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Old 01-06-2010, 07:19 AM   #1
vruotti
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Default RNA SEQ Bias toward short transcripts (RPKM)

Hi there.
Just wanted to post this to see if anyone else see this interesting pattern. When taking the average expression (RPKMs) of short genes, say 0.5kb to 2.5kb, we see that the average is much higher when comparing to the average of longer genes, say 10.5-50.5kb. We have done a few wet lab work and were not able to find an answer to this pattern.

We have also took a few samples from the Mortazavi's data and were able to replicate the same pattern. This is telling us that for some reason, when looking at the entire RNA Seq run, we see a higher number of reads mapping to short transcript and lower number of reads mapping to longer transcript. The question is why? You expect to see similar averages, especially when you know that you are using the random primed protocol.

Do you see the same bias towards short transcripts in your RNA SEQ runs?
Thanks in advance.
Victor
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Old 01-06-2010, 08:31 AM   #2
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The most highly expressed genes are short. This is presumably because there is a strong evolutionary pressure for transcriptional efficiency.
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Old 01-06-2010, 08:46 AM   #3
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Hi Zigster,
You might be right. But, we don't see the same pattern when looking at microarray expression in human. The average expression is about the same for short and long transcripts.

Victor
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Old 01-06-2010, 09:17 AM   #4
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I think measuring absolute expression in microarrays is very difficult or impossible at the top end of the spectrum. Basically microarrays are only good for ratios, if that.
http://www.pnas.org/content/99/11/7554.full

This article might shed some light on the subject (although I am unable to access it)
Relationship between gene compactness and base composition in rice and human genome. Journal of biomolecular structure & dynamics 2010;27(4):477-88

http://www.jbsdonline.com/c4297/Rela...88-p17743.html

This subject has interested me since we used to see high viral integration in the very shortest genes, which made for some wacky u-shaped graphs. I'd like to hear more about what you discover.
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Old 01-06-2010, 10:09 AM   #5
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a better article:
Selection for short introns in highly expressed genes
http://www.nature.com/ng/journal/v31/n4/abs/ng940.html
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