A systems approach for determining gene expression from experimental observation of compound presence and absence
Different genes are expressed in different tissues, depending on functional objectives and selection pressures. Based on complete knowledge of the structure of the metabolic network and all the reactions taking place in the cell, elementary modes (EMs) and minimal cut sets (MCSs) can relate compounds observed in a tissue, to the genes being expressed by respectively providing the full set of non-decomposable routes of reactions and compounds that lead to the synthesis of external products, and the full set of possible target genes for blocking the synthesis of external products. So, for a particular tissue, only the EMs containing the reactions that are related to the genes being expressed in those tissues, are active for the production of the corresponding compounds. This concept is used to develop an algorithm for determining a matrix of reactions (which can be related to corresponding genes) taking place in a tissue, using experimental observations of compounds in a tissue. The program is applied to the Arabidopsis flower and identified 20 core reactions occurring in all the viable EMs. They originate from the trans-cinnamate compound and lead to the formation of kaempferol and quercetin compounds and their derivatives, as well as anthocyanin compounds. Analyses of the patterns in the matrix identify reaction sets related to certain functions such as the formation of derivatives of the two anthocyanin compounds present, as well as the reactions leading from the network’s external substrate erythrose-4P to L-Phenyla- lanine, cinnamyl-alc to trans-cinnamate and so on. The program can be used to successfully determine genes taking place in a tissue, and the patterns in the resulting matrix can be analysed to determine gene sets and the state of the tissue.... [Show full abstract]
Fields of Research0604 Genetics; 060405 Gene Expression (incl. Microarray and other genome-wide approaches); 080201 Analysis of Algorithms and Complexity
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