Qualimap RNA-Seq Report High Intronic Coverage Explanation

Question

[Aynur]

Hello, I have my mouse RNA-Seq mapped to the mouse genome using STAR Aligner. I performed the Qualimap RNA-seq Quality assessment. Here is my overall result.

Sample        Exonic region          Intergenic Region            Intronic region 

1.               88.36%                  1.66%                              9.98%

My all other samples have similar results. So, my question is - 1. How to understand this result? Should I be concerned with any biasses? 2. Also, how to interpret these results for publication purposes? I read another article, in which they stated they got very high intergenic regions on their Qualimap result and they said "the high number of mapped reads within the intergenic region allowed us to perform additional analyses to determine whether the sequences might encode novel transcripts". 3. Does that mean I don't have chance of finding novel transcripts? What about other results that Qualimap reported? any article for understanding how to understand and utilize these statistics for further analysis? I am interested to continue with DEG analysis using DESeq2, and in fact, I already did DEG analysis, but for my report, I gotta explain my every result and document it, so I am having HARD TIME understanding these. Please kindly explain to me or recommend me any articles.

Thank you very much,
Regards,

Aynur ,

Answer 1

[JC]

First, do you have a clear concept of Exon, Intron, and Intergenic region?

1. The mapping rate is fine, it means 88% of your data is in exons, which it is supposed to be, other regions are also common to have some hits, in your case, ~10% in introns (could be intron expression or novel isoforms) ad 1% in intergenic regions (could be novel genes)

2. To define if you have novel transcripts, it is better to have another analysis to find them, as you are using mouse, make sure to use the latest genome annotation

3. Well, mouse genome is highly studied, so there it is expected you can find novel genes/isoforms but don't expect hundreds.

[Aynur]

Thank you. I am using DESeq2 for DEGs and IsoformSwitchanalyzerr for isoform identification.