Five quantitative trait loci control radiation-induced adenoma multiplicity in Mom 1R ApcMin/+ mice

Eiram Elahi*, Nirosha Suraweera, Emmanouil Volikos, Jacqueline Haines, Natalie Brown, Gerovie Davidson, Mike Churchman, Mohammed Ilyas, Ian Tomlinson, Andrew Silver

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    5 Citations (Scopus)


    Ionising radiation is a carcinogen capable of inducing tumours, including colorectal cancer, in both humans and animals. By backcrossing a recombinant line of ApcMin/+ mice to the inbred BALB/c mouse strain, which is unusually sensitive to radiation-induced tumour development, we obtained panels of 2Gy-irradiated and sham-irradiated N2 ApcMin/+ mice for genotyping with a genome-wide panel of microsatellites at ∼15 cM density and phenotyping by counting adenomas in the small intestine. Interval and composite interval mapping along with permutation testing identified five significant susceptibility quantitative trait loci (QTLs) responsible for radiation induced tumour multiplicity in the small intestine. These were defined as Mom (Modifier of Min) radiation-induced polyposis (Mrip 1-5) on chromosome 2 (log of odds, LOD 2.8, p = 0.0003), two regions within chromosome 5 (LOD 5.2, p<0.00001, 6.2, p<0.00001) and two regions within chromosome 16 respectively (LOD 4.1, p =4×10-5, 4.8, p<0.00001). Suggestive QTLs were found for sham-irradiated mice on chromosomes 3, 6 and 13 (LOD 1.7, 1.5 and 2.0 respectively; p<0.005). Genes containing BALB/c specific non-synonymous polymorphisms were identified within Mrip regions and prediction programming used to locate potentially functional polymorphisms. Our study locates the QTL regions responsible for increased radiation-induced intestinal tumorigenesis in ApcMin/+ mice and identifies candidate genes with predicted functional polymorphisms that are involved in spindle checkpoint and chromosomal stability (Bub1b, Casc5, and Bub1), DNA repair (Recc1 and Prkdc) or inflammation (Duox2, Itgb2l and Cxc15). Our study demonstrates use of in silico analysis in candidate gene identification as a way of reducing large-scale backcross breeding programmes.

    Original languageEnglish
    Article numbere4388
    JournalPLoS ONE
    Issue number2
    Publication statusPublished - 5 Feb 2009


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