Book contents
- Frontmatter
- Contents
- List of contributors
- 1 An introduction to systems genetics
- 2 Computational paradigms for analyzing genetic interaction networks
- 3 Mapping genetic interactions across many phenotypes in metazoan cells
- 4 Genetic interactions and network reliability
- 5 Synthetic lethality and chemoresistance in cancer
- 6 Joining the dots: network analysis of gene perturbation data
- 7 High-content screening in infectious diseases: new drugs against bugs
- 8 Inferring genetic architecture from systems genetics studies
- 9 Bayesian inference for model selection: an application to aberrant signalling pathways in chronic myeloid leukaemia
- 10 Dynamic network models of protein complexes
- 11 Phenotype state spaces and strategies for exploring them
- 12 Automated behavioural fingerprinting of Caenorhabditis elegans mutants
- Index
- Plate Section
- References
8 - Inferring genetic architecture from systems genetics studies
Published online by Cambridge University Press: 05 July 2015
- Frontmatter
- Contents
- List of contributors
- 1 An introduction to systems genetics
- 2 Computational paradigms for analyzing genetic interaction networks
- 3 Mapping genetic interactions across many phenotypes in metazoan cells
- 4 Genetic interactions and network reliability
- 5 Synthetic lethality and chemoresistance in cancer
- 6 Joining the dots: network analysis of gene perturbation data
- 7 High-content screening in infectious diseases: new drugs against bugs
- 8 Inferring genetic architecture from systems genetics studies
- 9 Bayesian inference for model selection: an application to aberrant signalling pathways in chronic myeloid leukaemia
- 10 Dynamic network models of protein complexes
- 11 Phenotype state spaces and strategies for exploring them
- 12 Automated behavioural fingerprinting of Caenorhabditis elegans mutants
- Index
- Plate Section
- References
Summary
In recent years many efforts have been invested in comprehensively evaluating the behavior and relationships of all genes/proteins in a particular biological system and at a particular state. Here, we review how genome-wide RNAi screens together with mass spectrometry can be integrated to generate high-confidence functional interac- tome networks. Next we review the mathematical modeling methods available today that allow the computational reconstruction of such networks. Network modeling will play an important role in generating hypotheses, driving further experimentation and thus novel insights into network structure and behavior.
Introduction
Most biologists study a specific biological problem by investigating the activities of a limited number of genes or proteins involved in a particular biological process. This traditional approach is critical and has proven to be extremely successful to reveal the detailed molecular functions of individual genes and proteins. For example, genetic studies of embryonic patterning in Drosophila identified about 40 genes with striking segmentation defects that fell into distinct phenotypic classes: gap genes, pair rule genes, segment polarity genes, and homeotic genes (Nusslein-Volhard & Wieschaus 1980). Detailed analyses of the mutant phenotypes and functions of even this relatively small set of genes led to a comprehensive molecular framework of the process of embryonic patterning (St Johnston & Nusslein-Volhard 1992). Reductionist approaches, however, are not sufficient for generating the big picture of how a biological system, including multiple levels of many different gene products and the interactions among them, works at different physiological states or developmental stages (Friedman & Perrimon 2007). Thus, as our knowledge of individual genes and proteins accumulates, there is a need to comprehensively evaluate the behavior and relationships of all genes/proteins in a particular biological system and at a particular state. In recent years, progress has been made in multi cellular organisms towards this goal mostly in tissue culture, a platform that allows a sufficient amount of homogeneous material to be easily obtained.
- Type
- Chapter
- Information
- Systems GeneticsLinking Genotypes and Phenotypes, pp. 139 - 160Publisher: Cambridge University PressPrint publication year: 2015