Sources of variation in cell-type RNA-Seq profiles
Artikel i vetenskaplig tidskrift, 2020

Cell-type specific gene expression profiles are needed for many computational methods operating on bulk RNA-Seq samples, such as deconvolution of cell-type fractions and digital cytometry. However, the gene expression profile of a cell type can vary substantially due to both technical factors and biological differences in cell state and surroundings, reducing the efficacy of such methods. Here, we investigated which factors contribute most to this variation. We evaluated different normalization methods, quantified the variance explained by different factors, evaluated the effect on deconvolution of cell type fractions, and examined the differences between UMI-based single-cell RNA-Seq and bulk RNA-Seq. We investigated a collection of publicly available bulk and single-cell RNA-Seq datasets containing B and T cells, and found that the technical variation across laboratories is substantial, even for genes specifically selected for deconvolution, and this variation has a confounding effect on deconvolution. Tissue of origin is also a substantial factor, highlighting the challenge of using cell type profiles derived from blood with mixtures from other tissues. We also show that much of the differences between UMI-based single-cell and bulk RNA-Seq methods can be explained by the number of read duplicates per mRNA molecule in the single-cell sample. Our work shows the importance of either matching or correcting for technical factors when creating cell-type specific gene expression profiles that are to be used together with bulk samples.

Författare

Johan Gustafsson

Chalmers, Biologi och bioteknik, Systembiologi

Wallenberg Center for Protein Research (WCPR)

Felix Held

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Jonathan Robinson

Chalmers, Biologi och bioteknik, Systembiologi, CSBI

Wallenberg Center for Protein Research (WCPR)

Elias Björnson

Chalmers, Biologi och bioteknik, Systembiologi

Göteborgs universitet

Rebecka Jörnsten

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Jens B Nielsen

Wallenberg Center for Protein Research (WCPR)

Chalmers, Biologi och bioteknik, Systembiologi

BioInnovation Institute

PLoS ONE

1932-6203 (ISSN)

Vol. 15 9 e0239495-

Ämneskategorier

Immunologi

Cell- och molekylärbiologi

Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)

DOI

10.1371/journal.pone.0239495

PubMed

32956417

Mer information

Senast uppdaterat

2020-10-12