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8 - Inferring genetic architecture from systems genetics studies
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- By Xiaoyun Sun, Brandeis University, Stephanie Mohr, Harvard Medical School, Arunachalam Vinayagam, Harvard Medical School, Pengyu Hong, Brandeis University, Norbert Perrimon, Harvard Medical School
- Edited by Florian Markowetz, Michael Boutros
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- Book:
- Systems Genetics
- Published online:
- 05 July 2015
- Print publication:
- 02 July 2015, pp 139-160
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- Chapter
- Export citation
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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.