Literature DB >> 8770600

A genetic map of quantitative trait loci for body weight in the mouse.

P D Keightley1, T Hardge, L May, G Bulfield.   

Abstract

The genetic basis of body weight in the mouse was investigated by measuring frequency changes of microsatellite marker alleles in lines divergently selected for body weight from a base population of a cross between two inbred strains. In several regions of the genome, sharp peaks of frequency change at linked markers were detected, which suggested the presence of single genes of moderate effect, although in several other regions, significant frequency changes occurred over large portions of chromosomes. A method based on maximum likelihood was used to infer effects and map positions of quantitative trait loci (QTLs) based on genotype frequencies at one or more marker loci. Eleven QTLs with effects in the range 0.17-0.28 phenotypic standard deviations were detected; but under an additive model, these did not fully account for the observed selection response. Tests for the presence of more than one QTL in regions where there were large changes of marker allele frequency were mostly inconclusive.

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Mesh:

Year:  1996        PMID: 8770600      PMCID: PMC1206951     

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  25 in total

1.  A genetic map of the mouse suitable for typing intraspecific crosses.

Authors:  W Dietrich; H Katz; S E Lincoln; H S Shin; J Friedman; N C Dracopoli; E S Lander
Journal:  Genetics       Date:  1992-06       Impact factor: 4.562

2.  Molecular and phenotypic variation in the achaete-scute region of Drosophila melanogaster.

Authors:  T F Mackay; C H Langley
Journal:  Nature       Date:  1990-11-01       Impact factor: 49.962

Review 3.  Actions of insulin-like growth factors.

Authors:  E R Froesch; C Schmid; J Schwander; J Zapf
Journal:  Annu Rev Physiol       Date:  1985       Impact factor: 19.318

4.  The analysis of selection in experimental populations.

Authors:  W H DuMouchel; W W Anderson
Journal:  Genetics       Date:  1968-03       Impact factor: 4.562

5.  High resolution of quantitative traits into multiple loci via interval mapping.

Authors:  R C Jansen; P Stam
Journal:  Genetics       Date:  1994-04       Impact factor: 4.562

6.  Naturally occurring variation in bristle number and DNA polymorphisms at the scabrous locus of Drosophila melanogaster.

Authors:  C Lai; R F Lyman; A D Long; C H Langley; T F Mackay
Journal:  Science       Date:  1994-12-09       Impact factor: 47.728

7.  RFLPs for somatotropic genes identify quantitative trait loci for growth in mice.

Authors:  D C Winkelman; R B Hodgetts
Journal:  Genetics       Date:  1992-08       Impact factor: 4.562

8.  The use of retrotransposons as markers for mapping genes responsible for fitness differences between related Drosophila melanogaster strains.

Authors:  S V Nuzhdin; P D Keightley; E G Pasyukova
Journal:  Genet Res       Date:  1993-10       Impact factor: 1.588

9.  Additional microsatellite markers for mouse genome mapping.

Authors:  C M Hearne; M A McAleer; J M Love; T J Aitman; R J Cornall; S Ghosh; A M Knight; J B Prins; J A Todd
Journal:  Mamm Genome       Date:  1991       Impact factor: 2.957

10.  Interval mapping of high growth (hg), a major locus that increases weight gain in mice.

Authors:  S Horvat; J F Medrano
Journal:  Genetics       Date:  1995-04       Impact factor: 4.562

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  25 in total

1.  A genomewide linkage scan for quantitative-trait loci for obesity phenotypes.

Authors:  Hong-Wen Deng; Hongyi Deng; Yong-Jun Liu; Yao-Zhong Liu; Fu-Hua Xu; Hui Shen; Theresa Conway; Jin-Long Li; Qing-Yang Huang; K M Davies; Robert R Recker
Journal:  Am J Hum Genet       Date:  2002-03-28       Impact factor: 11.025

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

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

3.  Adjusting data to body size: a comparison of methods as applied to quantitative trait loci analysis of musculoskeletal phenotypes.

Authors:  Dean H Lang; Neil A Sharkey; Arimantas Lionikas; Holly A Mack; Lars Larsson; George P Vogler; David J Vandenbergh; David A Blizard; Joseph T Stout; Joseph P Stitt; Gerald E McClearn
Journal:  J Bone Miner Res       Date:  2004-12-20       Impact factor: 6.741

Review 4.  Theoretical models of selection and mutation on quantitative traits.

Authors:  Toby Johnson; Nick Barton
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-07-29       Impact factor: 6.237

5.  Quantitative trait loci analysis of structural and material skeletal phenotypes in C57BL/6J and DBA/2 second-generation and recombinant inbred mice.

Authors:  Dean H Lang; Neil A Sharkey; Holly A Mack; George P Vogler; David J Vandenbergh; David A Blizard; Joseph T Stout; Gerald E McClearn
Journal:  J Bone Miner Res       Date:  2004-10-11       Impact factor: 6.741

6.  The molecular basis of quantitative genetic variation in central and secondary metabolism in Arabidopsis.

Authors:  T Mitchell-Olds; D Pedersen
Journal:  Genetics       Date:  1998-06       Impact factor: 4.562

7.  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

8.  Selection with recurrent backcrossing to develop congenic lines for quantitative trait loci analysis.

Authors:  W G Hill
Journal:  Genetics       Date:  1998-03       Impact factor: 4.562

9.  An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice.

Authors:  João Pl Castro; Michelle N Yancoskie; Campbell Rolian; Yingguang Frank Chan; Marta Marchini; Stefanie Belohlavy; Layla Hiramatsu; Marek Kučka; William H Beluch; Ronald Naumann; Isabella Skuplik; John Cobb; Nicholas H Barton
Journal:  Elife       Date:  2019-06-06       Impact factor: 8.140

10.  Development of a highly fecund inbred strain of mice.

Authors:  Marte Holt; Frank W Nicholas; John W James; Chris Moran; Ian C A Martin
Journal:  Mamm Genome       Date:  2004-12       Impact factor: 2.957

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