Truncated radial glia as a common precursor in the late corticogenesis of gyrencephalic mammals
Curation statements for this article:-
Curated by eLife
eLife assessment
This is an important study that improves gene models for the ferret genome and identifies neural progenitors that are comparable to those found in developing human brains. The data are convincing and clearly presented. Of particular interest to the field, the work identifies enriched expression of FOXJ1 in late truncated radial glia, strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. The work is of interest to anyone studying the development of the nervous system, especially colleagues studying the evolution of development.
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (eLife)
- Evaluated articles (Review Commons)
Abstract
The diversity of neural stem cells is a hallmark of the cerebral cortex development in gyrencephalic mammals, such as Primates and Carnivora. Among them, ferrets are a good model for mechanistic studies. However, information on their neural progenitor cells (NPC), termed radial glia (RG), is limited. Here, we surveyed the temporal series of single-cell transcriptomes of progenitors regarding ferret corticogenesis and found a conserved diversity and temporal trajectory between human and ferret NPC, despite the large timescale difference. We found truncated RG (tRG) in ferret cortical development, a progenitor subtype previously described in humans. The combination of in silico and in vivo analyses identified that tRG differentiate into both ependymal and astrogenic cells. Via transcriptomic comparison, we predict that this is also the case in humans. Our findings suggest that tRG plays a role in the formation of adult ventricles, thereby providing the architectural bases for brain expansion.
Article activity feed
-
-
-
-
Author Response
The following is the authors’ response to the original reviews.
Reviewer #1 (Recommendations For The Authors):
- The improvement of the gene annotations of the ferret genome was an important part of this study, and so I would recommend that the authors have a results section and figure dedicated to documenting this.
Thank you so much for appreciating our efforts on improving gene models, which was indeed a critical part in this study. According to the reviewer’s suggestion, we added a new section to the main text, “Improvement of the gene model for scRNA-seq of ferrets” with a figure (Fig.1 C, D, E).
- Are the references to figure S8A, B alright (line 306)? In fact, that entire figure was not well described or out of place. In general, unlike the rest of the manuscript, the section dealing with the human-ferret …
Author Response
The following is the authors’ response to the original reviews.
Reviewer #1 (Recommendations For The Authors):
- The improvement of the gene annotations of the ferret genome was an important part of this study, and so I would recommend that the authors have a results section and figure dedicated to documenting this.
Thank you so much for appreciating our efforts on improving gene models, which was indeed a critical part in this study. According to the reviewer’s suggestion, we added a new section to the main text, “Improvement of the gene model for scRNA-seq of ferrets” with a figure (Fig.1 C, D, E).
- Are the references to figure S8A, B alright (line 306)? In fact, that entire figure was not well described or out of place. In general, unlike the rest of the manuscript, the section dealing with the human-ferret comparison was a little bit confusing, and the figure legends were not extremely helpful. Could the authors please revisit the main text and figure legends of this section for clarity?
We agree with the reviewer’s recommendation. We removed references to Figure S8A, B. In place of that, we explained the reason more carefully; “We chose a recently published human dataset (Bhaduri et al, 2021) for comparison, because this study containing GW25 dataset which included more tRG cells than previous studies that did not contain GW25 data. Furthermore, we used only data at GW25”
We also revised several parts in this section to understand more easily by additional explanations as well as in the legends of Fig. 7 and Fig. S8.
Reviewer #2 (Recommendations For The Authors):
I have a few very minor comments on the manuscript.
- I would caution the authors against claiming that they have demonstrated bona fide generation of ependymal cells from tRG cells. While the expression of FOXJ1 is a very good indication, they have not demonstrated the morphological transformation of a tRG cell into an ependymal cell.
We agree the reviewer’s opinion. We have never thought that we proved that tRG differentiates ependymal cells, but we consider that this is highly likely the case (We use the term “suggest” in the abstract). To prove this genetically, we extensively tried to knock the EGFP gene into the CRYAB gene by the CRISPR/Cas9 method, to be able to show the lineage relationship between tRG and ependymal cells. However, we have so far failed to do this for a year trial. We also tried to just label tRG with EGFP and follow it in the slice culture.
However, we failed to keep the slice in the culture until we observed the transition from tRG shape to the ependymal shape. It seems to be a slow process. What we could do was to observe the transition from single cilia to multi-cilia, which is part of the morphological transition from epithelial neural stem cells such as Radial Glia to an ependymal-like sheet form. To prove this transition from tRG to ependymal cells (and also astrocytes) is one of the most important issue which needs some new idea, technique or strategy.
- There are several typos throughout the manuscript that I would recommend fixing for example, page 5 line 123 says "OLIGO2" instead of "OLIG2"
Thank you so much. We carefully read and corrected typos. We wish we corrected all of them.
Besides these two points, the manuscript is already prepared to a high standard.
I really appreciate reviewersʼ efforts to finish reviews in a short time, responding to our request related to the first authorʼs thesis application.
-
eLife assessment
This is an important study that improves gene models for the ferret genome and identifies neural progenitors that are comparable to those found in developing human brains. The data are convincing and clearly presented. Of particular interest to the field, the work identifies enriched expression of FOXJ1 in late truncated radial glia, strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. The work is of interest to anyone studying the development of the nervous system, especially colleagues studying the evolution of development.
-
Reviewer #1 (Public Review):
In this manuscript, Bilgic et al aim to identify the progenitor types (and their specific progeny) that underlie the expanded nature of gyrencephalic brains. To do this, they take a comparative scRNAseq (single cell transcriptomics) approach between neurodevelopment of the gyrencephalic ferret, and previously published primary human brain and organoid data.
They first improve gene annotations of the ferret genome and then collect a time series of scRNAseq data of 6 stages of the developing ferret brain spanning both embryonic and post-natal development. Among the various cell types they identify are a small proportion of truncated radial glial cells (tRGs), a population known to be enriched in humans and macaques that emerges late in neurogenesis as the RGC scaffold splits into an oRGC that contact the pial …
Reviewer #1 (Public Review):
In this manuscript, Bilgic et al aim to identify the progenitor types (and their specific progeny) that underlie the expanded nature of gyrencephalic brains. To do this, they take a comparative scRNAseq (single cell transcriptomics) approach between neurodevelopment of the gyrencephalic ferret, and previously published primary human brain and organoid data.
They first improve gene annotations of the ferret genome and then collect a time series of scRNAseq data of 6 stages of the developing ferret brain spanning both embryonic and post-natal development. Among the various cell types they identify are a small proportion of truncated radial glial cells (tRGs), a population known to be enriched in humans and macaques that emerges late in neurogenesis as the RGC scaffold splits into an oRGC that contact the pial surface and a tRG that contacts the ventricular surface. They find that the tRGs consist of three distinct subpopulations two of which are committed to ependymal and astroglial fates.
By integrating these data with publicly available data of developing human brains and human brain organoids they make some important observations. Human and ferret tRGs have very similar transcriptional states, suggesting that the human tRGs too give rise to ependymal and astroglial fates. They also find that the current culture conditions of human brain organoids seem to lack tRGs, something that will need to be addressed if they are to be used to study tRGs. While the primary human data set did contain tRGs, the stage or the region sampled were likely not appropriate, and therefore, the number of cells they could retrieve was low.
The authors have spent considerable efforts in improving gene modeling of the ferret genome, which will be important for the field. They've generated valuable time series data for the developing ferret brain, and have proposed the lineal progeny for the tRGs in the human brain. Whether tRGs actually do give rise to the ependymal and astrogial fates needs to be validated in future studies.
-
Reviewer #2 (Public Review):
Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of …
Reviewer #2 (Public Review):
Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. This study represents a major advancement in the field of cortical development and a valuable dataset for future studies of ferret cortical development.
-
-
-
Author Response
Summary of reviewers recommendations.
Reviewer 1
Point# 1. Make a new section in the text with a figure about the improvement of the genomic information (gene modeling) of ferrets ".
Point# 2. the references to figure S8A, B alright (line 306)?
Point# 3. Revise the main text and figure legends of the section dealing with the human-ferret comparison for clarity.
Reviewer 2
Point# 4. Weaken (change the text from “conclusive” to suggestive” ) the expression that we identified that tRG become ependymal cells, because we have not demonstrated the morphological transformation of a tRG cell into an ependymal cell, which is practically difficult although we have shown morphological change in terms of the single-cilia to multi-cilia form transition (Fig. S6A).
Point# 5. Correct several typos throughout the …
Author Response
Summary of reviewers recommendations.
Reviewer 1
Point# 1. Make a new section in the text with a figure about the improvement of the genomic information (gene modeling) of ferrets ".
Point# 2. the references to figure S8A, B alright (line 306)?
Point# 3. Revise the main text and figure legends of the section dealing with the human-ferret comparison for clarity.
Reviewer 2
Point# 4. Weaken (change the text from “conclusive” to suggestive” ) the expression that we identified that tRG become ependymal cells, because we have not demonstrated the morphological transformation of a tRG cell into an ependymal cell, which is practically difficult although we have shown morphological change in terms of the single-cilia to multi-cilia form transition (Fig. S6A).
Point# 5. Correct several typos throughout the manuscript that I would recommend fixing for example, page 5 line 123 says "OLIGO2" instead of “OLIG2.
Provisional revision plan and our responses.
Point #1 The new section for the improvement of gene models will be made by transferring the part of methods to the main text and Fig S2B,C to new Figure 1 with one schematic panel.
Point #2; We cited (Bhaduri et al., 2020) as a reference in the figure S8A , while "Bhaduri et, al, 2021” was cited in the text. Which is correct? We will correct this, by choosing the correct one. Descriptions are indeed poor regarding Fig. S8A and S8B in the text as well as in the legends.
Point #3 : We will describe the methods of comparison between ferrets and humans more thoroughly, by adding definition of words such as gene scores, subtype scores in the main text. (as well, the explanation of (Figure S3C) will be improved. ). Legends for Fig. 6 are too simple. So we would explain more in these legends. Explanations of analysis and figures, which we made, responding to the reviewer comments of “review commons” are generally not easy to understand with too short explanations, comparing with complexity of figures and contents, let’s say, Figure S8A-D. We will give more explanations for each of panel in Figure S8A-D, and E and F.
Point #4; The authors' response to this point goes like this; we totally agree that we need to genetically labeling (knocking in the Cryab gene) to prove “tRG cells differentiate ependymal cells”. We tried many times but eventually failed. We have partially show single-cilia to multi-cilia transition which is characteristic to epithelial-ependymal transition. This process appears to take a long time and therefore, morphological tracing by time-lapse imaging in tissue culture is not a realistic way, Therefore, we weakened the conclusion; it is "highly likely" that tRG cells differentiate to be ependymal cells.
Point#5: We will survey typos-> correct them, by all authors read the manuscript carefully again.
-
eLife assessment
This is an important study that improves gene models for the ferret genome and identifies neural progenitors that are comparable to those found in developing human brains. The data are convincing and clearly presented. Of particular interest to the field, the work identifies enriched expression of FOXJ1 in late truncated radial glia, strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. The work is of interest to anyone studying the development of the nervous system, especially colleagues studying the evolution of development.
-
Reviewer #1 (Public Review):
In this manuscript, Bilgic et al aim to identify the progenitor types (and their specific progeny) that underlie the expanded nature of gyrencephalic brains. To do this, they take a comparative scRNAseq (single cell transcriptomics) approach between neurodevelopment of the gyrencephalic ferret, and previously published primary human brain and organoid data.
They first improve gene annotations of the ferret genome and then collect a time series of scRNAseq data of 6 stages of the developing ferret brain spanning both embryonic and post-natal development. Among the various cell types they identify are a small proportion of truncated radial glial cells (tRGs), a population known to be enriched in humans and macaques that emerges late in neurogenesis as the RGC scaffold splits into an oRGC that contact the pial …
Reviewer #1 (Public Review):
In this manuscript, Bilgic et al aim to identify the progenitor types (and their specific progeny) that underlie the expanded nature of gyrencephalic brains. To do this, they take a comparative scRNAseq (single cell transcriptomics) approach between neurodevelopment of the gyrencephalic ferret, and previously published primary human brain and organoid data.
They first improve gene annotations of the ferret genome and then collect a time series of scRNAseq data of 6 stages of the developing ferret brain spanning both embryonic and post-natal development. Among the various cell types they identify are a small proportion of truncated radial glial cells (tRGs), a population known to be enriched in humans and macaques that emerges late in neurogenesis as the RGC scaffold splits into an oRGC that contact the pial surface and a tRG that contacts the ventricular surface. They find that the tRGs consist of three distinct subpopulations two of which are committed to ependymal and astroglial fates.
By integrating these data with publicly available data of developing human brains and human brain organoids they make some important observations. Human and ferret tRGs have very similar transcriptional states, suggesting that the human tRGs too give rise to ependymal and astroglial fates. They also find that the current culture conditions of human brain organoids seem to lack tRGs, something that will need to be addressed if they are to be used to study tRGs. While the primary human data set did contain tRGs, the stage or the region sampled were likely not appropriate, and therefore, the number of cells they could retrieve was low.
The authors have spent considerable efforts in improving gene modeling of the ferret genome, which will be important for the field. They've generated valuable time series data for the developing ferret brain, and have proposed the lineal progeny for the tRGs in the human brain. Whether tRGs actually do give rise to the ependymal and astrogial fates needs to be validated in future studies.
-
Reviewer #2 (Public Review):
Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of …
Reviewer #2 (Public Review):
Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. This study represents a major advancement in the field of cortical development and a valuable dataset for future studies of ferret cortical development.
-
-
Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Manuscript number: RC-2023-01919
Corresponding author(s): Fumio, Matsuzaki and Quan, Wu.
[The “revision plan” should delineate the revisions that authors intend to carry out in response to the points raised by the referees. It also provides the authors with the opportunity to explain their view of the paper and of the referee reports.
The document is important for the editors of affiliate journals when they make a first decision on the transferred manuscript. It will also be useful to readers of the reprint and help them to obtain a balanced view of the paper.
If you wish to submit a full revision, please use our "Full Revision" template. It is important to use the appropriate …
Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Manuscript number: RC-2023-01919
Corresponding author(s): Fumio, Matsuzaki and Quan, Wu.
[The “revision plan” should delineate the revisions that authors intend to carry out in response to the points raised by the referees. It also provides the authors with the opportunity to explain their view of the paper and of the referee reports.
