Expression profiling in Medicago truncatula identifies more than 750 genes differentially expressed during nodulation, including many potential regulators of the symbiotic program

Abstract

In this study, we describe a large-scale expression-profiling approach to identify genes differentially regulated during the symbiotic interaction between the model legume Medicago truncatula and the nitrogen-fixing bacterium Sinorhizobium meliloti. Macro- and microarrays containing about 6,000 probes were generated on the basis of three cDNA libraries dedicated to the study of root symbiotic interactions. The experiments performed on wild-type and symbiotic mutant material led us to identify a set of 756 genes either up- or down-regulated at different stages of the nodulation process. Among these, 41 known nodulation marker genes were up-regulated as expected, suggesting that we have identified hundreds of new nodulation marker genes. We discuss the possible involvement of this wide range of genes in various aspects of the symbiotic interaction, such as bacterial infection, nodule formation and functioning, and defense responses. Importantly, we found at least 13 genes that are good candidates to play a role in the regulation of the symbiotic program. This represents substantial progress toward a better understanding of this complex developmental program.

Figure 1.

Hierarchical clustering of M. truncatula genes differentially regulated during symbiotic interactions with S. meliloti. The expression patterns of 539 genes found as differentially regulated in Mt6k-RIT macroarray hybridizations were analyzed under 10 symbiotic conditions, and ratios were calculated between the inoculated and the corresponding noninoculated samples. All genes exhibit a minimum 2-fold expression ratio with a P value ≤0.05 in at least one condition. Whole root systems from wild-type Jemalong A17 (J), supernodulating mutant TR122 (T), and nfp and hcl mutants were harvested at 3 or 6 dpi with either wild-type (W3, W6) or nodA (A3, A6) S. meliloti strains and compared to noninoculated material (0). Isolated nodules were collected at 4 (N4) and 10 dpi (N10) and compared to noninoculated roots (N0). Hierarchical clustering was carried out using average linkage values and Pearson correlations. The global clustering analysis is presented in (A), where five clusters (designated I–V) can be distinguished. Close-ups of clusters I and II, respectively, are shown in B and C, with corresponding MtC EST cluster numbers and annotations.

Figure 2.

Functional class distribution of M. truncatula genes identified as differentially regulated during nodulation. The up-regulated (A) and down-regulated (B) genes were sorted into the 16 broad functional categories used for classification in the MENS database. This diagram shows relative distributions expressed as percentages of the total number of up- or down-regulated genes in each sample: 4-d nodules (N4), TR122 nodulated roots, 6 dpi (TR122-6d), and 10-d nodules (N10). Bars represent the relative abundance of each class expressed as a percentage of the up- or down-regulated genes.

Figure 3.

Expression analysis by qRT-PCR of four putative TF genes predicted by macro- and microarrays to be up-regulated in nodules. Corresponding cDNA concentrations were estimated according to quantified DNA standards in the following samples: roots before inoculation with S. meliloti (N0), isolated nodules at 4 and 10 dpi (N4 and N10), TR122 roots before inoculation (T0), and at 3 or 6 dpi (TW3 and TW6). Concentrations were normalized using their respective EF1-α cDNA concentration, measured by qRT-PCR. Means and sds of two to three repeated experiments are reported in the graphs. Induction ratios to control noninoculated samples (N0 and T0) are indicated above bars (R=).