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We did a stranded RNA-seq library prep on a bacterial sample (Mycobacterium tuberculosis). When using this kit for human/mouse/fly, the correct strand is always "second" or "reverse" strand (different tools have different nomenclature). This time, I am getting 90% of the reads on the other strand. It doesn't make much sense to me that the reads would somehow be on the wrong strand. At worst, they should be 50/50. Do the bacterial annotations have different assumptions? Should I be concerned?
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Last edited by id0; 04-07-2015, 01:26 PM. -
Hi,
a lot of strand-specific RNA-Seq kits produce "reverse" reads. See http://seqanswers.com/forums/showthread.php?t=50459 and http://seqanswers.com/forums/showthread.php?t=50711.
I'd guess it is more a library-prep issue than an annotation issue; so I don't think you should be concerned. -
I think you misunderstood my question. I am familiar with the kit and I've used it for other species many times. The reads are always "reverse". Now I did bacteria and they are not "reverse".Originally posted by Michael.Ante View PostComment
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Reverse while mapping, or reverse when doing an assembly?Comment
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What kit are you using?
Yes, if you use the same kit in the same way your strandedness should remain the same.
My first suspicion would be that the annotation for your Mycobacterium is wrong.
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PhillipComment
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The kit is ScriptSeq Complete Gold Kit (http://www.illumina.com/products/scr...demiology.html). It even says on the website: "choose the FR=secondstrand option". That always works fine for me.Originally posted by pmiguel View Post
I am also concerned that the annotation is wrong, but I am using the references from Ensembl (http://bacteria.ensembl.org/mycobact..._2/Info/Index/). I assume their info would be consistent across all species. I never ran into any issues like this with non-bacterial references.Comment
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It would be odd to have entire genome annotation wrong from Ensembl (but strange things do happen). Are you using the GFF file Ensembl is providing?
Can you compare the annotation from NCBI: http://www.ncbi.nlm.nih.gov/genome/?...culosis+H37Rv?Comment
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When you write "This time, I am getting 90% of the reads on the other strand." what do you mean by "getting". I presume you use some program or browser to derive this figure? What program or browser did you use? Was it the same one you used for previous projects?
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PhillipComment
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I used the Ensembl GFF. I also tried the NCBI GFF. Similar result with both.Originally posted by GenoMax View Post
I use Picard CollectRnaSeqMetrics to collect the stats. It also generates graphs for normalized coverage across transcript. Usually, the middle is much higher than the ends. With this RNA-seq, the ends are actually slightly higher.
It's really bizarre. I've never seen anything like this.Comment
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Actually Illumina has excellent tech support. I suggest you phone or email them. There may be something obvious happening, but it isn't apparent to me.
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PhillipComment
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...
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