Literature DB >> 24240761

Maturing patterns of organ weights in mice selected for rapid postweaning gain.

E J Eisen1.   

Abstract

Correlated responses to selection for increased 3-6 week postweaning gain in male mice were estimated for seven internal organs (testes, spleen, liver, kidneys, heart, small intestine (S intest) and stomach) weighed at specific degrees of maturity in body weight (37.5, 50.0, 62.5, 75.0, 87.5 and 100%). Correlated responses in organ weights were generally large, but the magnitude and direction of response depended upon whether 1) comparisons were made at the same age, degree of maturity or body weight and 2) absolute or proportional organ weights were used. The selected line (M16) weighed more and had larger organ weights than controls (ICR) when compared at either the same degree of maturity or the same age, indicating positive genetic correlations between body weight and the respective organ weights. Positive correlated responses were found in spleen weight/body weight at all degrees of maturity and in liver and S intest weights as a proportion of body weight at some degrees of maturity. Testes, kidneys, heart and stomach weights as a proportion of body weight had negative correlated responses, though this was consistent only for kidneys across all degrees of maturity. Correlated responses in organ weights adjusted for body weight by covariance analysis were positive for spleen, S intest and stomach and negative for testes and kidneys. Based on the constrained quadratic model, degree of maturity in organ weight relative to degree of maturity in body weight responded positively for testes, kidneys and S intest and negatively for spleen and liver. Selection for increased growth caused negative correlated responses in allometric growth of testes, kidneys, S intest and stomach.

Entities:  

Year:  1986        PMID: 24240761     DOI: 10.1007/BF00273732

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  17 in total

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Journal:  Toxicol Appl Pharmacol       Date:  1976-03       Impact factor: 4.219

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Authors:  E J Eisen
Journal:  J Anim Sci       Date:  1987-01       Impact factor: 3.159

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Journal:  Biol Rev Camb Philos Soc       Date:  1966-11

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Authors:  W R Atchley
Journal:  Genet Res       Date:  1984-06       Impact factor: 1.588

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Authors:  D S Falconer; I K Gauld; R C Roberts
Journal:  Genet Res       Date:  1978-06       Impact factor: 1.588

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Journal:  Nahrung       Date:  1985

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Authors:  E J Eisen; B H Johnson
Journal:  Genetics       Date:  1981 Nov-Dec       Impact factor: 4.562

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Authors:  E J Eisen; J M Leatherwood
Journal:  J Nutr       Date:  1978-10       Impact factor: 4.798

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Authors:  M W Tess; G E Dickerson; J A Nienaber; C L Ferrell
Journal:  J Anim Sci       Date:  1986-04       Impact factor: 3.159

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  6 in total

1.  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

2.  Organ growth of selected lines of chickens and their F1 crosses to a common body weight or age.

Authors:  M N Katanbaf; P B Siegel; E A Dunnington
Journal:  Theor Appl Genet       Date:  1988-10       Impact factor: 5.699

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Journal:  Heredity (Edinb)       Date:  2011-06-22       Impact factor: 3.821

4.  Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice.

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Journal:  Animal Model Exp Med       Date:  2018-10-24

5.  Growth performance, biochemical and haematological parameters of BALB/c mice fed on staple grains and bee larvae (Apis Mellifera) blended complementary foods.

Authors:  Shewangzaw Addisu Mekuria; John N Kinyuru; Beatrice Kiage Mokua; Mesfin Wogayehu Tenagashaw
Journal:  Heliyon       Date:  2022-02-24

6.  Body composition and gene expression QTL mapping in mice reveals imprinting and interaction effects.

Authors:  Ye Cheng; Satyanarayana Rachagani; Angela Cánovas; Mary Sue Mayes; Richard G Tait; Jack C M Dekkers; James M Reecy
Journal:  BMC Genet       Date:  2013-10-29       Impact factor: 2.797

  6 in total

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