Abstract
Quantitative analysis of gene expression is a fundamental experimental approach in many fields of plant biology, but it requires the use of internal controls representing constitutively expressed genes for reliable transcript quantification. In this study, we identified fifteen putative reference genes from an A. angustifolia transcriptome database. Variation in transcript levels was first evaluated in silico by comparing read counts and then by quantitative real-time PCR (qRT-PCR), resulting in the identification of six candidate genes. The consistency of transcript abundance was also calculated applying geNorm and NormFinder software packages followed by a validation approach using four target genes. The results presented here indicate that a diverse set of samples should ideally be used in order to identify constitutively expressed genes, and that the use of any two reference genes in combination, of the six tested genes, is sufficient for effective expression normalization. Finally, in agreement with the in silico prediction, a comprehensive analysis of the qRT-PCR data combined with validation analysis revealed that AaEIF4B-L and AaPP2A are the most suitable reference genes for comparative studies of A. angustifolia gene expression.
Highlights
Quantitative analysis of gene expression is important for many fields of biological research and in this regard, quantitative real-time PCR is a popular method for mRNA detection and quantification due to its high sensitivity, reproducibility and high throughput capability [1–3], as well as its wide dynamic range [4–9]
Identification of putative Araucaria angustifolia reference genes Using the sequences of previously reported A. thaliana orthologs, fifteen putative reference genes were retrieved from the A. angustifolia transcriptome database
An in silico analysis of the A. angustifolia transcriptome data set indicated that of the candidate genes, only AaPSAB, AaPP2A and AaEIF4B-L showed consistent transcript levels amongst the samples represented in the transcriptome database (Table 3), suggesting that these represented the most promising candidates to be used as constitutively expressed reference genes
Summary
Quantitative analysis of gene expression is important for many fields of biological research and in this regard, quantitative real-time PCR (qRT-PCR) is a popular method for mRNA detection and quantification due to its high sensitivity, reproducibility and high throughput capability [1–3], as well as its wide dynamic range [4–9]. A reliable constitutively expressed control for qRT-PCR analysis should, by definition, exhibit constant levels of transcript abundance between the cells of different tissues and under different experimental conditions [21]; the identification of such control genes can be laborious, especially with species for whom a comprehensive genome sequence is not yet available, such as the Brazilian pine (Araucaria angustifolia) [24–25] This native conifer is currently classified as a critically endangered species [26] and the seeds are recalcitrant to storage, since they maintain high levels of water and active metabolic rates at the mature stage, resulting in a rapid loss of viability, so conservation strategies are restricted [27]. A comparative transcriptome analysis of Brazilian pine early somatic embryo formation and seed development was reported, providing a foundation for further gene expression studies [25]
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