The document is important for the editors of affiliate journals when they make a first decision on the transferred manuscript. It will also be useful to readers of the reprint and help them to obtain a balanced view of the paper.
If you wish to submit a full revision, please use our "Full Revision" template. It is important to use the appropriate template to clearly inform the editors of your intentions.]
General Statements [optional]
This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.
We thank two reviewers very much for their comments. Their comments greatly contribute to our revision plan. Reviewer 1 fairly evaluated our data and provided us constructive and supportive comments. We incorporated responses to Reviewer 1’s comments to our revision plan, in which we made some novel analyses and discussions according to Reviewer1’s comments. Reviewer 2 also provided us very helpful comments, which are based on his/her careful reading of our manuscript, especially from the viewpoints of a ferret specialist. These comments help us to improve our manuscript very much, whereas some of the reviewer 2’s requests appear beyond the scope of our paper and against the policy of Review Comments; the standard policy of the review for Review Commons is “do not add new pipeline of experiments” such as adding additional replicates for scRNAseq. We have made revision plans (section 2) according to the order of comments given by reviewer 1 and then next by reviewer 2, considering all the statements of the two reviewers on balance; there are 6 comments from reviewer 1, and 25 comments from reviewer 2. In the section 2, we selected revision plans that we have reflected to the preliminary revision of our manuscript.
Finally, we would like to note our fundamental interest; we are studying the cortical development of ferrets as a model of brain development to understand what mechanisms are conserved or species-specific during brain size expansion in the mammalian evolution, which, of course, includes humans. It would be great if the ferret model can be a tool used to study tRG cell biology, contributing to understanding the human cortical development.
For this purpose, it’s been critical to create series of single cell transcriptomes along cortical development. A comparison between humans and ferrets, focused in this paper, is the first attempt, because human data of single cell transcriptomes have been extraordinary enriched. These attempts of comparisons between ferrets and humans will provide valuable information about which mechanism is shared and which is not shared for the cortical development in the gyrencephalic mammals. To represent the usefulness of our approach, we chose finding of tRG in ferrets as a symbolic example, and analyzed its origin and fates.
Description of the planned revisions
Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.
Reviewer #1 (Evidence, reproducibility and clarity (Required)):
Summary: Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).
In this manuscript, the authors conduct a series of single-cell transcriptomic analyses and imaging assays in the developing ferret cortex suggesting that (1) ferrets harbor a radial glia (RG) subtype similar to the truncated radial glia (tRG) described previously in humans that may have the potential to (2) produce ependymal and astrogenic lineages which (3) can also be found in the developing human cortex. These findings appear to be an important step in the validation and development of the ferret model towards a tool that can be used to study tRG cell biology, a feat currently difficult due to the inaccessibility of a genetically tractable source of tRG for molecular and cell biology experiments.
Major comments:
- Are the key conclusions convincing?
I found the key conclusions described above and in the authors' abstract convincing. I found the identification of a distinct, tRG-like cell type from the authors' single-cell transcriptomic analysis of the ferret cortex compelling, particularly because (1) the expression of the previously utilized tRG marker gene CRYAB is specific to the tRG-like cluster and (2) the tRG-like cluster marker genes (including CRYAB) are relatively unique to the tRG-like cluster. I found this strengthened by their morphological analyses showing the tRG-characteristic apical endfoot and short basal process in these CRYAB+ cells in the ferret cortex. I found the combination of imaging and bioinformatic analyses showing the increase in FOXJ1 co-expression in CRYAB+ cells to compellingly suggest that CRYAB+ cells can produce FOXJ1+ ependymal cells, and similarly with the authors' analyses to suggest that tRG-like cells can also contribute to SPARCL1+ astrocyte cells. I found that the cluster score analyses compelling suggest that the tRG-like cells in the ferret dataset correlate with the tRG cells annotated in a separate, human developing cortical dataset. I also appreciated the comparison of astroglial, ependymal, and uncommited ferret tRG sub populations from the pseudo time analysis with the clusters generated from the integrated ferret-human dataset in Fig. 7.
- Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
- Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
- Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
1-1. The weakest claim in the paper is lines 202: "...tRG cells are formed by apical asymmetric division(s) from unique apical IPC". From my understanding, the main evidence that the tRG parent cells shown in Fig. 3 are not tRGs are the data from Fig. 2E-G showing the low amounts of CRYAB+ cells co-expressing KI67, TBR2, or OLIG2 in P5 and P10. Especially given that these timepoints are after those used in Fig. 3, I believe further evidence is needed to confirm the cell type identity of tRG parent cells in Fig. 3. Such experiments (isolating IPCs from ferret cortex and growing in vitro to determine progeny cells) may be outside of the scope of this paper, in which case I believe the text can be strengthened with either (1) presenting the data from the cited Tsunekawa et al, in preparation that would suggest this claim or (2) rephrasing these claims to omit the mention of IPCs.
We thank the reviewer for the suggestion to revise the definition of tRG parent cells in lines 194-204. This issue is also pointed out by the reviewer 2.
Revision plan:
- We revise the term “IPC” as “mitotic sibling of vRG” and stated that these cells might be tRG (CRYAB+) or non-tRG (CRYAB-) intermediate progenitors. By the term of “intermediate progenitors”, we did not intend to refer to TBR2+ neurogenic IPCs, but rather to an intermediate state of progenitors, in a general sense, with a similar morphology as tRG. To avoid any confusions on this terminology, we revised our manuscript by replacing “IPC” with “a sibling of vRG”.
- We delete all statements relevant to Tsunekawa et al. data from the manuscript. We regret that we are not able to include Tsunekawa et al. data because we are planning to submit this data as a separate manuscript, which describes that in ferrets, vRG frequently (30% of apical division) generate non-Tbr2-positive mitotic sibling cells bearing a short basal process during the entire neurogenesis. This study includes a large volume of data with human ones and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not appropriate to combine these data with those described in this manuscript.
- As also pointed by reviewer 2, we cannot exclude the possibility that the mitotic sibling cells of vRG with a short basal process (IPC in the previous version of the manuscript) are also CRYAB positive tRG. To clarify the identity and variety of vRG sibling cells at tRG-generating stage, we are examining the sibling pairs of vRG by immunostaining for a mitotic marker Ki67 and CRYAB during P0-P5 after incorporating EGFP by electroporation to label vRG lineages. We will increase the sample size for a quantification and statistical analyses of this newly provided data to incorporate in our fully revised manuscript.
1-2. I also believe the claim in Line 365-366 is overstated: "We found that ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." While I believe the transcriptomic comparisons suggest the presence of uncommitted tRG in both the ferret and human datasets, I would appreciate further analyses to confirm the prevalence of astroglial and ependymal tRG in the humans and/or functional analyses before claiming that human tRG cells make ependymal and astrogenic cells. I appreciate the authors' note that "GW25 is...the latest stages experimentally available" (line 376-377), but their comparative approaches could be applied to existing datasets of the human cortex (Herring et al., 2022, PMID: 36318921) that span later developmental ages. Identifying the presence of astroglial and ependymal tRGs in this and/or similar datasets would provide more convincing evidence of the tRGs' developmental potential. If this computational analysis is outside the scope of the paper, I believe paring the certainty of these claims (especially lines 379 - 383) and recognizing the need for further functional analyses would negate the need for deeper mechanistic validation.
We agree with the Reviewer 1 that identifying the presence of astroglial and ependymal tRGs in datasets spanning later developmental stages would provide convincing evidence for the potential of human tRG.
Revision plan:
- We compared our ferret dataset to the human postnatal dataset recommended by the Reviewer 1 (Herring et al., 2022). As a conclusion of our analyses shown below, we found that Herring et al., (2022) dataset was not favorable for a comparative analysis with our ferret dataset regarding the fates of human tRG, because Herring’s human dataset was derived from the prefrontal cortex; This human dataset does not include neither tRG cell population nor ependymal clusters. We have also elaborated our discussion after analyzing Herring et al. dataset in the discussion.
- We, therefore, pare down our claim in lines 365-366, by removing “(and presumably human)” to state that “Our pseudotime trajectory analyses and immunohistochemistry analyses strongly suggested that…”.
- We also tone down the statements as for the discussion of the relationship between human and ferrets regarding the tRG progeny fates (originally lines from 372 to the end) also elaborated our discussion after analyzing Herring et al. dataset in the same paragraph.
We will describe the details of our analysis of Herring et al. (2022) below.
As mentioned above, Herring’s human dataset was derived from the prefrontal cortex, and that it did not include a specific subtype defined as tRG nor other HES1-expressing progenitor clusters such as RG in the original cluster annotation. We, therefore, re-clustered the raw dataset from GW22 (the earliest stage available) up to 10-months after birth by using Seurat pipeline with default parameters (B), and found a CRYAB-expressing population in the original “Astrocyte_GFAP” subtype among astrocyte clusters (A), which distribute in the most of collected stages, from late development through the adulthood. We then examined this dataset to find out whether tRG or its progenies are present.
After reclustering, CRYAB-expressing cells (with more than 1 raw count) represented 0.15% of the dataset and were grouped as a part of cluster 44, which was mostly derived from postnatal stages (among which 4-months was the most enriched one; C). Several astrocyte markers, such as SPARCL1, HOPX, CLU, and GJA1, as well as CRYAB, were enriched in the cluster 44 as revealed by FindMarkers (Methods). FOXJ1 expression was nearly absent overall in this dataset, indicating the absence of the ependymal cell population, a tRG-descendant cell types in ferrets (C).
To evaluate the similarity between cluster 44 and tRG or astroglial tRG, we next integrated Herring dataset with our ferret subset (about 15,000 cells) and the human GW25 subset from Bhaduri et al. (2021) of approx. 3,000 cells, both of which contained only progenitor cells. As we have done in Figure 7 of our original manuscript; we have removed cells other than progenitors, astrocytes and oligodendrocytes, such as neurons, microglia, endothelial cells. This resulted in about 20,000 cells in Herring dataset.
This integration (D) reveals that Herring’s cluster 44 is closely located to Bhaduri’s human and our ferret tRG clusters on UMAP, but does not overlap with these tRG clusters. This result further suggested that tRG population might be lacking or very rare in this neuron- and glia-dominated dataset, which might be due to the sampling method that targeted the enrichment of neuronal layers (Herring et al., 2022). It is also possible that this fragmented information on astrocyte and ependymal lineages could be due to the regional and/or temporal difference of samples between two human datasets.
1-3. I believe the most significant advance for this paper is the potential to use ferret tRG cells to model those of the human brain. However to support this claim (see Lines 83-84), I believe a comparison of the ferret tRG cells with existing cortical organoid datasets (Bhaduri et al., 2020, PMID: 31996853) would be helpful. If cortical organoids currently lack the presence of tRG cell types, that would strengthen the importance of the ferret model and the findings of this paper - otherwise, I feel that the use of the ferret model needs to be justified in light of the greater accesibility and genetic tractability of the cortical organoid system.
We absolutely agree that human organoids are good models to study human brain development.
Revision plan:
According to the suggestion of reviewer 1, we analyzed two cortical organoid datasets (Bhaduri et al., 2020; Herring et al., 2022) to examine whether different tRG populations are present in organoids. Our analyses led us to conclude that tRG-like populations seem to be lacking in available organoid datasets; organoids can have CRYAB-expressing astrocyte-like cells in single-cell transcriptome datasets, but the presence of tRG-like cells seem to be unstable and dependent of lines and protocols how organoids are generated. A further assessment on tRGs’ cellular features is required on organoids by immunostaining experiments. In the light of this analysis, we elaborated our discussion by describing observations shown below. Below is our analysis of organoid data.
Bhaduri dataset contained organoids generated from 4 different lines, which showed a variability in terms of cell distribution on UMAP while overall temporal and differentiation axes were recapitulated (A). While keeping the original cluster annotations except for YH10 line, we performed reclustering. CRYAB was expressed in clusters 26 and 30 enriched in YH10 line, and cluster 29 enriched in 13234 line (B).
To confirm the identity of these clusters, we integrated organoid dataset with the dataset of primary tissues from the same paper (Bhaduri et al., 2020; C).
As a result of the integration, tRG cells from the primary tissue were not overlapped with organoid-derived CRYAB-expressing cells, although a part of CRYAB-expressing organoid cells were localized in the integrated cluster 16 where primary tRG resided (D). Other cell types that were included in the integrated cluster 16 were “lateRG”, “vRG”, “oRG” from primary tissue dataset, and “glycolyticRG” from organoid dataset. We found that CRYAB-expressing organoid clusters 26 and 30 overlapped with “oRG/astrocyte” clusters of primary tissues.
Furthermore, we have analyzed another organoid dataset in stages including 5-months, 9-months and 12-months (Herring et al., 2022; E), but found no clusters that specifically expressed CRYAB (F).
1-4. I found the total number of tRG-like cells in the ferret dataset quite small (162), but I understand the difficulty with isolating and sequencing rare cell types from primary tissue sources. I believe most of the transcriptomic analyses were conducted with this low n in consideration, but this caveat is even more reason to pare down the wording for the weaker claims mentioned above.
We thank the Reviewer for appreciating the difficulties associated with isolating and sequencing rare cell types. We were able to identify a total of 409 tRG cells (in tRG-like cluster) after merging all timepoints of sequencing, (Figure 1C, S3C) as stated in line 162 of the original manuscript. However, to perform pseudotime analyses, we subset our dataset using 6,000 cells in total (excluding neuron and non-progenitor clusters; Methods), which included 162 tRG cells. Pseudotime analysis transcriptomically distinguished tRG into 3 subgroups (Figure 4E). Remaining 247 tRG cells also appear to distribute similarly into these subgroups rather than forming a distinct subregion within tRG cluster (right panel in figure below). Furthermore, we conducted extensive immunohistochemical analyses of tRG-like cells, and we found that both the morphology and gene/protein expression were consistent with the notion that “tRG-like” cluster in our ferret dataset represents tRG defined in humans (Nowakowski et al., 2016).
Revision plan:
As for human dataset, we agree that the population of committed tRG was minor. Thus, we pared down our statements regarding the fates of tRG as mentioned in other comments, both in the Results and Discussion.
- Are prior studies referenced appropriately?
