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Consensus multivariate methods in gas chromatography mass spectrometry and denaturing gradient gel electrophoresis : MHC-congenic and other strains of mice can be classified according to the profiles of volatiles and microflora in their scent-marks

House mice (Mus domesticus) communicate using scent-marks, and the chemical and microbial composition of these 'extended phenotypes' are both influenced by genetics. This study examined how the genes of the major histocompatibility complex (MHC) and background genes influence the volatile...

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Published in:Analyst (London) 2009-01, Vol.134 (1), p.114-123
Main Authors: ZOMER, Simeone, DIXON, Sarah J, BRERETON, Richard G, YUN XU, JENSEN, Susanne P, HUITU WANG, LANYON, Clare V, O'DONNELL, Anthony G, CLARE, Anthony S, GOSLING, L. Morris, PENN, Dustin J
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Language:English
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Summary:House mice (Mus domesticus) communicate using scent-marks, and the chemical and microbial composition of these 'extended phenotypes' are both influenced by genetics. This study examined how the genes of the major histocompatibility complex (MHC) and background genes influence the volatile compounds (analysed with Gas Chromatography Mass Spectrometry or GC/MS) and microbial communities (analysed using Denaturating Gradient Gel Electrophoresis or DGGE) in scent-marks produced by congenic strains of mice. The use of Consensus Principal Components Analysis is described and shows relationships between the two types of fingerprints (GC/MS and DGGE profiles). Classification methods including Support Vector Machines and Discriminant Partial Least Squares suggest that mice can be classified according to both background strain and MHC-haplotype. As expected, the differences among the mice were much greater between strains that vary at both MHC and background loci than the congenics, which differ only at the MHC. These results indicate that the volatiles in scent-marks provide information about genetic similarity of the mice, and support the idea that the production of these genetically determined volatiles is influenced by commensal microflora. This paper describes the application of consensus methods to relate two blocks of analytical data.
ISSN:0003-2654
1364-5528
DOI:10.1039/b807061j