Accuracy in quantitative real-time polymerase chain reaction (qPCR) requires the use of stable endogenous controls. Normalization with multiple reference genes is the gold standard, but their identification is a laborious task, especially in species with limited sequence information. Coffee (Coffea ssp.) is an important agricultural commodity and, due to its economic relevance, is the subject of increasing research in genetics and biotechnology, in which gene expression analysis is one of the most important fields. Notwithstanding, relatively few works have focused on the analysis of gene expression in coffee. Moreover, most of these works have used less accurate techniques such as northern blot assays instead of more accurate techniques (e.g., qPCR) that have already been extensively used in other plant species. Aiming to boost the use of qPCR in studies of gene expression in coffee, we uncovered reference genes to be used in a number of different experimental conditions. Using two distinct algorithms implemented by geNorm and Norm Finder, we evaluated a total of eight candidate reference genes (psaB, PP2A, AP47, S24, GAPDH, rpl39, UBQ10, and UBI9) in four different experimental sets (control versus drought-stressed leaves, control versus droughtstressed roots, leaves of three different coffee cultivars, and four different coffee organs). The most suitable combination of reference genes was indicated in each experimental set for use as internal control for reliable qPCR data normalization. This study also provides useful guidelines for reference gene selection for researchers working with coffee plant samples under conditions other than those tested here.
AtGRP3 is a glycine-rich protein (GRP) from Arabidopsis thaliana shown to interact with the receptor-like kinase AtWAK1 in yeast, in vitro and in planta. In this work, phenotypic analyses using transgenic plants were performed in order to better characterize this GRP. Plants of two independent knockout alleles of AtGRP3 develop longer roots suggesting its involvement in root size determination. Confocal microscopy analysis showed an abnormal cell division and elongation in grp3-1 knockout mutants. Moreover, we also show that grp3-1 exhibits an enhanced Aluminum (Al) tolerance, a feature also described in AtWAK1 overexpressing plants. Together, these results implicate AtGRP3 function root size determination during development and in Al stress.
The study of tolerance mechanisms for drought stress in soybean is fundamental to the understanding and development of tolerant varieties. Using in silico analysis, four marker genes involved in the classical ABA-dependent and ABA-independent pathways of drought response were identified in the Glycine max genome in the present work. The expression profiles of the marker genes ERD1-like, GmaxRD20A-like, GmaxRD22-like and GmaxRD29B-like were investigated by qPCR in root samples of drought sensitive and tolerant soybean cultivars (BR 16 and Embrapa 48, respectively), submitted to water deficit conditions in hydroponic and pot-based systems. Among the four putative soybean homologs to Arabidopsis genes investigated herein, only GmaxRD29B-like was not regulated by water deficit stress. Distinct expression profiles and different induction levels were observed among the genes, as well as between the two drought-inducing systems. Our results showed contrasting gene expression responses for the GmaxRD20A-like and GmaxRD22-like genes. GmaxRD20A-like was highly induced by continuous drought acclimating conditions, whereas GmaxRD22-like responses decreased after abrupt water deprivation. GmaxERD1-like showed a different expression profile for the cultivars in each system. Conversely, GmaxRD20A-like and GmaxRD22-like genes exhibited similar expression levels in tolerant plants in both systems.
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