Deconvolution of bulk blood eQTL effects into immune cell subpopulations.

BACKGROUND: Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method, Decon2, as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL). RESULTS: The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (≥ 96-100%) and chromatin mark QTL (≥87-92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect. CONCLUSIONS: Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application (https://github.com/molgenis/systemsgenetics/tree/master/Decon2) and as a web tool (www.molgenis.org/deconvolution).

Regulation of mitochondrial gene expression, the epigenetic enigma.

Epigenetics provides an important layer of information on top of the DNA sequence and is essential for establishing gene expression profiles. Extensive studies have shown that nuclear DNA methylation and histone modifications influence nuclear gene expression. However, it remains unclear whether mitochondrial DNA (mtDNA) undergoes similar epigenetic changes to regulate mitochondrial gene expression. Recently, it has been shown that mtDNA is differentially methylated in various diseases such as diabetes and colorectal cancer. Interestingly, this differential methylation was often associated with altered mitochondrial gene expression. However, the direct role of mtDNA methylation on gene expression remains elusive. Alternatively, the activity of the mitochondrial transcription factor A (TFAM), a protein involved in mtDNA packaging, might also influence gene expression. This review discusses the role of mtDNA methylation and potential epigenetic-like modifications of TFAM with respect to mtDNA transcription and replication. We suggest three mechanisms: (1) methylation within the non-coding D-loop, (2) methylation at gene start sites (GSS) and (3) post-translational modifications (PTMs) of TFAM. Unraveling mitochondrial gene expression regulation could open new therapeutic avenues for mitochondrial diseases.