Literature DB >> 15058380

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

Joao L Rocha1, Eugene J Eisen, L Dale Van Vleck, Daniel Pomp.   

Abstract

By use of long-term selection lines for high and low growth, a large-sample (n = approximately 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 approximately 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.

Entities:  

Mesh:

Year:  2004        PMID: 15058380     DOI: 10.1007/s00335-003-2312-x

Source DB:  PubMed          Journal:  Mamm Genome        ISSN: 0938-8990            Impact factor:   2.957


  67 in total

1.  A large-sample QTL study in mice: III. Reproduction.

Authors:  Joao L Rocha; Eugene J Eisen; Frank Siewerdt; L Dale Van Vleck; Daniel Pomp
Journal:  Mamm Genome       Date:  2004-11       Impact factor: 2.957

2.  Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth.

Authors:  G A Brockmann; C S Haley; U Renne; S A Knott; M Schwerin
Journal:  Genetics       Date:  1998-09       Impact factor: 4.562

3.  Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects.

Authors:  A E Melchinger; H F Utz; C C Schön
Journal:  Genetics       Date:  1998-05       Impact factor: 4.562

4.  Quantitative trait loci affecting growth in high growth (hg) mice.

Authors:  P M Corva; S Horvat; J F Medrano
Journal:  Mamm Genome       Date:  2001-04       Impact factor: 2.957

5.  Stocks for detecting linkage in the mouse, and the theory of their design.

Authors:  T C CARTER; D S FALCONER
Journal:  J Genet       Date:  1951-01       Impact factor: 1.166

6.  Growth quantitative trait loci (QTL) on mouse chromosome 10 in a Quackenbush-Swiss x C57BL/6J backcross.

Authors:  A C Collins; I C Martin; B W Kirkpatrick
Journal:  Mamm Genome       Date:  1993       Impact factor: 2.957

7.  Reproductive performance in a diallel cross among lines of mice selected for litter size and body weight.

Authors:  G Hörstgen-Schwark; E J Eisen; A M Saxton; T R Bandy
Journal:  J Anim Sci       Date:  1984-04       Impact factor: 3.159

8.  Quantitative trait loci for murine growth.

Authors:  J M Cheverud; E J Routman; F A Duarte; B van Swinderen; K Cothran; C Perel
Journal:  Genetics       Date:  1996-04       Impact factor: 4.562

9.  Dietary obesity linked to genetic loci on chromosomes 9 and 15 in a polygenic mouse model.

Authors:  D B West; J Goudey-Lefevre; B York; G E Truett
Journal:  J Clin Invest       Date:  1994-10       Impact factor: 14.808

Review 10.  Construction of a genetic linkage map in man using restriction fragment length polymorphisms.

Authors:  D Botstein; R L White; M Skolnick; R W Davis
Journal:  Am J Hum Genet       Date:  1980-05       Impact factor: 11.025

View more
  41 in total

1.  A large-sample QTL study in mice: II. Body composition.

Authors:  Joao L Rocha; Eugene J Eisen; L Dale Van Vleck; Daniel Pomp
Journal:  Mamm Genome       Date:  2004-02       Impact factor: 2.957

2.  Genetic analysis of atherosclerosis and glucose homeostasis in an intercross between C57BL/6 and BALB/cJ apolipoprotein E-deficient mice.

Authors:  Zhimin Zhang; Jessica S Rowlan; Qian Wang; Weibin Shi
Journal:  Circ Cardiovasc Genet       Date:  2012-01-31

3.  Accurate prediction of genetic values for complex traits by whole-genome resequencing.

Authors:  Theo Meuwissen; Mike Goddard
Journal:  Genetics       Date:  2010-03-22       Impact factor: 4.562

4.  A large-sample QTL study in mice: III. Reproduction.

Authors:  Joao L Rocha; Eugene J Eisen; Frank Siewerdt; L Dale Van Vleck; Daniel Pomp
Journal:  Mamm Genome       Date:  2004-11       Impact factor: 2.957

5.  Genomic mapping of direct and correlated responses to long-term selection for rapid growth rate in mice.

Authors:  Mark F Allan; Eugene J Eisen; Daniel Pomp
Journal:  Genetics       Date:  2005-06-08       Impact factor: 4.562

6.  Bayesian analyses of multiple epistatic QTL models for body weight and body composition in mice.

Authors:  Nengjun Yi; Denise K Zinniel; Kyoungmi Kim; Eugene J Eisen; Alfred Bartolucci; David B Allison; Daniel Pomp
Journal:  Genet Res       Date:  2006-02       Impact factor: 1.588

7.  An efficient Bayesian model selection approach for interacting quantitative trait loci models with many effects.

Authors:  Nengjun Yi; Daniel Shriner; Samprit Banerjee; Tapan Mehta; Daniel Pomp; Brian S Yandell
Journal:  Genetics       Date:  2007-05-04       Impact factor: 4.562

8.  Genetic variation for body weight change in mice in response to physical exercise.

Authors:  Larry J Leamy; Daniel Pomp; J Timothy Lightfoot
Journal:  BMC Genet       Date:  2009-09-21       Impact factor: 2.797

9.  Genetic influences on growth and body composition in mice: multilocus interactions.

Authors:  G A Ankra-Badu; D Pomp; D Shriner; D B Allison; N Yi
Journal:  Int J Obes (Lond)       Date:  2008-11-04       Impact factor: 5.095

10.  Genotype X diet interactions in mice predisposed to mammary cancer. I. Body weight and fat.

Authors:  Ryan R Gordon; Kent W Hunter; Peter Sørensen; Daniel Pomp
Journal:  Mamm Genome       Date:  2008-02-20       Impact factor: 2.957

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.