A Drive to Driven Model of Mapping Intraspecific Interaction Networks

Libo Jiang, Jian Xu, Mengmeng Sang, Yan Zhang, Meixia Ye, Hanyuan Zhang, Biyin Wu, Youxiu Zhu, Peng Xu, Ruyu Tai, Zixia Zhao, Yanliang Jiang, Chuanju Dong, Lidan Sun, Christopher H. Griffin, Claudia Gragnoli, Rongling Wu

Research output: Contribution to journalArticle

Abstract

Community ecology theory suggests that an individual's phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities.

Original languageEnglish (US)
Pages (from-to)109-122
Number of pages14
JournaliScience
Volume22
DOIs
StatePublished - Dec 20 2019

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All Science Journal Classification (ASJC) codes

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Cite this

Jiang, L., Xu, J., Sang, M., Zhang, Y., Ye, M., Zhang, H., Wu, B., Zhu, Y., Xu, P., Tai, R., Zhao, Z., Jiang, Y., Dong, C., Sun, L., Griffin, C. H., Gragnoli, C., & Wu, R. (2019). A Drive to Driven Model of Mapping Intraspecific Interaction Networks. iScience, 22, 109-122. https://doi.org/10.1016/j.isci.2019.11.002