LC-MS Profiling to Link Metabolic and Phenotypic Diversity in Plant Mapping Populations
Numerous studies have revealed the extent of genetic, phenotypic, and metabolic variation between different plant cultivars/varieties. We present a specialized protocol for large-scale targeted and untargeted metabolite profiling for samples from large plant mapping populations using both reversed-phase and aqueous normal-phase LC-MS. This methodology provides a fast and combined targeted/nontargeted workflow as a powerful tool to discriminate related plant phenotypes and describes methods to combine mass features and agronomic traits to link phenotypic to metabolic traits independent of putative metabolite identities. This easily reproducible analytical strategy, in combination with a sophisticated data processing and analysis workflow, can be applicable to a wide range of plant mapping populations.
Key wordsLiquid chromatography Mass spectrometry Quantitative trait locus mapping Mapping populations Metabolite profiling Metabolic trait Metabolomics Genomics
This work was supported by the Australian Research Council and the Grains Research and Development Corporation, by the South Australian Government, the University of Adelaide, the University of Queensland, and the University of Melbourne, and by a Melbourne International Fee Remission Scholarship, a Melbourne International Research Scholarship, and a University of Melbourne Special Postgraduate Studentship to C.B.H.
- 9.Snyder LR, Kirkland JJ, Dolan JW (eds) (2010) Introduction to modern liquid chromatography, 3rd edn. Wiley, Hoboken, NJGoogle Scholar
- 26.Taylor J, Verbyla A (2011) R package wgaim: QTL analysis in bi-parental populations using linear mixed models. J Stat Softw 40:1–18Google Scholar
- 27.Arends D, Prins P, Jansen RC et al (2010) R/qtl: high-throughput multiple QTL mapping. Bioinformatics 26:2990–2992Google Scholar
- 28.Fu J, Swertz MA, Keurentjes JJ et al (2007) MetaNetwork: a computational protocol for the genetic study of metabolic networks. Nature Protocols 2:685–694Google Scholar
- 29.Van Ooijen JW, Kyazma BV (2009) MapQTL 6. Software for the mapping of quantitative trait loci in experimental populations of diploid species. Kyazma BV: Wageningen, NetherlandsGoogle Scholar