Chickpea genes regulated by salicylic acid, methyl jasmonate, and aminocyclopropane carboxylic acid

Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes and grasspea (Lathyrus sativus L.) ESTs, chickpea responses to treatments with the defence signalling compounds salicylic acid (SA), methyl jasmonate (MeJA), and aminocyclopropane carboxylic acid (ACC) were studied in four chickpea genotypes with ranging levels of resistance to ascochyta blight (Ascochyta rabiei (Pass.) L.). The experimental system minimized environmental effects and was conducted in reference design, where samples from untreated controls acted as references against post-treatment samples. Robust data quality was achieved through the use of three biological replicates (including a dye-swap), the inclusion of negative controls, and strict selection criteria for differentially expressed genes including a fold change cut-off determined by self-to-self hybridizations, Students t test and multiple testing correction (P<0.05). Microarray observations were also validated by quantitative RT-PCR. The time-course expression patterns of 715 experimental microarray features resulted in differential expression of 425 genes in at least one condition. The A. rabiei resistant chickpea genotypes showed a more substantial range of defence-related gene induction by all treatments, indicating that they may possess stronger abilities to resist infection. Further, the involvement of SA, MeJA, and ACC signalling was identified for the regulation of some important A. rabiei responsive genes, as well as cross-talk between these pathways. This study also found evidence to suggest the involvement of A. rabiei-specific signalling mechanisms for the induction of several genes that were previously implicated in A. rabiei resistance. Overall, this study characterised the regulatory mechanisms of many chickpea genes that may be important in defence against various pathogens, as well as other cellular functions. Although the size of the microarray was limited, the results provided novel insights to the molecular control of chickpea cellular processes, which may assist the understanding of chickpea defence mechanisms and allow enhanced development of disease resistant cultivars. Keywords: time course defence-signalling teatment analysis Overall design: Total RNA was extracted from pooled stem and leaf samples for each genotype (FLIP94-508C, ICC3996 and Lasseter) at each time-point (including control samples) using the RNeasy® Plant Mini Kit (Qiagen, Valencia, CA). The quantity and quality of the total RNA samples were assessed by OD260/OD280 ratios and gel electrophoresis respectively. Fluorescent-labeled targets were prepared and hybridized to array slides according to [Coram, TE. and Pang, ECK. 2006. Expression profiling of Chickpea genes differentially regulated during a resistance response to Ascochyta rabiei. Published in Plant Biotechnology Journal]. All hybridizations were performed with six technical replicates and three biological replicates, incorporating dye-swapping (i.e. reciprocal labelling of Cy3 and Cy5) to eliminate any dye bias. Overall, 324 images were analyzed from 54 slides, resulting in 18 data points for each time-point of each genotype. Slides were scanned at 532 nm (Cy3 green laser) and 660 nm (Cy5 red laser) at 10 µm resolution using an Affymetrix® 428™ array scanner (Santa Clara, CA), and captured with the Affymetrix® Jaguar™ software (v. 2.0, Santa Clara, CA). Image analysis was performed using Imagene™ 5 (BioDiscovery, Marina Del Rey, CA) software. Quantified spot data was then compiled and transformed using GeneSight™ 3 (BioDiscovery, Marina Del Rey, CA). Data transformations consisted of a local background correction (mean intensity of background was subtracted from mean signal intensity for each spot), omitting flagged spots, Lowess normalisation of the entire population, creating a Cy5/Cy3 mean signal ratio, taking a shifted log (base 2), and combination of duplicated spot data. To identify differentially expressed (DE) genes, expression ratio results were filtered to eliminate genes whose 95% confidence interval for mean fold change (FC) did not extend to 2.0-fold up or down, followed by Students t test with False Discovery Rate (FDR) multiple testing correction to retain only genes in which expression changes versus untreated control were significant at P < 0.05.