Removing rRNA and tRNA sequences using GTF files
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6.3 years ago
pixie@bioinfo ★ 1.4k

Hello,

The reference build on which I am currently working did not provide the FASTA files for rRNA and tRNA. However, they have provided the GTF files. How can I use them to remove the sequences and which software should I use for my RNA-seq data?

RNA-Seq • 7.8k views
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You strictly don't need to remove the sequences. Just ignore those features when you do your gene counts or before you do the DE analysis.

Take a look at this for software suggestions: (Modern, mid-2016) RNA-seq software pipeline

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Thank You, yea this looks simple

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What are your goals and what species are you using? I've tried prefiltering by mapping against the reference rRNA cassette for mouse/human and a good chunk of rRNA reads remain for things like RiboSeq. I usually deal with that by creating blacklist regions, but if you just need to do normal DE analysis then you can just ignore these regions.

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Hi Devon, can you elaborate on how you came about your reference rRNA cassette? I too have been grappling with rRNA contamination within my samples, there are some where depletion was not as effective as the rest.

What I have done in my work is to take the GTF from repeatmasker annotations of rRNA as well as the fasta sequences from this annotation. I too, find rRNA reads remain with my pipeline (taking the GTF file and using split_bam.py in RNA-SeQC)

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You can find the human rDNA repeat sequence in this post: entire human rDNA

Mouse rDNA repeat can be found here.

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Thank you genomax, don't know how I missed this annotation (well to be honest wasn't aware of it) I will add this to my rRNA reference and try again.

Cheers.

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Thanks for the suggestions. I am new to this. I am working on rice and would be interested in 1) DE analysis 2) Co-expression Networks. I plan to carry out the following pre-processing steps before I go for DE:

1) Remove low quality bases from 5' and 3' end 2) Remove rRNA and tRNA sequences 3) Remove bases that are shorter that 20 bp Does this look fine ?

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For that you can skip (2).

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