Identification of a suitable endogenous control gene in porcine blastocysts for use in quantitative PCR analysis of microRNAs

Sci China Life Sci. 2012 Feb;55(2):126-31. doi: 10.1007/s11427-012-4289-8. Epub 2012 Mar 15.

Abstract

To obtain reliable results in quantitative PCR (qPCR) reactions, an endogenous control (EC) gene is needed to correct for systematic variations. In this study, a TaqMan low density array was used to quantify the expression levels of microRNA (miRNA) genes in in vivo fertilized, in vitro fertilized, parthenogenetic and somatic cell nuclear transfer blastocysts. The aim was to identify suitable EC genes for the qPCR analysis of miRNAs in porcine blastocysts. The results showed that thirty-six miRNAs were commonly expressed in the four kinds of embryos and the expression levels of eleven miRNAs were similar in the different embryo types (P-value>0.05). These 11 miRNAs were selected as candidate EC genes for further analysis and, of these, miR-16 was identified as the most stable EC gene by the GeNorm (a tool based on a pair-wise comparison model that calculates the internal control genes stability measure and determines the most reliable pair of EC genes) and NormFinder (an excel plug-in that uses an ANOVA-based model to estimate intra- and inter-group variation to indicate the single most stable EC gene) programs. In addition, a cell number normalization method validated miR-16 as a suitable EC gene for use in future qPCR analysis of miRNAs in porcine blastocysts.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Animals
  • Blastocyst / metabolism*
  • Female
  • Fertilization in Vitro / methods
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / standards
  • Gene Expression Regulation, Developmental*
  • Male
  • MicroRNAs / genetics*
  • Reference Standards
  • Reverse Transcriptase Polymerase Chain Reaction / methods*
  • Reverse Transcriptase Polymerase Chain Reaction / standards
  • Software
  • Swine

Substances

  • MicroRNAs