Publications
4 results found
Liebeke M, Bruford MW, Donnelly RK, et al., 2014, Identifying biochemical phenotypic differences between cryptic species., Biology Letters, Vol: 10, ISSN: 1744-9561
Molecular genetic methods can distinguish divergent evolutionary lineages in what previously appeared to be single species, but it is not always clear what functional differences exist between such cryptic species. We used a metabolomic approach to profile biochemical phenotype (metabotype) differences between two putative cryptic species of the earthworm Lumbricus rubellus. There were no straightforward metabolite biomarkers of lineage, i.e. no metabolites that were always at higher concentration in one lineage. Multivariate methods, however, identified a small number of metabolites that together helped distinguish the lineages, including uncommon metabolites such as Nε-trimethyllysine, which is not usually found at high concentrations. This approach could be useful for characterizing functional trait differences, especially as it is applicable to essentially any species group, irrespective of its genome sequencing status.
Hao J, Liebeke M, Astle W, et al., 2014, Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN, NATURE PROTOCOLS, Vol: 9, Pages: 1416-1427, ISSN: 1754-2189
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- Citations: 126
Liebeke M, Hao J, Ebbels TMD, et al., 2013, Combining Spectral Ordering with Peak Fitting for One-Dimensional NMR Quantitative Metabolomics, ANALYTICAL CHEMISTRY, Vol: 85, Pages: 4605-4612, ISSN: 0003-2700
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- Citations: 16
Hao J, Astle W, De Iorio M, et al., 2012, BATMAN-an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model, BIOINFORMATICS, Vol: 28, Pages: 2088-2090, ISSN: 1367-4803
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- Citations: 102
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