1-5. I found it interesting that tRGs persist and even expand in number in postnatal timepoints (Fig. 2C). I'd be interested to know if this is in line with what is known in human developing cortex. If so, it would strengthen the conclusion that ferret tRGs can model that of humans - and if not, this would either be an important finding regarding tRG function or an important caveat in the use of ferret tRGs to model the cell type in humans.
We thank the Reviewer for bringing up this issue. This is an important issue because we wanted in this study to use the ferret as a good model for the complex brain development in gyrencephalic animals, in general, to know what characteristics are shared or not, across gyrencephalic species (such as the presence of the OSVZ vs. the temporal scale).
Revision plan:
Our study demonstrated the presence of tRG cells up to P10 by immunohistochemistry and scRNA-seq. P5~P10 is the stage where neurogenesis became dominated by gliogenesis in the dorsal cortex in ferrets, although its timing is delayed in the visual cortex. On the other hand, Nowakowski et al. (2016) originally identified and defined CRYAB-expressing tRG, based on morphology and gene expression on human primary tissues during mid-neurogenic stages, while cortical neurogenesis is mostly declined in human postnatal stages. We have failed to find literatures or textbooks describing the presence of CRYAB-expressing tRG, while an ependymal layer was detected in the postnatal human cortices (Honig et al., 1996; preprint Nascimento et al., 2022). At the moment, the lack of information thus makes it difficult to compare the relationship of birth timing with the period of tRG persistence between ferrets and humans. In the revised manuscript, the “Discussion” will include this argument as well as the following difference between humans and ferrets in the RG scaffold.
Besides birth timing, Nowakowski et al. also reported that radial glia scaffold spanning from the VZ to the pial surface undergoes a transformation during neurogenic stages; tRG becomes the major RG population in the VZ, disconnecting VZ and OSVZ. In contrast, we did not find a discontinuous scaffold stage over the course of ferret neurogenesis. Instead, we still detected CRYAB-negative vRG with an apical attachment and a basal process extending beyond the OSVZ during stages where the peak of tRG expansion is achieved (such as P5 in Figure 2A, S3A). This appears to be a prominent difference between human and ferret corticogenesis.
- Are the text and figures clear and accurate? Yes
- Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
1-6. For Fig. 2A, I would find it helpful to compare the morphology of GFP+/CRYAB+ cells vs GFP+/CRYAB- cells, with the hypothesis that GFP+/CRYAB- cells will have elongated basal processes. I believe this could be done by finding GFP+/CRYAB- cells in the raw images obtained to generate Fig. 2A (or similar), and showing those cells in an adjacent panel. This side-by-side comparison could provide more support that the CRYAB+ cells from the single-cell analyses are indeed specifically linked to tRG-like morphology.
Revision plan:
We prepared the images for GFP+/CRYAB- vRG cells in an adjacent panel in Figure 2A as recommended by the reviewer (below). To better distinguish the morphology of an isolated vRG cell from other labelled cells, we sparsely labeled RG cells with EGFP at P3 by electroporation (Methods), and fixed the samples two days later (right panel). We highlighted the morphology (cell body and basal fiber) of a CRYAB- GFP+ vRG and that of a neighboring CRYAB+ GFP- tRG on the same panel to clarify that vRG did not express CRYAB.
Reviewer #1 (Significance (Required)):
This paper primarily presents a technical advance in the field, showing that tRG cells that can model those found in the developing human cortex are found in the developing ferret cortex.
- Place the work in the context of the existing literature (provide references, where appropriate).
- State what audience might be interested in and influenced by the reported findings.
Several studies in the human and macaque brain have identified the presence of tRGs (deAzevedo et al., 2003; Nowakowski et al., 2016), but understanding the molecular functions and development of these cells - and many human-specific cell types in the brain - is difficult due to the lack of tractable models of human neurodevelopment. Ferrets, given their layered cortices, may be a potential model system for these cell types, but further analyses to determine their transcriptomic similarity to the developing human cortex and their ability to recapitulate human cell types are required in order to evaluate their use as a model system. By generating a useful resource in the ferret single-cell transcriptomic atlas, this study provides evidence that - at least for the tRG subtypes - ferrets may be useful in dissecting the generation and functional importance of tRG cells. With the caveat that a direct comparison with the use of cortical organoids to study tRG is lacking in this paper (see above), I believe this work can provide useful insight into the field's current search for model systems to functionally interrogate human-specific aspects of cortical development.
Reviewer #2 (Evidence, reproducibility and clarity (Required)):
2-1. In this report, Bilgic and colleagues study the diversity of progenitor cell types in the developing ferret cerebral cortex, a valuable in vivo model to understand cortex expansion and folding, as in primates including human. Using a single-cell transcriptomics approach, they describe a diversity of progenitor cell types and their interrelation by transcriptomic trajectories, which are conserved but biased as development progresses. Most interestingly, they identify in ferret a type of cell only identified in human before, tRG, which they then characterize throughoutly by transcriptomics. They also identify these cells in histological sections, and via time-lapse videomicroscopy they characterize their cell type of origin. They also provide indirect evidence that tRG may be the source of ependymal cells in the ventricle of the mature cerebral cortex, as well as astroglial progenitor cells. Finally, they extend their analyses to identify oRG in ferret based on previous human single cell data, concluding that they have in ferret a quite different transcriptomic profile than in human.
We would like to thank the reviewer for carefully reading our manuscript and providing us with valuable feedback. However, we would like to clarify that there might have been a misunderstanding regarding our conclusion about the identification of oRG-like cells in ferrets.
Our study did not conclude that we have identified oRG cells in ferrets with “a quite different transcriptomic profile than in human”. Instead, our findings indicate that unlike oRG cells in human, ferret oRG-like cells did not exhibit specificity for human oRG markers (such as HOPX and CLU) that would enable us to distinguish them from other late RG cells in ferrets. Despite this, oRG score derived from human oRG marker expression showed higher values in predicted ferret oRG-like cells compared to other ferret RG cells, reflecting a similarity of the transcriptome profile between human oRG and ferret oRG-like cells (Figure 7H-I). We will carefully describe our methodology to reach this conclusion in response to reviewer 2’s comment regarding how we determined ferret oRG in a later comment.
Major issues:
2-2. The authors must provide evidence that the cortical area they are examining will give rise to Somatosensory cortex. Their sampling area appears more like Cingulate cortex, while somatosensory may be a bit more lateral. The cingulate cortex is a very unique region, with some unique characteristics including lamination and connectivity. It would be important to provide some justification as to why they chose this particular part of the cerebral cortex, and keep this into consideration when discussing the general value of their findings.
The reviewer 2 seems to misunderstand that we took cortical strips shown in Figure S1A as samples for scRNA seq. If our description in the main text is confusing, that would be our fault.
In Figure S1A of the original manuscript, we showed the cropped images of the medial part to emphasize the distinguishment of different germinal layers (VZ/iSVZ/oSVZ) and their temporal changes in ferret cortices.
Revision Plan. To avoid such a misleading, we inserted the dotty lines in the revised Figure S1A to demarcate the tissue parts for scRNAseq, which correspond to almost all lateral cortices, mainly including the somatosensory area 1 and 2 with surrounding areas. We accordingly added the following sentence in the legend, “The approximate boundaries of dorsal cortex area used for scRNA sequencing are highlighted with dotty line segments in the dorsal cortex hemisphere above each strip.”.
We also show actual sampling for single-cell transcriptomics below. As our sampling was not restricted to the somatosensory cortex, we have revised “somatosensory cortex” as “dorsal cortex” in Lines 131 and 1191 of our manuscript.
2-3. It seems that the single cell datasets were collected from only 1 replica at each developmental stage. Current best practice sets the inclusion of several biological replicates. Whereas this represents multiplying the workload (and costs) and re-doing many of the analyses, it is currently highly valued. On the other hand, the authors already have their analysis pipelines defined, and so the time involved should be much shorter than before.
We disagree with the reviewer 2’s comment. We would like to clarify that we collected brain tissues in two different ways for the same set of developmental stages; one brain tissue by removing cortical plate (T); another independent brain tissue at the same developmental stage by sorting GFP-labelled lineage from neural progenitors that were electroporated at embryonic stages (AG, Methods). Both manipulations of samples aimed to increase progenitor cell populations in scRNAseq. Therefore, we have two sets of samples of the same temporal series, each prepared in a totally different way. All cell types were present in both methods of collection shown as Supplementary Figure 2E’ (below left) that separates samples by different preparations at each stage (by modifying Supplementary Figure 2E; below right). We believe that the biological replica (n=2) in this manuscript would be sufficiently reliable, judged by its reproducibility.
Here, we also cite several examples of papers important in the field of single-cell or bulk transcriptomics of brain tissue, where only a single replicate or pair (replica) was taken for experiments on mice, humans and ferrets:
mice: Ogrodnik et al., 2021 PMID: 33470505, Hochgerner et al., 2018 PMID: 29335606, Joglekar et al., 2021 PMID: 33469025;
human: Herring et al., 2022 PMID: 36318921, Polioudakis et al., 2019 PMID: 31303374, Mayer et al., 2019 PMID: 30770253, Fietz et al., 2012 PMID: 22753484;
macaque: Schmitz et al., 2022 PMID: 35322231;
ferret: Johnson et al., 2018 PMID: 29643508.
2-4. Single cell QC methods are incomplete as described in Methods. It is key to consider the relative abundance of mitochondrial RNAs when assessing the integrity and validity of cells, and thus a key criterion to select the cells for clustering analysis. The criteria for the selected choice of clustering resolution is also missing.
The reviewer pointed out an important criterion, the abundance of mitochondria.
Revision Plan:
We have now added the mitochondrial QC metrics in the new Figure S2A, and revised the legends as follows: “Violin plots showing the number of genes, mRNAs and the percentage of mitochondrial genes per cell in each sample and time point”. We have computed the percentage of mitochondrial genes for each cell type and found that the majority of cells in each cell type had a value less than 5% while the content value in some cells distributed along the range between 0% and 10%, up to a maximum of 28% (Figure S2A). Despite this, we have decided to include all cells that had less than 30% of mitochondrial genes in our analysis based on the percentage of reads mapped on mitochondrial genome for the following reasons:
- The percentage of mitochondrial indicates respiratory activity, rather than apoptosis and the percentage of mitochondrial quite depends on the tissue type and species. For example, in human case, such percentage range from 5%~30% (Mercer et al., 2011 Cell; The human mitochondrial transcriptome).
- Unfortunately, unlike human and mouse brains, there is no reference to show the percentage of mitochondrial in ferret brains. Therefore, the suitable way is to keep all of these cells.
- These cells showing high percentage of mitochondrial genes are not clustered as an apoptosis cluster in UMAP, instead, these cells are observed in most of clusters (below). Therefore, we believed that these cells are not apoptotic cells and include these cells in further analysis.
- After all, we have obtained similar clustering overall after filtering cells with a higher percentage for mitochondrial genes; we set the threshold to 10%. This filtering resulted in 28,686 cells in our dataset. We then performed our workflow from the normalization step with the same settings that we applied to our original ferret dataset (Methods). Below, we show the results comparing newly generated clusters in this filtered subset on UMAP (left), and the original clusters shown in Figure 1B (right). 26 clusters were obtained in both conditions, and both major cell types and subtypes were conserved after filtering.
Clustering resolution: Our choice of the resolution was based on avoiding over- or under-clustering of ferret cells. After trying several resolution values, including 0.6, 0.8, 1.0 and 1.2, we have decided to use the resolution of 0.8 as the separation of cell types was the most reasonable among other resolutions that we have tried, in a similar way to actual known cell types. For example, the resolution of 0.6 did not distinguish “tRG” cells from “late_RG1” cells, as well as “early_RG” subtypes which were distinctly enriched with different cell cycle markers (Figure S2D). On the other hand, the resolution of 1.2 resulted in an over-clustering of IPC, OPC, DL neurons and microglia.
2-5. When first describing tRGs (line 171), orthogonal views of the image z-stacks must be shown to demonstrate the full morphology of these cells. The basal process might have been cut during tissue sectioning. The same applies to images in Fig. 2C, 2D, S3A.
Revision plan:
We focused on Figure 2A and S3A (2D is a histogram) to show the full morphology of CRYAB+ tRG, because Figure 2A is the initial presentation of tRG in this paper, and Fig. 2A and Fig.S3A images are taken on a 200-micrometer thick section, originally aiming to indicate that CRYAB-positive fiber is short, spanning nearly along the VZ and the SVZ. We made 3D-reconstructions of those images, which are rather better than orthogonal projections, in order to show that CRYAB+ fibers are shorter than those of vRG (terminating at positions around the upper boundary of the SVZ) and that the short basal processes are not due to the cut of long radial fibers during tissue sectioning.
We will show these 3D-reconstruction below. Please download movie files from the following URLs to look at them clearly.
Figure 2A
https://www.dropbox.com/s/qocve596c5xhtlc/%E2%98%85fig2A-Ver02.mp4?dl=0
Figure S3A
https://www.dropbox.com/s/v8gqwfi1r8ff5n5/%E2%98%85figS3A-P0%20movie-ver2.mp4?dl=0
2-6. In Figure 3, the authors perform time-lapse imaging to visualize and characterize the cells and lineage that give rise to tRGs. While very nice and a technical challenge that must be properly acknowledged, they unfortunately only obtained a total of three examples, which is clearly insufficient to reach any meaningful conclusion on this respect. These conclusions, while fascinating, are based only on 3 cell divisions. If this is to be taken as a strong argument for the conclusions of the study, the authors must obtain. If the authors want to make a solid statement out of this experimental approach, they must obtain a sufficient amount of additional data, which will depend on the variability of the results they find.
We thank the reviewer for appreciating our time-lapse imaging data as very nice and a technical challenge. The number of time-lapse imaging that could follow the cell fates was from “4” samples instead of 3. It is indeed very infrequent and difficult to obtain a complete set of consecutive divisions from vRG, followed by histochemical examinations (fixation, cryo-sectioning and immunostaining of slices). This is because some of EGFP-labeled cells are frequently indistinguishable from each other by overlapping within a clone or with cells in other clones. Therefore, we decided to take a different way to clarify the pathways from vRG and its variety to generate tRG at the tRG-generating stage.
