Metabolic Profiles and cDNA-AFLP Analysis of Salvia miltiorrhiza and Salvia castanea Diel f. tomentosa Stib

Plants of the genus Salvia produce various types of phenolic compounds and tanshinones which are effective for treatment of coronary heart disease. Salvia miltiorrhiza and S. castanea Diels f. tomentosa Stib are two important members of the genus. In this study, metabolic profiles and cDNA-AFLP analysis of four samples were employed to identify novel genes potentially involved in phenolic compounds and tanshinones biosynthesis, including the red roots from the two species and two tanshinone-free roots from S. miltiorrhiza. The results showed that the red roots of S. castanea Diels f. tomentosa Stib produced high contents of rosmarinic acid (21.77 mg/g) and tanshinone IIA (12.60 mg/g), but low content of salvianolic acid B (1.45 mg/g). The red roots of S. miltiorrhiza produced high content of salvianolic acid B (18.69 mg/g), while tanshinones accumulation in this sample was much less than that in S. castanea Diels f. tomentosa Stib. Tanshinones were not detected in the two tanshinone-free samples, which produced high contents of phenolic compounds. A cDNA-AFLP analysis with 128 primer pairs revealed that 2300 transcript derived fragments (TDFs) were differentially expressed among the four samples. About 323 TDFs were sequenced, of which 78 TDFs were annotated with known functions through BLASTX searching the Genbank database and 14 annotated TDFs were assigned into secondary metabolic pathways through searching the KEGGPATHWAY database. The quantitative real-time PCR analysis indicated that the expression of 9 TDFs was positively correlated with accumulation of phenolic compounds and tanshinones. These TDFs additionally showed coordinated transcriptional response with 6 previously-identified genes involved in biosynthesis of tanshinones and phenolic compounds in S. miltiorrhiza hairy roots treated with yeast extract. The sequence data in the present work not only provided us candidate genes involved in phenolic compounds and tanshinones biosynthesis but also gave us further insight into secondary metabolism in Salvia

Relating gene expression data on two-component systems to functional annotations in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionally, this has been done in two consecutive steps. The first step identifies important genes through clustering or statistical techniques, while the second step assigns biological functions to the identified groups. Recently, techniques have been developed that identify such relationships in a single step.</p> <p>Results</p> <p>We have developed an algorithm that relates patterns of gene expression in a set of microarray experiments to functional groups in one step. Our only assumption is that patterns co-occur frequently. The effectiveness of the algorithm is demonstrated as part of a study of regulation by two-component systems in <it>Escherichia coli</it>. The significance of the relationships between expression data and functional annotations is evaluated based on density histograms that are constructed using product similarity among expression vectors. We present a biological analysis of three of the resulting functional groups of proteins, develop hypotheses for further biological studies, and test one of these hypotheses experimentally. A comparison with other algorithms and a different data set is presented.</p> <p>Conclusion</p> <p>Our new algorithm is able to find interesting and biologically meaningful relationships, not found by other algorithms, in previously analyzed data sets. Scaling of the algorithm to large data sets can be achieved based on a theoretical model.</p