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Nat Biotechnol. 2014 Nov;32(11):1158-65. doi: 10.1038/nbt.3019. Epub 2014 Oct 12.

Comparative analyses of C₄ and C₃ photosynthesis in developing leaves of maize and rice.

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The Donald Danforth Plant Science Center, St. Louis, Missouri, USA.
The Max Planck Institute for Molecular Plant Physiology, Wissenschaftspark Golm, Potsdam-Golm, Germany.
Department of Statistics, Iowa State University, Ames, Iowa, USA.
The Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
The Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Hainan, Haikou, China.
Department of Agronomy, Purdue University, West Lafayette, Indiana, USA.
Department of Biology, Skidmore College, Saratoga Springs, New York, USA.
Computational Biology Service Unit, Life Sciences Core Laboratories Center, Cornell University, Ithaca, New York, USA.
Department of Cell and Systems Biology/Center for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario, Canada.
1] The Donald Danforth Plant Science Center, St. Louis, Missouri, USA. [2] Collaborative Innovation Center of Henan Grain Crops and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, China.


C₄ and C₃ photosynthesis differ in the efficiency with which they consume water and nitrogen. Engineering traits of the more efficient C₄ photosynthesis into C₃ crops could substantially increase crop yields in hot, arid conditions. To identify differences between C₄ and C₃ photosynthetic mechanisms, we profiled metabolites and gene expression in the developing leaves of Zea mays (maize), a C₄ plant, and Oryza sativa (rice), a C₃ plant, using a statistical method named the unified developmental model (UDM). Candidate cis-regulatory elements and transcription factors that might regulate photosynthesis were identified, together with differences between C₄ and C₃ nitrogen and carbon metabolism. The UDM algorithms could be applied to analyze and compare development in other species. These data sets together with community viewers to access and mine them provide a resource for photosynthetic research that will inform efforts to engineer improvements in carbon fixation in economically valuable grass crops.

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