Revision plan:
Increasing the number of time-lapse image series will be extremely inefficient because of the reasons described above, perhaps taking a long time such as 3-5 months according to our breeding schedule of ferrets. Therefore, we take an alternative way to clarify the division patterns from vRG to generate tRG, especially focusing on the identity and variety of vRG sibling cells at the tRG-generating stage; we are examining the sibling pair of vRG and/or precursor of tRG to see what kind of cell the vRGs actually generate at their mitosis. For this purpose, we electroporate ferret cortices with the EGFP-expressing plasmid approximately one cell cycle prior to fixation (E38 or P0). We then stain ferret cortices for a mitotic marker Ki67 and tRG marker CRYAB and other markers during the tRG-generating state (P0-P5), assuming the cell cycle length of vRG and IPC as approximately 33h~45h based on our own consecutive EdU labeling experiments and time-lapse imaging.
2-7. Still regarding the time-lapse results presented in Figure 3, it is unclear why after first division the authors identify the blue cell as IPC, when it has the exact features of tRG: apical process anchored in VZ surface + short basal process. This is applicable to all three examples shown. For example, the authors describe: "the mother IPC of tRG also possessed both an apical endfoot and a short basal fiber (Fig. 3D)". Why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC? The interpretation of IPCs being the mother cells to tRGs must be changed, to those being vRGs. Or else, more convincing data must be provided.
In fact, their analyses in Fig 4A contradict their interpretation on tRG mother cells, showing that the transcriptomic trajectory leading to tRGs does not inlcude Eomes+ cells, accumulated in the neurogenic state 2. At the end of this section, the authors indicate: "our data suggest that tRG cells are formed by apical asymmetric division(s) from unique apical IPC with a short basal fiber (Tsunekawa et al, in preparation).". Being as important as this point is, if there is solid supporting data the authors must include it in this study.
We appreciate the reviewer 2’s question about “why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC?”
Revision plan.
- We are confident that this blue-labeled cells in Figure 3A and D are not vRG but mitotic sibling cell (of vRG) with a short basal fiber (that we named IPC in the initial manuscript). We now made the morphological features of these cells clearly visible by constructing 3D-views of the images with different snapshot images (we show below and in the preliminary revision as a supplementary movie). In addition, it divides once as time-lapse imaging revealed, hence this cell is still mitotic, instead of a postmitotic cell. Therefore, we used the term that is generally used for this type of cells, namely, intermediate progenitor cells (IPC), by which we did not intend to refer to TBR2+ neurogenic IPC. We plan to include these revised images into our fully revised manuscript.
- We agree the reviewer 2 on the point that this blue-labeled cell may express CRYAB (the next comment of reviewer 2 essentially claims the same point), as we also wrote this possibility in line 204-207 of the original manuscript. It could not be technically possible at the moment to examine CRYAB expression in a cell emerging only in the course of time-lapse imaging. If we could label vRG with a transgenic or knock-in fluorescence marker, which mimics CRYAB gene expression, we could have figured out whether blue cells (the mitotic vRG sibling cells) express the CRYAB gene. Indeed, we tried to knock the EGFP gene in the CRYAB gene many times over a year, but have so far failed. Given that tRG is defined as the cell type expressing CRYAB with a short basal fiber at late-neurogenic stage, irrespective of its mitotic activity, this blue labeled vRG sibling cell in Fig. 3A (and/or Fig. 3D) might express CRYAB, hence can be a “mitotic tRG” (although its possibility seems to be low as shown in Fig. 2E). To avoid any possible misleading, we have changed the term of these cells to a “mitotic vRG sibling cell (or mitotic tRG parental cell) with a short basal process”, and add a comment that “this cell might be mitotic tRG with CRYAB expression”.
- As for the TBR2 expression, we do not know these cells that appeared in the course of time-lapse imaging express TBR2 or not. As shown in Fig. 2F, 10% (P10) to 30 % (P5) of CRYAB+ cells express TBR2. On the other hand, “intermediate progenitors” do not necessarily express TBR2 in general. Therefore, we disagree on the reviewer 2’s comment “their analyses in Fig 4A contradict their interpretation on tRG’s parent cells”, but “our analyses in Fig 4A is compatible with our interpretation on tRG’s parent cells in time-lapse imaging”, and that is “a mitotic vRG sibling (or mitotic tRG parental cell) with a short basal fiber divides to produce CRYAB+ tRG at the end of timelapse imaging”. However, to avoid any overstatements or misunderstanding on this issue, we have revised related text as described above.
- We are not able to include the data taken by Tsunekawa et al.. This is because we are going to submit a separate paper, which includes a large volume of data with human ones in collaboration with another group and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not practical to combine these data with those described in this manuscript. Therefore, we remove all descriptions related with Tsunekawa et al.
Below we show snapshot images and 3D-reconstructions for Figure 3A and 3D. Please download movie files from the following URLs to view at them at the highest resolution.
@Figure 3A:
1)A time lapse movie (20 min interval) showing images around time 40:00 at which vRG underwent the second division.
https://www.dropbox.com/s/znx3bboxefhj0jt/%E2%98%85Fig_3A%20movies%20around%2040%20h.mp4?dl=0
2)Snapshot images for time 40:00
https://www.dropbox.com/s/6y25mk4jhwqy6v7/%E2%98%85E38-fig3A-sRG-2.png?dl=0
- 3D-reconstruction images at the same time point (40:00)
- The entire time-lapse movies of time 0:00-84:00; The mitotic sibling cell of the vRG is indicated by a white arrow.
https://www.dropbox.com/s/ywua95f8fmohsmc/%E2%98%85Fig3A-arrow-time.mp4?dl=0
@Figure 3D:
A revised time-lapse snapshots of Figure 3D.
The assignment of the cell has corrected to the right one for the same mitotic cell because cell body position at the first two time points were misassigned in the original manuscript (at the following time points, there is no change).
Snapshot image at time point of 06:20; https://www.dropbox.com/s/hn3v6ao1qkhnfjh/%E2%98%85Fig3D%20sRG%20at%200620.png?dl=0
Rotating movie of 3D-reconstruction at time point of 06:40:
2-8. Alternative interpretation of time-lapse images (lines 196-197): maybe a tRG can generate one tRG CRYAB+, and one IPC CRYAB-.
We agree with reviewer 2 that there is an alternative interpretation of cell identity appearing in time-lapse imaging of Fig. 3. In line 196-197, we wrote that “These mother IPC underwent an asymmetric division to generate a non-CRYAB expressing cell and a CRYAB+ tRG”. As pointed by reviewer 2 here and in the previous comment, we cannot exclude the possibility that this vRG sibling cell may be a mitotic tRG (see our response to the previous reviewer 2 comment). If so, what we observed in Fig. 3A and D could be interpreted as a mitotic tRG, and generate one CRYAB+ tRG and one CRYAB- climbing cell. However, as we haven’t confirmed or stated whether this parent cell was a mitotic tRG, we also did not examine the identity of this sister cell of CRYAB+ tRG. It can be an IPC or nascent neuron or even an astroglial progenitor cell. From our data, we cannot say anything about the identity of the CRYAB-negative sister cell other than that this cell is CRYAB-negative, migrating upward. That is why we did not mention about the identity of this CRYAB-negative sister cell of tRG other than that the sister cell of tRG is CRYAB-negative.
Revision plan. We changed the term of IPC to “a mitotic vRG sibling cell” and describe the possibility that “This mitotic vRG sibling cell (or mitotic tRG parental cell) can be a mitotic tRG if this cell express CRYAB, and its apical division generates one tRG and one CRYAB-negative climbing cell with an unknown identity, replacing the description of line 196-197.
2-9. Arrows in Fig 5E are shifted between the top and bottom panels. There is no obvious evidence of mitosis visible. This should be unequivocally labeled with anti-PH3 antibodies.
We thank reviewer 2 for pointing our careless mistake.
Revision plan. We have corrected the shifted position of arrows in Figure 5E. We have removed “mitosis” in the title of Figure 5E since the initial manuscript did not include descriptions on mitosis in the text.
2-10. Line 277: “Transcriptomic trajectories were homologous across the two species”. What does this refer to? What are these trajectories? Pseudotime? Is this statistically tested?
The meaning of the term “Transcriptomic trajectories” was not clear.
Revision plan. We revised our description in this part as “Temporal patterns and variety of neural progenitors during the cortical development were similar to each other between humans and ferrets at the single cell transcriptome level”.
2-11. When comparing tRG cells between ferret and human, the authors indicate a remarkable similarity between the two species as represented by CRYAB, EGR1, and CYR61 expression. As shown in Fig 6E, EGR1 and CYR61 are not expressed selectively in human tRG as they clearly are in ferret tRG. Hence, this argument is not valid.
In lines 291-292, we mention that “tRG cells also showed a remarkable similarity between the two species (Fig. 6C, 6D), as represented by CRYAB, EGR1, and CYR61 expression (Fig. 6E)”. Here, what we wanted to claim is that the same combination of gene expression (CRYAB, EGR1, and CYR61) is characteristically at relatively high levels in both ferrets and human tRG. As the reviewer 2 claimed, CRYAB and CYR61 genes are highly selective for ferret tRG among mid-late RG types, while the expression of EGR1 and CYR1 are just relatively enriched in tRG than in other cell types in human RG (except for highly selective CRYAB). Irrespective of the difference in their relative enrichment in tRG between humans and ferrets, one can still state that the combination of these marker expression at higher levels is shared in these two species”. We were not able to find which part in the manuscript was the reviewer referring to for the claimed argument (“EGR1 and CYR61 are expressed selectively in human tRG”).
Revision plan. To clarify our statement, we changed this sentence into “tRG cells also showed a remarkable similarity between the two species (Fig. 6C, 6D), as represented by a high level of expression for the combination of CRYAB, EGR1, and CYR61 (Fig. 6E)”
2-12. In the last part, the authors try to identify oRG-like cells in ferret by comparison with their transcriptomes identified in human. For this, they decide to call ferret oRG-like cells those that are near human oRGs in the integrated UMAP, as identified in a previous human study. What was the criterion for this? How much near is "near"? The fact that the selected cells have higher oRG scores is expected and obvious, as these cells were selected precisely based on their proximity in the UMAP. Even more importantly, the identification of oRGs in the human study is not unambiguous. Therefore, the correlate in ferret cells is also non-conclusive as to the identity of such cells.
We apologize for a confusion caused by insufficient explanations for our methodology. We want to clarify that we did not find " ferret oRG-like cells as those near human oRGs in the integrated UMAP." Rather, we try to identify oRG-like cells in ferrets based on the hypothesis that, when comparing ferret and human datasets, oRG-like cells in ferrets would exhibit a higher degree of similarity to human oRG cells than to other cell types. This hypothesis was supported by our observations of other clusters such as tRG, later RG, and IPC (Figure 6 C and D).
To identify oRG-like cells in ferrets, we utilized the mutual nearest neighbor (MNN) method to determine the similarity between cells from different species (Stuart et al., 2019 PMID: 31178118). For example, when attempting to identify the human cell that was most similar to a given ferret cell (F), we calculated the distance between cell F and all the cells in the human dataset in the high dimensional expression space. This allowed us to identify a human cell (H) that exhibited the smallest distance to cell F. Subsequently, we computed the distance between cell H and all the cells in the ferret dataset. If cell F had the smallest distance to cell H in the human dataset, we considered cells H and F as a pair of mutual nearest neighbors.
Using this method, we can find all pair of mutual nearest neighbors in two datasets. We then find these pairs that one is human oRG and define the other is oRG-like in ferret. However, upon further investigation of the characteristics of these cells, we would not find any specific markers (such as HOPX and CLU in human oRG) that would enable us to distinguish them from other later RG cells in ferrets.
Accordingly, only when our strategy to find mutual nearest neighbors is suitable, the selected cells can get higher oRG score, otherwise, the selected set of ferret cells will not show a high oRG score. Therefore, we disagree with the notion that “The fact that the selected cells have higher oRG scores is expected and obvious”.
We hope this explanation provides a clearer understanding of our methodology and the rationale behind our approach to identifying potential oRG cells in ferrets.
2-13. Discussion is surprisingly short, given the emphasis that the authors place on the importance of their findings. I would suggest extending it for a better coverage of those findings that have the greatest relevance and interest to a wider readership.
Thank reviewer 2 for his/her precious advice.
Revision plan.
We added several issues discussed in the responses to the reviewers to Discussion. Please look at our responses to comment 2-14 and 2-15 as well as the preliminary manuscript.
2-14. In Discussion, the authors state that "ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." Again, this conclusion is purely based on transcriptomic trajectories, which must not be confused with cell lineage. This sentence must be rephrased and toned down accordingly.
We appreciate Reviewer’s comment regarding the difference between transcriptomic trajectories and cell lineage. We agree that transcriptomic trajectories do not necessarily reflect cell lineage. However, relationships along transcriptomic trajectories provides useful information about the differentiation potential of cells. Furthermore, in this study, we examined the temporal and spatial relationships between CRYAB+ tRG and FoxJ1+ ependymal cells that were predicted as tRG descendant cells by transcriptomic trajectories. We could confirm an increasing overlap of FoxJ1+cells with tRG cells along the course of post-natal development in Figure 5. We thus accessed the relationship of the two cell types by not only in silico but also in vivo analyses.
Revision plan. We disagree with the reviewer 2 as for ferrets, because we accessed the relationship of tRG and their progeny cells by not only in silico but also in vivo analyses.
On the other hand, as for progenies of human tRG, they were predicted certainly depending on the molecular relationship by comparison with ferrets without histochemical evidence, as pointed by reviewer 2, and the populations of these committed tRG are small. Therefore, we removed “(and presumably also human)” and we tone down about the progeny relationship of tRG as a prediction. We also acknowledge that further studies are needed to confirm the lineage relationships among cell types, as we discussed in the Discussion part.
2-15. In Discussion: “our cross-species analysis highlights the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter”. As mentioned above, this is only based on transcriptomic trajectories, it is not demonstrated in this study. In vivo analyses of cell fate are needed to support this conclusion, and a more extensive videomicroscopy analysis is needed to confirm the cell lineage progression suggested by transcriptomes.
The statement “the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter” is certainly a speculation based on our results, but not experimentally indicated yet by such as gene knockout, as the reviewer pointed out. Although we repeatedly tried to knock out the CRYAB gene in ferrets for a year, we have so far failed.
