Cited by 1,065Single-cell and spatial transcriptomicsNeuroscience and Neuropharmacology ResearchMemory and Neural Mechanisms

The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index; none of the 65 sources its claims cite is checked for support yet.

A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation

Open access

Yao, Zizhen, van Velthoven, Cindy T.J., Nguyen, Thuc Nghi, Goldy, Jeff, Sedeno-Cortes, Adriana E., Baftizadeh, Fahimeh, Bertagnolli, Darren, Casper, Tamara, Chiang, Megan, Crichton, Kirsten, Ding, Song-Lin, Fong, Olivia, Garren, Emma, Glandon, Alexandra, Gouwens, Nathan W., Gray, James, Graybuck, Lucas T., Hawrylycz, Michael J., Hirschstein, Daniel, Kroll, Matthew, Lathia, Kanan, Lee, Changkyu, Levi, Boaz, McMillen, Delissa, Mok, Stephanie, Pham, Thanh, Ren, Qingzhong, Rimorin, Christine, Shapovalova, Nadiya, Sulc, Josef, Sunkin, Susan M., Tieu, Michael, Torkelson, Amy, Tung, Herman, Ward, Katelyn, Dee, Nick, Smith, Kimberly A., Tasic, Bosiljka, Zeng, Hongkui·2021·Cell

DOI 10.1016/j.cell.2021.04.021PMC PMC8195859

Published version of a preprint

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Abstract

SUMMARY The isocortex and hippocampal formation (HPF) in the mammalian brain play critical roles in perception, cognition, emotion and learning. We profiled ~1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and isocortex share a common circuit organization. We also identify large-scale continuous and graded variation of cell types along isocortical depth, across isocortical sheet and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity and function of these brain structures.

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Crossref · 10.1016/j.cell.2021.04.021

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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The GABAergic inhibitory neuronal class is divided into two neighborhoods that correlate with distinct developmental origins: caudal ganglionic eminence (CGE) (Fig. 2A–E) and medial ganglionic eminence (MGE) (Fig. 2F–J).”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
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- Rests on an assumption: Transcriptomic neighborhoods of GABAergic neurons correlate with distinct developmental origins (CGE and MGE).
In the paper
“Our CTX-HPF GABAergic taxonomy corresponds well with a previous scRNA-seq study of CA1 interneurons (Harris et al., 2018), particularly for some HPF-specific clusters identified here”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Harris et al., 2018 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes

