RNAseq: same reads + more complete scaffold = fewer DEGs?
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20 months ago

Hello!

I have a set of RNAseq data for a couple of relatively under-studied species.

During the analytical period, a collaborator created new DNA scaffolds for these species which we'd like to use.

However when I redid our RNAseq using the existing reads mapped to the new scaffolds, one of our species had the number of differentially-expressed genes drop by anywhere from 20-50% per condition.

As the reads themselves haven't changed we weren't expecting significant changes in differential gene expression, and indeed for our other species changes have been minimal.

Does anybody know what might cause this kind of change?

Thank you!

RNAseq • 724 views
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Assuming that the genes are spliced and that new assembly => new annotation. One possibility is that previously counted as 2 or more gene fragments are just one gene int he new assembly. IMHO without numbers (50% of what number of DEGs? how many genes you have?) it is hard to speculate.

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That's certainly believable - thank you. Our collaborator was able to condense the assemblies from 250-300 fragments down to 60-90, but obviously that's not the end of the road. Reference genomes don't exist for our species yet, and our genes don't even have names - we're working off predicted orthology...

DEG counts are a bit across the board; in general we see losses from ~900-1000 per condition to ~500-600. The more extreme case was a bit of an outlier - ~350 down to ~150. Total number of genes is expected to be around ~15000.

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You may try to check what happened with DEGs obtained using the 300 fragments assembly by getting the sequences of these genes and comparing them with just DEGs or all sequences from the new assembly. I quite like LAST (https://gitlab.com/mcfrith/last) but blastn should be OK. In the best case scenario the old DEGs will have a bunch of gene fragments fully matching the new DEGs. Realistically probably you will find some extra putative exon(s) here and there. Hopefully you will not find artificial chimeric genes (two different genes joined into one). If your RNA-Seq reads are paired and say > 100bp each you may try to assemble the transcripts.

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