tailieunhanh - báo cáo khoa học: " A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation | Street et al. BMC Plant Biology 2011 11 13 http 1471-2229 11 13 BMC Plant Biology RESEARCH ARTICLE Open Access A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation Nathaniel Street1 Stefan Jansson1 Torgeir R Hvidsten1 2 Abstract Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus a woody perennial tree in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators such as synergistic and competitive relationships by evaluating increasingly more complex regulatory mechanisms and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves and show how treating genes as interacting .