Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis
Author(s)
Type
Journal Article
Abstract
When profiling blood samples by RNA-sequencing (RNA-seq), RNA from haemoglobin (Hgb) can account for up to 70% of the transcriptome. Due to considerations of sequencing depth and power to detect biological variation, Hgb RNA is typically depleted prior to sequencing by hybridisation-based methods; an alternative approach is to deplete reads arising from Hgb RNA bioinformatically. In the present study, we compared the impact of these two approaches on the outcome of differential gene expression analysis performed using RNA-seq data from 58 human tuberculosis (TB) patient or contact whole blood samples-29 globin kit-depleted and 29 matched non-depleted-a subset of which were taken at TB diagnosis and at six months post-TB treatment from the same patient. Bioinformatic depletion of Hgb genes from the non-depleted samples (bioinformatic-depleted) substantially reduced library sizes (median = 57.24%) and fewer long non-coding, micro, small nuclear and small nucleolar RNAs were captured in these libraries. Profiling published TB gene signatures across all samples revealed inferior correlation between kit-depleted and bioinformatic-depleted pairs when the proportion of reads mapping to Hgb genes was higher in the non-depleted sample, particularly at the TB diagnosis time point. A set of putative "globin-fingerprint" genes were identified by directly comparing kit-depleted and bioinformatic-depleted samples at each timepoint. Two TB treatment response signatures were also shown to have decreased differential performance when comparing samples at TB diagnosis to six months post-TB treatment when profiled on the bioinformatic-depleted samples compared with their kit-depleted counterparts. These results demonstrate that failure to deplete Hgb RNA prior to sequencing has a negative impact on the sensitivity to detect disease-relevant gene expression changes even when bioinformatic removal is performed.
Date Issued
2023-02-01
Date Acceptance
2023-01-16
Citation
Scientific Reports, 2023, 13 (1), pp.1-11
ISSN
2045-2322
Publisher
Nature Publishing Group
Start Page
1
End Page
11
Journal / Book Title
Scientific Reports
Volume
13
Issue
1
Copyright Statement
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
© The Author(s) 2023
© The Author(s) 2023
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/36725870
PII: 10.1038/s41598-023-28218-7
Subjects
Humans
Gene Expression Profiling
Hemoglobins
RNA
RNA, Messenger
RNA-Seq
Sequence Analysis, RNA
Transcriptome
Computational Biology
Publication Status
Published
Coverage Spatial
England
Article Number
1859
Date Publish Online
2023-02-01