4.6 Review

From ABC genes to regulatory networks, epigenetic landscapes and flower morphogenesis: Making biological sense of theoretical approaches

期刊

SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
卷 21, 期 1, 页码 108-117

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcdb.2009.11.010

关键词

Gene regulatory networks; Flower morphogenesis models; Simulations; Positional information; Epigenetic landscapes; Stochastic models

资金

  1. Programa de Apoyo a Proyectos de Investigacion e Innovacion Tecnologica
  2. Universidad Nacional Autonoma de Mexico [IN230002, IX207104]
  3. University of California-MEXUS [ECO IE 271]
  4. Ciencia y Tecnologia [CO1.41848/A-1, CO1.0538/A-1, CO1.0435.B-1]
  5. Conacyt [79641]

向作者/读者索取更多资源

The ABC model postulates that expression combinations of three classes of genes (A, B and C) specify the four floral organs at early stages of flower development. This classic model provides a solid framework to study flower development and has been the foundation for multiple studies in different plant species, as well as for new evolutionary hypotheses. Nevertheless, it has been shown that in spite of being necessary, these three gene classes are not sufficient for flower organ specification. Rather, flower organ specification depends on complex interactions of several genes, and probably other non-genetic factors. Being useful to study systems of complex interactions, mathematical and computational models have enlightened the origin of the A, B and C stereotyped and robust expression patterns and the process of early flower morphogenesis. Here, we present a brief introduction to basic modeling concepts and techniques and review the results that these models have rendered for the particular case of the Arabidopsis thaliana flower organ specification. One of the main results is the uncovering of a robust functional module that is sufficient to recover the gene configurations characterizing flower organ primordia. Another key result is that the temporal sequence with which such gene configurations are attained may be recovered only by modeling the aforementioned functional module as a noisy or stochastic system. Finally, modeling approaches enable testable predictions regarding the role of non-genetic factors (noise, mechano-elastic forces, etc.) in development. These predictions, along with some perspectives for future work, are also reviewed and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据