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Reference genes for livestock gene expression profiling – Literature review
81-89Views:144Quantitative real-time polymerase chain reaction (qPCR) is an essential tool for understanding animal cell’s response to developmental progression or to different experimental conditions at gene expression level. However the reliability of this method heavily lies on proper normalization (measuring a target and a reference gene’s expression from the same sample to correct for technical related variations).
Our literature review aimed to summarize the articles addressing the most important livestock species in regards of reference gene stability used as normalizers for quantitative real-time polymerase chain reaction experiments. Stably expressing reference genes were categorized into 14 distinct groups according to gene function. The number of reference genes tested and the publication numbers according to years and the ranking algorithms were also noted.
Counting showed that genes encoding ribosomal protein components are ranked as most stable in majority of cases and therefore should be taking into account for qPCR stable normalizer gene finding experiments. -
Development of seed analyses by means of various matrix solutions and the MALDI-TOF MS technique
53-57Views:273The earth's population is growing steadily, currently accounting for about 7.3 billion people. Population growth causes food demand to rise, approximately 36 million people die each year due to starvation or related diseases. One solution to this problem is the continuous examination and development of the agricultural economy. In this study, matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI -TOF MS) were used to analyse of sunflower, soybean and hemp. In order to analyse the protein of maize, this method has already been applied. However, for sunflower, soy and hemp, it is necessary to develop a sample preparation method. Choosing the optimal matrix solution for ionization the traget molecule is an essential part of developing the method. Our aim is to compare two different matrix solutions (α-HCCA, SA matrix), based on the properties (intensity, noise ratio, value of spectra) of the spectra.