Candidate reference genes and their annotated functions.

<p>^a<i>Araucaria angustifolia</i> transcriptome database (Elbl et al. 2015).</p><p>^b Encoded-protein function according to TAIR database (<a href="http://www.arabidopsis.org/" target="_blank">http://www.arabidopsis.org/</a>).</p><p>Candidate reference genes and their annotated functions.</p

Primers used for gene amplification.

<p>^a Genes used for reference gene validation.</p><p>Primers used for gene amplification.</p

cDNA quality (a) and primer (b) test.

<p>Amplification products of PCR analyses using genomic DNA (gDNA) or a pool of all cDNA samples (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136714#pone.0136714.g001" target="_blank">Fig 1</a>) and <i>UBI</i> intron-flanking specific primers (A). Amplicons obtained by PCR using a pool of all cDNA samples and specific primers for the reference genes (B). bp = base pairs.</p

Box plot of the Cq value distribution of candidate reference genes in all <i>Araucaria angustifolia</i> samples (Fig 1).

<p>The median is indicated by a thick horizontal line. Gray boxes and vertical lines indicate interquartile range and the variance between Cq values for each gene, respectively. E: primer efficiency.</p

Ranking of <i>Araucaria angustifolia</i> candidate reference genes based on GeNorm analysis.

<p>^a Stability coefficient is the mean of the variation of two internal control genes between an individual and all other tested genes. The most stable gene has the lowest <i>M</i> value (cut-off < 1.5).</p><p>^b Pairwise variation values <i>Vn/n+1</i> < 0.15 mean that use of the two most stable genes is sufficient to normalize the expression of a test gene in the corresponding set of samples. <i>n</i>: number of genes.</p><p>Ranking of <i>Araucaria angustifolia</i> candidate reference genes based on GeNorm analysis.</p

Identification and Evaluation of Reference Genes for Quantitative Analysis of Brazilian Pine (<i>Araucaria angustifolia</i> Bertol. Kuntze) Gene Expression

<div><p>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 <i>A</i>. <i>angustifolia</i> transcriptome database. Variation in transcript levels was first evaluated <i>in silico</i> 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 <i>in silico</i> prediction, a comprehensive analysis of the qRT-PCR data combined with validation analysis revealed that <i>AaEIF4B-L</i> and <i>AaPP2A</i> are the most suitable reference genes for comparative studies of <i>A</i>. <i>angustifolia</i> gene expression.</p></div

<i>In silico</i> analysis of RPMK average ± standard deviation values of the candidate reference genes retrieved from the <i>Araucaria angustifolia</i> transcriptome database (Elbl et al. 2015).

<p>^a Samples according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136714#pone.0136714.g001" target="_blank">Fig 1</a>.</p><p>^b Genes with significant differential expression among samples are highlighted in bold.</p><p><i>In silico</i> analysis of RPMK average ± standard deviation values of the candidate reference genes retrieved from the <i>Araucaria angustifolia</i> transcriptome database (Elbl et al. 2015).</p

Validation of the most stable reference genes.

<p>(A) Relative expression of <i>AaADC</i>, <i>AaCAT</i>, <i>AaTPS3</i> and <i>AaUGP</i> in the samples used in this study, normalized with different combinations of reference genes. (B) Co-variation patterns by neural network analysis, performed by applying the *omeSOM software [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0136714#pone.0136714.ref043" target="_blank">43</a>].</p

Ranking of <i>Araucaria angustifolia</i> reference genes calculated using NormFinder.

<p>^a Genes are ranked according to minimal estimated intra- and intergroup variation. Genes with the lowest stability value have the most stable expression.</p><p>^b The pair of genes with the highest degree of similarity in their expression profiles.</p><p>Ranking of <i>Araucaria angustifolia</i> reference genes calculated using NormFinder.</p

<i>Araucaria angustifolia</i> tissues/organs used in this study.

<p>Globular zygotic embryos (left, scale bar = 1 mm, and the megagametophyte (right, scale bar = 10 mm) (A); late cotyledonal zygotic embryo (B) and the corresponding megagametophyte (C); aciculas (D); abscisic acid (ABA)-responsive (E), ABA non-responsive (F) and mature ABA-responsive (G) embryogenic cell lines. Arrows indicate globular somatic embryos. Scale bars for panels b-g = 10 mm, 10 mm, 100 mm, 10 mm, 10 mm and 10 mm, respectively.</p