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A mapping framework of competition-cooperation QTLs that drive community dynamics.

ABSTRACT: 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.

SUBMITTER: Jiang L

PROVIDER: S-EPMC6070507 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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A mapping framework of competition-cooperation QTLs that drive community dynamics.

Jiang Libo L He Xiaoqing X Jin Yi Y Ye Meixia M Sang Mengmeng M Chen Nan N Zhu Jing J Zhang Zuoran Z Li Jinting J Wu Rongling R

Nature communications 20180801 1

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 ...[more]

PMID: 30068948

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Project description:IntroductionInterspecies interactions are a crucial driving force of species evolution. The genes of each coexisting species play a pivotal role in shaping the structure and function within the community, but how to identify them at the genome-wide level has always been challenging.MethodsIn this study, we embed the Lotka-Volterra ordinary differential equations in the theory of community ecology into the systems mapping model, so that this model can not only describe how the quantitative trait loci (QTL) of a species directly affects its own phenotype, but also describe the QTL of the species how to indirectly affect the phenotype of its interacting species, and how QTL from different species affects community behavior through epistatic interactions.ResultsBy designing and implementing a co-culture experiment for 100 pairs of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), we mapped 244 significant QTL combinations in the interaction process of the two bacteria using this model, including 69 QTLs from E. coli and 59 QTLs from S. aureus, respectively. Through gene annotation, we obtained 57 genes in E. coli, among which the genes with higher frequency were ypdC, nrfC, yphH, acrE, dcuS, rpnE, and ptsA, while we obtained 43 genes in S. aureus, among which the genes with higher frequency were ebh, SAOUHSC_00172, capF, gdpP, orfX, bsaA, and phnE1.DiscussionBy dividing the overall growth into independent growth and interactive growth, we could estimate how QTLs modulate interspecific competition and cooperation. Based on the quantitative genetic model, we can obtain the direct genetic effect, indirect genetic effect, and genome-genome epistatic effect related to interspecific interaction genes, and then further mine the hub genes in the QTL networks, which will be particularly useful for inferring and predicting the genetic mechanisms of community dynamics and evolution. Systems mapping can provide a tool for studying the mechanism of competition and cooperation among bacteria in co-culture, and this framework can lay the foundation for a more comprehensive and systematic study of species interactions.

Dataset Information

A mapping framework of competition-cooperation QTLs that drive community dynamics.

Publications

A mapping framework of competition-cooperation QTLs that drive community dynamics.

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