Sequencing degraded RNA addressed by 3' tag counting
| Autor: | Joakim Lundeberg, Benjamín Sigurgeirsson, Olof Emanuelsson |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Microarrays
RNA Stability lcsh:Medicine Biochemistry Transcriptome Degradation Gene expression Biologiska vetenskaper Genome Sequencing lcsh:Science Genetics Multidisciplinary Number food and beverages Genomics Biological Sciences Genomic Databases Bioassays and Physiological Analysis SEQ RNA extraction Transcriptome Analysis Sequence Analysis Transcription Research Article Biotechnology Integrity DNA transcription Sequence Databases Biological Data Management Biology Research and Analysis Methods Cell Line Tumor Quantification Humans Molecular Biology Techniques Sequencing Techniques Molecular Biology Sequence Assembly Tools Biology and life sciences cDNA library Sequence Analysis RNA lcsh:R RNA Computational Biology Ribosomal RNA Genome Analysis Gene expression profiling Small Molecules lcsh:Q Genome Expression Analysis |
| Zdroj: | PLoS ONE, Vol 9, Iss 3, p e91851 (2014) PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | 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. QC 20140423 |
| Databáze: | OpenAIRE |
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