Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- List of abbreviations
- 1 Introduction
- I Network Reconstruction
- II Mathematical Properties of Reconstructed Networks
- III Determining the Phenotypic Potential of Reconstructed Networks
- IV Basic and Applied Uses
- 22 Environmental Parameters
- 23 Genetic Parameters
- 24 Analysis of Omic Data
- 25 Model-Driven Discovery
- 26 Adaptive Laboratory Evolution
- 27 Model-driven Design
- V Conceptual Foundations
- 29 Epilogue
- References
- Index
23 - Genetic Parameters
from IV - Basic and Applied Uses
Published online by Cambridge University Press: 05 February 2015
- Frontmatter
- Dedication
- Contents
- Preface
- List of abbreviations
- 1 Introduction
- I Network Reconstruction
- II Mathematical Properties of Reconstructed Networks
- III Determining the Phenotypic Potential of Reconstructed Networks
- IV Basic and Applied Uses
- 22 Environmental Parameters
- 23 Genetic Parameters
- 24 Analysis of Omic Data
- 25 Model-Driven Discovery
- 26 Adaptive Laboratory Evolution
- 27 Model-driven Design
- V Conceptual Foundations
- 29 Epilogue
- References
- Index
Summary
Prediction is at least two things: important and hard
– Howard StevensonGenetic parameters can be represented explicitly in genome-scale models enabling the assessment of their effects on phenotypic functions. There are three issues associated with genetic parameters discussed in this chapter. First, the analysis of the consequences of the loss of function (LOF) or gain of gene function (GOF) will be explored. For essential genes, it is important to understand how the loss of a gene product may lead to cell death. Further, sophisticated methods have been developed to assess the minimal perturbation of phenotypic states resulting from non-lethal gene knock-outs. Second, the simultaneous removal of two genes allows one to address issues related to synthetic lethality and epistasis in general. Such understanding has implications for many studies, such as finding drug targets. Third, sequence variations in genes or their gene dosage, i.e., gene copy number, can determine their activity level. Gene dosage may be of interest in many situations, ranging from imprinted genes in humans (where one copy is active), to aneuploidy in cancer, to cell line engineering (where gene dosage can be manipulated). The coordinated functions of genes can be assessed through reaction co-sets, and genetic variations in a co-set may have similar consequences on network functions, and thus phenotypic states. The following contains some examples of how to describe genetic parameters within GEMs; there will undoubtedly be many more applications developed in the future.
Single Gene Knock-outs
23.1.1 Concept
The network function of a gene is traced through its gene–protein–reaction (GPR) association to the reactions with which the gene product is involved. Thus, if a gene is deleted, then flux constraints for the reaction(s) affected by the loss of a gene product are put to zero and thus no flux can take place through the corresponding reaction.
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- Systems BiologyConstraint-based Reconstruction and Analysis, pp. 378 - 397Publisher: Cambridge University PressPrint publication year: 2015