Show all 146 claims

It may state two separate claims as one. 123
Probably not a substantial claim. 43
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None of the sources cited for this claim have been checked yet.
In the paper
“For CGE, the Ntng1 HPF supertype does not express canonical pan-CGE marker Prox1 (Miyoshi et al., 2015; Rubin and Kessaris, 2013) nor its subclass markers Vip, Sncg or Lamp5”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Miyoshi et al., 2015 source
- Not checked yetcites Rubin and Kessaris, 2013
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In the paper
“most clusters are shared by all isocortical areas, consistent with our previous observations (Tasic et al., 2018), and also by RHP regions”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Tasic et al., 2018 source
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None of the sources cited for this claim have been checked yet.
In the paper
“It is also consistent with the large body of literature on cortical GABAergic interneurons (Lim et al., 2018; Pelkey et al., 2017; Tremblay et al., 2016), and our Patch-seq study (Gouwens et al., 2020) with MET types defined in that study corresponding well with the supertypes defined here”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Lim et al., 2018 source
- Not checked yetcites Pelkey et al., 2017 source
- Not checked yetcites Tremblay et al., 2016 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The current CTX-HPF GABAergic taxonomy is largely consistent with previous transcriptomic taxonomies derived from cortical areas VISp-ALM (Tasic et al., 2018) and MOp (Yao et al., 2020) at the supertype level but exhibits notable ambiguity at the type/cluster level”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Tasic et al., 2018 source
- Not checked yetcites Yao et al., 2020
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In the paper
“Projection mapping (http://connectivity.brain-map.org/; experiments 166269090, 166458363 and 181860879) (Oh et al., 2014) showed that neurons labeled via Scnn1a-Tg3-Cre driver line in RSP have long-range projections to both intra- and extratelencephalic targets; they project to ACA, RHP regions, contralateral RSP, and anteroventral nucleus (AV) of thalamus”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > Comparison of glutamatergic cell types between hippocampal formation and isocortex
What the sources say
- Not checked yetcites Oh et al., 2014
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None of the sources cited for this claim have been checked yet.
In the paper
“The three ALM L5 PT types previously identified (Economo et al., 2018; Tasic et al., 2018) correspond to cluster #248 (thalamus-projecting cells) in the Npnt supertype and clusters #249 and #252 (medulla-projecting cells) in the Cdh13 supertype, respectively”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > Comparison of glutamatergic cell types between hippocampal formation and isocortex
What the sources say
- Not checked yetcites Economo et al., 2018 source
- Not checked yetcites Tasic et al., 2018 source
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“Across all isocortical areas, most glutamatergic cell types are shared among multiple areas (Fig. 3B, S2), contrary to what we found in our previous study of two distantly located cortical areas, VISp and ALM”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > DISCUSSION
What the sources say
- Not checked yetcites Tasic et al., 2018 source
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“a previously known CA3 proximal gene, Fmo1 (Thompson et al., 2008), that is expressed in dorsal clusters #356 and #358, but not #357.”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > STAR METHODS > METHOD DETAILS
What the sources say
- Not checked yetcites Thompson et al., 2008 source
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“while many deep layer markers such as Lpl have ubiquitous expression in the dorsal distal CA1, positioning these cells closer to the deep end of the pseudo Su-De axis.”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > STAR METHODS > METHOD DETAILS
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- Rests on an assumption: The top principal component computed from a selected gene set faithfully represents the biological axis it is named after (e.g., Pr-Di, Do-Ve, Su-De, activity).
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“While our initial attempt using random forest classifier produced a very strong result (data not shown), we realized that the results were partially driven by donor-specific genes.”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > STAR METHODS > METHOD DETAILS
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- Rests on an assumption: Donor-specific transcriptional signatures are subtle and do not affect the global clustering results.
In the paper
“Glutamatergic neuronal types are organized by layers and their long-range projection patterns”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Harris and Shepherd, 2015 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Archicortex and paleocortex are considered evolutionarily older structures, whereas iso/neocortex emerged later and substantially expanded in vertebrate evolution”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Rakic, 2009 source
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“their tremendous diversity in interareal axon-projection patterns forms the structural basis of the hierarchical network”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites D’Souza et al., 2016 source
- Not checked yetcites Harris et al., 2019 source
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“This area specialization is likely a major contributing factor to the diversity of functions supported by cortex”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Cadwell et al., 2019 source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“The cortex is partitioned into multiple areas with specific input and output connections with many subcortical and other cortical regions”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Rakic, 2009 source
