Abstract
Cell subtype proportion variability between samples contributes significantly to the variation of functional genomic properties such as gene expression or DNA methylation. Although the impact of the variation of cell subtype composition on measured genomic quantities is recognized, and some innovative tools have been developed for the analysis of heterogeneous samples, most functional genomics studies using samples with mixed cell types still ignore the influence of cell subtype proportion variation, or just deal with it as a nuisance variable to be eliminated. Here we demonstrate how harvesting information about cell subtype proportions from functional genomics data can provide insights into cellular changes associated with phenotypes. We focused on two types of mixed cell populations, human blood and mouse kidney. Cell type prediction is well developed in the former, but not currently in the latter. Estimating the cellular repertoire is easier when a reference dataset from purified samples of all cell types in the tissue is available, as is the case for blood. However, reference datasets are not available for most other tissues, such as the kidney. In this study, we showed that the proportion of alterations attributable to changes in the cellular composition varies strikingly in the two disorders (asthma and systemic lupus erythematosus), suggesting that the contribution of cell subtype proportion changes to functional genomic properties can be disease-specific. We also showed that a reference dataset from a single-cell RNA-seq study successfully estimated the cell subtype proportions in mouse kidney and allowed us to distinguish altered cell subtype differences between two different knock-out mouse models, both of which had reported a reduced number of glomeruli compared to their wild-type counterparts. These findings demonstrate that testing for changes in cell subtype proportions between conditions can yield important insights in functional genomics studies.
Highlights
Assays that test genomic function are used to understand the cellular and genetic differences in phenotypes between individuals
Our cell subtype deconvolution revealed that the proportion of monocytes was significantly increased and the proportion of resting natural killer (NK) cells was significantly decreased in SLE, obtaining the same results using either DNA methylation or gene expression data (Fig 2A and S2 Fig)
When we re-analyzed gene expression differences between SLE and control subjects having accounted for cell subtype variability, we found that only 4 genes remained significantly differentiallyexpressed out of the 485 differentially-expressed genes (DEGs) (false discovery rate (FDR) 1.2, S7
Summary
Assays that test genomic function are used to understand the cellular and genetic differences in phenotypes between individuals. Several cell type deconvolution approaches for genome-wide assays have been published, and applied to test for sample heterogeneity in gene expression [1,2,3,4,5,6,7] or DNA methylation [8,9,10,11,12,13,14,15], mostly often in studies of tumors or peripheral blood mononuclear cells (PBMCs) [2,6,7,9,12,13,15,16,17]. When the influence of cell subtype variation is included in the analysis of functional genomics studies, in most cases the cellular heterogeneity is treated as a nuisance variable, confounding the researchers’ ability to identify cell-intrinsic changes. By treating cell proportion variation as a nuisance variable to exclude, we fail to identify potentially interesting tissue compositional differences associated with disease phenotypes
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