A century after Fisher: time for a new paradigm in quantitative genetics Ronald M. Nelson, Mats E. Pettersson, and O ¨ rjan Carlborg Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Box 7078, SE-750 07 Uppsala, Sweden Quantitative genetics traces its roots back through more than a century of theory, largely formed in the absence of directly observable genotype data, and has remained essentially unchanged for decades. By contrast, molec- ular genetics arose from direct observations and is cur- rently undergoing rapid changes, making the amount of available data ever greater. Thus, the two disciplines are disparate both in their origins and their current states, yet they address the same fundamental question: how does the genotype affect the phenotype? The rapidly accumulating genomic data necessitate sophisticated analysis, but many of the current tools are adaptations of methods designed during the early days of quantita- tive genetics. We argue here that the present analysis paradigm in quantitative genetics is at its limits in regards to unraveling complex traits and it is necessary to re-evaluate the direction that genetic research is taking for the field to realize its full potential. The quantitative genetics paradigm Nearly a century ago, Sir Ronald Fisher’s theoretical advancements established the theory that formed the field of quantitative genetics (Box 1). Since then, the field has been extremely productive while conforming to this central paradigm. However, the anomalous results that are emerg- ing from analyses of large data sets collected using new molecular genetics and genomics technologies cast doubts as to whether the current quantitative genetics paradigm is sufficient to meet the challenges of genetically dissecting complex trait variation. The current models are stretched to their limits and require substantial adjustments to explain and deal with the observations. Here, we argue that the field is now in a crisis and at a point where a new genetics framework is needed that can encompass previous results as well as what are, at present, anomalies (see ‘The current crisis’). Genetics is a field of the future, but a paradigm shift is needed to realize its full potential in agriculture, medicine, and evolutionary biology. Overall, there is strong resistance to change in this field; considerable efforts are spent on either showing that new data do not present a major anomaly [1,2], even though many of the original assumptions of Fisher no longer hold [3–15] or focusing on data or technologies that do not challenge the paradigm [1,2,16,17]. However, it is difficult to ignore the fact that research utilizing genomic data, in many ways, has outpaced developments in quantitative genetic theory. Therefore, it is timely to look back on what has been achieved, while asking: is the original paradigm the foundation upon which to build the future? Will ideas presented at a time when no molecular data were available be appropriate for not only quantifying the contribution of genes to complex traits, but also guiding solutions to challenges involved in predicting the phenotypes of indi- viduals within a population as well as understanding the genetic architecture of traits expressed in the same indi- vidual? The current crisis: ample challenges for quantitative genetics theory In 1918, Fisher provided a new conceptual way to think about genetic inheritance that made it possible to interpret the findings in biometrical genetics within the Mendelian schemes of inheritance [18] (Box 1). By establishing the additive paradigm of quantitative genetics, a framework was provided that facilitated the dissection of the genetic Opinion Glossary Additive approach: the assumption that the contribution of genes to the phenotypic trait are independent of each other and sum up to the total genetic contribution. Biometrics: the application of statistical analysis to biological data. Epigenetic effects: genome-linked effects on the phenotype not caused by the DNA sequence. Epistasis: when the alleles at one locus influence the effects of alleles at other loci [42]. Genetic capacitation: the effect where one allele at a given locus (the capacitator) amplifies the effect of alleles at other loci. Genome-wide association study (GWAS): analysis that examines the associa- tion between the genetic variants at a large number of genotyped loci in the genome with the expression of a trait in the studied population Genotype–phenotype map (GP map): a schematic representation of the mean phenotypic value for each genotypic class. Genotypic class: all the individuals in a population that share a common single- or multilocus genotype, depending on context. Infinitesimal model: a model describing the phenotypic variation in a population as the contribution of an infinite number of genes, each making a small additive contribution to the trait [19]. Variance heterogeneity: when the phenotypic variance differs between genotype classes. 0168-9525/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tig.2013.09.006 Corresponding author: Nelson, R.M. (ronnie.nelson@slu.se). Keywords: quantitative genetics; paradigm shift; Fisher; phenotype–genotype map; additive model; epistasis. Trends in Genetics, December 2013, Vol. 29, No. 12 669