Background: Quantitative PCR (qPCR) is one of the most common and accurate methods of gene expression analysis. However, the biggest challenge for this kind of examinations is normalization of the results, which requires the application of dependable internal controls. The selection of appropriate reference genes (RGs) is one of the most crucial points in qPCR data analysis and for correct assessment of gene expression. Because of the fact that many reports indicate that the expression profiles of typically used RGs can be unstable in certain experimental conditions, species or tissues, reference genes with stable expression levels should be selected individually for each experiment. In this study, we analysed a set of ten candidate RGs for wheat seedlings under short-term drought stress. Our tests included five ‘traditional’ RGs (GAPDH, ACT, UBI, TUB, and TEF1) and five novel genes developed by the RefGenes tool from the Genevestigator database. Results: Expression stability was assessed using five different algorithms: geNorm, NormFinder, BestKeeper, RefFinder and the delta Ct method. In the final ranking, we identified three genes: CJ705892, ACT, and UBI, as the best candidates for housekeeping genes. However, our data indicated a slight variation between the different algorithms that were used. We revealed that the novel gene CJ705892, obtained by means of in silico analysis, showed the most stable expression in the experimental tissue and condition. Conclusions: Our results support the statement, that novel genes selected for certain experimental conditions have a more stable level of expression in comparison to routinely applied RGs, like genes encoding actin, tubulin or GAPDH. Selected CJ705892 gene can be used as a housekeeping gene in the expression analysis in wheat seedlings under short-term drought. The results of our study will be useful for subsequent analyses of gene expression in wheat tissues subjected to drought.

Foot rot and crown rot are fungal diseases of wheat caused by a complex of Fusarium species. They have a huge economic impact mainly due to yield reduction. A survey was conducted to identify four Fusarium species, occurring on wheat stem bases, using species-specific PCR assays in samples collected during spring of 2012. The dominant species was F. graminearum, which was identified in above 64 % of samples. F. culmorum was detected in 15.71 %, F. poae in 15.71 % and F. sporotrichioides in 5.71 % wheat fields. Most of the wheat fields in the eastern Poland were infected with at least one or two of Fusarium species, while in central Poland no Fusarium species were identified in most of the fields. The presence of F. graminearum tends to favor the presence of F. culmorum and this effect was visible also for F. poae and F. sporotrichioides. The frequency of F. graminearum and F. culmorum detections were highest where wheat crops were preceded by maize and in the samples from late sown fields. The opposite observation was made for F. poae and F. sporotrichioides, where the number of detections of these species was higher in samples from early sown fields. The number of detected Fusarium species was significantly lower in samples collected from fields protected with autumn herbicide in comparison to unprotected fields. The rate of autumn N fertilization did not affect the number of Fusarium detections.

Infection of phyllosphere (stems, leaves, husks, and grains) by pathogenic fungi reduces the wheat yield and grain quality. Detection of the main wheat pathogenic fungi provides information about species composition and allows effective and targeted plant treatment. Since conventional procedures for the detection of these organisms are unreliable and time consuming, diagnostic DNA-based methods are required. Nucleic acid amplification technologies are independent of the morphological and biochemical characteristics of fungi. Microorganisms do not need to be cultured. Therefore, a number of PCR-based methodologies have been developed for the identification of key pathogenic fungi, such as Fusarium spp., Puccinia spp., Zymoseptoria tritici, Parastagonospora nodorum, Blumeria graminis f. sp. tritici, and Pyrenophora tritici-repentis. This article reviews frequently used DNA regions for fungus identification and discusses already known PCR assays for detection of the aforementioned wheat pathogens. We demonstrate that PCR-based wheat pathogen identification assays require further research. In particular, the number of diagnostic tests for Fusarium graminearum, Puccinia spp., and P. tritici-repentis are insufficient.