Fig. 1

Identification of specific reference genes in strawberry receptacle development based on RNA-seq data. To discover additional superior RGs during receptacle development, we adopted a screening procedure with cut-off values for coefficient of variation (CV) ≤ 0.15 and reads per kilobase per million (FPKM) ≥ 100 in nine RNA-seq data sets that include receptacle development experiments in strawberry. a Venn diagram showing nine candidate RGs identified from the complete genome. The numbers represent the gene numbers meet the criteria for the each RNA-seq data set. b Statistical analysis of CV and FPKM values of strawberry receptacle development specific (“SRDS”) RGs, “Commonly used” HKGs and “Traditional” HKGs identified from the nine RNA-seq data sets. The CV analysis is shown on the left side of the figure, and the FPKM analysis is shown on the right side of the figure. Each data point in the box-plot is derived from one RNA-seq data set. The horizontal line in the box represents the median. The red dashed lines indicate the cut-off values. c Ranking of the candidate RGs into nine lists on the basis of expression stability from CV values in each experiment of the RNA-seq data set. The RankAggreg package for R was used to generate a consensus ranking from the nine lists. The merged list revealed that “SRDS” RGs showed greater expression stability except for UBC12. d Expression data for the candidate RGs were analyzed using geNorm to evaluate their expression stability by calculating a stability value (M) for each gene. Increase in gene expression stability corresponds with a lower M value. The results were consistent with the ranking of the RGs. The RNA-seq data implied that the expression stability of “SRDS” RGs was superior to that of the “Commonly used” HKGs and “Traditional” HKGs during strawberry receptacle development. The colors indicate different sets of candidate RGs in b–d. Note: 26–18S rRNA was not analyzed here because it was not annotated on the F. vesca genome assembly v4