Real-time PCR data from every gene expression analysis experiment have to be normalised with appropriate reference genes, which are uniformly expressed in a sample set being analysed. Ref-erence genes have to be tested independently for each experimental set. We estimated the gene expression of five potential reference genes (Phosphoprotein phosphatase 2A, histone H3, β-tubulin, transcription factor IIA and actin) in 33 pea (Pisum sativum L.) samples. Plant material comprised stem fragments from four pea accessions (three cultivars with different lodging susceptibility and stem stiffness and one wild-type accession). Different phenological development stages of plants and environmental conditions were tested under three sample subsets. Phosphoprotein phosphatase 2A and β-tubulin were the most stable genes in the subset of 30-day plants, grown in the greenhouse. Plants at the beginning of flowering stage were grown in the greenhouse and in the field. Phosphoprotein phosphatase 2A and transcription factor IIA exhibited the most stable expression under field conditions, while histone H3 and β-tubulin were the most stable under greenhouse conditions. Phosphoprotein phosphatase 2A and β-tubulin were also the most stable genes among all the tested samples. We have identified stably expressed genes, which may be used as a reference for normalisation of real-time PCR data in our sample subset.Our research is a good starting point for other studies of gene expression in pea stem tissue. This is the first step to perform gene expression studies connected with lodging resistance of pea. K E Y W O R D Spea, quantitative PCR, reference genes

Knopkiewicz M., Gawłowska M., Święcicki W. (2014): The application of high resolution melting in the analysis of simple sequence repeat and single nucleotide polymorphism markers in a pea (Pisum sativum L.) population. Czech J. Genet. Plant Breed., 50: 151-156.The aim of this study was to verify the high resolution melting (HRM) method in the analysis of single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers in pea (Pisum sativum L.). A recombinant inbred line population, Carneval × MP1401, was tested for three SNP and 103 SSR markers. HRM analysis was conducted on a LightScanner 96 instrument with LC Green dye. The melting curve shape permitted two polymorphic genotypes to be distinguished. The results were confirmed by gel electrophoresis. Three SSR markers were sequenced and analysed by the melting prediction software. The results confirmed the presence of one polymerase chain reaction (PCR) product with two melting domains. Sequence tagged site (STS) markers produced specific products: Psat_EST_00189_01_1 (300 bp), Pis_GEN_18_2_1 (400 bp), Pis_GEN_7_1-2_1 (600 bp). Amplicons contained one, four and seven single nucleotide polymorphisms, respectively. Melting curve differences enabled the population genotyping except for Psat_EST_00189_01_1 where resolution was too low. Primers for Psat_EST_00189_01_1 were redesigned to obtain a shorter (100 bp) PCR product which increased the resolution. The number of SNPs and amplicon length are crucial for HRM resolution. The HRM method is fast and has a high throughput. The melting analysis of 96 samples takes less than 10 min. Agarose gel analysis confirmed the reliability of HRM, which eliminates laborious post-PCR analysis.Keywords: genotyping; high resolution melting; molecular markers; Pisum sativum L.DNA analysis via high resolution melting (HRM) is a relatively new technique. It is useful for genotyping, mutation scanning and sequence matching. HRM is based on the properties of fluorescent dyes which bind only to double-stranded DNA. These dyes emit strong fluorescence when they bind to DNA. When the sample is heated, DNA slowly denatures and releases the fluorescent dye, which causes the fluorescence to decrease. When the temperature reaches the melting point of the fragment being analysed, a rapid decrease in fluorescence is observed. HRM instruments measure the fluorescence during the entire heating time to generate a melting curve. The melting temperature of a DNA duplex depends on its length and sequence; thus, different sequences generate different melting curves (Reed et al. 2007). et al. 2011). HRM is an alternative to the time consuming and laborious gel techniques; however, in the field of plant genetics it still requires further testing and improvement. There are few reports of simple sequence repeat (SSR) markers analysed by HRM.

The field pea (Pisum sativum L.) is studied as an important grain legume used in both human and animal feed. DNA markers can contribute to the rapid breeding of novel pea cultivars. This study aimed to identify such molecular markers as the number of days to the beginning of flowering, plant lodging, and stem geometry. Phenotypic measurements were recorded during the field trials. Qualitative and quantitative analyses of soluble carbohydrates (e.g., monosaccharides, sucrose, and raffinose family oligosaccharides) in the pea seeds were performed. A t-test was used to detect the significance of markers associated with each trait. Fifteen markers that were significant for thirteen traits were identified in this analysis. The same markers were identified for verbascose concentration in 2013 and 2014 and stem-wall thickness in 2014 and 2015. Our marker for the number of days to the beginning of flowering (AB141) was 4 cM from the AB64 marker, which was identified as a marker linked to days to 50% bloom. We found a negative correlation between lodging score at the end of flowering and stem diameter in the middle (2015, −0.40) of this study set of pea lines. Although similar correlations were detected in the Carneval × MP1401 population, the correlation between lodging at maturity and diameter in the middle and upper stem sections was positive. In markers validation, particularly for polygenic traits, a statistical analysis of the observed characters is an important step for a division of the trait values into a bimodal distribution.

Lodging is the major factor that determines whether pea (Pisum sativum L.) can be mechanically harvested. The aim of this experiment was to investigate the relationship between stem mechanical parameters (diameter, stem wall thickness, stiffness [rigidity], and maximum self-weight moment [stem strength]) and lodging in pea.Three years of data on stem mechanical parameters and 2 yr of data on lodging resistance were collected on the 'Carneval' × 'MP1401' pea cultivars and Wt10245 × Wt11238 lines. Mechanical parameters were measured separately for three stem sections: lower, middle, and upper. Nine quantitative trait loci (QTL) associated with stem mechanical parameters were identified in the Carneval × MP1401 genetic map. Eight QTL associated with stem mechanical parameters were identified in the Wt10245 × Wt11238 genetic map. These results confirmed QTL for lodging resistance found previously, especially in regards to located in chr5LG3 close to the A004 marker. Quantitative trait loci for stem diameter and stem strength of the upper and lower stem colocated with the Rfs marker in chr5LG3. A plant height QTL was detected close to AB141 marker, 2 cM (3.3 Mbp) from the Le gene. These results enable identification of pea genomic regions associated with agriculturally important traits and provide a foundation for further research to improve lodging resistance in pea.