The genetic architecture of trait covariation in Populus euphratica, a desert tree

Kaiyan Lu, Xueshun Wang, Huiying Gong, Dengcheng Yang, Meixia Ye, Qing Fang, Xiao Yu Zhang, Rongling Wu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Introduction: The cooperative strategy of phenotypic traits during the growth of plants reflects how plants allocate photosynthesis products, which is the most favorable decision for them to optimize growth, survival, and reproduction response to changing environment. Up to now, we still know little about why plants make such decision from the perspective of biological genetic mechanisms. Methods: In this study, we construct an analytical mapping framework to explore the genetic mechanism regulating the interaction of two complex traits. The framework describes the dynamic growth of two traits and their interaction as Differential Interaction Regulatory Equations (DIRE), then DIRE is embedded into QTL mapping model to identify the key quantitative trait loci (QTLs) that regulate this interaction and clarify the genetic effect, genetic contribution and genetic network structure of these key QTLs. Computer simulation experiment proves the reliability and practicability of our framework. Results: In order to verify that our framework is universal and flexible, we applied it to two sets of data from Populus euphratica, namely, aboveground stem length - underground taproot length, underground root number - underground root length, which represent relationships of phenotypic traits in two spatial dimensions of plant architecture. The analytical result shows that our model is well applicable to datasets of two dimensions. Discussion: Our model helps to better illustrate the cooperation-competition patterns between phenotypic traits, and understand the decisions that plants make in a specific environment that are most conducive to their growth from the genetic perspective.

Original languageEnglish (US)
Article number1149879
JournalFrontiers in Plant Science
Volume14
DOIs
StatePublished - 2023

All Science Journal Classification (ASJC) codes

  • Plant Science

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