An introduction to systems genetics
- Abstract:
- Systems genetics is an emerging field based on old approaches going back to the genetic studies performed by Gregor Mendel (Mendel 1866). Mendel's experiments primarily focused on explaining inheritance of single traits and their phenotypes – for example how specific genetic alleles influence colour or size of peas – but recently developed technologies can comprehensively dissect the genetic architecture of complex traits and quantify how genes interact to shape phenotypes by using natural variation or experimental perturbations as a basis to understand links from genotypes to phenotypes. This exciting new area has recently been termed ‘systems genetics’ (Civelek and Lusis 2014). While the basic, underlying questions are not new, systems genetics builds upon major methodological advances that facilitate the measurement of genotypes and pheno-types in a previously unforeseen and comprehensive manner. With this arsenal at hand, one of the major aims of systems genetics is to understand “how genetic information is integrated, coordinated and ultimately transmitted through molecular, cellular and physiological networks to enable the higher-order functions and emergent properties of biological systems” (Nadeau and Dudley 2011). Definition of systems genetics. Systems genetics is born out of a synthesis of multiple fields: it integrates approaches of genetics, genomics, systems biology and ‘phenomics’, that is, our increased ability to obtain quantitative and detailed measurements on a broad spectrum of phenotypes. One of the first papers using the term ‘systems genetics’ defines it as “the integration and anchoring of multi-dimensional data-types to underlying genetic variation” (Threadgill 2006). Since then, many studies have aimed at integrating genome-wide data across many different levels, and possibly different environments, in approaches that are closely related to quantitative genetics. In our view, a systems genetic approach should bring together three dimensions: it should combine (i) a genome-wide analysis with (ii) many quantitative phenotypes, both at the molecular and organismal level, (iii) in many different conditions or environments (Fig. 1.1).