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Determining the age of juvenile blow flies is one of the key tasks of forensic entomology when providing evidence for the minimum post mortem interval. While the age determination of blow fly larvae is well established using morphological parameters, the current study focuses on molecular methods for estimating the age of blow flies during the metamorphosis in the pupal stage, which lasts about half the total juvenile development. It has already been demonstrated in several studies that the intraspecific variance in expression of so far used genes in blow flies is often too high to assign a certain expression level to a distinct age, leading to an inaccurate prediction. To overcome this problem, we previously identified new markers, which show a very sharp age dependent expression course during pupal development of the forensically-important blow fly Calliphora vicina Robineau–Desvoidy 1830 (Diptera: Calliphoridae) by analyzing massive parallel sequencing (MPS) generated transcriptome data. We initially designed and validated two quantitative polymerase chain reaction (qPCR) assays for each of 15 defined pupal ages representing a daily progress during the total pupal development if grown at 17 °C. We also investigated whether the performance of these assays is affected by the ambient temperature, when rearing pupae of C. vicina at three different constant temperatures—namely 17 °C, 20 °C and 25 °C. A temperature dependency of the performance could not be observed, except for one marker. Hence, for each of the defined development landmarks, we can present gene expression profiles of one to two markers defining the mentioned progress in development.
The biotrophic pathogen Ustilago maydis causes smut disease on maize (Zea mays) and induces the formation of tumours on all aerial parts of the plant. Unlike in other biotrophic interactions, no gene-for-gene interactions have been identified in the maize–U. maydis pathosystem. Thus, maize resistance to U. maydis is considered a polygenic, quantitative trait. Here, we study the molecular mechanisms of quantitative disease resistance (QDR) in maize, and how U. maydis interferes with its components. Based on quantitative scoring of disease symptoms in 26 maize lines, we performed an RNA sequencing (RNA-Seq) analysis of six U. maydis-infected maize lines of highly distinct resistance levels. The different maize lines showed specific responses of diverse cellular processes to U. maydis infection. For U. maydis, our analysis identified 406 genes being differentially expressed between maize lines, of which 102 encode predicted effector proteins. Based on this analysis, we generated U. maydis CRISPR/Cas9 knock-out mutants for selected candidate effector sets. After infections of different maize lines with the fungal mutants, RNA-Seq analysis identified effectors with quantitative, maize line-specific virulence functions, and revealed auxin-related processes as a possible target for one of them. Thus, we show that both transcriptional activity and virulence function of fungal effector genes are modified according to the infected maize line, providing insights into the molecular mechanisms underlying QDR in the maize–U. maydis interaction.