TY - JOUR
T1 - A mapping framework of competition–cooperation QTLs that drive community dynamics
AU - Jiang, Libo
AU - He, Xiaoqing
AU - Jin, Yi
AU - Ye, Meixia
AU - Sang, Mengmeng
AU - Chen, Nan
AU - Zhu, Jing
AU - Zhang, Zuoran
AU - Li, Jinting
AU - Wu, Rongling
N1 - Funding Information:
This work is supported by Fundamental Research Funds for the Central Universities (No. 2015ZCQ-SW-06, 2017JC05), National Natural Science Foundation of China (grant 31700576), the “one-thousand person” plan, grant U01 HL119178, and grant NICHD 5R01HD086911-02.
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Genes have been thought to affect community ecology and evolution, but their identification at the whole-genome level is challenging. Here, we develop a conceptual framework for the genome-wide mapping of quantitative trait loci (QTLs) that govern interspecific competition and cooperation. This framework integrates the community ecology theory into systems mapping, a statistical model for mapping complex traits as a dynamic system. It can characterize not only how QTLs of one species affect its own phenotype directly, but also how QTLs from this species affect the phenotype of its interacting species indirectly and how QTLs from different species interact epistatically to shape community behavior. We validated the utility of the new mapping framework experimentally by culturing and comparing two bacterial species, Escherichia coli and Staphylococcus aureus, in socialized and socially isolated environments, identifying several QTLs from each species that may act as key drivers of microbial community structure and function.
AB - Genes have been thought to affect community ecology and evolution, but their identification at the whole-genome level is challenging. Here, we develop a conceptual framework for the genome-wide mapping of quantitative trait loci (QTLs) that govern interspecific competition and cooperation. This framework integrates the community ecology theory into systems mapping, a statistical model for mapping complex traits as a dynamic system. It can characterize not only how QTLs of one species affect its own phenotype directly, but also how QTLs from this species affect the phenotype of its interacting species indirectly and how QTLs from different species interact epistatically to shape community behavior. We validated the utility of the new mapping framework experimentally by culturing and comparing two bacterial species, Escherichia coli and Staphylococcus aureus, in socialized and socially isolated environments, identifying several QTLs from each species that may act as key drivers of microbial community structure and function.
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U2 - 10.1038/s41467-018-05416-w
DO - 10.1038/s41467-018-05416-w
M3 - Article
C2 - 30068948
AN - SCOPUS:85050971686
SN - 2041-1723
VL - 9
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 3010
ER -