Back to Search Start Over

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

Authors :
Weiwei Shen
Jinxing Lin
Huimin Xu
Xiaohong Zhuang
Yuling Jiao
Shunyao Yang
Guangchao Wang
Xi Zhang
Yanping Jing
Yi Man
Xiaojuan Li
Ruili Li
Yi Zhang
Jinbo Shen
Yaning Cui
Jingjing Xing
Jiahui Bian
Sodmergen
Hu Zijian
Tonglin Mao
Lingyu Ma
Meng Yu
Na Lian
Haiyun Ren
Source :
Science China Life Sciences. 64:1392-1422
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

Details

ISSN :
18691889 and 16747305
Volume :
64
Database :
OpenAIRE
Journal :
Science China Life Sciences
Accession number :
edsair.doi...........f3f207e25e7794df18ab497cac0e873d
Full Text :
https://doi.org/10.1007/s11427-020-1910-1