Statistical epistasis is a generic feature of gene regulatory networks.

@article{citeulike:1064979, abstract = {Functional dependencies between genes are a defining characteristic of gene networks underlying quantitative traits. However, recent studies show that the proportion of the genetic variation that can be attributed to statistical epistasis varies from almost zero to very high. It is thus of fundamental as well as instrumental importance to better understand whether different functional dependency patterns among polymorphic genes give rise to distinct statistical interaction patterns or not. Here we address this issue by combining a quantitative genetic model approach with genotype-phenotype models capable of translating allelic variation and regulatory principles into phenotypic variation at the level of gene expression. We show that gene regulatory networks with and without feedback motifs can exhibit a wide range of possible statistical genetic architectures with regard to both type of effect explaining phenotypic variance and number of apparent loci underlying the observed phenotypic effect. Although all motifs are capable of harboring significant interactions, positive feedback gives rise to higher amounts and more types of statistical epistasis. The results also suggest that the inclusion of statistical interaction terms in genetic models will increase the chance to detect additional QTLs as well as functional dependencies between genetic loci over a broad range of regulatory regimes. The paper illustrates how statistical genetic methods can fruitfully be combined with nonlinear systems dynamics to elucidate biological issues beyond reach of each methodology in isolation.}, address = {Cigene - Norvegian University of Life Sciences.}, author = {Gjuvsland, Arne B B. and Hayes, Ben J J. and Omholt, Stig W W. and Carlborg, Orjan }, citeulike-article-id = {1064979}, doi = {10.1534/genetics.106.058859}, issn = {0016-6731}, journal = {Genetics}, keywords = {epistasis, network, regulation, statistics}, month = {October}, posted-at = {2008-04-17 13:16:33}, priority = {2}, title = {Statistical epistasis is a generic feature of gene regulatory networks.}, url = {http://dx.doi.org/10.1534/genetics.106.058859}, year = {2006} }

TY - JOUR ID - citeulike:1064979 L3 - citeulike-article-id:1064979 TI - Statistical epistasis is a generic feature of gene regulatory networks. JF - Genetics AD - Cigene - Norvegian University of Life Sciences. SN - 0016-6731 N2 - Functional dependencies between genes are a defining characteristic of gene networks underlying quantitative traits. However, recent studies show that the proportion of the genetic variation that can be attributed to statistical epistasis varies from almost zero to very high. It is thus of fundamental as well as instrumental importance to better understand whether different functional dependency patterns among polymorphic genes give rise to distinct statistical interaction patterns or not. Here we address this issue by combining a quantitative genetic model approach with genotype-phenotype models capable of translating allelic variation and regulatory principles into phenotypic variation at the level of gene expression. We show that gene regulatory networks with and without feedback motifs can exhibit a wide range of possible statistical genetic architectures with regard to both type of effect explaining phenotypic variance and number of apparent loci underlying the observed phenotypic effect. Although all motifs are capable of harboring significant interactions, positive feedback gives rise to higher amounts and more types of statistical epistasis. The results also suggest that the inclusion of statistical interaction terms in genetic models will increase the chance to detect additional QTLs as well as functional dependencies between genetic loci over a broad range of regulatory regimes. The paper illustrates how statistical genetic methods can fruitfully be combined with nonlinear systems dynamics to elucidate biological issues beyond reach of each methodology in isolation. KW - epistasis KW - network KW - regulation KW - statistics AU - Gjuvsland, Arne B AU - Hayes, Ben J AU - Omholt, Stig W AU - Carlborg, Orjan PY - 2006/10/08/ UR - http://dx.doi.org/10.1534/genetics.106.058859 ER -