Revision plan. Taking the comments from reviewer 1 and 2 into account, we largely revised “Discussion” with a more moderate expression, by incorporating comparative analyses with other human datasets, and we also emphasize the importance of in vivo studies as the next step. We just paste the last paragraph of the preliminary revised Discussion. Please see the “Discussion” in the preliminary revision of our manuscript.
“In ferrets, genetic manipulations can be achieved through in utero or postnatal electroporation, as well as via virus-mediated transfer of DNA (Borrell, 2010; Kawasaki et al, 2012; Matsui et al, 2013; Tsunekawa et al, 2016). Thus, it is theoretically possible to disrupt the CRYAB gene in vivo in ferrets to investigate its role in tRG and their progeny, including ependymal cells, and to track the tRG lineage. If the CRYAB gene is essential to form ependymal layers, we will be able to explore how the ventricle contributes to cortical folding and expansion. Despite extensive efforts over a year, we have thus far been unsuccessful in knocking in and/or knocking out the CRYAB gene. Nevertheless, we anticipate that technical advances will surpass our expectations, both in ferret and human organoids. Taken together, these functional studies in ferrets as well as in human organoids hold promising insights into the understanding of the tRG lineage and its contribution to cortical development in the near future”.
Minor issues:
2-16. In line 59, the authors state: "cerebral carcinogenesis independently evolved to gain an additional germinal layer (outer SVZ (OSVZ);". Assuming that they mean "cerebral neurogenesis", what is the evidence for this independent evolution? Original publications demonstrating this must be cited.
Revision plan. We removed the mentioned statement from our manuscript and revised lines 58-59 as follows: “In many mammalian phylogenic states, cerebral cortex evolved to gain an additional germinal layer (Smart et al. 2002; Zecevic et al. 2005; Kriegstein et al. 2006; Reillo et al. 2011)”.
2-17. Lines 60-61, the third key publication reporting the existence of bRG must be cited together with Hansen 2010 and Fietz 2010: Reillo et al., 2011, Cerebral Cortex.
We appreciate Reviewer 2’s remark.
Revision plan. We now added these citations in lines 60-61 and in the Reference list as Reillo I, De Juan Romero C, García-Cabezas MÁ & Borrell V (2011). A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. Cereb Cortex 21: 1674–1694.
2-18. When introducing ferret as an interesting or important animal model, suitable original studies should be cited.
Revision plan:
For ferrets, there is a long history as experimental animals for electrophysiology similarly with cats and monkeys, but this is not a review of ferret biology. We thus added 6 additional references regarding ferret brain morphology and development listed below.
Jackson, C.A., J.D. Peduzzi, and T.L. Hickey (1989) Visual cortex development in the ferret. I. Genesis and migration of visual cortical neurons. J. Neurosci.9:1242–1253. PMID: 2703875.
Chapman B & Stryker MP (1992) Origin of orientation tuning in the visual cortex. Curr Opin Neurobiol 2: 498–501.
Chenn A., and McConnell S.K. (1995) Cleavage orientation and the asymmetric inheritance of Notch1 immunoreactivity in mammalian neurogenesis. Chenn A, et al. Cell PMID: 7664342.
Noctor SC, Scholnicoff NJ, and Juliano SL. (1997) Histogenesis of ferret somatosensory cortex. J Comp Neurol. 387(2):179-93.PMID: 9336222.
Reid CB, Tavazoie SF, Walsh CA. (1997) Clonal dispersion and evidence for asymmetric cell division in ferret cortex. Development. 1997 124(12):2441-2450. doi: 10.1242/dev.124.12.2441.PMID: 9199370
2-19. In Figure 2F-H, layer borders should be labeled. The density of CRYAB+ cells in VZ (?) at P5 seems much greater in Fig 2E,F than in Fig. 2B. Clarifying this discrepancy is important to validate the quantification of Fig 2D.
Revision plan.
Layer borders: We now labeled the approximate position of the boundary of the VZ in Figure 2E-G. We have revised the legends as follows; “The border of the VZ is shown with a white line”. For counting, we have determined borders by the distribution of DAPI, and radial glia-specific markers in our hands and determined the approximative distance of the VZ border from the ventricular surface in the antero-posterior axis where we performed the imaging in Figure 2E-G. The distance was approximately determined as 80 µm at P5 and 40 µm at P10.
Discrepancy in the intensity of CRYAB: We apologize for the unclear statement on how the images were acquired in the legends of Figure 2E-G. We now revised as follows; “Representative images taken with a 100X-objective lens are shown with MAX projection.”. In Figure 2E-G, images were taken as optical sections of 1.5 µm interval for 12 µm-thick sections. Those images were processed as MAX-projection onto the Z plane. On the other hand, In Figure 2B, we have used 20X-objective lens, instead of 100X-objective lens and did not perform any image projection procedure such as a MAX-projection and only 1 z-plane is shown. Therefore, the visual difference in the CRYAB intensity between Figure 2B and Figure 2E-G derives from whether max projection of several consecutive images was done.
2-20. Co-expression of CRYAB and FOXJ1. In Fig 5B this must be demonstrated with merged channels.
Revision plan.
We added the images with merged channels as requested and revised corresponding legends as follows: “Images with merged channels in A are shown with the same color codes, antibodies and scale bars as A.”.
2-21. Line 247: "near which nuclear line aggregates are observed more frequently (Fig. 2B)". It is very much unclear what the authors refer to. Please, define nuclear line aggregates.
Revision plan.
We will revise the cited sentence and will change the referred figure as follows: “These cells often aligned on a line parallel to the ventricular surface (Fig. 5A)”. We show these nuclear rows by arrows.
2-22. There are a number of typos along the main text and figures, which must be fully checked and corrected. For example, line 59 "cerebral carcinogenesis"; also in Figure S4, Figure 5E. Labeling of graphs in Fig 5C is wrong. The plots present the fraction of CRYAB+ cells that express FOXJ1 (FOXJ1+/CRYAB+ cells), not the reverse.
Revision plan.
We thank the Reviewer for their remarks on typos. We corrected the typos indicated by Reviewer 2. We agree with the Reviewer and also modified the title of Figure 5B as suggested by the Reviewer.
Reviewer #2 (Significance (Required)):
This manuscript is of interest for being the first ferret single-cell study, and for identifying and characterizing to a great extent a unique population of cortical progenitor cells that so far had only been observed in human. The study is presented as a resource for studies of ferret cortex development, which as such is clearly of interest to a very limited audience. A more appealing perspective might be if this study in ferret is of interest or of use to the more general community studying cortex development, or even maybe cortex evolution.
We disagree the reviewer’s view that this study is clearly of interest to a very limited audience. This study first enabled a precise comparative analysis in which we could compare rich human single cell transcriptomes and the ferret dataset of single cell transcriptomes, which were based on greatly improved genomic information (especially, gene models). This study is also first to show global temporal patterns of cortical progenitors of a carnivore species, a famous gyrencephalic mammalian model, and have been shown to be similar to a primate species at the single cell transcriptomic level. Indeed, upon uploading this manuscript in BioRxiv, many non-ferret specialists as well as specialists have inquired datasets and requested some collaborations with us. So we believe that this paper has already attract a general interest of brain scientists.
Advance: it is, so far, the first study of single cell profiling of the ferret cerebral cortex, a well established and highly valued model of gyrencephalic mammals, and a suitable best-alternative to work in primates. In addition to the technical advance, providing a new resource for work in ferret, it shows for the first time the existence of truncated Radial Glia (tRG) in a non-human cortex, and even more importantly in this model, strengthening even more its value.
This study as is presented will be of most interest to a specialized audience, those directly working with ferret. Nevertheless, it will also be of conceptual interest to the community of cortex development and evolution for the concepts that one can extract on cell type conservation.
Description of the revisions that have already been incorporated in the transferred manuscript
Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.
1-1. The weakest claim in the paper is lines 202: "...tRG cells are formed by apical asymmetric division(s) from unique apical IPC". From my understanding, the main evidence that the tRG parent cells shown in Fig. 3 are not tRGs are the data from Fig. 2E-G showing the low amounts of CRYAB+ cells co-expressing KI67, TBR2, or OLIG2 in P5 and P10. Especially given that these timepoints are after those used in Fig. 3, I believe further evidence is needed to confirm the cell type identity of tRG parent cells in Fig. 3. Such experiments (isolating IPCs from ferret cortex and growing in vitro to determine progeny cells) may be outside of the scope of this paper, in which case I believe the text can be strengthened with either (1) presenting the data from the cited Tsunekawa et al, in preparation that would suggest this claim or (2) rephrasing these claims to omit the mention of IPCs.
- We revise the term “IPC” as “mitotic sibling of vRG” and stated that these cells might be tRG (CRYAB+) or non-tRG (CRYAB-) intermediate progenitors. By the term of “intermediate progenitors”, we did not intend to refer to TBR2+ neurogenic IPCs, but rather to an intermediate state of progenitors, in a general sense, with a similar morphology as tRG. To avoid any confusions on this terminology, we revised our manuscript by replacing “IPC” with “a sibling of vRG”.
- We delete all statements relevant to Tsunekawa et al. data from the manuscript. We regret that we are not able to include Tsunekawa et al. data because we are planning to submit this data as a separate manuscript, which describes that in ferrets, vRG frequently (30% of apical division) generate non-Tbr2-positive mitotic sibling cells bearing a short basal process during the entire neurogenesis. This study includes a large volume of data with human ones and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not appropriate to combine these data with those described in this manuscript.
1-2. I also believe the claim in Line 365-366 is overstated: "We found that ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." While I believe the transcriptomic comparisons suggest the presence of uncommitted tRG in both the ferret and human datasets, I would appreciate further analyses to confirm the prevalence of astroglial and ependymal tRG in the humans and/or functional analyses before claiming that human tRG cells make ependymal and astrogenic cells. I appreciate the authors' note that "GW25 is...the latest stages experimentally available" (line 376-377), but their comparative approaches could be applied to existing datasets of the human cortex (Herring et al., 2022, PMID: 36318921) that span later developmental ages. Identifying the presence of astroglial and ependymal tRGs in this and/or similar datasets would provide more convincing evidence of the tRGs' developmental potential. If this computational analysis is outside the scope of the paper, I believe paring the certainty of these claims (especially lines 379 - 383) and recognizing the need for further functional analyses would negate the need for deeper mechanistic validation.
- We compared our ferret dataset to the human postnatal dataset recommended by the Reviewer 1 (Herring et al., 2022). As a conclusion of our analyses shown below, we found that Herring et al., (2022) dataset was not favorable for a comparative analysis with our ferret dataset regarding the fates of human tRG, because Herring’s human dataset was derived from the prefrontal cortex; This human dataset does not include neither tRG cell population nor ependymal clusters. We have also elaborated our discussion after analyzing Herring et al. dataset in the discussion.
- We, therefore, pare down our claim in lines 365-366, by removing “(and presumably human)” to state that “Our pseudotime trajectory analyses and immunohistochemistry analyses strongly suggested that…”.
- We also tone down the statements as for the discussion of the relationship between human and ferrets regarding the tRG progeny fates (originally lines from 372 to the end) and also elaborated our discussion after analyzing Herring et al. dataset in the same paragraph.
We will describe the details of our analysis of Herring et al. (2022) below.
As mentioned above, Herring’s human dataset was derived from the prefrontal cortex, and that it did not include a specific subtype defined as tRG nor other HES1-expressing progenitor clusters such as RG in the original cluster annotation. We, therefore, re-clustered the raw dataset from GW22 (the earliest stage available) up to 10-months after birth by using Seurat pipeline with default parameters (B), and found a CRYAB-expressing population in the original “Astrocyte_GFAP” subtype among astrocyte clusters (A), which distribute in the most of collected stages, from late development through the adulthood. We then examined this dataset to find out whether tRG or its progenies are present.
After reclustering, CRYAB-expressing cells (with more than 1 raw count) represented 0.15% of the dataset and were grouped as a part of cluster 44, which was mostly derived from postnatal stages (among which 4-months was the most enriched one; C). Several astrocyte markers, such as SPARCL1, HOPX, CLU, and GJA1, as well as CRYAB, were enriched in the cluster 44 as revealed by FindMarkers (Methods). FOXJ1 expression was nearly absent overall in this dataset, indicating the absence of the ependymal cell population, a tRG-descendant cell types in ferrets (C).
To evaluate the similarity between cluster 44 and tRG or astroglial tRG, we next integrated Herring dataset with our ferret subset (about 15,000 cells) and the human GW25 subset from Bhaduri et al. (2021) of approx. 3,000 cells, both of which contained only progenitor cells. As we have done in Figure 7 of our original manuscript; we have removed cells other than progenitors, astrocytes and oligodendrocytes, such as neurons, microglia, endothelial cells. This resulted in about 20,000 cells in Herring dataset.
This integration (D) reveals that Herring’s cluster 44 is closely located to Bhaduri’s human and our ferret tRG clusters on UMAP, but does not overlap with these tRG clusters. This result further suggested that tRG population might be lacking or very rare in this neuron- and glia-dominated dataset, which might be due to the sampling method that targeted the enrichment of neuronal layers (Herring et al., 2022). It is also possible that this fragmented information on astrocyte and ependymal lineages could be due to the regional and/or temporal difference of samples between two human datasets.
1-3. I believe the most significant advance for this paper is the potential to use ferret tRG cells to model those of the human brain. However to support this claim (see Lines 83-84), I believe a comparison of the ferret tRG cells with existing cortical organoid datasets (Bhaduri et al., 2020, PMID: 31996853) would be helpful. If cortical organoids currently lack the presence of tRG cell types, that would strengthen the importance of the ferret model and the findings of this paper - otherwise, I feel that the use of the ferret model needs to be justified in light of the greater accesibility and genetic tractability of the cortical organoid system.
According to the suggestion of reviewer 1, we analyzed two cortical organoid datasets (Bhaduri et al., 2020; Herring et al., 2022) to examine whether different tRG populations are present in organoids. Our analyses led us to conclude that tRG-like populations seem to be lacking in available organoid datasets; organoids can have CRYAB-expressing astrocyte-like cells in single-cell transcriptome datasets, but the presence of tRG-like cells seem to be unstable and dependent of lines and protocols how organoids are generated. A further assessment on tRGs’ cellular features is required on organoids by immunostaining experiments. In the light of this analysis, we elaborated our discussion by describing observations shown below. Below is our analysis of organoid data.
Bhaduri dataset contained organoids generated from 4 different lines, which showed a variability in terms of cell distribution on UMAP while overall temporal and differentiation axes were recapitulated (A). While keeping the original cluster annotations except for YH10 line, we performed reclustering. CRYAB was expressed in clusters 26 and 30 enriched in YH10 line, and cluster 29 enriched in 13234 line (B).
To confirm the identity of these clusters, we integrated organoid dataset with the dataset of primary tissues from the same paper (Bhaduri et al., 2020; C). https://www.dropbox.com/scl/fi/qnqv2e87t74uom2pg836d/reviewer1_3CD.pdf?rlkey=mv370b3dlogwvgh6ig8bdathpdl=0
As a result of the integration, tRG cells from the primary tissue were not overlapped with organoid-derived CRYAB-expressing cells, although a part of CRYAB-expressing organoid cells were localized in the integrated cluster 16 where primary tRG resided (D). Other cell types that were included in the integrated cluster 16 were “lateRG”, “vRG”, “oRG” from primary tissue dataset, and “glycolyticRG” from organoid dataset. We found that CRYAB-expressing organoid clusters 26 and 30 overlapped with “oRG/astrocyte” clusters of primary tissues.
1-4. I found the total number of tRG-like cells in the ferret dataset quite small (162), but I understand the difficulty with isolating and sequencing rare cell types from primary tissue sources. I believe most of the transcriptomic analyses were conducted with this low n in consideration, but this caveat is even more reason to pare down the wording for the weaker claims mentioned above.
As for human dataset, we agree that committed tRG was minor. Thus, we pared down our statements regarding the fates of tRG as mentioned in other comments, both in the Results and Discussion.
1-5. I found it interesting that tRGs persist and even expand in number in postnatal timepoints (Fig. 2C). I'd be interested to know if this is in line with what is known in human developing cortex. If so, it would strengthen the conclusion that ferret tRGs can model that of humans - and if not, this would either be an important finding regarding tRG function or an important caveat in the use of ferret tRGs to model the cell type in humans.
Our study demonstrated the presence of tRG cells up to P10 by immunohistochemistry and scRNA-seq. P5~P10 is the stage where neurogenesis became dominated by gliogenesis in the dorsal cortex in ferrets, although its timing is delayed in the visual cortex. On the other hand, Nowakowski et al. (2016) originally identified and defined CRYAB-expressing tRG, based on morphology and gene expression on human primary tissues during mid-neurogenic stages, while cortical neurogenesis is mostly declined in human postnatal stages. We have failed to find literatures or textbooks describing the presence of CRYAB-expressing tRG, while an ependymal layer was detected in the postnatal human cortices (Honig et al., 1996; preprint Nascimento et al., 2022). At the moment, the lack of information thus makes it difficult to compare the relationship of birth timing with the period of tRG persistence between ferrets and humans. In the revised manuscript, the “Discussion” will include this argument as well as the following difference between humans and ferrets in the RG scaffold.
Besides birth timing, Nowakowski et al. also reported that radial glia scaffold spanning from the VZ to the pial surface undergoes a transformation during neurogenic stages; tRG becomes the major RG population in the VZ, disconnecting VZ and OSVZ. In contrast, we did not find a discontinuous scaffold stage over the course of ferret neurogenesis. Instead, we still detected CRYAB-negative vRG with an apical attachment and a basal process extending beyond the OSVZ during stages where the peak of tRG expansion is achieved (such as P5 in Figure 2A, S3A). This appears to be a prominent difference between human and ferret corticogenesis.
1-6. For Fig. 2A, I would find it helpful to compare the morphology of GFP+/CRYAB+ cells vs GFP+/CRYAB- cells, with the hypothesis that GFP+/CRYAB- cells will have elongated basal processes. I believe this could be done by finding GFP+/CRYAB- cells in the raw images obtained to generate Fig. 2A (or similar), and showing those cells in an adjacent panel. This side-by-side comparison could provide more support that the CRYAB+ cells from the single-cell analyses are indeed specifically linked to tRG-like morphology.
We prepared the images for GFP+/CRYAB- vRG cells in an adjacent panel in Figure 2A as recommended by the reviewer (below). To better distinguish the morphology of an isolated vRG cell from other labelled cells, we sparsely labeled RG cells with EGFP at P3 by electroporation (Methods), and fixed the samples two days later (right panel). We highlighted the morphology (cell body and basal fiber) of a CRYAB- GFP+ vRG and that of a neighboring CRYAB+ GFP- tRG on the same panel to clarify that vRG did not express CRYAB.
2-2. The authors must provide evidence that the cortical area they are examining will give rise to Somatosensory cortex. Their sampling area appears more like Cingulate cortex, while somatosensory may be a bit more lateral. The cingulate cortex is a very unique region, with some unique characteristics including lamination and connectivity. It would be important to provide some justification as to why they chose this particular part of the cerebral cortex, and keep this into consideration when discussing the general value of their findings.
To avoid such a misleading, we inserted the dotty lines in the revised Figure S1A to demarcate the tissue parts for scRNAseq, which correspond to almost all lateral cortices, mainly including the somatosensory area 1 and 2 with surrounding areas. We accordingly added the following sentence in the legend, “The approximate boundaries of dorsal cortex area used for scRNA sequencing are highlighted with dotty line segments in the dorsal cortex hemisphere above each strip.”.
We also show actual sampling for single-cell transcriptomics below. As our sampling was not restricted to the somatosensory cortex, we have revised “somatosensory cortex” as “dorsal cortex” in Lines 131 and 1191 of our manuscript.
2-4. Single cell QC methods are incomplete as described in Methods. It is key to consider the relative abundance of mitochondrial RNAs when assessing the integrity and validity of cells, and thus a key criterion to select the cells for clustering analysis. The criteria for the selected choice of clustering resolution is also missing.
We have now added the mitochondrial QC metrics in the new Figure S2A, and revised the legends as follows: “Violin plots showing the number of genes, mRNAs and the percentage of mitochondrial genes per cell in each sample and time point”. We have computed the percentage of mitochondrial genes for each cell type and found that the majority of cells in each cell type had a value less than 5% while the content value in some cells distributed along the range between 0% and 10%, up to a maximum of 28% (Figure S2A). Despite this, we have decided to include all cells that had less than 30% of mitochondrial genes in our analysis based on the percentage of reads mapped on mitochondrial genome for the following reasons:
- The percentage of mitochondrial indicates respiratory activity, rather than apoptosis and the percentage of mitochondrial quite depends on the tissue type and species. For example, in human case, such percentage range from 5%~30% (Mercer et al., 2011 Cell; The human mitochondrial transcriptome).
- Unfortunately, unlike human and mouse brains, there is no reference to show the percentage of mitochondrial in ferret brains. Therefore, the suitable way is to keep all of these cells.
- These cells showing high percentage of mitochondrial genes are not clustered as an apoptosis cluster in UMAP, instead, these cells are observed in most of clusters (below). Therefore, we believed that these cells are not apoptotic cells and include these cells in further analysis. https://www.dropbox.com/scl/fi/4kp3fczxzo6x4fx8hqt8m/reviewer2_4_1.pdf?rlkey=ypojzbuwgelt51qlf56g883s9&dl=0
- After all, we have obtained similar clustering overall after filtering cells with a higher percentage for mitochondrial genes; we set the threshold to 10%. This filtering resulted in 28,686 cells in our dataset. We then performed our workflow from the normalization step with the same settings that we applied to our original ferret dataset (Methods). Below, we show the results comparing newly generated clusters in this filtered subset on UMAP (left), and the original clusters shown in Figure 1B (right). 26 clusters were obtained in both conditions, and both major cell types and subtypes were conserved after filtering.
Clustering resolution: Our choice of the resolution was based on avoiding over- or under-clustering of ferret cells. After trying several resolution values, including 0.6, 0.8, 1.0 and 1.2, we have decided to use the resolution of 0.8 as the separation of cell types was the most reasonable among other resolutions that we have tried, in a similar way to actual known cell types. For example, the resolution of 0.6 did not distinguish “tRG” cells from “late_RG1” cells, as well as “early_RG” subtypes which were distinctly enriched with different cell cycle markers (Figure S2D). On the other hand, the resolution of 1.2 resulted in an over-clustering of IPC, OPC, DL neurons and microglia.
2-5. When first describing tRGs (line 171), orthogonal views of the image z-stacks must be shown to demonstrate the full morphology of these cells. The basal process might have been cut during tissue sectioning. The same applies to images in Fig. 2C, 2D, S3A.
We focused on Figure 2A and S3A (2D is a histogram) to show the full morphology of CRYAB+ tRG, because Figure 2A is the initial presentation of tRG in this paper, and Fig. 2A and Fig.S3A images are taken on a 200-micrometer thick section, originally aiming to indicate that CRYAB-positive fiber is short, spanning nearly along the VZ and the SVZ. We made 3D-reconstructions of those images, which are rather better than orthogonal projections, in order to show that CRYAB+ fibers are shorter than those of vRG (terminating at positions around the upper boundary of the SVZ) and that the short basal processes are not due to the cut of long radial fibers during tissue sectioning (we show in below and in the final version as a supplementary figure and movies).
We show these 3D-reconstruction in below. Please download movie files from the following URLs to look at them clearly.
Figure 2A
https://www.dropbox.com/s/qocve596c5xhtlc/%E2%98%85fig2A-Ver02.mp4?dl=0
Figure S3A
https://www.dropbox.com/s/v8gqwfi1r8ff5n5/%E2%98%85figS3A-P0%20movie-ver2.mp4?dl=0
2-7. Still regarding the time-lapse results presented in Figure 3, it is unclear why after first division the authors identify the blue cell as IPC, when it has the exact features of tRG: apical process anchored in VZ surface + short basal process. This is applicable to all three examples shown. For example, the authors describe: "the mother IPC of tRG also possessed both an apical endfoot and a short basal fiber (Fig. 3D)". Why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC? The interpretation of IPCs being the mother cells to tRGs must be changed, to those being vRGs. Or else, more convincing data must be provided.
In fact, their analyses in Fig 4A contradict their interpretation on tRG mother cells, showing that the transcriptomic trajectory leading to tRGs does not inlcude Eomes+ cells, accumulated in the neurogenic state 2. At the end of this section, the authors indicate: "our data suggest that tRG cells are formed by apical asymmetric division(s) from unique apical IPC with a short basal fiber (Tsunekawa et al, in preparation).". Being as important as this point is, if there is solid supporting data the authors must include it in this study.
- We are confident that this blue-labeled cells in Figure 3A and D are not vRG but mitotic sibling cell (of vRG) with a short basal fiber (that we named IPC in the initial manuscript). We now made the morphological features of these cells clearly visible by constructing 3D-views of the images with different snapshot images (we show below and in the final revision as a supplementary figure and movies). In addition, it divides once as time-lapse imaging revealed, hence this cell is still mitotic, instead of a postmitotic cell. Therefore, we used the term that is generally used for this type of cells, namely, intermediate progenitor cells (IPC), by which we did not intend to refer to TBR2+ neurogenic IPC. We plan to include these revised images into our fully revised manuscript.
- We agree the reviewer 2 on the point that this blue-labeled cell may express CRYAB (the next comment of reviewer 2 essentially claim the same point), as we also wrote this possibility in line 204-207 of the original manuscript. It could not be technically possible at the moment to examine CRYAB expression in a cell emerging only in the course of time-lapse imaging. If we could label vRG with a transgenic or knock-in fluorescence marker, which mimics CRYAB gene expression, we could have figured out whether blue cells the mitotic vRG sibling cells (or mitotic tRG parental cell) express the CRYAB gene. Indeed, we tried to knock the EGFP gene in the CRYAB gene many times over a year, but have so far failed. Given that tRG is defined as the cell type expressing CRYAB with a short basal fiber at late-neurogenic stage, irrespective of its mitotic activity, this blue labeled vRG sibling cell in Fig. 3A (and/or Fig. 3D) might express CRYAB, hence can be a “mitotic tRG” (although its possibility seems to be low as shown in Fig. 2E). To avoid any possible misleading, we have changed the term of these cells to a “mitotic vRG sibling cell (or mitotic tRG parental cell) with a short basal process”, and add a comment that “this cell might be mitotic tRG with CRYAB expression”.
- As for the TBR2 expression, we do not know these cells that appeared in the course of time-lapse imaging express TBR2 or not. As shown in Fig. 2F, 10% (P10) to 30 % (P5) of CRYAB+ cells express TBR2. On the other hand, “intermediate progenitors” do not necessarily express TBR2 in general. Therefore, we disagree on the reviewer 2’s comment “their analyses in Fig 4A contradict their interpretation on tRG’s parent cells”, but “our analyses in Fig 4A is compatible with our interpretation on tRG’s parent cells in time-lapse imaging”, and that is “a mitotic vRG sibling (or mitotic tRG parental cell) with a short basal fiber divides to produce CRYAB+ tRG at the end of timelapse imaging”. However, to avoid any overstatements or misunderstanding on this issue, we have revised related text as described above.
- We are not able to include the data taken by Tsunekawa et al.. This is because we are going to submit a separate paper, which includes a large volume of data with human ones in collaboration with another group and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not practical to combine these data with those described in this manuscript. Therefore, we remove all descriptions related with Tsunekawa et al.
Below we show snapshot images and 3D-reconstructions for Figure 3A and 3D. Please download movie files from the following URLs to look at them clearly.
@Figure 3A:
1)A time lapse movie (20 min interval) showing images around time 40:00 at which vRG underwent the second division. https://www.dropbox.com/s/znx3bboxefhj0jt/%E2%98%85Fig_3A%20movies%20around%2040%20h.mp4?dl=0
2)Snapshot images for time 40:00
https://www.dropbox.com/s/6y25mk4jhwqy6v7/%E2%98%85E38-fig3A-sRG-2.png?dl=0
- 3D-reconstruction images at the same time point (40:00)
- The entire time-lapse movies of time 0:00-84:00; The mitotic sibling cell of the vRG is indicated by a white arrow.
https://www.dropbox.com/s/ywua95f8fmohsmc/%E2%98%85Fig3A-arrow-time.mp4?dl=0
@Figure 3D:
A revised time-lapse snapshots of Figure 3D.
The assignment of the cell has corrected to the right one for the same mitotic cell because cell body position at the first two time points were misassigned in the original manuscript (at the following time points, there is no change).
Snapshot image at time point of 06:20; https://www.dropbox.com/s/hn3v6ao1qkhnfjh/%E2%98%85Fig3D%20sRG%20at%200620.png?dl=0
Rotating movie of 3D-reconstruction at time point of 06:40:
2-8. Alternative interpretation of time-lapse images (lines 196-197): maybe a tRG can generate one tRG CRYAB+, and one IPC CRYAB-.
We changed the term of IPC to “a mitotic vRG (or mitotic tRG parental cell) sibling cell” and describe the possibility that “This mitotic vRG sibling cell (or mitotic tRG parental cell) can be a mitotic tRG if this cell express CRYAB, and its apical division generates one tRG and one CRYAB-negative climbing cell with an unknown identity, replacing the description of line 196-197.
2-9. Arrows in Fig 5E are shifted between the top and bottom panels. There is no obvious evidence of mitosis visible. This should be unequivocally labeled with anti-PH3 antibodies.
We have corrected the shifted position of arrows in Figure 5E. We have removed “mitosis” in the title of Figure 5E since the initial manuscript did not include descriptions on mitosis in the text.
2-10. Line 277: “Transcriptomic trajectories were homologous across the two species”. What does this refer to? What are these trajectories? Pseudotime? Is this statistically tested?
We revised our description in this part as “Temporal patterns and variety of neural progenitors during the cortical development were similar to each other between humans and ferrets at the single cell transcriptome level”.
2-11. When comparing tRG cells between ferret and human, the authors indicate a remarkable similarity between the two species as represented by CRYAB, EGR1, and CYR61 expression. As shown in Fig 6E, EGR1 and CYR61 are not expressed selectively in human tRG as they clearly are in ferret tRG. Hence, this argument is not valid.
To clarify our statement, we changed this sentence into “tRG cells also showed a remarkable similarity between the two species (Fig. 6C, 6D), as represented by a high level of expression for the combination of CRYAB, EGR1, and CYR61 (Fig. 6E)”
2-13. Discussion is surprisingly short, given the emphasis that the authors place on the importance of their findings. I would suggest extending it for a better coverage of those findings that have the greatest relevance and interest to a wider readership.
We added several issues discussed in the responses to the reviewers to Discussion. Please look at our responses to comment 2-14 and 2-15 as well as the preliminary manuscript.
2-15. In Discussion: “our cross-species analysis highlights the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter”. As mentioned above, this is only based on transcriptomic trajectories, it is not demonstrated in this study. In vivo analyses of cell fate are needed to support this conclusion, and a more extensive videomicroscopy analysis is needed to confirm the cell lineage progression suggested by transcriptomes.
Taking the comments from reviewer 1 and 2 into account, we largely revised “Discussion” with a more moderate expression, by incorporating comparative analyses with other human datasets, and we also emphasize the importance of in vivo studies as the next step. We just paste the last paragraph of the preliminary revised Discussion. Please see the “Discussion” in the preliminary revision of our manuscript.
“In ferrets, genetic manipulations can be achieved through in utero or postnatal electroporation, as well as via virus-mediated transfer of DNA (Borrell, 2010; Kawasaki et al, 2012; Matsui et al, 2013; Tsunekawa et al, 2016). Thus, it is theoretically possible to disrupt the CRYAB gene in vivo in ferrets to investigate its role in tRG and their progeny, including ependymal cells, and to track the tRG lineage. If the CRYAB gene is essential to form ependymal layers, we will be able to explore how the ventricle contributes to cortical folding and expansion. Despite extensive efforts over a year, we have thus far been unsuccessful in knocking in and/or knocking out the CRYAB gene. Nevertheless, we anticipate that technical advances will surpass our expectations, both in ferret and human organoids. Taken together, these functional studies in ferrets as well as in human organoids hold promising insights into the understanding of the tRG lineage and its contribution to cortical development in the near future”.
2-16. In line 59, the authors state: "cerebral carcinogenesis independently evolved to gain an additional germinal layer (outer SVZ (OSVZ);". Assuming that they mean "cerebral neurogenesis", what is the evidence for this independent evolution? Original publications demonstrating this must be cited.
We removed the mentioned statement from our manuscript and revised lines 58-59 as follows: “In many mammalian phylogenic states, cerebral cortex evolved to gain an additional germinal layer (Smartet al. 2002; Zecevic et al. 2005; Kriegstein et al. 2006; Reillo et al. 2011)”.
2-17. Lines 60-61, the third key publication reporting the existence of bRG must be cited together with Hansen 2010 and Fietz 2010: Reillo et al., 2011, Cerebral Cortex.
We now added these citations in lines 60-61 and in the Reference list as Reillo I, De Juan Romero C, García-Cabezas MÁ & Borrell V (2011). A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. Cereb Cortex 21: 1674–1694.
2-18. When introducing ferret as an interesting or important animal model, suitable original studies should be cited.
For ferrets, there is a long history as experimental animals for electrophysiology similarly with cats and monkeys, but this is not a review of ferret biology. We thus added 6 additional references regarding ferret brain morphology and development listed below.
Jackson, C.A., J.D. Peduzzi, and T.L. Hickey (1989) Visual cortex development in the ferret. I. Genesis and migration of visual cortical neurons. J. Neurosci.9:1242–1253. PMID: 2703875.
Chapman B & Stryker MP (1992) Origin of orientation tuning in the visual cortex. Curr Opin Neurobiol 2: 498–501.
Chenn A., and McConnell S.K. (1995) Cleavage orientation and the asymmetric inheritance of Notch1 immunoreactivity in mammalian neurogenesis. Chenn A, et al. Cell PMID: 7664342.
Noctor SC, Scholnicoff NJ, and Juliano SL. (1997) Histogenesis of ferret somatosensory cortex. J Comp Neurol. 387(2):179-93.PMID: 9336222.
Reid CB, Tavazoie SF, Walsh CA. (1997) Clonal dispersion and evidence for asymmetric cell division in ferret cortex. Development. 1997 124(12):2441-2450. doi: 10.1242/dev.124.12.2441.PMID: 9199370
2-19. In Figure 2F-H, layer borders should be labeled. The density of CRYAB+ cells in VZ (?) at P5 seems much greater in Fig 2E,F than in Fig. 2B. Clarifying this discrepancy is important to validate the quantification of Fig 2D.
Layer borders: We now labeled the approximate position of the boundary of the VZ in Figure 2E-G. We have revised the legends as follows; “The border of the VZ is shown with a white line”. For counting, we have determined borders by the distribution of DAPI, and radial glia-specific markers in our hands and determined the approximative distance of the VZ border from the ventricular surface in the antero-posterior axis where we performed the imaging in Figure 2E-G. The distance was approximately determined as 80 µm at P5 and 40 µm at P10.
2-20. Co-expression of CRYAB and FOXJ1. In Fig 5B this must be demonstrated with merged channels.
We added the images with merged channels as requested and revised corresponding legends as follows: “Images with merged channels in A are shown with the same color codes, antibodies and scale bars as A.”.
2-21. Line 247: "near which nuclear line aggregates are observed more frequently (Fig. 2B)". It is very much unclear what the authors refer to. Please, define nuclear line aggregates.
We revise the cited sentence and will change the referred figure as follows: “These cells often aligned on a line parallel to the ventricular surface (Fig. 5A)”. We show these nuclear rows by arrows.
2-22. There are a number of typos along the main text and figures, which must be fully checked and corrected. For example, line 59 "cerebral carcinogenesis"; also in Figure S4, Figure 5E. Labeling of graphs in Fig 5C is wrong. The plots present the fraction of CRYAB+ cells that express FOXJ1 (FOXJ1+/CRYAB+ cells), not the reverse.
We thank the Reviewer for their remarks on typos. We corrected the typos indicated by Reviewer 2. We agree with the Reviewer and also modified the title of Figure 5B as suggested by the Reviewer.
Description of analyses that authors prefer not to carry out
Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.
2-1. In this report, Bilgic and colleagues study the diversity of progenitor cell types in the developing ferret cerebral cortex, a valuable in vivo model to understand cortex expansion and folding, as in primates including human. Using a single-cell transcriptomics approach, they describe a diversity of progenitor cell types and their interrelation by transcriptomic trajectories, which are conserved but biased as development progresses. Most interestingly, they identify in ferret a type of cell only identified in human before, tRG, which they then characterize throughoutly by transcriptomics. They also identify these cells in histological sections, and via time-lapse videomicroscopy they characterize their cell type of origin. They also provide indirect evidence that tRG may be the source of ependymal cells in the ventricle of the mature cerebral cortex, as well as astroglial progenitor cells. Finally, they extend their analyses to identify oRG in ferret based on previous human single cell data, concluding that they have in ferret a quite different transcriptomic profile than in human.
We would like to thank the reviewer for carefully reading our manuscript and providing us with valuable feedback. However, we would like to clarify that there might have been a misunderstanding regarding our conclusion about the identification of oRG-like cells in ferrets.
Our study did not conclude that we have identified oRG cells in ferrets with “a quite different transcriptomic profile than in human”. Instead, our findings indicate that unlike oRG cells in human, ferret oRG-like cells did not exhibit specificity for human oRG markers (such as HOPX and CLU) that would enable us to distinguish them from other late RG cells in ferrets. Despite this, oRG score derived from human oRG marker expression showed higher values in predicted ferret oRG-like cells compared to other ferret RG cells, reflecting a similarity of the transcriptome profile between human oRG and ferret oRG-like cells (Figure 7H-I). We will carefully describe our methodology to reach this conclusion in response to reviewer 2’s comment regarding how we determined ferret oRG in a later comment.
2-3. It seems that the single cell datasets were collected from only 1 replica at each developmental stage. Current best practice sets the inclusion of several biological replicates. Whereas this represents multiplying the workload (and costs) and re-doing many of the analyses, it is currently highly valued. On the other hand, the authors already have their analysis pipelines defined, and so the time involved should be much shorter than before.
We disagree with the reviewer 2’s comment. We would like to clarify that we collected brain tissues in two different ways for the same set of developmental stages; one brain tissue by removing cortical plate (T); another independent brain tissue at the same developmental stage by sorting GFP-labelled lineage from neural progenitors that were electroporated at embryonic stages (AG, Methods). Both manipulations of samples aimed to increase progenitor cell populations in scRNAseq. Therefore, we have two sets of samples of the same temporal series, each prepared in a totally different way. All cell types were present in both methods of collection shown as Supplementary Figure 2E’ (section 2) that separates samples by different preparations at each stage (by modifying Supplementary Figure 2E; section 2). We believe that the biological replica (n=2) in this manuscript would be sufficiently reliable, judged by its reproducibility.
Here, we also cite several examples of papers important in the field of single-cell or bulk transcriptomics of brain tissue, where only a single replicate or pair (replica) was taken for experiments on mice, humans and ferrets:
mice: Ogrodnik et al., 2021 PMID: 33470505, Hochgerner et al., 2018 PMID: 29335606, Joglekar et al., 2021 PMID: 33469025;
human: Herring et al., 2022 PMID: 36318921, Polioudakis et al., 2019 PMID: 31303374, Mayer et al., 2019 PMID: 30770253, Fietz et al., 2012 PMID: 22753484;
macaque: Schmitz et al., 2022 PMID: 35322231;
ferret: Johnson et al., 2018 PMID: 29643508.
2-14. In Discussion, the authors state that "ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." Again, this conclusion is purely based on transcriptomic trajectories, which must not be confused with cell lineage. This sentence must be rephrased and toned down accordingly.
We disagree with the reviewer 2 as for ferrets, because we accessed the relationship of tRG and their progeny cells by not only in silico but also in vivo analyses.
On the other hand, as for progenies of human tRG, they were predicted certainly depending on the molecular relationship by comparison with ferrets without histochemical evidence, as pointed by reviewer 2, and the populations of these committed tRG are small. Therefore, we removed “(and presumably also human)” and we tone down about the progeny relationship of tRG as a prediction. We also acknowledge that further studies are needed to confirm the lineage relationships among cell types, as we discussed in the Discussion part.
Reviewer #2 (Significance (Required)):
This manuscript is of interest for being the first ferret single-cell study, and for identifying and characterizing to a great extent a unique population of cortical progenitor cells that so far had only been observed in human. The study is presented as a resource for studies of ferret cortex development, which as such is clearly of interest to a very limited audience. A more appealing perspective might be if this study in ferret is of interest or of use to the more general community studying cortex development, or even maybe cortex evolution.
We disagree the reviewer’s view that this study is clearly of interest to a very limited audience. This study first enabled a precise comparative analysis in which we could compare rich human single cell transcriptomes and the ferret dataset of single cell transcriptomes, which were based on greatly improved genomic information (especially, gene models). This study is also first to show global temporal patterns of cortical progenitors of a carnivore species, a famous gyrencephalic mammalian model, and have been shown to be similar to a primate species at the single cell transcriptomic level. Indeed, upon uploading this manuscript in BioRxiv, many non-ferret specialists as well as specialists have inquired datasets and requested some collaborations with us. So we believe that this paper has already attract a general interest of brain scientists.
-
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #2
Evidence, reproducibility and clarity
In this report, Bilgic and colleagues study the diversity of progenitor cell types in the developing ferret cerebral cortex, a valuable in vivo model to understand cortex expansion and folding, as in primates including human. Using a single-cell transcriptomics approach, they describe a diversity of progenitor cell types and their interrelation by transcriptomic trajectories, which are conserved but biased as development progresses. Most interestingly, they identify in ferret a type of cell only identified in human before, tRG, which they then characterize throughoutly by transcriptomics. They also identify these cells in …
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #2
Evidence, reproducibility and clarity
In this report, Bilgic and colleagues study the diversity of progenitor cell types in the developing ferret cerebral cortex, a valuable in vivo model to understand cortex expansion and folding, as in primates including human. Using a single-cell transcriptomics approach, they describe a diversity of progenitor cell types and their interrelation by transcriptomic trajectories, which are conserved but biased as development progresses. Most interestingly, they identify in ferret a type of cell only identified in human before, tRG, which they then characterize throughoutly by transcriptomics. They also identify these cells in histological sections, and via time-lapse videomicroscopy they characterize their cell type of origin. They also provide indirect evidence that tRG may be the source of ependymal cells in the ventricle of the mature cerebral cortex, as well as astroglial progenitor cells. Finally, they extend their analyses to identify oRG in ferret based on previous human single cell data, concluding that they have in ferret a quite different transcriptomic profile than in human.
