Choose several reference genes and check whether they satisfy the criteria for a good reference gene. If you pick only one reference gene and your pick is not constant across different conditions or samples, your results will be skewed. Picking reference genes will make or break your quantification via qPCR (real time PCR). Reference mRNAs Main article: Choosing reference genes for qPCR normalisation Drawbacks: RNA degrades faster than RNA which can distort the data sample cannot be DNase treated efficiency of cDNA synthesis not taken into account. Drawback: rapidly dividing cells will have more rRNA and different rRNA/mRNA ratio which will complicate comparison difference in cDNA synthesis not taken into account. It is available at the Genevestigator website. There is a public tool called RefGenes that searches a microarray database of more than 50,000 arrays to identify genes that are stable across subsets of conditions. A recent approach is to select a reference gene based on its stability across microarrays done within one's condition of interest. However, more than 100 peer-reviewed articles report problems related to genes chosen from a panel, because they were not suitable for a particular context. It is to be noted that panels are often composed of genes that are supposed to be stable based on their function. Often housekeeping gene is used here instead of reference gene but the term is poorly defined and can be misleading. not just a single reference gene and including data on suitability as reference genes. Frequently, a panel is used for normalization, e.g. Total RNA, ribosomal RNA, and genomic DNA have been suggested as alternative methods. Reference genes are the most common method, although single unverified reference genes invalidate the qPCR data generated. There is an ongoing debate what is the best way to normalise qPCR data. 6.2 Sources of variability: Reagent lots/age.5.2 Efficiency estimation based on the kinetics of single PCR runs.5.1 Linear regression on dilution curve C t data.
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