báo cáo khoa học: " Functional mapping of reaction norms to multiple environmental signals through nonparametric covariance estimation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Functional mapping of reaction norms to multiple environmental signals through nonparametric covariance estimation | Yap et al. BMC Plant Biology 2011 11 23 http 1471-2229 11 23 BMC Plant Biology METHODOLOGY ARTICLE Open Access Functional mapping of reaction norms to multiple environmental signals through nonparametric covariance estimation I n u c V n k 1 V n I I2 IT i K i rtnr3 ìl . I 13 11 A I4 3 John S Yap Yao LI Kiranmoy Das Jianan LI Rongling wu Abstract Background The identification of genes or quantitative trait loci that are expressed in response to different environmental factors such as temperature and light through functional mapping critically relies on precise modeling of the covariance structure. Previous work used separable parametric covariance structures such as a Kronecker product of autoregressive one AR 1 matrices that do not account for interaction effects of different environmental factors. Results We implement a more robust nonparametric covariance estimator to model these interactions within the framework of functional mapping of reaction norms to two signals. Our results from Monte Carlo simulations show that this estimator can be useful in modeling interactions that exist between two environmental signals. The interactions are simulated using nonseparable covariance models with spatio-temporal structural forms that mimic interaction effects. Conclusions The nonparametric covariance estimator has an advantage over separable parametric covariance estimators in the detection of QTL location thus extending the breadth of use of functional mapping in practical settings. Background The phenotype of a quantitative trait exhibits plasticity if the trait differs in phenotypes with changing environment 1-7 . Such environment-dependent changes also called reaction norms are ubiquitous in biology. For example thermal reaction norms show how performance such as caterpillar growth rate 8 or growth rate and body size in ectotherms 9 varies continuously with temperature 10 . Another example is the flowering time of Arabidopsis thaliana with .

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