- THIS ARTICLE
- Full Text (Rapid PDF)
-
All Versions of this Article:
genetics.106.058859v1
175/1/411 most recent - Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- CITING ARTICLES
- Citing Articles via HighWire
- Citing Articles via Google Scholar
- GOOGLE SCHOLAR
- Articles by Gjuvsland, A. B.
- Articles by Carlborg, O.
- Search for Related Content
- PUBMED
- PubMed Citation
- Articles by Gjuvsland, A. B.
- Articles by Carlborg, O.
doi:10.1534/genetics.106.058859
A more recent version of this article appeared on January 1, 2007.
REGULAR RESEARCH PAPERS |
Statistical epistasis is a generic feature of gene regulatory networks
Arne B. Gjuvsland 1*, Ben J. Hayes 2, Stig W. Omholt 1 and Örjan Carlborg 3
1 Cigene - Norvegian University of Life Sciences
2 Department of Primary Industries
3 Uppsala University
* To whom correspondence should be addressed. E-mail: arne.gjuvsland{at}cigene.no.
Submitted on April 3, 2006
Revised on June 28, 2006
Accepted on 18 September 2006
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.
Key Words: Epistasis, Feedback, Gene regulatory networks, Systems biology
This article has been cited by other articles:
 |
|
 |
|
  H. Rajasingh, A. B. Gjuvsland, D. I. Vage, and S. W. Omholt When Parameters in Dynamic Models Become Phenotypes: A Case Study on Flesh Pigmentation in the Chinook Salmon (Oncorhynchus tshawytscha) Genetics, June 1, 2008; 179(2): 1113 - 1118. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. N. Benfey and T. Mitchell-Olds From Genotype to Phenotype: Systems Biology Meets Natural Variation Science, April 25, 2008; 320(5875): 495 - 497. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. J. Wittkopp, B. K. Haerum, and A. G. Clark Independent Effects of cis- and trans-regulatory Variation on Gene Expression in Drosophila melanogaster Genetics, March 1, 2008; 178(3): 1831 - 1835. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. Barendse, B. E. Harrison, R. J. Hawken, D. M. Ferguson, J. M. Thompson, M. B. Thomas, and R. J. Bunch Epistasis Between Calpain 1 and Its Inhibitor Calpastatin Within Breeds of Cattle Genetics, August 1, 2007; 176(4): 2601 - 2610. [Abstract] [Full Text] [PDF]
|
|