Literature DB >> 8944028

Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse.

R J Fijneman1, S S de Vries, R C Jansen, P Demant.   

Abstract

Many complex traits, including susceptibility to lung cancer, are controlled by multiple genes--quantitative trait loci (QTLs). We facilitated the mapping of QTLs by making use of recombinant congenic strains (RCS), a system of mouse inbred strains in which the genetic complexity is reduced, and by applying MQM-mapping (multiple-QTL models or marker-QTL-marker), a multilocus method with an increased power of detecting of individual QTLs and interacting QTLs (epistasis). The mouse strain O20 develops significantly larger N-ethyl-N-nitrosourea induced lung tumours than mice of the RC strain OcB-9 (ref. 5); the latter share approximately 87.5% of their genes with strain O20 and 12.5% with strain B10.O20 (refs 6,7). QTL analysis of 222 (OcB-9 x O20) F2 mice revealed four new loci that influence susceptibility to lung cancer (Sluc genes). They are involved in two significant, partly counteracting interactions which mask their individual main effects: Sluc1 (on chromosome 19) interacts with Sluc2 (chromosome 2), and Sluc3 (chromosome 6) interacts with Sluc4 (chromosome 11). Together with the data of van Wezel et al. in the accompanying report, our results indicate that interactions between tumour susceptibility genes are a common phenomenon which complicates their mapping.

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Year:  1996        PMID: 8944028     DOI: 10.1038/ng1296-465

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  35 in total

1.  Mapping epistatic quantitative trait loci with one-dimensional genome searches.

Authors:  J L Jannink; R Jansen
Journal:  Genetics       Date:  2001-01       Impact factor: 4.562

2.  Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.

Authors:  Nengjun Yi; Shizhong Xu; David B Allison
Journal:  Genetics       Date:  2003-10       Impact factor: 4.562

3.  A penalized likelihood method for mapping epistatic quantitative trait Loci with one-dimensional genome searches.

Authors:  Martin P Boer; Cajo J F Ter Braak; Ritsert C Jansen
Journal:  Genetics       Date:  2002-10       Impact factor: 4.562

4.  Modifying the Schwarz Bayesian information criterion to locate multiple interacting quantitative trait loci.

Authors:  Malgorzata Bogdan; Jayanta K Ghosh; R W Doerge
Journal:  Genetics       Date:  2004-06       Impact factor: 4.562

5.  Little epistasis for anxiety-related measures in the DeFries strains of laboratory mice.

Authors:  Jonathan Flint; John C DeFries; Norman D Henderson
Journal:  Mamm Genome       Date:  2004-02       Impact factor: 2.957

Review 6.  [Evaluation of cancer risk through genetic analysis?].

Authors:  A Luz
Journal:  Strahlenther Onkol       Date:  1997-09       Impact factor: 3.621

7.  Methods for predicting superior genotypes under multiple environments based on QTL effects.

Authors:  Jian Yang; Jun Zhu
Journal:  Theor Appl Genet       Date:  2005-04-02       Impact factor: 5.699

8.  Simultaneous mapping of epistatic QTL in DU6i x DBA/2 mice.

Authors:  Orjan Carlborg; Gudrun A Brockmann; Chris S Haley
Journal:  Mamm Genome       Date:  2005-07       Impact factor: 2.957

9.  Epistatic interactions govern chemically-induced lung tumor susceptibility and Kras mutation site in murine C57BL/6J-ChrA/J chromosome substitution strains.

Authors:  Lori D Dwyer-Nield; Jay McQuillan; Annie Hill-Baskin; Richard A Radcliffe; Ming You; Joseph H Nadeau; Alvin M Malkinson
Journal:  Int J Cancer       Date:  2010-01-01       Impact factor: 7.396

10.  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

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