|Application:||Gene expression microarray analysis|
|Number of samples:||4|
|Release date:||Oct 5 2012|
|Last update date:||Oct 9 2012|
|Dataset link||Differential expression in response to water deficit in diploid leaves of sweet orange scion grafted alternatively on a diploid or auto-tetraploid Rangpur lime rootstock: data concerning the scion grafted onto diploid rootstock.|
Transcriptional profiling of sweet orange (Citrus sinensis) scion leaves comparing control untreated with water deficit conditions. We examined the drought tolerance in diploid (2x) and autotetraploid (4x) clones of Rangpur lime (Citrus limonia) rootstocks grafted with 2x Valencia Delta sweet orange (Citrus sinensis) scions, named V/2xRL and V/4xRL, respectively. Physiological studies showed that V/4xRL was much more tolerant to water deficit than V/2xRL. Global gene expression changes induced by water deficit were monitored in the leaves of V/2xRL and V/4xRL by microarray hybridization. The Citrus genome-wide cDNA microarray was used, which includes 21,081 putative unigenes described in Martinez-Godoy et al. (2008). Two independent microarray hybridization experiments with leaves of the 2x Valencia Delta orange alternatively grafted onto 2x or 4x RL rootstocks were respectively performed. For each experiment, the Cy-labelled cDNA of control leaves was hybridized with labelled cDNA from water-stressed samples. To avoid Cy3 and CY5 dye-related artefacts, control and water-stressed cDNA samples were dye-swapped and used to hybridize four slides corresponding to different combinations of the four biological replicates obtained from every treatment. The microarray hybridizations were performed according to Allario et al. (2011). A GenePix 4000B microarray scanner (Axon Instruments, Inc.) and the GenePix Pro 4.1 acquisition software were used to scan the chips at 5-10 µm resolution. Photomultiplier gains for the two channels were adjusted so that the ratio of total intensities was approximately 1 and the percentage of saturated spots was about 1%. High-resolution tiff images were generated and used for quantification of gene expression data. Spot positions were identified on the colour images and quality flags were assigned to individual spots both automatic and manually. Only spots with background-subtracted foreground intensity greater than two in at least one channel were used, and only microarrays with optimal hybridization data were pre-processed and normalized for further analyses. Raw data were imported into the R computing environment for pre-processing, visualization, and statistical analysis. To identify probes showing significant differential gene expression between samples, the Linear Models in Microarrays (LIMMA; Smyth, 2005) software package was used. Pre-processing and normalization of two-color microarray data including signal intensity, background correction, uniformity of the expression ratio over the chip surface (within-array normalization), and normality of M-value distributions were evaluated according to Smyth and Speed (2003). M-value was defined as the logarithm in base-2 of water-deficit versus control expression ratio. Reproducibility between replicates that were assessed indicated that the experimental system provided consistent signals in spots corresponding to the same gene and acceptable low variability between biological replicates (not shown). P-values associated to the statistical analysis of differential expression obtained from Limma analysis are corrected for multiple comparisons using the Benjamini-Hochberg false discovery rate (FDR) procedure (Benjamini & Hochberg, 1995). Differences in gene expression were considered to be significant when the M-value was higher than 0.7 (absolute value) and the FDR-adjusted P-value was smaller than 0.05.
Jose M. Colmenero-Flores