Literature DB >> 12360413

Linkage disequilibrium mapping of novel lung tumor susceptibility quantitative trait loci in mice.

Daolong Wang1, William J Lemon, Ming You.   

Abstract

Linkage disequilibrium (LD) has been used to map chromosomal regions regulating quantitative traits, also called quantitative trait loci (QTLs). With the increasing number of available mouse polymorphic genetic markers, LD can be estimated for the purpose of fine-mapping a given QTL or in the identification of novel QTLs. A whole-genome LD analysis was conducted for mapping mouse lung tumor susceptibility QTLs in 25 strains of mice with known susceptibility to lung cancer using 5638 genetic markers. A total of 63 markers were found to be significantly associated with lung tumor susceptibility, many of which were novel QTLs. This study demonstrates the feasibility of using LD to map QTLs on a whole genome level. Further characterization of the newly identified lung tumor susceptibility QTLs may lead to the identification of genes whose human homologue may predispose some individuals to lung cancer.

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Year:  2002        PMID: 12360413     DOI: 10.1038/sj.onc.1205886

Source DB:  PubMed          Journal:  Oncogene        ISSN: 0950-9232            Impact factor:   9.867


  4 in total

1.  Loci controlling lymphocyte production of interferon c after alloantigen stimulation in vitro and their co-localization with genes controlling lymphocyte infiltration of tumors and tumor susceptibility.

Authors:  Marie Lipoldová; Helena Havelková; Jana Badalova; Jarmila Vojtísková; Lei Quan; Magdaléna Krulova; Yahya Sohrabi; Alphons P Stassen; Peter Demant
Journal:  Cancer Immunol Immunother       Date:  2010-02       Impact factor: 6.968

2.  Deciphering the regulation of porcine genes influencing growth, fatness and yield-related traits through genetical genomics.

Authors:  Angel M Martínez-Montes; Anixa Muiños-Bühl; Almudena Fernández; Josep M Folch; Noelia Ibáñez-Escriche; Ana I Fernández
Journal:  Mamm Genome       Date:  2016-12-10       Impact factor: 2.957

3.  Modeling cancer patient populations in mice: complex genetic and environmental factors.

Authors:  Daniel R Radiloff; Erica S Rinella; David W Threadgill
Journal:  Drug Discov Today Dis Models       Date:  2008

Review 4.  Experimental Models to Define the Genetic Predisposition to Liver Cancer.

Authors:  Rosa M Pascale; Maria M Simile; Graziella Peitta; Maria A Seddaiu; Francesco Feo; Diego F Calvisi
Journal:  Cancers (Basel)       Date:  2019-09-27       Impact factor: 6.639

  4 in total

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