Hey,
If I have RNAseq data that was obtained from total RNA sequencing (not only the mRNA), and I wanted to analyse only the mRNA expression and exclude the other forms:
Thank you!
you need to define better what you mean by "exclude the other forms"
You expect to find small RNA, tRNA and so on, but this can be discarded after a mapping is done with a reference genome or when comparing with a particular data base containing this data
With total RNA you will pull down rRNA and other larger ncRNA; rRNA will represent the vast majority of your sample unless you remove it via rRNA depletion (generally using kits that utilize hybridization probes like RiboMinus, etc). Also keep in mind a typical library prep will not adequately capture small RNA (<100nt) as the filtering process has a general size cutoff of ~100nt, you would need to prep samples for small RNA separately unless your prep kits account for this.
After that point, as Antonio points you would need to decide what transcripts you plan on 'excluding'. I align all data and then assess the read fates (e.g. how much aligns to genic vs. non-genic based on the annotation file, how many multi-map or are ambiguous, etc). EDIT: Should have added, I use the latter to see relative #'s of sequences aligning based on annotation used.
You can use whatever annotation is available for and relevant to your assembly, though keep in mind potential issues. For example we have seen cases where certain RNAs (e.g. miRNA) change in a global way with some treatments, which directly breaks the assumption that most normalization procedures have, namely that only a small group of genes change.
Other 'harder to work around' issues include draft-quality annotations with little evidence for gene calls. In those cases it may be worth going the reference-based assembly route (Cufflinks or Trinity), then running DGE analysis. This way you try to capture as much information as possible, though even in the reference-based assembly case you are still reliant on a genome assembly which is hopefully trustworthy.
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Thank you for your reply. That was I'm asking about, how to exclude them after mapping?
For example, I thought I could be using an annotation file for only the coding genes. Will that get me only the expression of mRNA?
My second question was about the quality of the experiment itself, if the sequencing was done on the total RNA. i.e. the mRNA was not extracted, will the quality of the mRNA reads be the same compared to an experiment with the extracted mRNA experiment only?
Thank you so much!
I think you have several possibilities. But I would try the following: to extract the information of coding sequences from a gtf or gff file, and the do the mapping. The reads that remain unmapped are those you have not interest either because they do not map, or because they map to genes which you are not interested
In relation to the second question. The quality of your mRNA reads don't have to be affected by the method you isolate the RNA. If you are asking for how good is a population of poliadenilated mRNA when you do a total extraction compared with when you use oligo-dT , I cannot answer with confidence, because I am not experienced not I read a paper comparing both methods. I believe however, that there is a global acceptation the total RNA method is valid when a method a suitable and effective method for getting rid of the ribosomal RNA is present, and this is a obligated step for procaryotic organisms where I never heard a complain