Abstract
BackgroundIdentification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development. Ideally expression of these genes should be independent of the morphogenetic process or environmental condition tested as well as the methods used for RNA purification and analysis.ResultsIn an effort to identify endogenous genes meeting these criteria nine reference genes (RG) were tested in two Petunia lines (Mitchell and V30). Growth conditions differed in Mitchell and V30, and different methods were used for RNA isolation and analysis. Four different software tools were employed to analyze the data. We merged the four outputs by means of a non-weighted unsupervised rank aggregation method. The genes identified as optimal for transcriptomic analysis of Mitchell and V30 were EF1α in Mitchell and CYP in V30, whereas the least suitable gene was GAPDH in both lines.ConclusionsThe least adequate gene turned out to be GAPDH indicating that it should be rejected as reference gene in Petunia. The absence of correspondence of the best-suited genes suggests that assessing reference gene stability is needed when performing normalization of data from transcriptomic analysis of flower and leaf development.
Highlights
Identification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development
From the original list we developed a short list of nine, including genes encoding Actin-11 (ACT), Cyclophilin-2 (CYP) [10], Elongation factor 1a (EF1a), Ubiquitin (UBQ) Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), GTPbinding protein GTP-binding nuclear protein (RAN1) (RAN1), SAND family protein (SAND) protein (SAND) [8,24,25], Ribosomal protein S13 (RPS13) [6] and b-Tubulin 6 (TUB) [26] (Table 1)
The fact that each program identified slightly different genes as best suited for normalization prompted us to merge the data in an unsupervised way and giving identical weight to the output of the different programs
Summary
Identification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development. Expression of these genes should be independent of the morphogenetic process or environmental condition tested as well as the methods used for RNA purification and analysis. The general aims of transcriptomic analysis are identification of genes differentially expressed and measurement of the relative levels of their transcripts. The programs geNorm and qBasePlus use pairwise comparisons and geometric averaging across a matrix of reference genes. BestKeeper uses pairwise correlation analysis of each internal gene to an optimal normalization factor that merges data from all of them. NormFinder fits data to a mathematical model, which allows comparison of intra- and intergroup variation and calculation of expression stability
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