A Holling Functional Response Model for Mapping QTLs Governing Interspecific Interactions.

Xiao-Yu Zhang,Huiying Gong,Xuli Zhu,Qing Fang,Libo Jiang,Rongling Wu

doi:10.3389/fgene.2021.766372

Abstract

Genes play an important role in community ecology and evolution, but how to identify the genes that affect community dynamics at the whole genome level is very challenging. Here, we develop a Holling type II functional response model for mapping quantitative trait loci (QTLs) that govern interspecific interactions. The model, integrated with generalized Lotka-Volterra differential dynamic equations, shows a better capacity to reveal the dynamic complexity of inter-species interactions than classic competition models. By applying the new model to a published mapping data from a competition experiment of two microbial species, we identify a set of previously uncharacterized QTLs that are specifically responsible for microbial cooperation and competition. The model can not only characterize how these QTLs affect microbial interactions, but also address how change in ecological interactions activates the genetic effects of the QTLs. This model provides a quantitative means of predicting the genetic architecture that shapes the dynamic behavior of ecological communities.

Highlights

Understanding the internal workings of ecological communities is of fundamental importance to predict community dynamics and improve ecosystem services (Whitham et al, 2006; Vellend, 2020)
Community genetics has emerged as a subdiscipline of genetics that combines community ecology and ecological genetics to gain insight into the genetic mechanisms underlying phenotypic diversity and evolution within and between species (Whitham et al, 2006; Hersch-Green et al, 2011)
We develop and implement a computational model to address three fundamental questions in community genetics: 1) how a given species genetically adapts to its coexisting conspecifics, 2) which genetic machineries mediate a species’ phenotypes expressed in ecological communities, and 3) what is the genetic architecture underlying interspecific interactions

Summary

Introduction

Understanding the internal workings of ecological communities is of fundamental importance to predict community dynamics and improve ecosystem services (Whitham et al, 2006; Vellend, 2020). Genetic mapping is a statistical approach widely used to map and identify genes, known as quantitative trait loci (QTLs), which control complex traits (Flint et al, 2005; Atwell et al, 2010; Consortium et al, 2015; Zeng et al, 2018). By integrating the mathematical aspect of trait formation, functional mapping has been developed to reveal the spatiotemporal pattern of the genetic architecture underlying phenotypic variation and evolution (Ma et al, 2002; Wu et al, 2005; Wu and Lin, 2006; Zhao et al, 2012; Li and Sillanpaa, 2015). The interpretable advantage of Holling Model for Interspecific Interactions functional mapping has been leveraged to capture the biological rule governing how the components constituting a complex trait are interconnected, interdepended and interacted to mediate trait variation. A so-called system mapping approach has been assembled to map the genetic machineries underlying such component-component interconnections (Gai et al, 2011; Bo et al, 2014; Sun and Wu, 2015)

Methods

Results

Conclusion