The Spring of Systems Biology-Driven Breeding

被引:25
|
作者
Lavarenne, Jeremy [1 ,2 ]
Guyomarc'h, Soazig [1 ]
Sallaud, Christophe [2 ]
Gantet, Pascal [1 ]
Lucas, Mikael [1 ]
机构
[1] Univ Montpellier, IRD, UMR DIADE, 911 Ave Agropolis, F-34394 Montpellier 5, France
[2] Ctr Rech Chappes, Biogemma, Route dEnnezat, F-63720 Chappes, France
关键词
GENE REGULATORY NETWORK; PROTEIN-INTERACTION NETWORKS; MARKER-ASSISTED SELECTION; TRANSCRIPTION FACTORS; PRIOR KNOWLEDGE; INFERENCE; MODELS; OMICS; CELLS; TOOLS;
D O I
10.1016/j.tplants.2018.04.005
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies.
引用
收藏
页码:706 / 720
页数:15
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