With regard to RIN, be also alert that some organisms do not give typical rRNA peaks that are used to calculate the RIN. So for these organisms, check the overall Bioanalyzer trace. Also sometimes the Bioanalyzer software does not produce a RIN because the peaks are mis-aligned. So for these atypical circumstances do not despair if you don't have an ideal RIN.
Also some degree of degradation and therefore lower RIN are tolerable depending on the application and purpose. If you only want to have a general survey of what are transcribed, degradation may not be not a big issue.
Most NGS sequencers do not sequence very long fragments (Illumina HiSeq 50-150 bp). So the size of degraded RNA fragments is not the issue here. The main issue is the bias caused by degradation in representation of RNA species after trying to deplete the vast majority of rRNA molecules. If polyA RNAs are the target, degraded RNA samples may lead to overrepresentation of 3'-end fragments of transcripts.
Typically, values over 8 are good enough for transcriptome analysis. If you are dealing with small RNAseq I will prefer to work with values above 8.5 to ensure that you are fishing just the physiological RNAs and not degradation products.
Besides the numerical RIN value you should look carefully to the fluorogram coming from Bioanalyzer to detect small degradations.
Of course that everything depends also on the type of sample that you are dealing with. Cells in culture are very easy to manipulate and you can get RINs close to 10. Some tissues as heart or liver are more difficult to handle and you must be happy by getting RINs around 8.
The standard in the scientific community seems to be a minimum of 8. However, I wouldn't blindly trust this number. The electropherogram can be very informative here, as it will show you if the peaks are where they should be, and the level of degradation that has occurred. It may also depend on the tissue you are using, as some tissues will yield slightly different rRNA ratios, and these differences are not accounted for by the algorithm that produces the RIN. That being said, using samples with RIN below 8 is an expensive risk, and if at all possible, I would abide by this guideline.
With regard to RIN, be also alert that some organisms do not give typical rRNA peaks that are used to calculate the RIN. So for these organisms, check the overall Bioanalyzer trace. Also sometimes the Bioanalyzer software does not produce a RIN because the peaks are mis-aligned. So for these atypical circumstances do not despair if you don't have an ideal RIN.
Also some degree of degradation and therefore lower RIN are tolerable depending on the application and purpose. If you only want to have a general survey of what are transcribed, degradation may not be not a big issue.
Most NGS sequencers do not sequence very long fragments (Illumina HiSeq 50-150 bp). So the size of degraded RNA fragments is not the issue here. The main issue is the bias caused by degradation in representation of RNA species after trying to deplete the vast majority of rRNA molecules. If polyA RNAs are the target, degraded RNA samples may lead to overrepresentation of 3'-end fragments of transcripts.
In your question you didn't mention which platform you are going to use for RNAseq. The quality of RNA differ as per the platform or library preparation step.
For eg:
In case of Illumina they prefer RIN greater than or equal to 8. But in case of Nugen Ovation RNA seq system , RIN=5 or i think they gave even lesser RIN values for more degraded RNA.
It is always safe to work with higher RIN. But it also depends on the sample. With some samples it is hard to get a good RIN value.
Let me give you a microbiologists view as the previous replies seem to be from eukaryotic biologists (correct me if I'm wrong). We never use RNA with a RIN less that 9.7. Bacterial mRNA cannot be extracted from total RNA (like eukaryotic mRNA can via poly A). Therefore we have to remove the rRNA from the total RNA and use what's left over as out mRNA sample. Any degradation of rRNA (i.e. RINs >9.7) will result in RNA-seq runs where >90% of the reads are rRNA. With RINs in the 9.8-10 range we get good RNA-seq data.
They always recommend 9-10 but as Vrundha sid it really depend on your sample. working with cell lines 10 is easy but when it comes to primary cells 5-7 is even rare. I have done RNAseq with 5-6 too.
In the ideal world, the RIN # should be over 8, but I personally processed a lot RNA sample with an inexistent RIN# and it worked perfectly. If you have RNA coming from cell culture or fresh tissue, you should have RIN # around 9, but if the RNA is coming from FFPE, just forget about the RIN# and try you chance...
I'm new to the site and RNA work so really welcome your coments. Basically we want to look at microRNA expression profiles using RNAseq but RIN numbers are quite variable (8-4.8). Would this be a problem as we are only interested in the small non coding RNAs anyway? Would love to hear your thoughts as I'm a novice in this area.
I can see a problem.. but if it is miRNA, it is still tolerant to lower RIN quality. But, possibly I wont go down below 6:00 by any mean. Actually it depends, how precious the sample is. Sometime its still better to have some data than nothing.
I typically only use RNA with a RIN of 9.7 or higher when doing RNAseq in S. aureus. RIN values of 9.7 or higher are fairly easy to get in this bacteria.
Do you mean for making cDNA for qPCR? I am less stringent when doing qPCR. RIN values of 9 might be OK. I have found that it is quite easy to get high RIN values when isolating RNA from S. aureus. Check out my publications, I published an RNA extraction and RNAseq protocol for S. aureus. This RNA extraction protocol usually generates high quality samples with RIN values around 10.
Mean RNA fragment size is a more trustworthy factor of RNA quality (at least for the TruSeq RNA Library Preparation). Illumina has developed the DV200 metric which is the percentage of RNA fragments > 200 nucleotides. Considering DV200 to assess RNA quality allows accurate adjustment of the minimal RNA input required for successful library preparation. One has to use a RNA sample with DV200>30%.
The DV200 value can be calculated from Fragment Analyzer or Bioanalyzer trace by performing a Smear Analysis as follows:
1) Under the Local tab, change Normal to Advanced.
2) Check box for Smear Analysis.
3) Click Table, add a region, and enter 200–10,000 bp in the popup window.
4) Select the Region Table tab in the trace window to display the results.
Thank you very much, peaks are seen very clearly, as a better RNA. I think samples could be good enough to do the attempt. Thank you very much again. Dr. Mohammed Al-Nussairawi.
Dorsa Morshedi Rad I was following the thread and came across your question ;). So, The RIN value represents the integrity of RNA molecules which is deemed to be pretty useful particularly when you are going to come up quantitatively and accurately with the gene expression through a snapshot at the time of RNA extraction. There are a couple of platforms measuring the RIN including Bioanalyzer and High-sensitivity RNA Screen Tape which both have been offered by Agilent. The basic idea about how does it work is also based on micro-capillary separation of RNA (ending up with 28s/18s ratio) providing detailed info about the integrity and quantity of your RNA.
In my experience, I have obtained comparable transcriptome profiles starting from RNA samples with a RIN value >7 and it does not really matter as long as the number is higher than 7. I always obtain a similar number of reads aligned to the human transcriptome comparing samples with RIN values of 7 with samples with RIN values of 9. I have used TruSeq and ScriptSeq library preparation kits for bulk-sequencing in different platforms from Illumina (MiSeq, NextSeq, HiSeq...). I have no experience with RNA samples with RIN values under 7.