Functional mapping of genotype-environment interactions for soybean growth by a semiparametric approach.
BACKGROUND
Functional mapping is a powerful approach for mapping quantitative trait loci (QTLs) that control biological processes. Functional mapping incorporates mathematical aspects of growth and development into a general QTL mapping framework and has been recently integrated with composite interval mapping to build up a so-called composite functional mapping model, aimed to separate multiple linked QTLs on the same chromosomal region.


RESULTS
This article reports the principle of using composite functional mapping to estimate the effects of QTL-environment interactions on growth trajectories by parametrically modeling the tested QTL in a marker interval and nonparametrically modeling the markers outside the interval as co-factors. With this new model, we can characterize the dynamic patterns of the genetic effects of QTLs governing growth trajectories, estimate the global effects of the underlying QTLs during the course of growth and development, and test the differentiation in the shapes of QTL genotype-specific growth curves between different environments. By analyzing a real example from a soybean genome project, our model detects several QTLs that cause significant genotype-environment interactions for plant height growth processes.


CONCLUSIONS
The model provides a basis for deciphering the genetic architecture of trait expression adjusted to different biotic and abiotic environments for any organism.
Department of Statistics, University of Florida, Gainesville, FL 32611 USA.
Qin
Q
Li
Department of Agronomy, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China.|National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
Zhongwen
Z
Huang
Key Laboratory of Forest Genetics and Tree Engineering, Nanjing Forestry University, Nanjing, Jiangsu 210037, China.
Meng
M
Xu
Department of Statistics, University of Florida, Gainesville, FL 32611 USA.
Chenguang
C
Wang
National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
Junyi
J
Gai
School of Forestry and Biotechnology, Zhejiang Forestry University, Lin'an, Zhejiang 311300, China.
Youjun
Y
Huang
Center for Computational Biology, Beijing Forestry University, Beijing 100083, China.|National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Beijing Forestry University, Beijing 100083, China.
Xiaoming
X
Pang
Center for Computational Biology, Beijing Forestry University, Beijing 100083, China.|National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Beijing Forestry University, Beijing 100083, China.
Rongling
R
Wu