Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph

Growth is the developmental process involving important genetic components. Functional mapping (FunMap) has been used as an approach to map quantitative trait loci (QTLs) governing growth trajectories by incorporating growth equations. FunMap is based on reductionism thinking, with a power to identi...

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Main Authors: Li Feng, Peng Jiang, Caifeng Li, Jinshuai Zhao, Ang Dong, Dengcheng Yang, Rongling Wu
Format: Article
Language:English
Published: Maximum Academic Press 2021-01-01
Series:Forestry Research
Subjects:
Online Access:https://www.maxapress.com/article/doi/10.48130/FR-2021-0019
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author Li Feng
Peng Jiang
Caifeng Li
Jinshuai Zhao
Ang Dong
Dengcheng Yang
Rongling Wu
author_facet Li Feng
Peng Jiang
Caifeng Li
Jinshuai Zhao
Ang Dong
Dengcheng Yang
Rongling Wu
author_sort Li Feng
collection DOAJ
description Growth is the developmental process involving important genetic components. Functional mapping (FunMap) has been used as an approach to map quantitative trait loci (QTLs) governing growth trajectories by incorporating growth equations. FunMap is based on reductionism thinking, with a power to identify a small set of significant QTLs from the whole pool of genome-wide markers. Yet, increasing evidence shows that a complex trait is controlled by all genes the organism may possibly carry. Here, we describe and demonstrate a different mapping approach that encapsulates all markers into genetic interaction networks. This approach, symbolized as FunGraph, combines functional mapping, evolutionary game theory, and prey-predator theory into mathematical graphs, allowing the observed genetic effect of a locus to be decomposed into its independent component (resulting from this locus’ intrinsic capacity) and dependent component (due to extrinsic regulation by other loci). Using FunGraph, we can visualize and trace the roadmap of how each locus interact with every other locus to impact growth. In a population-based association study of Euphrates poplar, we use FunGraph to identify the previously neglected genetic interaction effects that contribute to the genetic architecture of juvenile stem growth. FunGraph could open up a novel gateway to comprehend the global genetic control mechanisms of complex traits.
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spelling doaj.art-824691e1705a4b7fbee08bec73dc937a2024-02-28T01:55:17ZengMaximum Academic PressForestry Research2767-38122021-01-011111010.48130/FR-2021-0019FR-2021-0019Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraphLi Feng0Peng Jiang1Caifeng Li2Jinshuai Zhao3Ang Dong4Dengcheng Yang5Rongling Wu6Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, ChinaCenter for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, ChinaCenter for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USAGrowth is the developmental process involving important genetic components. Functional mapping (FunMap) has been used as an approach to map quantitative trait loci (QTLs) governing growth trajectories by incorporating growth equations. FunMap is based on reductionism thinking, with a power to identify a small set of significant QTLs from the whole pool of genome-wide markers. Yet, increasing evidence shows that a complex trait is controlled by all genes the organism may possibly carry. Here, we describe and demonstrate a different mapping approach that encapsulates all markers into genetic interaction networks. This approach, symbolized as FunGraph, combines functional mapping, evolutionary game theory, and prey-predator theory into mathematical graphs, allowing the observed genetic effect of a locus to be decomposed into its independent component (resulting from this locus’ intrinsic capacity) and dependent component (due to extrinsic regulation by other loci). Using FunGraph, we can visualize and trace the roadmap of how each locus interact with every other locus to impact growth. In a population-based association study of Euphrates poplar, we use FunGraph to identify the previously neglected genetic interaction effects that contribute to the genetic architecture of juvenile stem growth. FunGraph could open up a novel gateway to comprehend the global genetic control mechanisms of complex traits.https://www.maxapress.com/article/doi/10.48130/FR-2021-0019growthgrowth equationforest treegenetic architecturefunctional mappingfunctional graphing
spellingShingle Li Feng
Peng Jiang
Caifeng Li
Jinshuai Zhao
Ang Dong
Dengcheng Yang
Rongling Wu
Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
Forestry Research
growth
growth equation
forest tree
genetic architecture
functional mapping
functional graphing
title Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
title_full Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
title_fullStr Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
title_full_unstemmed Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
title_short Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph
title_sort genetic dissection of growth trajectories in forest trees from funmap to fungraph
topic growth
growth equation
forest tree
genetic architecture
functional mapping
functional graphing
url https://www.maxapress.com/article/doi/10.48130/FR-2021-0019
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