A large-sample QTL study in mice: I. Growth

A large-sample QTL study in mice: I. Growth By use of long-term selection lines for high and low growth, a large-sample (n = ~1,000 F2) experiment was conducted in mice to further understand the genetic architecture of complex polygenic traits. In combination with previous work, we conclude that QTL analysis has reinforced classic polygenic paradigms put in place prior to molecular analysis. Composite interval mapping revealed large numbers of QTL for growth traits with an exponential distribution of magnitudes of effects and validated theoretical expectations regarding gene action. Of particular significance, large effects were detected on Chromosome (Chr) 2. Regions on Chrs 1, 3, 6, 10, 11, and 17 also harbor loci with significant contributions to phenotypic variation for growth. Despite the large sample size, average confidence intervals of ~20 cM exhibit the poor resolution for initial estimates of QTL location. Analysis with genome-wide and chromosomal polygenic models revealed that, under certain assumptions, large fractions of the genome may contribute little to phenotypic variation for growth. Only a few epistatic interactions among detected QTL, little statistical support for gender-specific QTL, and significant age effects on genetic architecture were other primary observations from this study. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mammalian Genome Springer Journals

A large-sample QTL study in mice: I. Growth

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Publisher
Springer Journals
Copyright
Copyright © 2004 by Springer-Verlag New York Inc.
Subject
Philosophy
ISSN
0938-8990
eISSN
1432-1777
D.O.I.
10.1007/s00335-003-2312-x
Publisher site
See Article on Publisher Site

Abstract

By use of long-term selection lines for high and low growth, a large-sample (n = ~1,000 F2) experiment was conducted in mice to further understand the genetic architecture of complex polygenic traits. In combination with previous work, we conclude that QTL analysis has reinforced classic polygenic paradigms put in place prior to molecular analysis. Composite interval mapping revealed large numbers of QTL for growth traits with an exponential distribution of magnitudes of effects and validated theoretical expectations regarding gene action. Of particular significance, large effects were detected on Chromosome (Chr) 2. Regions on Chrs 1, 3, 6, 10, 11, and 17 also harbor loci with significant contributions to phenotypic variation for growth. Despite the large sample size, average confidence intervals of ~20 cM exhibit the poor resolution for initial estimates of QTL location. Analysis with genome-wide and chromosomal polygenic models revealed that, under certain assumptions, large fractions of the genome may contribute little to phenotypic variation for growth. Only a few epistatic interactions among detected QTL, little statistical support for gender-specific QTL, and significant age effects on genetic architecture were other primary observations from this study.

Journal

Mammalian GenomeSpringer Journals

Published: Jan 1, 2003

References

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