IMR Press / FBL / Volume 26 / Issue 11 / DOI: 10.52586/5003
Open Access Original Research
Functional mapping of gravitropism and phototropism for a desert tree, Populus euphratica
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1 Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, 100083 Beijing, China
2 Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA
*Correspondence: yemeixia123@bjfu.edu.cn (Meixia Ye); ronglingwu@phs.psu.edu (Rongling Wu)
Front. Biosci. (Landmark Ed) 2021, 26(11), 988–1000; https://doi.org/10.52586/5003
Submitted: 2 June 2021 | Revised: 17 July 2021 | Accepted: 28 July 2021 | Published: 30 November 2021
Copyright: © 2021 The Author(s). Published by BRI.
This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/).
Abstract

Background: Plants have evolved the dual capacity for maximizing light assimilation through stem growth (phototropism) and maximizing water and nutrient absorption through root growth (gravitropism). Previous studies have revealed the physiological and molecular mechanisms of these two processes, but the genetic basis for how gravitropism and phototropism interact and coordinate with one another to determine plant growth remains poorly understood. Methods: We designed a seed germination experiment using a full-sib F1 family of Populus euphratica to simultaneously monitor the gravitropic growth of the radicle and the phototropic growth of the plumule throughout seedling ontogeny. We implemented three functional mapping models to identify quantitative trait loci (QTLs) that regulate gravitropic and phototropic growth. Univariate functional mapping dissected each growth trait separately, bivariate functional mapping mapped two growth traits simultaneously, and composite functional mapping mapped the sum of gravitropic and phototropic growth as a main axis. Results: Bivariate model detected 8 QTLs for gravitropism and phototropism (QWRF, GLUR, F-box, PCFS4, UBQ, TAF12, BHLH95, TMN8), composite model detected 7 QTLs for growth of main axis (ATL8, NEFH, PCFS4, UBQ, SOT16, MOR1, PCMP-H), of which, PCFS4 and UBQ were pleiotropically detected with the both model. Many of these QTLs are situated within the genomic regions of candidate genes. Conclusions: The results from our models provide new insight into the mechanisms of genetic control of gravitropism and phototropism in a desert tree, and will stimulate our understanding of the relationships between gravity and light signal transduction pathways and tree adaptation to arid soil.

Keywords
Root-shoot growth
Gravitropism
Phototropism
Functional mapping
Growth
Populus euphratica
Figures
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