기술동향
From genes to plant metabolism
- 등록일2008-12-18
- 조회수9234
- 분류기술동향
-
자료발간일
2008-12-12
-
출처
Riken
- 원문링크
-
키워드
#gene#metabolism
출처 : Riken
From genes to plant metabolism
- An analytical survey maps out the genetic connections of the flavonols -
Plant molecular biologists from RIKEN’s Plant Science Center in Yokohama and Chiba University are using a combination of bioinformatics and biochemical analytical techniques to complete a map of all the reactions involving flavonols in the model plant Arabidopsis thaliana. Already the researchers have succeeded in identifying a new gene that encodes an important enzyme and in determining the physiological role played by another gene. The information gained in the study should be applicable to other plants.
Flavonols are health-promoting, dietary antioxidants. In plants, they are involved in defense responses, such as reactions to pathogens and UV radiation. The genes and biochemical pathways for flavonol synthesis have been well studied in several plants, but the details of subsequent chemical modification are less well known.
The research team is involved in a major project applying the latest techniques to finding the links between the genes of Arabidopsis, for which the entire genome has already been sequenced, and the compounds found in the plants themselves. The flavonol study is aimed at identifying these connections for a whole class of compounds, and results were published recently in The Plant Cell1.
Initially, the researchers catalogued all the flavonol related compounds in Arabidopsis by comparing what was present in normal plants with what they found in a mutant form in which no flavonol was produced. They determined the compounds in the flowers, leaves, stems and roots of the plant by preparing extracts and putting them through liquid chromatography?mass spectros (LC?MS) analysis. The study detected 30 flavonol-related products in Arabidopsis, some of which were intermediates for making others. Two other compounds have been reported in earlier studies.
Using plants with flavonol-related mutations, the LC?MS results, and data from previous studies, the researchers determined the structures and metabolic relationships of 15 newly identified and eight known flavonols. In a technique known as tranome coexpression analysis, they were then able to use software to identify the flavonol-related genes in the published genome, linking enzymes and regulatory factors with the products found in the plants themselves (Fig. 1).
Figure 1: Relationships of the coexpression of genes involved in the flavonoid pathways in Arabidopsis. Orange circles represent known flavonoid-related genes, red circles represent the closely linked anthocyanin-related genes, and pale green circles represent the genes that may be involved in flavonoid metabolism.
On the basis of their results they undertook detailed analysis of two genes using genetically engineered mutants, uncovering one previously unknown gene and determining the metabolic role of another. “We now wish to complete our map of the flavonoids in Arabidopsis and then in other plant species, including the metabolic relationships,” says lead author, Keiko Yonekura-Sakakibara.
1. Yonekura-Sakakibara, K., Tohge, T., Matsuda, F., Nakabayashi, R., Takayama, H., Niida, R., Watanabe-Takahashi, A., Inoue, E. & Saito, K. Comprehensive flavonol profiling and tranome coexpression analysis leading to decoding gene?metabolite correlations in Arabidopsis. The Plant Cell 20, 2160?2176 (2008). | article |
The corresponding author for this highlight is based at the RIKEN Metabolic Function Research Team
...................(계속)
☞ 자세한 내용은 내용바로가기 또는 첨부파일을 이용하시기 바랍니다.
-
이전글
- 앱타머 기반 바이오센서 및 분리기술
-
다음글
- Pass the protein
관련정보
지식
동향
- 제도동향 [보건산업브리프 Vol. 393] 캘리포니아 재생 의학 연구소(California Institute for Regenerative Medicine, CIRM)의 펀딩의 이해 2024-02-06
- 산업동향 [KBIOIS Vol.59] NGS(Next-generation Sequencing)시장 전망 2023-08-08
- 정책동향 National Cell and Gene Manufacturing Blueprint 2023-07-27
- 기술동향 유전자 가위 기반 치료제의 비표적유전자(off-target gene) 분석방법 개발 동향 2022-04-01
- 기술동향 암에서 유전적 이질성 분석하기(Resolving genetic heterogeneity in cancer) 2021-04-16