Physiol. Genomics Fuel your research with LabChart
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
 QUICK SEARCH:   [advanced]


     


Physiol. Genomics (August 10, 2004). doi:10.1152/physiolgenomics.00129.2004
This Article
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
19/2/218    most recent
00129.2004v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Zhao, W.
Right arrow Articles by Wu, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Zhao, W.
Right arrow Articles by Wu, R.
Submitted on May 27, 2004
Accepted on August 5, 2004

A Unifying Statistical Model for QTL Mapping of Genotype x Sex Interaction for Developmental Trajectories

Wei Zhao1, Chang-Xing Ma1, James M Cheverud2, and Rongling Wu1*

1 Department of Statistics, University of Florida, Gainesville, FL, USA
2 Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO, USA

* To whom correspondence should be addressed. E-mail: rwu{at}stat.ufl.edu.

Most organisms display remarkable differences in morphological, anatomical and developmental features between the two sexes. It has been recognized that these sex-dependent differences are controlled by an array of specific genetic factors, mediated through various environmental stimuli. In this article, we present a unifying statistical model for mapping quantitative trait loci (QTL) that are responsible for sexual differences in growth trajectories during ontogenetic development. This model is derived within the maximum likelihood context, incorporated by sex stimulated differentiation in growth form that is described by mathematical functions. A typical structural model is implemented to approximate time-dependent covariance matrices for longitudinal traits. This model allows for a number of biologically meaningful hypothesis tests regarding the effects of QTL on overall growth trajectories or particular stages of development. It is in particular powerful to test whether and how the genetic effect of QTL are expressed differently in different sexual backgrounds. Our model has been employed to map QTL affecting body mass growth trajectories in both male and female mice of an F2population derived from the Large (LG/J) and Small (SM/J) mouse strains. We detected four growth QTL on chromosomes 6, 7, 11 and 15, two of which trigger different effects on growth curves between the two sexes. All the four QTL display significant genotype-sex interaction effects on the timing of maximal growth rate in the ontogenetic growth of mice. The implications of our model for studying the genetic architecture of growth trajectories and its extensions to some more general situations are discussed.




This article has been cited by other articles:


Home page
GeneticsHome page
R. Yang, H. Gao, X. Wang, J. Zhang, Z.-B. Zeng, and R. Wu
A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits
Genetics, November 1, 2007; 177(3): 1859 - 1870.
[Abstract] [Full Text] [PDF]


Home page
GeneticsHome page
W. Zhao, H. Li, W. Hou, and R. Wu
Wavelet-Based Parametric Functional Mapping of Developmental Trajectories With High-Dimensional Data
Genetics, July 1, 2007; 176(3): 1879 - 1892.
[Abstract] [Full Text] [PDF]


Home page
GeneticsHome page
M. Gonzalo, T. J. Vyn, J. B. Holland, and L. M. McIntyre
Mapping Density Response in Maize: A Direct Approach for Testing Genotype and Treatment Interactions
Genetics, May 1, 2006; 173(1): 331 - 348.
[Abstract] [Full Text] [PDF]


Home page
GeneticsHome page
R. Wu and W. Hou
A Hyperspace Model to Decipher the Genetic Architecture of Developmental Processes: Allometry Meets Ontogeny
Genetics, January 1, 2006; 172(1): 627 - 637.
[Abstract] [Full Text] [PDF]


Home page
GeneticsHome page
R. Wu, C.-X. Ma, W. Hou, P. Corva, and J. F. Medrano
Functional Mapping of Quantitative Trait Loci That Interact With the hg Mutation to Regulate Growth Trajectories in Mice
Genetics, September 1, 2005; 171(1): 239 - 249.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
W. Zhao, Y. Q. Chen, G. Casella, J. M. Cheverud, and R. Wu
A non-stationary model for functional mapping of complex traits
Bioinformatics, May 15, 2005; 21(10): 2469 - 2477.
[Abstract] [Full Text] [PDF]


Home page
GeneticsHome page
W. Zhao, J. Zhu, M. Gallo-Meagher, and R. Wu
A Unified Statistical Model for Functional Mapping of Environment-Dependent Genetic Expression and Genotype x Environment Interactions for Ontogenetic Development
Genetics, November 1, 2004; 168(3): 1751 - 1762.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
Visit Other APS Journals Online
Copyright © 2004 by the American Physiological Society.