- Not checked yetcites Van Essen and Glasser, 2018
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Developmentally, cortex originates from pallium, a main part of the telencephalon, which can be divided into several parts”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Pessoa et al., 2019 source
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Many molecular, anatomical, and physiological studies have revealed a broad spectrum of neuronal cell types in different cortical and hippocampal regions”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Zeng and Sanes, 2017 source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“these neocortical areas together form a hierarchical neural network with functionally distinct modules and feedforward and feedback pathways both within and between modules”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Coogan and Burkhalter, 1993
- Not checked yetcites Felleman and Van Essen, 1991 source
- Not checked yetcites Harris et al., 2019 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“there is a prominent functional transition along the dorsal-ventral axis of HPF, with the dorsal network mainly mediating spatial navigation and the ventral network mainly mediating emotional behaviors”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Cembrowski and Spruston, 2019
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Since isocortical Sst Myh8 and Etv1 cells are L5 Martinotti cells (Gouwens et al., 2020) (Fig. S1B), the HPF Myh8 and Etv1 cells are likely the Martinotti-like oriens lacunosum-moleculare (OLM) cells (Leao et al., 2012).”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Gouwens et al., 2020 source
- Not checked yetcites Leao et al., 2012 source
Load-bearingStrength:hedged· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“Previously, we analyzed single-cell transcriptomes to define 133 cell types in two isocortical areas, primary visual cortex (VISp) and anterolateral motor cortex (ALM), in mice (Tasic et al., 2018) and found that they have shared GABAergic interneuron types but distinct glutamatergic neuron types.”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Tasic et al., 2018 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Note that some of the CGE cell types (e.g., some neurogliaform cells) may, in fact, be developmentally derived from the nearby preoptic region (PO) (Niquille et al., 2018).”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > GABAergic cell type taxonomy
What the sources say
- Not checked yetcites Niquille et al., 2018 source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Meis2 neurons were identified as related to olfactory bulb interneurons (Frazer et al., 2017).”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > Generation of the transcriptomic cell type taxonomy
What the sources say
- Not checked yetcites Frazer et al., 2017 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The distinct subclass of Car3, which includes neurons from L6 of many lateral cortical areas, is included here as our previous study showed that these Car3+ L6 neurons, like cortical IT neurons, have extensive intracortical axon projections (Peng et al., 2020).”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > Glutamatergic cell type taxonomy
What the sources say
- Not checked yetcites Peng et al., 2020
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Single-cell RNA-sequencing (scRNA-seq) studies have systematically characterized and classified cell types in individual regions of isocortex and hippocampus”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > INTRODUCTION
What the sources say
- Not checked yetcites Harris et al., 2018 source
- Not checked yetcites Hodge et al., 2019 source
- Not checked yetcites Tasic et al., 2016 source
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim.
In the paper
“likely corresponds to a subset of cortical L2/3 neurons that express IEG c-fos under basal conditions and are preferentially interconnected within the L2/3 network (Yassin et al., 2010)”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > RESULTS > Continuous variation of glutamatergic neuron types across layers and regions of isocortex
What the sources say
- Not checked yetcites Yassin et al., 2010 source
Strength:hedged· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This prediction is highly consistent with the currently known interareal connections of HPF, providing a level of validation to the transcriptomic cell type framework”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > DISCUSSION
What the sources say
- Not checked yetcites Bienkowski et al., 2018 source
- Not checked yetcites Ding et al., 2020 source
- Not checked yetcites Gergues et al., 2020 source
Load-bearingStrength:boosted· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“In addition to the classical single-cell clustering processing steps provided by other tools such as Seurat (Butler et al., 2018), this package features automatic iterative clustering while ensuring all pairs of clusters, even at the finest level, are separable by fairly stringent differential gene expression criteria (Tasic et al., 2018).”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > STAR METHODS > METHOD DETAILS
What the sources say
- Not checked yetcites Tasic et al., 2018 source
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The combination of these region-specific cell types and the continuous variation of shared cell types across isocortical areas collectively defines cortical areal modularity”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > DISCUSSION
What the sources say
- Not checked yetcites Harris et al., 2019 source
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, the prediction was based on global transcription signatures that are conserved across platforms, with no particular genes heavily weighted.”
§ A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation > STAR METHODS > METHOD DETAILS
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- Rests on an assumption: The 10xv2 and SSv4 datasets share conserved global transcriptional signatures that permit cross-platform mapping of regional identity.

