Title |
Integrated metabolomics and phytochemical genomics approaches for studies on rice
|
---|---|
Published in |
Giga Science, March 2016
|
DOI | 10.1186/s13742-016-0116-7 |
Pubmed ID | |
Authors |
Yozo Okazaki, Kazuki Saito |
Abstract |
Metabolomics is widely employed to monitor the cellular metabolic state and assess the quality of plant-derived foodstuffs because it can be used to manage datasets that include a wide range of metabolites in their analytical samples. In this review, we discuss metabolomics research on rice in order to elucidate the overall regulation of the metabolism as it is related to the growth and mechanisms of adaptation to genetic modifications and environmental stresses such as fungal infections, submergence, and oxidative stress. We also focus on phytochemical genomics studies based on a combination of metabolomics and quantitative trait locus (QTL) mapping techniques. In addition to starch, rice produces many metabolites that also serve as nutrients for human consumers. The outcomes of recent phytochemical genomics studies of diverse natural rice resources suggest there is potential for using further effective breeding strategies to improve the quality of ingredients in rice grains. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Hong Kong | 1 | 50% |
United Kingdom | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 1 | <1% |
Colombia | 1 | <1% |
Germany | 1 | <1% |
Unknown | 104 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 27 | 25% |
Researcher | 13 | 12% |
Student > Master | 11 | 10% |
Student > Doctoral Student | 7 | 7% |
Professor > Associate Professor | 7 | 7% |
Other | 18 | 17% |
Unknown | 24 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 46 | 43% |
Biochemistry, Genetics and Molecular Biology | 19 | 18% |
Chemistry | 6 | 6% |
Computer Science | 3 | 3% |
Engineering | 2 | 2% |
Other | 6 | 6% |
Unknown | 25 | 23% |