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A Holling Functional Response Model for Mapping QTLs Governing Interspecific Interactions.
Zhang, Xiao-Yu; Gong, Huiying; Fang, Qing; Zhu, Xuli; Jiang, Libo; Wu, Rongling.
Afiliação
  • Zhang XY; College of Science, Beijing Forestry University, Beijing, China.
  • Gong H; College of Science, Beijing Forestry University, Beijing, China.
  • Fang Q; Faculty of Science, Yamagata University, Yamagata, Japan.
  • Zhu X; Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
  • Jiang L; Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
  • Wu R; Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
Front Genet ; 12: 766372, 2021.
Article em En | MEDLINE | ID: mdl-34721549
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Genet Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Genet Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China