Sequencing degraded RNA addressed by 3' tag counting.

RNA sequencing has become widely used in gene expression profiling experiments. Prior to any RNA sequencing experiment the quality of the RNA must be measured to assess whether or not it can be used for further downstream analysis. The RNA integrity number (RIN) is a scale used to measure the qualit...

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Main Authors: Benjamín Sigurgeirsson, Olof Emanuelsson, Joakim Lundeberg
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3954844?pdf=render
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spelling doaj-dca4e1caaa8b4f4e9d1fb8025c10ece42020-11-25T01:19:08ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0193e9185110.1371/journal.pone.0091851Sequencing degraded RNA addressed by 3' tag counting.Benjamín SigurgeirssonOlof EmanuelssonJoakim LundebergRNA sequencing has become widely used in gene expression profiling experiments. Prior to any RNA sequencing experiment the quality of the RNA must be measured to assess whether or not it can be used for further downstream analysis. The RNA integrity number (RIN) is a scale used to measure the quality of RNA that runs from 1 (completely degraded) to 10 (intact). Ideally, samples with high RIN (> 8) are used in RNA sequencing experiments. RNA, however, is a fragile molecule which is susceptible to degradation and obtaining high quality RNA is often hard, or even impossible when extracting RNA from certain clinical tissues. Thus, occasionally, working with low quality RNA is the only option the researcher has. Here we investigate the effects of RIN on RNA sequencing and suggest a computational method to handle data from samples with low quality RNA which also enables reanalysis of published datasets. Using RNA from a human cell line we generated and sequenced samples with varying RINs and illustrate what effect the RIN has on the basic procedure of RNA sequencing; both quality aspects and differential expression. We show that the RIN has systematic effects on gene coverage, false positives in differential expression and the quantification of duplicate reads. We introduce 3' tag counting (3TC) as a computational approach to reliably estimate differential expression for samples with low RIN. We show that using the 3TC method in differential expression analysis significantly reduces false positives when comparing samples with different RIN, while retaining reasonable sensitivity.http://europepmc.org/articles/PMC3954844?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Benjamín Sigurgeirsson
Olof Emanuelsson
Joakim Lundeberg
spellingShingle Benjamín Sigurgeirsson
Olof Emanuelsson
Joakim Lundeberg
Sequencing degraded RNA addressed by 3' tag counting.
PLoS ONE
author_facet Benjamín Sigurgeirsson
Olof Emanuelsson
Joakim Lundeberg
author_sort Benjamín Sigurgeirsson
title Sequencing degraded RNA addressed by 3' tag counting.
title_short Sequencing degraded RNA addressed by 3' tag counting.
title_full Sequencing degraded RNA addressed by 3' tag counting.
title_fullStr Sequencing degraded RNA addressed by 3' tag counting.
title_full_unstemmed Sequencing degraded RNA addressed by 3' tag counting.
title_sort sequencing degraded rna addressed by 3' tag counting.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description RNA sequencing has become widely used in gene expression profiling experiments. Prior to any RNA sequencing experiment the quality of the RNA must be measured to assess whether or not it can be used for further downstream analysis. The RNA integrity number (RIN) is a scale used to measure the quality of RNA that runs from 1 (completely degraded) to 10 (intact). Ideally, samples with high RIN (> 8) are used in RNA sequencing experiments. RNA, however, is a fragile molecule which is susceptible to degradation and obtaining high quality RNA is often hard, or even impossible when extracting RNA from certain clinical tissues. Thus, occasionally, working with low quality RNA is the only option the researcher has. Here we investigate the effects of RIN on RNA sequencing and suggest a computational method to handle data from samples with low quality RNA which also enables reanalysis of published datasets. Using RNA from a human cell line we generated and sequenced samples with varying RINs and illustrate what effect the RIN has on the basic procedure of RNA sequencing; both quality aspects and differential expression. We show that the RIN has systematic effects on gene coverage, false positives in differential expression and the quantification of duplicate reads. We introduce 3' tag counting (3TC) as a computational approach to reliably estimate differential expression for samples with low RIN. We show that using the 3TC method in differential expression analysis significantly reduces false positives when comparing samples with different RIN, while retaining reasonable sensitivity.
url http://europepmc.org/articles/PMC3954844?pdf=render
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