Evolutionary Systems Biology: Advances, Questions, and Opportunities

✍ Scribed by Anton Crombach

• Publisher: SPRINGER NATURE
• Year: 2021
• Tongue: English
• Leaves: 299
• Edition: 2
• Category: Library

✦ Synopsis

This new edition captures the advances made in the field of evolutionary systems biology since the publication of the first edition. The first edition focused on laying the foundations of evolutionary systems biology as an interdisciplinary field, where a way of thinking and asking questions is combined with a wide variety of tools, both experimental and theoretical/computational. Since publication of the first edition, evolutionary systems biology is now a well-known term describing this growing field.

The new edition provides an overview of the current status and future developments of this interdisciplinary field. Chapters highlight several key achievements from the last decade and outline exciting new developments, including an understanding of the interplay between complexity and predictability in evolutionary systems, new viewpoints and methods to study organisms in evolving populations at the level of the genome, gene regulatory network, and metabolic network, and better analysis and modeling techniques that will open new avenues of scientific inquiry.

✦ Table of Contents

Preface
Contents
Of Evolution, Systems and Complexity
1 Introduction
2 Of Evolution, Systems and Complexity
3 Of Complex Evolution Models
4 Of Evolution of Complexity
4.1 Introduction
4.2 The Aevol Model
4.2.1 Information Coding in Aevol
4.3 Designing an Impossible Experiment
4.4 Results: The Complexity Ratchet
5 Conclusion
References
Modeling Complex Biological Systems: Tackling the Parameter Curse through Evolution
1 Introduction
2 Case Study: The lac Operon and Bistability
2.1 Background: ``State of the Art''
3 Eco-evolutionary Model of the lac Operon
3.1 Analysis of the Eco-evolutionary Dynamics of the Model
3.2 Internal Validation of the Model
3.3 Experimental Validation of the Model Results
3.4 Why Avoid Bistability?
4 Discussion
References
Direction and Constraint in Phenotypic Evolution: Dimension Reduction and Global Proportionality in Phenotype Fluctuation and Responses
1 Introduction
2 Constraint in a Steady-Growth System: Global Proportionality Law
3 Experimental Confirmation
4 Global Proportional Changes in Gene Expression Beyond the Simple Theory
5 Emergence of Global Proportionality Through Evolution: Formation of a Dominant Mode
5.1 Catalytic Reaction Network Model for Numerical Evolution
5.2 Emergent Global Proportionality Through Evolution
6 Evolutionary Dimension Reduction Hypothesis
7 Global Proportionality Between Responses by Environmental and Evolutionary Adaptations
7.1 Verification by the Reaction Network Model
7.2 Experimental Confirmation by Laboratory Evolution
8 Evolutionary Fluctuation-Response Relationship
9 Discussion
References
Life's Attractors Continued: Progress in Understanding Developmental Systems Through Reverse Engineering and In Silico Evolution
1 Introduction
2 Reverse Engineering with Gene Circuits
3 Challenges in Reverse-Engineering Gap Gene Networks
3.1 Bottleneck No. 1: Quantitative Data
3.2 Bottleneck No. 2: Model Fitting
4 The Art and Science of Network Decomposition
4.1 Bottom-up Decomposition into Regulatory Mechanisms
4.2 Top-Down Decomposition into Dynamical Modules
5 Drifting Shifts: The Evolution of the Gap Gene System
5.1 The Scuttle Fly Megaselia abdita: Compensatory Evolution
5.2 The Moth Midge Clogmia albipunctata: Shifts as Dynamic Fossils?
5.3 Evolving Mechanisms and Network Drift
6 Outlook: in silico Evolution
7 Conclusion
References
Systems Biology Approach to the Origin of the Tetrapod Limb
1 Introduction
2 Homology Debates on Fins and Limbs
3 Global Asymmetric Organization in Limb Development