142 of 142

The authors state this as an assumption.
A systematic study is needed for a complete picture of the number and distribution of cell types in isocortex and HPF and for understanding how these regions interact with the rest of the brain.
“But a systematic study is needed for a complete picture of the number and distribution of cell types in these regions and for understanding how different cortical and hippocampal regions interact with the rest of the brain and carry out their individual functions.”
The paper relies on this without support.
Fewer differentially expressed genes between two clusters indicates greater relatedness or similarity.
“the fewer DE genes, the more related”
The paper relies on this without support.
Correlation of gene expression between HPF and CTX clusters indicates homology.
“correlating gene expression for each HPF cell to the average expression of each CTX cluster”
The paper relies on this without support.
Mouse isocortex and hippocampal formation are representative of mammalian isocortex and hippocampal formation.
“our study establishes a molecular architecture of mammalian isocortex and hippocampal formation”
The paper relies on this without support.
Transcriptomic neighborhoods of GABAergic neurons correlate with distinct developmental origins (CGE and MGE).
“The GABAergic inhibitory neuronal class is divided into two neighborhoods that correlate with distinct developmental origins: caudal ganglionic eminence (CGE) (Fig. 2A–E) and medial ganglionic eminence (MGE) (Fig. 2F–J).”
The paper relies on this without support.
The anatomical locations assigned using existing RNA ISH data from the Allen Mouse Brain Atlas and a limited Visium dataset are accurate enough for major cell types.
“we assigned anatomical locations of major cell types (mostly at the supertype level) using existing RNA ISH data from the Allen Mouse Brain Atlas and a limited Visium dataset”
The paper relies on this without support.
The relative proportions estimated from 10xv2 data reflect true proportions of cell types in each region.
“we also provided an estimate of the relative proportions of different cell types in each region using the 10xv2 data”
The paper relies on this without support.
The top principal component computed from a selected gene set faithfully represents the biological axis it is named after (e.g., Pr-Di, Do-Ve, Su-De, activity).
“The top PC based on this set of genes is defined as the CA3 Pr-Di axis”
“defined the pseudo superficial-deep (Su-De) axis as the top PC based on these layer-specific genes”
“computed the top PC based on this gene set as the activity axis”
The paper relies on this without support.
The 10xv2 and SSv4 datasets share conserved global transcriptional signatures that permit cross-platform mapping of regional identity.
“the prediction was based on global transcription signatures that are conserved across platforms”
The paper relies on this without support.
Donor-specific transcriptional signatures are subtle and do not affect the global clustering results.
“While donor-specific transcriptional signatures are subtle and do not affect the global clustering results”

10 of 10

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Percentages, sums and reported differences re-computed from the paper’s own numbers.

Class-level subclass counts omit two subclasses
Minor
The four class counts of 6, 28, 2, and 4 subclasses sum to 40 rather than 42. CR and Meis2 are subsequently identified as neuronal subclasses, but are not accounted for in the stated class breakdown.
Reported 42 · recomputed 40

1 of 1

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Items 301–400 of 998

Oligodendrocyte precursor cells prune axons in the mouse neocortexPreprint
Buchanan, J., Elabbady, L., Collman, F., Jorstad, N. L., Bakken, T. E., Ott, C. M., Glatzer, J. C., Bleckert, A., Bodor, Á. L., Brittan, D., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.29.446047 · Cited by 28
Cellular rules underlying psychedelic control of prefrontal pyramidal neuronsPreprint
Ekins, T. G., Brooks, I. A. W., Kailasa, S., Rybicki-Kler, C., Jedrasiak‐Cape, I., Donoho, E., Mashour, G. A., Rech, J. C., & Ahmed, O. J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.20.563334 · Cited by 19
The neuropeptidergic connectome of C. elegansPreprint
Ripoll-Sánchez, L., Watteyne, J., Sun, H., Fernandez, R. W., Taylor, S. R., Weinreb, A., Hammarlund, M., Miller, D. M., Hobert, O., Beets, I., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.30.514396 · Cited by 21
SpaBatch: Deep Learning‐Based Cross‐Slice Integration and 3D Spatial Domain Identification in Spatial Transcriptomics
Niu, J., Fang, D., Chen, J., Xiong, Y., Liu, J., & Min, W. (2025) · Advanced Science · doi:10.1002/advs.202509090 · Cited by 25
Deletion of Abi3/Gngt2 influences age-progressive amyloid β and tau pathologies in distinctive ways
Ibanez, K. R., McFarland, K. N., Phillips, J., Allen, M., Lessard, C. B., Zobel, L., De La Cruz, E. G., Shah, S., Vo, Q., Wang, X., et al. (2022) · Alzheimer's Research & Therapy · doi:10.1186/s13195-022-01044-1 · Cited by 18
Plasma membrane phospholipid phosphatase-related proteins as pleiotropic regulators of neuron growth and excitability
Fuchs, J., Bareesel, S., Kroon, C., Polyzou, A., Eickholt, B. J., & