Human brain MTG single cell data mapped to mouse brain single cell RNAseq?

Is anybody aware of a publication where human brain MTG snRNAseq dataset is projected onto mouse brain scRNAseq dataset entirely as opposed to projecting just specific cell classes (excitatory or inhibitory neurons only, etc)?

This is an interesting analysis question worthy of a whole publication. For some experiments and analysis that have covered this topic, refer to publication references in the Cell Taxonomy section of the Allen Institute for Brain Science website, here: This recent publication by Bakken, Hodge, at al may be interesting to you.

Dear Amy,
Thank you very much for your response! I was reading Hodge et al 2018 preprint in detail.
Would it be fair to extrapolate that by enriching for the specific neuronal class (excitatory for example) in human MTG the dataset would contain most (if not all?) excitatory neurons in human brain across brain regions?
My ultimate question for this pre-print is the following: when mapping the human MTG dataset to mouse scRNAseq, say, specifically for excitatory neurons, how confident we are in the exhaustiveness of each of the dataset (approximately what fraction of all possible human exc. neuron cell types is represented in the human data, and similarly, in the mouse data), and hence in the resulting equivalence of the cell types between the species?

Thank you very much for your help and for an interesting discussion!

Hi @ainej,
These are great questions and our ongoing lines of research are also trying to address them! IMHO, I doubt very much that we have ‘all’ excitatory cell classes represented in human brain based on what we see from the MTG data. I would expect most high level classes to be captured, but we can’t know what we are missing without actually being able to compare with other areas - we are actively gathering more data to help address this. For the most up-to-date access to raw data, consider visiting a collaborative repository of data being generated by the NIH BRAIN Initiative consortium, BICCN (we are part of this). NeMO is hosting RNASeq data from many labs, here: But the data here doesn’t include interpretative analysis, which is in progress.

So: In considering the Hodge et al paper, your question is THE open question for us, also. Drs. Hodge & Bakken, along with many other scientists and data analysts at the Allen Institute, are actively working on this very question and I would you encourage you to seek their newest work out at the Society for Neuroscience conference this year, if you are attending. There, we will have the scientists’ and their posters, presentations and workshops related to botth human and mouse transcriptomics; learn more from our events page.

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Hi @ainej,
To further address this question, I agree with @amyb that we haven’t yet sampled all of the excitatory types in human at the same resolution as in mouse. As a notable example, the cell type defined as “pyramidal tract” in our recent preprint is clearly undersampled. This type is significantly more rare in human than mouse and we have no published way to enrich for this type yet (but our mouse team has a promising enhancer in the works–see Figure 3 here). We have some evidence that these cells will subdivide into more types in human with additional sampling. Please visit our site again after our October release, when we will share our cell types defined using multiple cortical areas in both mouse and human.

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Hi Jeremy,
I had an cell type ontology/definition question. Are all excitatory neuron cell types say, in MTG human dataset, considered pyramidal? For example, I see THY1 and NRGN, reportedly markers of pyramidal cells seem to be highly expressed across all excitatory neuron clusters. Can one state that all the excitatory neurons in this dataset are pyramidal? WHat are the excitatory but non-pyramidal cell types that are not included int his data? Thank you very much!

Hi @ainej, I think it is safe to sat that excitatory neurons are largely, but not entirely, pyramidal, although for convenience we are often not careful with our terms. One example of excitatory cells that are not pyramidal in shape are Von Economo neurons (see our preprint, here). Finally, it is worth noting that we cannot prove that any neuron is excitatory based on transcriptomics alone, only that it expresses a large number of relevant glutamatergic genes. That said, overwhelming evidence from other sources almost guarantees that nearly all of these cell types are excitatory. Again, for convenience we often use these terms interchangeably.

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Thank you very much, Jeremy, for making sense of the terminology! :slight_smile:

Hi Jeremy,
I wanted to ask your opinion regarding neurons characterization in human brain based on snRNAseq.
In a recent paper ( ) human post mortem brain samples were profiled using snRNAseq. The analysis identified various types of neurons, dividing the into excitatory and inhibitory. Focusing on excitatory neurons, the authors chose classification by layers (EN-L2-3, EN-L4,EN-L5) and also included as a separate class excitatory pyramidal neurons (EN-PYR). After our discussion with you on this forum, I found such dichotomy a bit unusual, as I thought pyramidal neurons are present throughout layers and seems like should be a heterogenous class of cells. I looked in more detail into the data and found that EN-PYR labeled cells had about 100 lower total RNA count then other neurons, and so even less total RNA then glia cells. That’s why after library size correction this cluster of cells seemed to be highly expressing THY1 and NRGN which was then assigned to be EN-PYR cell type. I don’t see a snRNAseq out there where I can cross check this particular cell type. I wonder if those could be neuronal debris, however, since this data is snRNAseq the debris/ambient RNA should be discarded and the data should represent only intact nuclei, I’d think. Did you or your colleagues have encountered anything like this in your work? If so, would you have any suggestions on clarifying what these cells may? Thank you very much!

Hi @ainej, the short answer is that I don’t know what that cluster represents, but in our human snRNA-seq data spanning 6 cortical areas both THY1 and NRGN have moderate and nearly ubiquitous expression across all excitatory types. In our experience, all pyramidal cell types show some amount of layer specificity; however, in many types this specificity does not coincide with the cytoarchitectural definition of layer boundaries, and furthermore the borders are often fuzzy.