Nitrogen (N) is an essential macronutrient for plant growth and development. Plants adapt to changes in N availability partly by changes in global gene expression. We integrated publicly available root microarray data under contrasting nitrate conditions to identify new genes and functions important for adaptive nitrate responses in Arabidopsis thaliana roots. Overall, more than 2000 genes exhibited changes in expression in response to nitrate treatments in Arabidopsis thaliana root organs. Global regulation of gene expression by nitrate depends largely on the experimental context. However, despite significant differences from experiment to experiment in the identity of regulated genes, there is a robust nitrate response of specific biological functions. Integrative gene network analysis uncovered relationships between nitrate-responsive genes and 11 highly co-expressed gene clusters (modules). Four of these gene network modules have robust nitrate responsive functions such as transport, signaling, and metabolism. Network analysis hypothesized G2-like transcription factors are key regulatory factors controlling transport and signaling functions. Our meta-analysis highlights the role of biological processes not studied before in the context of the nitrate response such as root hair development and provides testable hypothesis to advance our understanding of nitrate responses in plants.

21171 Background: Background: Axillary lymph node metastasis is the most significant marker for the pathologic staging of breast cancer. However a proportion of lymph node-negative breast cancer will develop metastatic disease. Therefore, molecular markers of invasion in these patients are needed Methods: We selected 10 primary breast cancer cases, 5 lymph node-negative (T1N0) and 4 lymph node-positive (T1N1). In these cases we searched for gene expression of 8 genes (bbc3, cegp1, fgf18, flt1, cffm4, gstm3, hec, tgfb3) selected from previous studies as a good candidates for metastasis prediction. A quantitative Real-Time PCR was performed using beta-2- microglobulin gene expression to normalized gene expression of each gene. The expression average of beta-2-microglobulin was 303,291 among T1N0 and 342,533 among T1N1 cases (ratio 0.88). The expression average of these 8 genes was 2.11 and 0.002 at T1N0 and T1N1 respectively (ratio 1,055). At least 3 genes were significantly down-regulated in T1N1 (bbc3, flt1, gstm3) in comparison with T1N1 breast carcinomas Results: Computational analysis reveals that these 3 genes (bbc3, flt1, gstm3) contain CpG islands in their promoter regions. Although preliminary data, we found group of genes that are down-regulated in T1N1 tumor Conclusions: The finding that these genes are epigenetically regulated, suggest that could be a good candidates for metastasis prediction, by methylation approach (MethyLight System). Since this down-regulation occurs in primary tumor, the analysis of these genes might be useful to predict metastasis in lymph node-negative breast cancer. No significant financial relationships to disclose.