It may be that a treatment/condition may systematically (directly or indirectly) chop down the majority of the mRNA. This will bias the results when you "normalize" against the amount of biological material (e.g. cells), or extracted RNA, or used cDNA. However, normalization against the measured amount of one ore several reference gene(s) may correct this bias.

It may further be that the grade of degradation is not the same for all genes, so even the use of reference genes for normalization will introduce bias.

You should be confident that the samples/materials you like to compare with resprect to gene expression should have as similar qualities as possible. Large differences in the quality of the material will always raise the doubts that the measured differences might be contributed to the quality-difference rather than to the treatment/group-differences.

Slight degradations are - to my opinion - not really relevant, as long as the amplicon sequence is short. If oligo-dT priming in RT is used, the amplicon sequences should be proximate to the poly-A-tails. Otherwise, random hexamer priming is better; sequence specific priming is always best (but not always feasable), especially when using degraded RNA.

It may be that a treatment/condition may systematically (directly or indirectly) chop down the majority of the mRNA. This will bias the results when you "normalize" against the amount of biological material (e.g. cells), or extracted RNA, or used cDNA. However, normalization against the measured amount of one ore several reference gene(s) may correct this bias.

It may further be that the grade of degradation is not the same for all genes, so even the use of reference genes for normalization will introduce bias.

You should be confident that the samples/materials you like to compare with resprect to gene expression should have as similar qualities as possible. Large differences in the quality of the material will always raise the doubts that the measured differences might be contributed to the quality-difference rather than to the treatment/group-differences.

Slight degradations are - to my opinion - not really relevant, as long as the amplicon sequence is short. If oligo-dT priming in RT is used, the amplicon sequences should be proximate to the poly-A-tails. Otherwise, random hexamer priming is better; sequence specific priming is always best (but not always feasable), especially when using degraded RNA.

I agree with Jochen... At leas all samples should have the same quality.. If not you cannot really compare them with qPCR...

I agree with Jochen also. Centrifugation, for example, will chop your RNA/DNA into small pieces so analysis will get to be difficult depending on the fragment size you look at.

Yes it is. You should always check the quality and quantity of all RNA samples that you are going to use in a qRT-PCR.

I agree with all the above opinions. From personal experience, the quantification via spectrophotometer is not enough. First of all you cannot see the degradation. It gives you data about RNA, not about the quality. It also depends on the extraction method you use, as the most include and rRNA in final product. So you may have RNA, but not only mRNA. An easy way to check the integrity is to use different housekeeping genes and/or use primers that amplify a whole housekeeping gene. It's easy and you don't need extra equipment.

If your question relates to the use of Chip-based RNA analyses, then in my opinion this is way over the top for real-time PCR with respect to both time and cost. Multiple reference genes can be assessed and incorporated into your quantification which will give you confidence that your RNA samples are of a high enough quality. As with everything, if your experiment has been adequately controlled, you should not have to worry about issues of differential RNA quality.

Its always better to check the quality of RNA but can the quality of RNA affect the reproducibility of qPCR data?

I kindly refer to our paper detailing the impact of RNA degradation status on RT-qPCR results (see below). More papers from our group can be found on the Biogazelle website (http://www.biogazelle.com/knowledge-center/publications).

Article Measurable impact of RNA quality on gene expression results ...

Thank you all for sharing your valuable insights.

i agree with going for RNA QC , would be important to reduce varations among starting samples and thus reduce variation withing the RT PCR data itself.

i read that the current QC methods for RNA, are not so accurate representative of RNA integrity. For instance, RIN valuse from bioanalzyer..a sample that is shown to be of low integrity by the RIN value..doesn not mean that it is actually of lower quality...and cDNA can be made sucessfully from it. as mRNA specis much less % in the total RNA pool in relation to ribosomal RNA.

Thats what made me think...but i do agree to be better to reduce variations in data