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Domest Anim Endocrinol. 2002 Apr;22(2):91-102.

Real-time RT-PCR quantification of insulin-like growth factor (IGF)-1, IGF-1 receptor, IGF-2, IGF-2 receptor, insulin receptor, growth hormone receptor, IGF-binding proteins 1, 2 and 3 in the bovine species.

Author information

1
Institute of Physiology, Center of Life and Food Sciences, Technical University of Munich, 85354 Freising-Weihenstephan, Germany. pfaffl@wzw.tum.de

Abstract

Reverse transcription (RT) followed by polymerase chain reaction (PCR) is the technique of choice for analysing mRNA in extremely low abundance. Real-time RT-PCR using SYBR Green I detection combines the ease and necessary exactness to be able to produce reliable as well as rapid results. To obtain highly accurate and reliable results in a real-time RT-PCR a highly defined calibration curve is needed. We designed and developed nine different calibration curves, based on recombinant DNA plasmid standards and established them on a constant real-time PCR platform for the following factors: growth hormone receptor (GHR), insulin-like growth factor (IGF)-1, IGF-1 receptor (IGF-1R), IGF-2, IGF-2 receptor (IGF-2R), insulin receptor (INSR), and IGF-binding proteins (IGF-BP) 1, 2 and 3. Developed assays were applied in the LightCycler system on bovine ileum and liver total RNA and showed high specificity and sensitivity of quantification. All assays had a detection limit of under 35 recombinant DNA molecules present in the capillary. The SYBR Green I determination resulted in a reliable and accurate quantification with high test linearity (Pearson correlation coefficient r > 0.99) over seven orders of magnitude from <10(2) to >10(8) recombinant DNA start molecules and an assay variation of maximal 5.3%. Applicability of the method was shown by analysing mRNA levels in newborn calves: mRNA concentrations per gram tissue of mRNAs of IGF-1, IGF-1R, IGF-2, IGF-2R, GHR, INSR, and IGF-BP1, 2 and 3 were all different between in liver and ileum and the traits all exhibited individual differences.

PMID:
11900967
[Indexed for MEDLINE]

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