Running Head: Systems Biology and Natural Genetic Variation

The vast majority of measurable phenotypes within species are not fixed and populations contain significant levels of natural genetic variation among individuals affecting phenotypes from development to metabolism to abiotic resistance. All of which are of interest to both basic and applied biologists from a myriad of fields. Despite the ubiquity of this variation there is very little known about the molecular underpinnings of natural genetic variation or the forces behind its maintenance or generation. Recent advances in both genomics and systems biology are beginning to allow some of the first direct empirical tests of a suite of parameters that while being a foundation of natural variation were largely left to the theoreticians. These include the following basic questions: what is Pleiotropy? ; how many genes control a given quantitative trait? ; where is the heritability? and how is conditional genetic variation generated. This review highlights progress made towards addressing these questions via the use of systems biological inquiries into natural variation. www.plantphysiol. org on January 22, 2018 Published by Downloaded from Copyright © 2009 American Society of Plant Biologists. All rights reserved. Introduction The vast majority of measurable phenotypes within species are not fixed and populations contain significant levels of natural genetic variation among individuals for traits ranging from development to metabolism to abiotic resistance. While the presence of this diversity is widely acknowledged, much less is known about the consequences of natural genetic variation or the forces behind its maintenance or generation which are fundamental to evolution and ecology. In addition, a wide range of applied fields are finding a need to better understand the systematic basis of natural variation, including efforts to improve crop yields via breeding and attempts towards individualized medicine for humans. These efforts are complicated because this diversity is typically polygenic and can involve complex interactions with numerous factors including, but not limited to, the environment, development, epistatic interactions between genes and potential higher-order interaction among these factors (Falconer and Mackay, 1996; Lynch and Walsh, 1998; Wentzell and Kliebenstein, 2008). While most studies on natural variation todate have queried one or two phenotypes, there is an obvious need for more intricate, genomic and broad phenotypic analyses of natural variation to address the fundamentals of quantitative genetics. Systems Biology is a newly defined and emerging field that attempts to conduct massively parallel experiments that differentially perturb a system to identify the properties of the system being tested (Ideker et al., 2001; Kitano, 2002). This has led to the systematic identification of networks controlling gene expression within bacteria, protein interactions in numerous species and metabolic networks (Fiehn, 2002; Rosenfeld et al., 2002; Covert et al., 2004; Martins et al., 2004). The utility of systems biology has gone beyond the ability to www.plantphysiol. org on January 22, 2018 Published by Downloaded from Copyright © 2009 American Society of Plant Biologists. All rights reserved. describe individual phenotypes to begin describing the shape of the mechanistic interactions or rules that define how the networks can be shaped (Albert, 2005). Systems Biology has also begun to make great headway in helping to better understand and describe plant biology (Brady and Provart, 2009). This includes the development of key approaches to combine metabolomic and transcript data to identify novel enzymatic and regulatory genes (Hirai et al., 2005; Hansen et al., 2007). This approach has further been extended to establish links between gene expression and root development and between development and abiotic stress within Arabidopsis thaliana (Brady et al., 2007; Dinneny et al., 2008). As such, the concept and implementation of systems biology is showing great promise to establish both individual gene linkages and more theoretical rules guiding these linkages. Numerous systems biology approaches are now being applied to the study of natural genetic variation including transcriptomics (Keurentjes et al., 2008; Kliebenstein, 2009), metabolomics (Keurentjes, 2009; Kliebenstein, 2009), proteomics (Stylianou et al., 2008), compilation of large physiological datasets (Keurentjes et al., 2008), network analysis tools (Hansen et al., 2008; Kliebenstein, 2009) and whole genome sequencing (Borevitz and Chory, 2004; Nordborg and Weigel, 2008). Each of these approaches has a myriad of strengths and aid in the rapid identification of the genes underlying phenotypes ranging from flowering time to biotic resistance mechanisms. However, their potential uses in understanding the genetic underpinnings of specific biological phenotypes have been reviewed extensively in the past several years as