Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, ...Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions be- tween species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ＇stable＇ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime op- timisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change （or, in practice, any other disturbance） on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to meas- ureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here.展开更多
Despite fluctuations in embryo size within a species,the spatial gene expression pattern and hence the embryonic structure can nonetheless maintain the correct proportion to the embryo size.This is known as the scalin...Despite fluctuations in embryo size within a species,the spatial gene expression pattern and hence the embryonic structure can nonetheless maintain the correct proportion to the embryo size.This is known as the scaling phenomenon.For morphogen-induced patterning of gene expression,the positional information encoded in the local morphogen concentrations is decoded by the downstream genetic network(the decoder).In this paper,we show that the requirement of scaling sets severe constraints on the geometric structure of such a local decoder,which in turn enables deduction of mutants’behavior and extraction of regulation information without going into any molecular details.We demonstrate that the Drosophila gap gene system achieves scaling in the way consistent with our theory—the decoder geometry required by scaling correctly accounts for the observed gap gene expression pattern in nearly all maternal morphogen mutants.Furthermore,the regulation logic and the coding/decoding strategy of the gap gene system can also be revealed from the decoder geometry.Our work provides a general theoretical framework for a large class of problems where scaling output is achieved by non-scaling inputs and a local decoder,as well as a unified understanding of scaling,mutants’behavior,and gene regulation for the Drosophila gap gene system.展开更多
文摘Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically infe- rior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions be- tween species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ＇stable＇ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime op- timisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change （or, in practice, any other disturbance） on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to meas- ureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here.
基金supported by the National Natural Science Foundation of China(12090053 and 32088101)。
文摘Despite fluctuations in embryo size within a species,the spatial gene expression pattern and hence the embryonic structure can nonetheless maintain the correct proportion to the embryo size.This is known as the scaling phenomenon.For morphogen-induced patterning of gene expression,the positional information encoded in the local morphogen concentrations is decoded by the downstream genetic network(the decoder).In this paper,we show that the requirement of scaling sets severe constraints on the geometric structure of such a local decoder,which in turn enables deduction of mutants’behavior and extraction of regulation information without going into any molecular details.We demonstrate that the Drosophila gap gene system achieves scaling in the way consistent with our theory—the decoder geometry required by scaling correctly accounts for the observed gap gene expression pattern in nearly all maternal morphogen mutants.Furthermore,the regulation logic and the coding/decoding strategy of the gap gene system can also be revealed from the decoder geometry.Our work provides a general theoretical framework for a large class of problems where scaling output is achieved by non-scaling inputs and a local decoder,as well as a unified understanding of scaling,mutants’behavior,and gene regulation for the Drosophila gap gene system.