4 Turing Mechanism as Local Interactions
5 Intertwining the Turing Mechanism and Positional Information in Limb Development
6 Emergence of Homology by Coupling Turing Mechanism and Positional Information
7 Evolutionary Systems Biology Toward the Genotype-Phenotype Mapping
References
Experimental Evolution to Understand the Interplay Between Genetics and Adaptation
1 Understanding Adaptation by Experimental Evolution
2 Experimental Evolution to Study Genes and Traits
2.1 Evolving the Progeny of Crosses to Understand the Genetic Structure of Complex Traits
2.2 Gene Essentiality and Evolvability
2.3 Compensatory Trajectories After Gene Loss
3 Outlook: Using Experimental Evolution for Systems Genetics
4 Conclusions
References
Addressing Evolutionary Questions with Synthetic Biology
1 Introduction
2 Synthetic Regulatory Networks
2.1 Exploring Network Design Space with Synthetic Regulatory Networks
2.2 Exploring Evolutionary Dynamics with Synthetic Regulatory Networks
3 Rewired Regulatory Networks
4 Synthetic Genomics
4.1 Extending the Alphabet of Life
4.2 Synthetic Karyotyping
4.3 Synthetic Viruses
4.4 Designing a Synthetic Minimal Genome
4.5 Synthetic Self-Replicating Systems in Cell-Like Compartments
5 Outlook
References
An Evolutionary Systems Biology View on Metabolic System Structure and Dynamics
1 Introduction
2 Structural Features of Metabolic Systems
2.1 Metabolic Maps as Graphs (Networks)
2.2 Connectivity Within Metabolic Networks
2.3 Modules in Metabolic Networks
2.4 Network Motifs
3 Dynamics of Metabolic Systems
3.1 Overflow Metabolism and the Respiration-Fermentation Switch
3.2 Carbon Preference and Catabolic Pathway Switching
3.3 Oscillations and Bistability
4 Evolutionary and Physical Drivers (and Constraints) on Metabolic Systems
4.1 Thermodynamics
4.2 Biomass and Energy Production
4.3 Maintenance of Metabolic Gradients and Physicochemical Constraints
5 Conclusion and Future Outlook
References
Robustness and Evolvability in Transcriptional Regulation
1 Introduction
2 Robustness and Evolvability of Gene Regulatory Circuit Components
2.1 Robustness and Evolvability of Transcription Factors
2.1.1 The Robustness of the Protein Structure of Transcription Factors
2.1.2 Robustness in Duplicated Transcription Factors
2.1.3 Many Transcription Factors Are Clients of the Molecular Chaperone HSP90
2.1.4 The Evolvability of Transcription Factors
2.2 Robustness and Evolvability of Transcription Factor Binding Sites
2.2.1 The Robustness of Regulatory Sequences
2.2.2 The Evolvability of Regulatory Sequences
3 Robustness and Evolvability of Whole Gene Regulatory Circuits
4 Concluding Remarks
References
Understanding the Genotype-Phenotype Map: Contrasting Mathematical Models
1 Introduction
2 Epigenesis and Epigenetic Factors
3 GPM Models
4 Mendelian and Quantitative Genetics
5 Evolutionary Genetics Models on Epistasis
6 Wagner's Model
7 Genetic-Epigenetic Models
8 The Lattice Pattern Formation Model
9 Models Including Morphogenesis: The Tooth Model
10 The Differences Between Purely Genetic Models and Genetic-Epigenetic Models
10.1 Genetic-Epigenetic Models Reproduce Individual Phenotypes and the GPM
10.2 Epigenetic Factors Inform About the Space of Possible Networks
10.3 In Genetic-Epigenetic Models Not All Aspects of the Phenotype Can Change
10.4 Genetic-Epigenetic Models Can Explain Changes in Phenotypic Dimensionality and Novelty
10.5 Genetic-Epigenetic Models Can Explain How the GPM Evolves
11 Conclusions
References
Dynamical Modularity of the Genotype-Phenotype Map
1 Introduction: Modular Traits and the Genotype-Phenotype Map
2 Functional Modules
3 Structural Modules
4 Regulatory Modules
5 Dynamical Modules: Definition and Detection
6 Dynamical Modules: Gradients, Gap Genes, and the AC/DC Circuit
7 Dynamical Modules Everywhere
8 Evolutionary Implications
9 Conclusions
References
Index