First, a quick note to WIMG users: I'll be disappearing into the Himalayas for 2 months or so. Forgive the absence of new posts, database updates, and responses to your e-mails.
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We've made a couple additions to the "Cell Type" filter that can be applied in most of our apps.
First, you'll see a "Dominant Tissue" choice. What does that mean? A number of big science studies (e.g. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues) have attempted to delineate proteomes/transcriptomes across whole organisms. Such studies allow one to ask, "what genes are expressed uniquely in a particular tissue (versus other tissues)?" We've combed through these studies to find these genes. Thus, for example, the gene MAGEE2 is expressed near exclusively in nerve tissue.
Knowledge of a gene's tissue-uniqueness is potentially useful for at least two purposes, we think. First, if you see an abundance of, say, appendix-unique genes in the blood, perhaps there's some leakage from the appendix. We've indeed noticed an enrichment for appendix transcripts in septic blood in some studies. Unexpected levels of particular genes could also indicate sample contamination. Secondly, tissue-unique genes could be excellent drug targets in some cases. You can place current drug treatments at some point between two extremes. At one extreme, a very general sort of treatment would have an equal effect on all cells in the body. At the other end, you have modern personalized medicine approaches that only target very specific cells (e.g. neoantigen vaccines against cancer). In the middle, or perhaps toward the "specialized" end of the spectrum, you could have treatments that only target specific organs or cell types. If a gene is both lung-unique and necessary in lung cancer, one could target that gene without effects on other organs.
The most obvious use of this feature is with the "Fisher" or "Match Studies" apps. Let's say you have a list of blood transcripts. Plug them into the Fisher app and select "Dominant Tissue" in the "Cell Type" filter (left side of the screen, black background). Submit. You'll receive information about the various tissue types found within the blood sample. Of course, if the blood is absolutely "pure", you won't get any interesting output...perhaps you'll find that the blood is enriched with blood-only transcripts, which is not particularly exciting. In any case, you probably won't see extreme P-values in the list; some of the "tissue dominant" lists in our database are fairly short, simply because tissue-unique transcripts/protein are not common. The shortness of these lists limits the possibility of seeing crazy P-values.
Bear in mind that the output is only as good as the tissue-dominant lists we've constructed. As seen above, one of the studies we draw upon is a deep analysis of 29 human tissues. In this case, we base "uniqueness" on the fact that particular transcripts were seen in only one of the 29 tissues. There are, of course, more than 29 tissues in the human body, so it's possible that a transcript we've labeled as "tissue-unique" could be found in a tissue (say, tissue #30) that was not examined in the study. One can also question whether some transcripts/proteins would be so unique under perturbation (e.g. cancer, infection, drug treatment, etc), as the underlying studies focus primarily on healthy, equilibrium tissues.
The second addition to choices under the "Cell Type" filter involves blood. You could select "blood" or "blood plus." Mere "blood" will eliminate all studies not involving whole blood, or large fractions of blood. "Blood plus", however, includes studies involving all the sorts of cells that are expected to be found in blood; macrophages, lymphocytes, mast cells, monocytes, erythrocytes, blood stem cells, as well as whole blood. If you're examining the blood transcriptome, you may find this minor alteration to be of use.
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