The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be normalized, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples are at times the sole means of addressing specific questions e.g., samples collected in the course of fieldwork. We sought to quantify the impact of variation in RNA quality on estimates of gene expression levels based on RNA-seq data. To do so, we collected expression data from tissue samples that were allowed to decay for varying amounts of time prior to RNA extraction. The RNA samples we collected spanned the entire range of RNA Integrity Number (RIN) values (a quality metric commonly used to assess RNA quality). We observed widespread effects of RNA quality on measurements of gene expression levels, as well as a slight but significant loss of library complexity in more degraded samples. While standard normalizations failed to account for the effects of degradation, we found that a simple linear model that controls for the effects of RIN can correct for the majority of these effects. We conclude that in instances where RIN and the effect of interest are not associated, this approach can help recover biologically meaningful signals in data from degraded RNA samples.
- Downloaded 2,604 times
- Download rankings, all-time:
- Site-wide: 2,189 out of 84,908
- In genomics: 431 out of 5,475
- Year to date:
- Site-wide: 62,351 out of 84,908
- Since beginning of last month:
- Site-wide: 42,070 out of 84,908
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!