AUTHOR=Martins Madlles Q. , Fortunato Ana S. , Rodrigues Weverton P. , Partelli Fábio L. , Campostrini Eliemar , Lidon Fernando C. , DaMatta Fábio M. , Ramalho José C. , Ribeiro-Barros Ana I. TITLE=Selection and Validation of Reference Genes for Accurate RT-qPCR Data Normalization in Coffea spp. under a Climate Changes Context of Interacting Elevated [CO2] and Temperature JOURNAL=Frontiers in Plant Science VOLUME=8 YEAR=2017 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2017.00307 DOI=10.3389/fpls.2017.00307 ISSN=1664-462X ABSTRACT=
World coffee production has faced increasing challenges associated with ongoing climatic changes. Several studies, which have been almost exclusively based on temperature increase, have predicted extensive reductions (higher than half by 2,050) of actual coffee cropped areas. However, recent studies showed that elevated [CO2] can strongly mitigate the negative impacts of heat stress at the physiological and biochemical levels in coffee leaves. In addition, it has also been shown that coffee genotypes can successfully cope with temperatures above what has been traditionally accepted. Altogether, this information suggests that the real impact of climate changes on coffee growth and production could be significantly lower than previously estimated. Gene expression studies are an important tool to unravel crop acclimation ability, demanding the use of adequate reference genes. We have examined the transcript stability of 10 candidate reference genes to normalize RT-qPCR expression studies using a set of 24 cDNAs from leaves of three coffee genotypes (CL153, Icatu, and IPR108), grown under 380 or 700 μL CO2 L−1, and submitted to increasing temperatures from 25/20°C (day/night) to 42/34°C. Samples were analyzed according to genotype, [CO2], temperature, multiple stress interaction ([CO2], temperature) and total stress interaction (genotype, [CO2], and temperature). The transcript stability of each gene was assessed through a multiple analytical approach combining the Coeficient of Variation method and three algorithms (geNorm, BestKeeper, NormFinder). The transcript stability varied according to the type of stress for most genes, but the consensus ranking obtained with RefFinder, classified