Selected article for: "differential expression and gene differential expression"

Author: Peña, Andrea A; Bols, Niels C; Marshall, Sergio H
Title: An evaluation of potential reference genes for stability of expression in two salmonid cell lines after infection with either Piscirickettsia salmonis or IPNV
  • Document date: 2010_4_14
  • ID: 0xn6mqh6_1
    Snippet: To date, cDNA microarray and quantitative real-time reverse transcription PCR (qRT-PCR) have become the most important and reliable tools to study differential gene expression in fish, where species-specific antibodies are scarce. Although qRT-PCR combines advantages of specificity, sensitivity, speed, throughput and reproducibility over conventional methods an accurate normalization of data is fully required [1] . Errors in the quantification of.....
    Document: To date, cDNA microarray and quantitative real-time reverse transcription PCR (qRT-PCR) have become the most important and reliable tools to study differential gene expression in fish, where species-specific antibodies are scarce. Although qRT-PCR combines advantages of specificity, sensitivity, speed, throughput and reproducibility over conventional methods an accurate normalization of data is fully required [1] . Errors in the quantification of mRNA transcripts arise from any variation in the amount of starting material between samples. A common strategy to overcome this problem is to simultaneously amplify a non-regulated housekeeping gene with those targeted to allow quantitative normalization of the experimental cDNA inputs. However, it has also been demonstrated that expression levels of these genes may vary considerably depending on cell types, tissues, experimental treatments and even under different diseases [2] . Moreover, the use of a single reference gene for normalization is nowadays discouraged by an increasing number of authors [3] [4] [5] . Consequently, it is highly necessary to validate their constitutive expression for a particular experimental setting and therefore a crucial component when assessing a new model [6] .

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