TY  - JOUR
A1  - Laitinen, Roosa A. E.
A1  - Nikoloski, Zoran
T1  - Genetic basis of plasticity in plants
JF  - Journal of experimental botany
N2  - The ability of an organism to change its phenotype in response to different environments, termed plasticity, is a particularly important characteristic to enable sessile plants to adapt to rapid changes in their surroundings. Plasticity is a quantitative trait that can provide a fitness advantage and mitigate negative effects due to environmental perturbations. Yet, its genetic basis is not fully understood. Alongside technological limitations, the main challenge in studying plasticity has been the selection of suitable approaches for quantification of phenotypic plasticity. Here, we propose a categorization of the existing quantitative measures of phenotypic plasticity into nominal and relative approaches. Moreover, we highlight the recent advances in the understanding of the genetic architecture underlying phenotypic plasticity in plants. We identify four pillars for future research to uncover the genetic basis of phenotypic plasticity, with emphasis on development of computational approaches and theories. These developments will allow us to perform specific experiments to validate the causal genes for plasticity and to discover their role in plant fitness and evolution.
KW  - Genetic architecture
KW  - GWA
KW  - GxE interaction
KW  - hub genes
KW  - plant adaptation
KW  - plasticity
KW  - variance
Y1  - 2018
U6  - https://doi.org/10.1093/jxb/ery404
SN  - 0022-0957
SN  - 1460-2431
VL  - 70
IS  - 3
SP  - 739
EP  - 745
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Basler, Georg
A1  - Fernie, Alisdair R.
A1  - Nikoloski, Zoran
T1  - Advances in metabolic flux analysis toward genome-scale profiling of higher organisms
JF  - Bioscience reports : communications and reviews in molecular and cellular biology
N2  - Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.
Y1  - 2018
U6  - https://doi.org/10.1042/BSR20170224
SN  - 0144-8463
SN  - 1573-4935
VL  - 38
PB  - Portland Press (London)
CY  - London
ER  -