Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae). Issue 1 (7th June 2016) - Piron Prunier, Florence; Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine
Abstract: Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in M inimum I nformation for publication of Q uantitative Real-Time PCR E xperiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes ( actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin ) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata . This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms.