Systems mapping: how to improve the genetic mapping of complex traits through design principles of biological systems

被引:33
|
作者
Wu, Rongling [1 ]
Cao, Jiguo [4 ]
Huang, Zhongwen [5 ]
Wang, Zhong [6 ]
Gai, Junyi [2 ]
Vallejos, Eduardo [3 ]
机构
[1] Beijing Forestry Univ, Ctr Computat Biol, Natl Engn Lab Tree Breeding, Key Lab Genet & Breeding Forest Trees & Ornamenta, Beijing 100083, Peoples R China
[2] Nanjing Agr Univ, Natl Key Lab Crop Genet & Germplasm Enhancement, Natl Ctr Soybean Improvement, Soybean Res Inst, Nanjing 210095, Peoples R China
[3] Univ Florida, Dept Hort Sci, Gainesville, FL 32611 USA
[4] Simon Fraser Univ, Dept Stat & Actuarial Sci, Burnaby, BC V5A 1S6, Canada
[5] Henan Inst Sci & Technol, Dept Agron, Xinxiang 453003, Peoples R China
[6] Penn State Univ, Ctr Stat Genet, Hershey, PA 17033 USA
来源
BMC SYSTEMS BIOLOGY | 2011年 / 5卷
基金
加拿大自然科学与工程研究理事会;
关键词
PARAMETER-ESTIMATION; CARBON ALLOCATION; BIOMASS ALLOCATION; BAYESIAN-APPROACH; GENERAL-MODEL; LOCI; ARCHITECTURE; GROWTH; RICE; DISSECTION;
D O I
10.1186/1752-0509-5-84
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Every phenotypic trait can be viewed as a "system" in which a group of interconnected components function synergistically to yield a unified whole. Once a system's components and their interactions have been delineated according to biological principles, we can manipulate and engineer functionally relevant components to produce a desirable system phenotype. Results: We describe a conceptual framework for mapping quantitative trait loci (QTLs) that control complex traits by treating trait formation as a dynamic system. This framework, called systems mapping, incorporates a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function through genes, and provides a quantitative and testable platform for assessing the interplay between gene action and development. We applied systems mapping to analyze biomass growth data in a mapping population of soybeans and identified specific loci that are responsible for the dynamics of biomass partitioning to leaves, stem, and roots. Conclusions: We show that systems mapping implemented by design principles of biological systems is quite versatile for deciphering the genetic machineries for size-shape, structural-functional, sink-source and pleiotropic relationships underlying plant physiology and development. Systems mapping should enable geneticists to shed light on the genetic complexity of any biological system in plants and other organisms and predict its physiological and pathological states.
引用
收藏
页数:11
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