described in the preceding citations. Given the depth of published reviews on the use of systems biology to identify causal genes in natural genetic variation, I will instead use this review to focus on how these genomics approaches are allowing researchers to begin developing www.plantphysiol. org on January 22, 2018 Published by Downloaded from Copyright © 2009 American Society of Plant Biologists. All rights reserved. a systems view of how the genetic architecture of natural variation is shaped and what evolutionary events are shaping this variation. At its essence, the application of systems biology to the analysis of natural genetic variation is allowing the research community to begin directly testing the long standing and fundamental yet little understood underpinnings of quantitative genetics that had previously been yielded to the theoreticians. This combination also benefits Systems Biology experiments as natural genotypes typically differ at hundreds to thousands of genes providing access to dramatically more than a single perturbation at a time. This combination provides access to experimental tests of several theoretical underpinnings of natural genetic diveristy that could be summed up with the following basic questions: What is Pleiotropy? , How many genes control a given quantitative trait? Where is the heritability? and How is conditional genetic variation generated? This list of questions is by no means exhaustive, for instance epistasis is a major factor in quantitative genetics but the use of systems biology to study epistasis has been dealt with in other reviews (Carlborg and Haley, 2004; Phillips, 2008; Kliebenstein, 2009). Each of the stated questions is beginning to be illuminated by recent systems biology interrogations of natural variation and will be a separate focus of this review. What is Pleiotropy? One of the first lectures in any introductory genetics class attempts to define the meaning of pleiotropy. While the general definition is simple enough, “when a gene influences multiple traits/phenotypes,” the mechanistic basis generating pleiotropy, or even the frequency to which it occurs are not frequently investigated nor understood. Often in molecular or Mendelian genetics when a mutation in a single gene is observed to have a predominant impact on one phenotype and smaller affects on other phenotypes, this is disregarded as being a www.plantphysiol. org on January 22, 2018 Published by Downloaded from Copyright © 2009 American Society of Plant Biologists. All rights reserved. secondary or indirect consequence and not an inherent part of the biology of the gene. Further, it is assumed that these secondary consequences are due to the presence of the gene within a network that responds both locally (direct effect) and distally (secondary effect) to the perturbation in the given gene. However, it is not known if these “secondary” linkages are random consequences of network architecture or if these distal network connections are present to generate pleiotropic linkages and that pleiotropy may be a direct part of the gene’s biology within the plant in the natural setting. In quantitative genetic systems where most gene polymorphisms have moderate to small effects, it becomes more difficult to discern local from distal effects by using phenotypic magnitude. However, pleiotropy takes on added importance because the presence of pleiotropy means that selection upon one phenotype can have unexpected consequences on other phenotypes if the phenotypes can be effected by the same gene. Systems biology allows for a unique survey into pleiotropy as it allows for a dramatic expansion in the number of phenotypes that can be measured from the typical study of one to a dozen phenotypes to expression studies querying thousands of genes across natural populations. Within these studies, evidence for high levels of pleiotropy for natural genetic polymorphisms arises from the presence of hotspots when measuring quantitative variation in either transcripts or metabolites (Keurentjes et al., 2008; Keurentjes, 2009; Kliebenstein, 2009; Kliebenstein, 2009). These hotspots are regions of the genome where a genetic polymorphism is linked to phenotypic diversity in thousands of transcripts or dozens of metabolites, vastly more than would be expected by chance. Often, this pleiotropy is used to argue for the presence of a polymorphic regulatory gene in this hotspot. Several transcript hotspots have been cloned and shown to be regulatory genes that have local/direct effects on dozens of genes representing a local network and this effect then www.plantphysiol. org on January 22, 2018 Published by Downloaded from Copyright © 2009 American Society of Plant Biologists. All rights reserved. permeates to distal/indirect effects on hundreds of additional genes (Keurentjes et al., 2007; Sønderby et al., 2007; Wentzell et al., 2007). In one case, the regulatory gene encoded a enzyme within a secondary metabolite pathway that altered both transcript and m