Major issues:
The authors must provide evidence that the cortical area they are examining will give rise to Somatosensory cortex. Their sampling area appears more like Cingulate cortex, while somatosensory may be a bit more lateral. The cingulate cortex is a very unique region, with some unique characteristics including lamination and connectivity. It would be important to provide some justification as to why they chose this particular part of the cerebral cortex, and keep this into consideration when discussing the general value of their findings.
It seems that the single cell datasets were collected from only 1 replica at each developmental stage. Current best practice sets the inclusion of several biological replicates. Whereas this represents multiplying the workload (and costs) and re-doing many of the analyses, it is currently highly valued. On the other hand, the authors already have their analysis pipelines defined, and so the time involved should be much shorter than before.
Single cell QC methods are incomplete as described in Methods. It is key to consider the relative abundance of mitochondrial RNAs when assessing the integrity and validity of cells, and thus a key criterion to select the cells for clustering analysis. The criteria for the selected choice of clustering resolution is also missing.
When first describing tRGs (line 171), orthogonal views of the image z-stacks must be shown to demonstrate the full morphology of these cells. The basal process might have been cut during tissue sectioning. The same applies to images in Fig. 2C, 2D, S3A.
In Figure 3, the authors perform time-lapse imaging to visualize and characterize the cells and lineage that give rise to tRGs. While very nice and a technical challenge that must be properly acknowledged, they unfortunately only obtained a total of three examples, which is clearly insufficient to reach any meaningful conclusion on this respect. These conclusions, while fascinating, are based only on 3 cell divisions. If this is to be taken as a strong argument for the conclusions of the study, the authors must obtain. If the authors want to make a solid statement out of this experimental approach, they must obtain a sufficient amount of additional data, which will depend on the variability of the results they find.
Still regarding the time-lapse results presented in Figure 3, it is unclear why after first division the authors identify the blue cell as IPC, when it has the exact features of tRG: apical process anchored in VZ surface + short basal process. This is applicable to all three examples shown. For example, the authors describe: "the mother IPC of tRG also possessed both an apical endfoot and a short basal fiber (Fig. 3D)". Why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC? The interpretation of IPCs being the mother cells to tRGs must be changed, to those being vRGs. Or else, more convincing data must be provided. In fact, their analyses in Fig 4A contradict their interpretation on tRG mother cells, showing that the transcriptomic trajectory leading to tRGs does not inlcude Eomes+ cells, accumulated in the neurogenic state 2. At the end of this section, the authors indicate: "our data suggest that tRG cells are formed by apical asymmetric division(s) from unique apical IPC with a short basal fiber (Tsunekawa et al, in preparation).". Being as important as this point is, if there is solid supporting data the authors must include it in this study.
Alternative interpretation of time-lapse images (lines 196-197): maybe a tRG can generate one tRG CRYAB+, and one IPC CRYAB-.
Arrows in Fig 5E are shifted between the top and bottom panels. There is no obvious evidence of mitosis visible. This should be unequivocally labeled with anti-PH3 antibodies.
Line 277: "Transcriptomic trajectories were homologous across the two species". What does this refer to? What are these trajectories? Pseudotime? Is this statistically tested?
When comparing tRG cells between ferret and human, the authors indicate a remarkable similarity between the two species as represented by CRYAB, EGR1, and CYR61 expression. As shown in Fig 6E, EGR1 and CYR61 are not expressed selectively in human tRG as they clearly are in ferret tRG. Hence, this argument is not valid.
In the last part, the authors try to identify oRG-like cells in ferret by comparison with their transcriptomes identified in human. For this, they decide to call ferret oRG-like cells those that are near human oRGs in the integrated UMAP, as identified in a previous human study. What was the criterion for this? How much near is "near"? The fact that the selected cells have higher oRG scores is expected and obvious, as these cells were selected precisely based on their proximity in the UMAP. Even more importantly, the identification of oRGs in the human study is not unambiguous. Therefore, the correlate in ferret cells is also non-conclusive as to the identity of such cells.
Discussion is surprisingly short, given the emphasis that the authors place on the importance of their findings. I would suggest extending it for a better coverage of those findings that have the greatest relevance and interest to a wider readership.
In Discussion, the authors state that "ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." Again, this conclusion is purely based on transcriptomic trajectories, which must not be confused with cell lineage. This sentence must be rephrased and toned down accordingly.
In Discussion: "our cross-species analysis highlights the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter". As mentioned above, this is only based on transcriptomic trajectories, it is not demonstrated in this study. In vivo analyses of cell fate are needed to support this conclusion, and a more extensive videomicroscopy analysis is needed to confirm the cell lineage progression suggested by transcriptomes.
Minor issues:
In line 59, the authors state: "cerebral carcinogenesis independently evolved to gain an additional germinal layer (outer SVZ (OSVZ);". Assuming that they mean "cerebral neurogenesis", what is the evidence for this independent evolution? Original publications demonstrating this must be cited.
Lines 60-61, the third key publication reporting the existence of bRG must be cited together with Hansen 2010 and Fietz 2010: Reillo et al., 2011, Cerebral Cortex.
When introducing ferret as an interesting or important animal model, suitable original studies should be cited.
In Figure 2F-H, layer borders should be labeled. The density of CRYAB+ cells in VZ (?) at P5 seems much greater in Fig 2E,F than in Fig. 2B. Clarifying this discrepancy is important to validate the quantification of Fig 2D.
Co-expression of CRYAB and FOXJ1. In Fig 5B this must be demonstrated with merged channels.
Line 247: "near which nuclear line aggregates are observed more frequently (Fig. 2B)". It is very much unclear what the authors refer to. Please, define nuclear line aggregates.
There are a number of typos along the main text and figures, which must be fully checked and corrected. For example, line 59 "cerebral carcinogenesis"; also in Figure S4, Figure 5E. Labeling of graphs in Fig 5C is wrong. The plots present the fraction of CRYAB+ cells that express FOXJ1 (FOXJ1+/CRYAB+ cells), not the reverse.
Significance
This manuscript is of interest for being the first ferret single-cell study, and for identifying and characterizing to a great extent a unique population of cortical progenitor cells that so far had only been observed in human. The study is presented as a resource for studies of ferret cortex development, which as such is clearly of interest to a very limited audience. A more appealing perspective might be if this study in ferret is of interest or of use to the more general community studying cortex development, or even maybe cortex evolution.
Advance: it is, so far, the first study of single cell profiling of the ferret cerebral cortex, a well established and highly valued model of gyrencephalic mammals, and a suitable best-alternative to work in primates. In addition to the technical advance, providing a new resource for work in ferret, it shows for the first time the existence of truncated Radial Glia (tRG) in a non-human cortex, and even more importantly in this model, strengthening even more its value.
This study as is presented will be of most interest to a specialized audience, those directly working with ferret. Nevertheless, it will also be of conceptual interest to the community of cortex development and evolution for the concepts that one can extract on cell type conservation.
My expertise: cerebral cortex development, brain evolution, ferret, cortex folding, neurogenesis, progenitor cell lineage, transcriptomics of developing brain
-
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
Summary: Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).
In this manuscript, the authors conduct a series of single-cell transcriptomic analyses and imaging assays in the developing ferret cortex suggesting that (1) ferrets harbor a radial glia (RG) subtype similar to the truncated radial glia (tRG) described previously in humans that may have the potential to (2) produce ependymal and astrogenic lineages which (3) can also be found in the developing human cortex. These findings appear to be an important step in the validation and development of the ferret …
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
Summary: Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).
In this manuscript, the authors conduct a series of single-cell transcriptomic analyses and imaging assays in the developing ferret cortex suggesting that (1) ferrets harbor a radial glia (RG) subtype similar to the truncated radial glia (tRG) described previously in humans that may have the potential to (2) produce ependymal and astrogenic lineages which (3) can also be found in the developing human cortex. These findings appear to be an important step in the validation and development of the ferret model towards a tool that can be used to study tRG cell biology, a feat currently difficult due to the inaccessibility of a genetically tractable source of tRG for molecular and cell biology experiments.
Major comments:
- Are the key conclusions convincing?
I found the key conclusions described above and in the authors' abstract convincing. I found the identification of a distinct, tRG-like cell type from the authors' single-cell transcriptomic analysis of the ferret cortex compelling, particularly because (1) the expression of the previously utilized tRG marker gene CRYAB is specific to the tRG-like cluster and (2) the tRG-like cluster marker genes (including CRYAB) are relatively unique to the tRG-like cluster. I found this strengthened by their morphological analyses showing the tRG-characteristic apical endfoot and short basal process in these CRYAB+ cells in the ferret cortex. I found the combination of imaging and bioinformatic analyses showing the increase in FOXJ1 co-expression in CRYAB+ cells to compellingly suggest that CRYAB+ cells can produce FOXJ1+ ependymal cells, and similarly with the authors' analyses to suggest that tRG-like cells can also contribute to SPARCL1+ astrocyte cells. I found that the cluster score analyses compelling suggest that the tRG-like cells in the ferret dataset correlate with the tRG cells annotated in a separate, human developing cortical dataset. I also appreciated the comparison of astroglial, ependymal, and uncommited ferret tRG sub populations from the pseudo time analysis with the clusters generated from the integrated ferret-human dataset in Fig. 7.
- Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?
- Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
- Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.
The weakest claim in the paper is lines 202: "...tRG cells are formed by apical asymmetric division(s) from unique apical IPC". From my understanding, the main evidence that the tRG parent cells shown in Fig. 3 are not tRGs are the data from Fig. 2E-G showing the low amounts of CRYAB+ cells co-expressing KI67, TBR2, or OLIG2 in P5 and P10. Especially given that these timepoints are after those used in Fig. 3, I believe further evidence is needed to confirm the cell type identity of tRG parent cells in Fig. 3. Such experiments (isolating IPCs from ferret cortex and growing in vitro to determine progeny cells) may be outside of the scope of this paper, in which case I believe the text can be strengthened with either (1) presenting the data from the cited Tsunekawa et al, in preparation that would suggest this claim or (2) rephrasing these claims to omit the mention of IPCs.
I also believe the claim in Line 365-366 is overstated: "We found that ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." While I believe the transcriptomic comparisons suggest the presence of uncommitted tRG in both the ferret and human datasets, I would appreciate further analyses to confirm the prevalence of astroglial and ependymal tRG in the humans and/or functional analyses before claiming that human tRG cells make ependymal and astrogenic cells. I appreciate the authors' note that "GW25 is...the latest stages experimentally available" (line 376-377), but their comparative approaches could be applied to existing datasets of the human cortex (Herring et al., 2022, PMID: 36318921) that span later developmental ages. Identifying the presence of astroglial and ependymal tRGs in this and/or similar datasets would provide more convincing evidence of the tRGs' developmental potential. If this computational analysis is outside the scope of the paper, I believe paring the certainty of these claims (especially lines 379 - 383) and recognizing the need for further functional analyses would negate the need for deeper mechanistic validation.
I believe the most significant advance for this paper is the potential to use ferret tRG cells to model those of the human brain. However to support this claim (see Lines 83-84), I believe a comparison of the ferret tRG cells with existing cortical organoid datasets (Bhaduri et al., 2020, PMID: 31996853) would be helpful. If cortical organoids currently lack the presence of tRG cell types, that would strengthen the importance of the ferret model and the findings of this paper - otherwise, I feel that the use of the ferret model needs to be justified in light of the greater accesibility and genetic tractability of the cortical organoid system.
- Are the data and the methods presented in such a way that they can be reproduced? Yes
- Are the experiments adequately replicated and statistical analysis adequate?
I found the total number of tRG-like cells in the ferret dataset quite small (162), but I understand the difficulty with isolating and sequencing rare cell types from primary tissue sources. I believe most of the transcriptomic analyses were conducted with this low n in consideration, but this caveat is even more reason to pare down the wording for the weaker claims mentioned above.
- Are prior studies referenced appropriately?
I found it interesting that tRGs persist and even expand in number in postnatal timepoints (Fig. 2C). I'd be interested to know if this is in line with what is known in human developing cortex. If so, it would strengthen the conclusion that ferret tRGs can model that of humans - and if not, this would either be an important finding regarding tRG function or an important caveat in the use of ferret tRGs to model the cell type in humans.
- Are the text and figures clear and accurate? Yes
- Do you have suggestions that would help the authors improve the presentation of their data and conclusions?
For Fig. 2A, I would find it helpful to compare the morphology of GFP+/CRYAB+ cells vs GFP+/CRYAB- cells, with the hypothesis that GFP+/CRYAB- cells will have elongated basal processes. I believe this could be done by finding GFP+/CRYAB- cells in the raw images obtained to generate Fig. 2A (or similar), and showing those cells in an adjacent panel. This side-by-side comparison could provide more support that the CRYAB+ cells from the single-cell analyses are indeed specifically linked to tRG-like morphology.
Significance
This paper primarily presents a technical advance in the field, showing that tRG cells that can model those found in the developing human cortex are found in the developing ferret cortex.
- Place the work in the context of the existing literature (provide references, where appropriate).
- State what audience might be interested in and influenced by the reported findings. Several studies in the human and macaque brain have identified the presence of tRGs (deAzevedo et al., 2003; Nowakowski et al., 2016), but understanding the molecular functions and development of these cells - and many human-specific cell types in the brain - is difficult due to the lack of tractable models of human neurodevelopment. Ferrets, given their layered cortices, may be a potential model system for these cell types, but further analyses to determine their transcriptomic similarity to the developing human cortex and their ability to recapitulate human cell types are required in order to evaluate their use as a model system. By generating a useful resource in the ferret single-cell transcriptomic atlas, this study provides evidence that - at least for the tRG subtypes - ferrets may be useful in dissecting the generation and functional importance of tRG cells. With the caveat that a direct comparison with the use of cortical organoids to study tRG is lacking in this paper (see above), I believe this work can provide useful insight into the field's current search for model systems to functionally interrogate human-specific aspects of cortical development.
- Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.
Single-cell transcriptomic profiling of primary developing human cortex and cortical organoids
Did not have sufficient expertise in:
- Ferret biology
-
-
