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Disentangling leaf-microbiome interactions in Arabidopsis thaliana by network mapping
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  • Kaihang LI,
  • Kexin CHENG,
  • Haochen WANG,
  • Qi ZHANG,
  • Yan YANG,
  • Yi Jin,
  • XIAOQING HE,
  • Rongling WU
Kaihang LI
Beijing Forestry University
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Kexin CHENG
Beijing Forestry University
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Haochen WANG
Beijing Forestry University
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Qi ZHANG
Beijing Forestry University
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Yan YANG
Beijing Forestry University
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Yi Jin
Beijing Forestry University
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XIAOQING HE
Beijing Forestry University

Corresponding Author:[email protected]

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Rongling WU
The Pennsylvania State University
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Abstract

The leaf microbiota plays a key role in plant development, but a detailed mechanism of microbe-plant relationships remains elusive. Many genome-wide association studies (GWAS) have begun to map leaf microbes, but few has systematically characterized the genetics of how microbes act and interact. Previously, we integrated behavioral ecology and game theory to define four types of microbial interactions – mutualism, antagonism, aggression, and altruism, in a microbial community assembly. Here, we apply network mapping to identify specific plant genes that mediate the topological architecture of microbial networks. Analyzing leaf microbiome data from an Arabidopsis GWAS, we identify several heritable hub microbes for leaf microbial communities and detect 140-728 SNPs responsible for emergent properties of microbial network. We reconstruct Bayesian genetic networks from which to identify 22-43 hub genes found to code molecular pathways related to leaf growth, abiotic stress responses, disease resistance and nutrition uptake. A further path analysis visualizes how genetic variants of Arabidopsis affect its fecundity through the internal workings of the leaf microbiome. We find that microbial networks and their genetic control vary along spatiotemporal gradients. Our study provides a new avenue to reveal the “endophenotype” role of microbial networks in linking genotype to end-point phenotypes in plants.