title: A novel procedure for absolute real-time quantification of gene expression patterns.
abstract: BACKGROUND
  Temporal and tissue-specific patterns of gene expression play important roles in functionality of a biological system. Real-time quantitative polymerase chain reaction (qPCR) technique has been widely applied to single gene expressions, but its potential has not been fully released as most results have been obtained as fold changes relative to control conditions. Absolute quantification of transcripts as an alternative method has yet to gain popularity because of unresolved issues.
  
  
  RESULTS
  We propose a solution here with a novel procedure, which may accurately quantify the total cDNA conventionally prepared from a biological sample at the resolution of ~70 pg/μl, and reliably estimate the absolute numbers of transcripts in a picogram of cDNA. In comparison to the relative quantification, cDNA-based absolute (CBA) qPCR method is found to be more sensitive to gene expression variations caused by factors such as developmental and environmental variations. If the number of target transcript copies is further normalized by reference transcripts, cell-level variation pattern of the target gene expression may also be detectable during a developmental process, as observed here in cases across species (Ipomoea purpurea, Nicotiana benthamiana) and tissues (petals and leaves).
  
  
  CONCLUSIONS
  By allowing direct comparisons of results across experiments, the new procedure opens a window to make inferences of gene expression patterns across a broad spectrum of living systems and tissues. Such comparisons are urgently needed for biological interpretations of gene expression variations in diverse cells.
authors.affiliation: State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, 20 Nan Xin Cun, Beijing 100093, China. yqlu@ibcas.ac.cn.
authors.forename: Yingqing
authors.initials: Y
authors.lastname: Lu
authors.forename: Lulu
authors.initials: L
authors.lastname: Xie
authors.forename: Jiani
authors.initials: J
authors.lastname: Chen