Literature DB >> 9927469

Multiple-trait quantitative trait loci analysis using a large mouse sibship.

A U Jackson1, A Fornés, A Galecki, R A Miller, D T Burke.   

Abstract

Quantitative trait loci influencing several phenotypes were assessed using a genetically heterogeneous mouse population. The 145 individuals were produced by a cross between (BALB/cJ x C57BL/6J)F1 females and (C3H/HeJ x DBA/2J)F1 males. The population is genetically equivalent to full siblings derived from heterozygous parents, with known linkage phase. Each individual in the population represents a unique combination of alleles from the inbred grandparents. Quantitative phenotypes for eight T cell measures were obtained at 8 and 18 mo of age. Single-marker locus, repeated measures analysis of variance identified nine marker-phenotype associations with an experimentwise significance level of P < 0.05. Six of the eight quantitative phenotypes could be associated with at least one locus having experiment-wide significance. Composite interval, repeated measures analysis of variance identified 13 chromosomal regions with comparisonwise (nominal) significance associations of P < 0.001. The heterozygous-parent cross provides a reproducible, general method for identification of loci associated with quantitative trait phenotypes or repeated phenotypic measures.

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Year:  1999        PMID: 9927469      PMCID: PMC1460485     

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


  19 in total

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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

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Journal:  Heredity (Edinb)       Date:  1992-10       Impact factor: 3.821

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Authors:  W R Atchley; W M Fitch
Journal:  Science       Date:  1991-10-25       Impact factor: 47.728

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Authors:  A B Korol; Y I Ronin; V M Kirzhner
Journal:  Genetics       Date:  1995-07       Impact factor: 4.562

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Authors:  C Jiang; Z B Zeng
Journal:  Genetics       Date:  1995-07       Impact factor: 4.562

6.  Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

Authors:  E S Lander; D Botstein
Journal:  Genetics       Date:  1989-01       Impact factor: 4.562

7.  Inheritance of immune responsiveness, life span, and disease incidence in interline crosses of mice selected for high or low multispecific antibody production.

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Journal:  J Immunol       Date:  1989-02-15       Impact factor: 5.422

8.  Aging can be genetically dissected into component processes using long-lived lines of Caenorhabditis elegans.

Authors:  T E Johnson
Journal:  Proc Natl Acad Sci U S A       Date:  1987-06       Impact factor: 11.205

9.  Murine chromosomal regions correlated with longevity.

Authors:  R Gelman; A Watson; R Bronson; E Yunis
Journal:  Genetics       Date:  1988-04       Impact factor: 4.562

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Authors:  R A Miller; P Turke; C Chrisp; J Ruger; A Luciano; J Peterson; K Chalmers; G Gorgas; S VanCise
Journal:  J Gerontol       Date:  1994-11
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  11 in total

1.  Preservation of femoral bone thickness in middle age predicts survival in genetically heterogeneous mice.

Authors:  Richard A Miller; Jaclynn Kreider; Andrzej Galecki; Steven A Goldstein
Journal:  Aging Cell       Date:  2011-03-22       Impact factor: 9.304

2.  Mammalian mRNA splice-isoform selection is tightly controlled.

Authors:  Jennifer L Chisa; David T Burke
Journal:  Genetics       Date:  2006-12-18       Impact factor: 4.562

3.  Quantitative trait loci modulate vertebral morphology and mechanical properties in a population of 18-month-old genetically heterogeneous mice.

Authors:  Grant M Reeves; Barbara R McCreadie; Shu Chen; Andrzej T Galecki; David T Burke; Richard A Miller; Steven A Goldstein
Journal:  Bone       Date:  2006-10-13       Impact factor: 4.398

4.  Bayesian quantitative trait loci mapping for multiple traits.

Authors:  Samprit Banerjee; Brian S Yandell; Nengjun Yi
Journal:  Genetics       Date:  2008-08-09       Impact factor: 4.562

5.  Translational Geroscience: From invertebrate models to companion animal and human interventions.

Authors:  Mitchell B Lee; Matt Kaeberlein
Journal:  Transl Med Aging       Date:  2018-08-17

6.  Three-locus and four-locus QTL interactions influence mouse insulin-like growth factor-I.

Authors:  Philip Hanlon; William Andrew Lorenz; Zhihong Shao; James M Harper; Andrzej T Galecki; Richard A Miller; David T Burke
Journal:  Physiol Genomics       Date:  2006-06-16       Impact factor: 3.107

7.  Single QTL effects, epistasis, and pleiotropy account for two-thirds of the phenotypic F(2) variance of growth and obesity in DU6i x DBA/2 mice.

Authors:  G A Brockmann; J Kratzsch; C S Haley; U Renne; M Schwerin; S Karle
Journal:  Genome Res       Date:  2000-12       Impact factor: 9.043

8.  Dissection of complex adult traits in a mouse synthetic population.

Authors:  David T Burke; Kenneth M Kozloff; Shu Chen; Joshua L West; Jodi M Wilkowski; Steven A Goldstein; Richard A Miller; Andrzej T Galecki
Journal:  Genome Res       Date:  2012-05-15       Impact factor: 9.043

9.  Simultaneous SNP selection and adjustment for population structure in high dimensional prediction models.

Authors:  Sahir R Bhatnagar; Yi Yang; Tianyuan Lu; Erwin Schurr; J C Loredo-Osti; Marie Forest; Karim Oualkacha; Celia M T Greenwood
Journal:  PLoS Genet       Date:  2020-05-04       Impact factor: 5.917

10.  Genetic loci that influence cause of death in a heterogeneous mouse stock.

Authors:  Ruth Lipman; Andrzej Galecki; David T Burke; Richard A Miller
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2004-10       Impact factor: 6.053

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