Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis
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 m...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-02-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-28218-7 |
| _version_ | 1811171754183229440 |
|---|---|
| author | Dylan Sheerin Francisco Lakay Hanif Esmail Craig Kinnear Bianca Sansom Brigitte Glanzmann Robert J. Wilkinson Matthew E. Ritchie Anna K. Coussens |
| author_facet | Dylan Sheerin Francisco Lakay Hanif Esmail Craig Kinnear Bianca Sansom Brigitte Glanzmann Robert J. Wilkinson Matthew E. Ritchie Anna K. Coussens |
| author_sort | Dylan Sheerin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T17:19:16Z |
| format | Article |
| id | doaj.art-4c58c4aa5ae14734864fe13b1e9a05cd |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-10T17:19:16Z |
| publishDate | 2023-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-4c58c4aa5ae14734864fe13b1e9a05cd2023-02-05T12:11:35ZengNature PortfolioScientific Reports2045-23222023-02-0113111110.1038/s41598-023-28218-7Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysisDylan Sheerin0Francisco Lakay1Hanif Esmail2Craig Kinnear3Bianca Sansom4Brigitte Glanzmann5Robert J. Wilkinson6Matthew E. Ritchie7Anna K. Coussens8Infectious Diseases and Immune Defence Division, The Walter and Eliza Hall Institute of Medical ResearchWellcome Centre for Infectious Diseases Research in Africa and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, ObservatoryWellcome Centre for Infectious Diseases Research in Africa and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, ObservatorySouth African Medical Research Council Genomics CentreSouth African Medical Research Council Genomics CentreSouth African Medical Research Council Genomics CentreWellcome Centre for Infectious Diseases Research in Africa and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, ObservatoryEpigenetics and Development Division, The Walter and Eliza Hall Institute of Medical ResearchInfectious Diseases and Immune Defence Division, The Walter and Eliza Hall Institute of Medical ResearchAbstract 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.https://doi.org/10.1038/s41598-023-28218-7 |
| spellingShingle | Dylan Sheerin Francisco Lakay Hanif Esmail Craig Kinnear Bianca Sansom Brigitte Glanzmann Robert J. Wilkinson Matthew E. Ritchie Anna K. Coussens Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis Scientific Reports |
| title | Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis |
| title_full | Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis |
| title_fullStr | Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis |
| title_full_unstemmed | Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis |
| title_short | Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis |
| title_sort | identification and control for the effects of bioinformatic globin depletion on human rna seq differential expression analysis |
| url | https://doi.org/10.1038/s41598-023-28218-7 |
| work_keys_str_mv | AT dylansheerin identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT franciscolakay identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT hanifesmail identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT craigkinnear identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT biancasansom identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT brigitteglanzmann identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT robertjwilkinson identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT mattheweritchie identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis AT annakcoussens identificationandcontrolfortheeffectsofbioinformaticglobindepletiononhumanrnaseqdifferentialexpressionanalysis |