BACKGROUND: Genetic variation explains a considerable part of observed phenotypic variation in gene expression networks. This variation has been shown to be located both locally (cis) and distally (trans) to the genes being measured. Here we explore to which degree the phenotypic manifestation of local and distant polymorphisms is a dynamic feature of regulatory design. RESULTS: By combining mathematical models of gene expression networks with genetic maps and linkage analysis we find that very different network structures and regulatory motifs give similar cis/trans linkage patterns. However, when the shape of the cis-regulatory input functions is more nonlinear or threshold-like, we observe for all networks a dramatic increase in the phenotypic expression of distant compared to local polymorphisms under otherwise equal conditions. CONCLUSION: Our findings indicate that genetic variation affecting the form of cis-regulatory input functions may reshape the genotype-phenotype map by changing the relative importance of cis and trans variation. Our approach combining nonlinear dynamic models with statistical genetics opens up for a systematic investigation of how functional genetic variation is translated into phenotypic variation under various systemic conditions.
BACKGROUND: Genetic variation explains a considerable part of observed phenotypic variation in gene expression networks. This variation has been shown to be located both locally (cis) and distally (trans) to the genes being measured. Here we explore to which degree the phenotypic manifestation of local and distant polymorphisms is a dynamic feature of regulatory design. RESULTS: By combining mathematical models of gene expression networks with genetic maps and linkage analysis we find that very different network structures and regulatory motifs give similar cis/trans linkage patterns. However, when the shape of the cis-regulatory input functions is more nonlinear or threshold-like, we observe for all networks a dramatic increase in the phenotypic expression of distant compared to local polymorphisms under otherwise equal conditions. CONCLUSION: Our findings indicate that genetic variation affecting the form of cis-regulatory input functions may reshape the genotype-phenotype map by changing the relative importance of cis and trans variation. Our approach combining nonlinear dynamic models with statistical genetics opens up for a systematic investigation of how functional genetic variation is translated into phenotypic variation under various systemic conditions.
Authors: Arvind Raghavan; Rachel L Ogilvie; Cavan Reilly; Michelle L Abelson; Shalini Raghavan; Jayprakash Vasdewani; Mitchell Krathwohl; Paul R Bohjanen Journal: Nucleic Acids Res Date: 2002-12-15 Impact factor: 16.971
Authors: Eric E Schadt; Stephanie A Monks; Thomas A Drake; Aldons J Lusis; Nam Che; Veronica Colinayo; Thomas G Ruff; Stephen B Milligan; John R Lamb; Guy Cavet; Peter S Linsley; Mao Mao; Roland B Stoughton; Stephen H Friend Journal: Nature Date: 2003-03-20 Impact factor: 49.962
Authors: Tong Ihn Lee; Nicola J Rinaldi; François Robert; Duncan T Odom; Ziv Bar-Joseph; Georg K Gerber; Nancy M Hannett; Christopher T Harbison; Craig M Thompson; Itamar Simon; Julia Zeitlinger; Ezra G Jennings; Heather L Murray; D Benjamin Gordon; Bing Ren; John J Wyrick; Jean-Bosco Tagne; Thomas L Volkert; Ernest Fraenkel; David K Gifford; Richard A Young Journal: Science Date: 2002-10-25 Impact factor: 47.728
Authors: Jon Olav Vik; Arne B Gjuvsland; Liren Li; Kristin Tøndel; Steven Niederer; Nicolas P Smith; Peter J Hunter; Stig W Omholt Journal: Front Physiol Date: 2011-12-28 Impact factor: 4.566