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Proceedings of the National Academy of Sciences of the United States of America DOI:10.1073/pnas.0810388105

Genetic architecture of complex traits: large phenotypic effects and pervasive epistasis.

Publication TypeJournal Article
Year of Publication2008
AuthorsShao, H, Burrage, LC, Sinasac, DS, Hill, AE, Ernest, SR, O'Brien, W, Courtland, HW, Jepsen, KJ, Kirby, A, Kulbokas, EJ, Daly, MJ, Broman, KW, Lander, ES, Nadeau, JH
JournalProceedings of the National Academy of Sciences of the United States of America
Date Published2008/12/16

The genetic architecture of complex traits underlying physiology and disease in most organisms remains elusive. We still know little about the number of genes that underlie these traits, the magnitude of their effects, or the extent to which they interact. Chromosome substitution strains (CSSs) enable statistically powerful studies based on testing engineered inbred strains that have single, unique, and nonoverlapping genetic differences, thereby providing measures of phenotypic effects that are attributable to individual chromosomes. Here, we report a study of phenotypic effects and gene interactions for 90 blood, bone, and metabolic traits in a mouse CSS panel and 54 traits in a rat CSS panel. Two key observations emerge about the genetic architecture of these traits. First, the traits tend to be highly polygenic: across the genome, many individual chromosome substitutions each had significant phenotypic effects and, within each of the chromosomes studied, multiple distinct loci were found. Second, strong epistasis was found among the individual chromosomes. Specifically, individual chromosome substitutions often conferred surprisingly large effects (often a substantial fraction of the entire phenotypic difference between the parental strains), with the result that the sum of these individual effects often dramatically exceeded the difference between the parental strains. We suggest that strong, pervasive epistasis may reflect the presence of several phenotypically-buffered physiological states. These results have implications for identification of complex trait genes, developmental and physiological studies of phenotypic variation, and opportunities to engineer phenotypic outcomes in complex biological systems.