. Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression. Cell. 2018 Nov 29;175(6):1701-1715.e16. Epub 2018 Nov 15 PubMed.

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  1. The Schmiedel et al. paper offers similar highlights to those found in Hammond et al.

    1. Sex differences.
    2. Disease differences, though this time done by comparing cell-type specific transcriptome data sets with already-available GWAS data sets.
    3. Done in human cells. It would have been nice to see a comparison with the “same” cell types from rodents, to see how well individual immune cell transcriptomes are preserved across species so that we can start to make some decisions about which cells are appropriate models for human.

    The website accompanying Schmiedel et al. is just beautiful. The sheer amount of data on it is a dream, as is the easy-to-manipulate visualization, e.g., changing FC cutoff to determine above/below expression of a gene in multiple cell types. Paired with the Hammond microglia paper, this manuscript provides a key pair of searchable data that the field has been lacking. (I would also add the manuscript by Tristan Qingyun Li/Ben Barres with additional single cell transcriptomics. It’s available on bioRxiv but accepted and to be out soon).

    References:

    . Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes. Immunity. 2018 Nov 21; PubMed.

    . Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencing. Neuron. 2019 Jan 16;101(2):207-223.e10. Epub 2018 Dec 31 PubMed.

  2. Stunning achievement, combining genome-wide SNP analysis with RNA-Seq—protein-coding; pseudogenes; lncRNAs; sncRNAs—in 13 human immune cell types, primarily lymphocytes. Once cis eQTL, i.e., SNPs that affected expression of a gene on the same chromosome, were identified, abundant salient, non-trivial, unexpected observations were made. Of all genes expressed across this panel of immune cells, more than half exhibited eQTLs, suggesting a strong effect of germline genetics on human adaptive immune responses. Of genes showing cis eQTL, 40 percent demonstrated effect in only one cell type, and the great majority in only one to three cell types. Importantly, most of these genes were expressed in multiple cell types so cis eQTL occurred due to an epigenomic landscape present in one, two or a few cell types. Further, it was common for cis eQTL to affect expression in a cell that expressed the regulated gene at lower levels than a cell not showing eQTL. Some eQTL were only apparent after cell activation, in this case polyclonal activation of naive CD4+ or CD8+ T cells.

    SNPs that appeared in GWAS analysis of the genetic architecture of human disease, primarily cancer and autoimmune conditions, were evaluated and shown to be nearly 20 percent of all SNPs associated with eQTL. Main emphasis was on T cells and their subtypes. Informative examples were provided: The LACC gene is known to harbor a risk allele for inflammatory bowel disease (IBD), and its strong expression in myeloid cells led to the interpretation that myeloid cell LACC mediates genetic risk for IBD. However, the eQTL analysis identified the effect only in T cells, which may refocus research on this gene-disease connection. For Crohn's disease, a substantial fraction of eQTL affected only one cell type, raising the question whether genetic subtypes of CD could be identified. 

    The sine qua non for cell-specific eQTL identification is sufficient numbers of genotyped samples. Efforts are underway to obtain such data resources, which require collaboration among groups with experience obtaining and analyzing purified human brain cell populations. Implications for brain eQTL in microglia are several: Given that genes harboring disease SNPs are expressed in multiple cells types, e.g. BIN1 in both neurons and microglia, or GRP56 in microglia, astrocytes, and oligodendrocyte lineage, microglia should be compared with other brain cells, as well as with other tissue macrophages.

    Effects of biological sex on expression of cell-type-specific genes in immune cells were impressive. Of all expressed genes in immune cells, 1,875 showed sex bias. More than 90 percent were on autosomes; they were enriched in protein-coding genes and nearly always showed sex bias in one or two cell types, despite expression across multiple cell types.

    The present resource will be of enormous value to the community of researchers interested in how the immune system affects disease. It also provides a useful game plan for extending this form of study to other tissues of interest. One would like to see experiments in which monocytes (classical and non-classical) are subjected to stimulation to elicit additional activation-dependent eQTL. Cells studied here were positively selected, which can induce activation. Some data from this study could also be replicated in negatively selected cells as well.

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