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Validation of reference genes for the determination of platelet transcript level in healthy individuals and in patients with the history of myocardial infarction.

Katalin S Zsóri | László Muszbek | Zoltán Csiki | Amir H Shemirani
International journal of molecular sciences | 2013

RT-qPCR is the standard method for studying changes in relative transcript level in different experimental and clinical conditions and in different tissues. No validated reference genes have been reported for the normalization of transcript level in platelets. The very low level of platelet RNA and the elimination of leukocyte contamination represented special methodological difficulties. Our aims were to apply a simple technique to separate platelets for transcript level studies, and select the most stable reference genes for platelets from healthy individuals and from patients with the history of myocardial infarction. We developed a simple, straightforward method of platelet separation for RNA isolation. Platelet activation was inhibited by using acid-citrate-dextrose for anticoagulation and by prostaglandin E1. Leukocyte contamination was eliminated by three consecutive centrifugations. Samples prepared by this method were free of leukocytes, showed no inhibition in PCR reaction and no RNA degradation. The assay demands low blood volume, which complies with the requirements of everyday laboratory routine. Seventeen potential reference genes were investigated, but eight of them were excluded during optimization. The stability of the remaining genes, EEF2, EAR, ACTB, GAPDH, ANAPC5, OAZ1, HDGF, GNAS, and CFL1, were determined by four different descriptive statistics. GAPDH, GNAS, and ACTB were shown to be the most stable genes in platelets of healthy individuals, while HDGF, GNAS, and ACTB were the most stable in platelets of patients with the history of myocardial infarction. The results confirm that data normalization needs assessment of appropriate reference genes for a particular sample set.

Pubmed ID: 23389042

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geNORM (tool)

RRID:SCR_006763

Software to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.

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