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Consensus Multivariate methods in Gas Chromatographic 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
Lookup NU author(s)
Dr Susanne Jensen
Dr Huitu Wang
Dr Clare Lanyon
Professor Anthony O'Donnell
Professor Tony Clare
Emeritus Professor Morris Gosling
Dr Dustin Penn
Author(s)
Zomer S, Dixon SJ, Xu Y, Jensen SP, Wang H, Lanyon CV, O'Donnell AG, Clare AS, Gosling LM, Penn DJ, Brereton RG
Publication type
Article
Journal
The Analyst
Year
2009
Volume
134
Issue
1
Pages
114-123
ISSN (print)
0003-2654
ISSN (electronic)
1364-5528
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
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.
Publisher
Royal Society of Chemistry
URL
http://dx.doi.org/10.1039/b807061j
DOI
10.1039/b807061j
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