Parallel analysis of transcript and metabolic profiles: a new approach in systems biology.
The past few years in the medical and biological sciences have been characterized by the advent of systems biology. However, despite the well-known connectivity between the molecules described by transcriptomic, proteomic and metabolomic approaches, few studies have tried to correlate parameters across the various levels of systemic description. When comparing the discriminatory power of metabolic and RNA profiling to distinguish between different potato tuber systems, using the techniques described here suggests that metabolic profiling has a higher resolution than expression profiling. When applying pairwise transcript-metabolite correlation analyses, 571 of the 26,616 possible pairs showed significant correlation, most of which was novel and included several strong correlations to nutritionally important metabolites. We believe this approach to be of high potential value in the identification of candidate genes for modifying the metabolite content of biological systems.
Urbanczyk-Wochniak
Ewa
E
Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, 14476 Golm, Germany.
Luedemann
Alexander
A
Kopka
Joachim
J
Selbig
Joachim
J
Roessner-Tunali
Ute
U
Willmitzer
Lothar
L
Fernie
Alisdair R
AR
D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D015894:Genome, Human; D006801:Humans; D008660:Metabolism; D020411:Oligonucleotide Array Sequence Analysis; D011198:Solanum tuberosum / Q000235:genetics / Q000378:metabolism; D013223:Statistics as Topic; D013598:Systems Theory