • Genomics (14281)
  • Immunology (9448)
  • Microbiology (22752)
  • Molecular Biology (9057)
  • Neuroscience (48813)
  • Paleontology (354)
  • Pathology (1478)
  • Pharmacology and Toxicology (2559)
  • Physiology (3818)
  • Plant Biology (8300)
  • Scientific Communication and Education (1467)
  • Synthetic Biology (2285)
  • Systems Biology (6163)
  • Zoology (1296)