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Article|25 Jun 2024|OPEN
A nested reciprocal experimental design to map the genetic architecture of transgenerational phenotypic plasticity
Jincan Che1 , Yu Wang1 , Ang Dong2 , Yige Cao1 , Shuang Wu1,2 , Rongling Wu,1,2,3 ,
1Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
2Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China
3Yau Mathematical Sciences Center, Tsinghua University, Beijing 100084, China
*Corresponding author. E-mail: rwu@bjfu.edu.cn

Horticulture Research 11,
Article number: uhae172 (2024)
doi: https://doi.org/10.1093/hr/uhae172
Views: 1081

Received: 22 Apr 2024
Accepted: 14 Jun 2024
Published online: 25 Jun 2024

Abstract

Extensive studies have revealed the ecological and evolutionary significance of phenotypic plasticity, but little is known about how it is inherited between generations and the genetic architecture of its transgenerational inheritance. To address these issues, we design a mapping study by growing Arabidopsis thaliana RILs in high- and low-light environments and further growing their offspring RILs from each maternal light environment in the same contrasting environments. This tree-like design of the controlled ecological experiment provides a framework for analysing the genetic regulation of phenotypic plasticity and its non-genetic inheritance. We implement the computational approach of functional mapping to identify specific QTLs for transgenerational phenotypic plasticity. By estimating and comparing the plastic response of leaf-number growth trajectories to light environment between generations, we find that the maternal environment affects phenotypic plasticity, whereas transgenerational plasticity is shaped by the offspring environment. The genetic architecture underlying the light-induced change of leaf number not only changes from parental to offspring generations, but also depends on the maternal environment the parental generation experienced and the offspring environment the offspring generation is experiencing. Most plasticity QTLs are annotated to the genomic regions of candidate genes for specific biological functions. Our computational-experimental design provides a unique insight into dissecting the non-genetic and genetic mechanisms of phenotypic plasticity shaping plant adaptation and evolution in various forms.