A computational-experimental framework for mapping plant coexistence

Libo Jiang, Chaozhong Shi, Meixia Ye, Feifei Xi, Yige Cao, Lina Wang, Miaomiao Zhang, Mengmeng Sang, Rongling Wu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Despite its importance in understanding the emergent property of plant communities and ecosystems, the question of how genes govern species coexistence has proven very difficult to answer. In a plant community that behaves like a network game, each coexisting plant strives to maximize its fitness by pursuing a “rational self-interest” strategy in a way that affects the decisive reaction of other plants. We integrated this principle founding game theory into a quantitative trait locus (QTL) mapping paradigm, on which to derive a game mapping model for the genetic landscaping of how plants coexist. The new mapping model dissolves the phenotype of each plant in a community into two components, autonomous phenotype, characteristic of the plant's intrinsic ability expected to be expressed in isolation, and social phenotype, determined by game theory-guided interactions between the plant and other members. We implemented the new model into a competition experiment by pairwise growing 116 recombinant inbred lines of Arabidopsis. Most QTLs detected from this experiment reside within biologically meaningful genes, including SCL6, CAR6, CLPB1, ALDH5F1, and EMB2217, which may mediate competitive interactions in unique ways. The new model can chart more detailed genetic architecture of plant community structure and diversity by extracting the genetic effects of QTLs on social phenotypes. Our model lays the groundwork for predicting and managing dynamic relationships between biodiversity and ecosystem functioning from co-species genotypes.

Original languageEnglish (US)
Pages (from-to)1335-1352
Number of pages18
JournalMethods in Ecology and Evolution
Issue number5
StatePublished - May 2018

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecological Modeling


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