%0 Journal Article %1 welch2005flowering %A Welch, S.M %A Dong, Z. %A Roe, J.L %A Das, S. %D 2005 %J Aust. J. Agric. Res. %K Arabidopsis GRN flowering_time regulatory_networks %N 9 %P 919--936 %T Flowering time control: gene network modelling and the link to quantitative genetics %U http://dx.doi.org/10.1071/AR05155 %V 56 %X Flowering is a key stage in plant development that initiates grain production and is vulnerable to stress. The genes controlling flowering time in the model plant Arabidopsis thaliana are reviewed. Interactions between these genes have been described previously by qualitative network diagrams. We mathematically relate environmentally dependent transcription, RNA processing, translation, and protein–protein interaction rates to resultant phenotypes. We have developed models (reported elsewhere) based on these concepts that simulate flowering times for novel A. thaliana genotype–environment combinations. Here we draw 12 contrasts between genetic network (GN) models of this type and quantitative genetics (QG), showing that both have equal contributions to make to an ideal theory. Physiological dominance and additivity are examined as emergent properties in the context of feed-forwards networks, an instance of which is the signal-integration portion of the A. thaliana flowering time network. Additivity is seen to be a complex, multi-gene property with contributions from mass balance in transcript production, the feed-forwards structure itself, and downstream promoter reaction thermodynamics. Higher level emergent properties are exemplified by critical short daylength (CSDL), which we relate to gene expression dynamics in rice (Oryza sativa). Next to be discussed are synergies between QG and GN relating to the quantitative trait locus (QTL) mapping of model coefficients. This suggests a new verification test useful in GN model development and in identifying needed updates to existing crop models. Finally, the utility of simple models is evinced by 80 years of QG theory and mathematical ecology.

@article{welch2005flowering, abstract = {Flowering is a key stage in plant development that initiates grain production and is vulnerable to stress. The genes controlling flowering time in the model plant Arabidopsis thaliana are reviewed. Interactions between these genes have been described previously by qualitative network diagrams. We mathematically relate environmentally dependent transcription, RNA processing, translation, and protein–protein interaction rates to resultant phenotypes. We have developed models (reported elsewhere) based on these concepts that simulate flowering times for novel A. thaliana genotype–environment combinations. Here we draw 12 contrasts between genetic network (GN) models of this type and quantitative genetics (QG), showing that both have equal contributions to make to an ideal theory. Physiological dominance and additivity are examined as emergent properties in the context of feed-forwards networks, an instance of which is the signal-integration portion of the A. thaliana flowering time network. Additivity is seen to be a complex, multi-gene property with contributions from mass balance in transcript production, the feed-forwards structure itself, and downstream promoter reaction thermodynamics. Higher level emergent properties are exemplified by critical short daylength (CSDL), which we relate to gene expression dynamics in rice (Oryza sativa). Next to be discussed are synergies between QG and GN relating to the quantitative trait locus (QTL) mapping of model coefficients. This suggests a new verification test useful in GN model development and in identifying needed updates to existing crop models. Finally, the utility of simple models is evinced by 80 years of QG theory and mathematical ecology.}, added-at = {2015-04-22T01:58:10.000+0200}, author = {Welch, S.M and Dong, Z. and Roe, J.L and Das, S.}, biburl = {https://www.bibsonomy.org/bibtex/293503ed250022c24792f989aa549539d/peter.ralph}, interhash = {3bed163975097c47da48e19d7d834fea}, intrahash = {93503ed250022c24792f989aa549539d}, journal = {Aust. J. Agric. Res.}, keywords = {Arabidopsis GRN flowering_time regulatory_networks}, number = 9, pages = {919--936}, timestamp = {2015-04-22T01:58:10.000+0200}, title = {Flowering time control: gene network modelling and the link to quantitative genetics}, url = {http://dx.doi.org/10.1071/AR05155}, volume = 56, year = 2005 }