Reference genes for accurate gene expression analyses across different tissues, developmental stages and genotypes in rice for drought tolerance

Abstract

Background: Quantitative reverse transcription PCR (qRT-PCR) has been routinely used to quantify gene expression level. This technique determines the expression of a target gene by comparison to an internal control gene uniformly expressed among the samples analyzed. The reproducibility and reliability of the results depend heavily on the reference genes used. To achieve successful gene expression analyses for drought tolerance studies in rice, reference gene selection should be based on consistency in expression across variables. We aimed to provide reference genes that would be consistent across different tissues, developmental stages and genotypes of rice and hence improve the quality of data in qRT-PCR analysis.

Findings: Ten candidate reference genes were screened from four ubiquitously expressed gene families by analyzing public microarray data sets that included profiles of multiple organs, developmental stages, and water availability status in rice. These genes were evaluated through qRT-PCR experiments with a rigorous statistical analysis to determine the best reference genes. A ubiquitin isogene showed the best gene expression stability as a single reference gene, while a 3-gene combination of another ubiquitin and two cyclophilin isogenes was the best reference gene combination. Comparison between the qRT-PCR and in-house microarray data on roots demonstrated reliability of the identified reference genes to monitor the differential expression of drought-related candidate genes.

Conclusions: Specific isogenes from among the regularly used gene families were identified for use in qRT-PCR-based analyses for gene expression in studies on drought tolerance in rice. These were stable across variables of treatment, genotype, tissue and growth stage. A single gene and/or a three gene set analysis is recommended, based on the resources available.

Keywords: Drought; Gene expression; Reference gene; Rice; Transcriptome; qRT-PCR.

Fig. 1

Schematic workflow used for reference gene identification. Expression of genes from four gene families were mined from five different microarray datasets (definitions of the datasets shown in Additional file 2: Table S1). Determination of each gene’s WRS is described in the Materials and Methods (Additional file 1). Ten candidate genes were selected based on their WRS and tested in qRT-PCR. The stabilities of the genes were then assessed using the ∆Ct approach. The most reliable reference genes were validated by the comparison of qRT-PCR and microarray data

Fig. 2

WRS of the reference gene candidates. Radar chart displays the WRS of each reference gene candidate in the five datasets (A to E in each graph). Vertices of the chart represent percentage scores of WRS calculated for genes in each gene family. The highest WRS was adjusted to 100 %. a GAPDH, b actin, c ubiquitin and d cyclophilin

Fig. 3

Gene expression patterns of the best different gene/gene combinations. Relative expression level was determined by the 10-gene reference and normalized by the roots of IR64 under well-watered condition. X-axis shows the different samples, and Y-axis shows the expression in log₂ scale. Error bar represents the standard error for each data point (n = 3). R: roots, S: shoots, L: flag leaves

Fig. 4

Comparison of qRT-PCR and microarray data of candidate genes from qDTY _12.1. Each scatterplot represents a comparison of the qRT-PCR results of the 6 candidate genes normalized using different reference gene combinations. The X-axis displays the fold-change of expression values from control to stressed conditions from the microarray data, while the Y-axis displays the fold-change of expression values from control to stressed conditions in the qRT-PCR. a Single reference gene, b 2-reference gene combination, c 3-reference gene combination, d 4-reference gene combination. The RV for each graph was shown at the bottom right corner of each graph. The values for the X and Y- axes are shown in log₂ scale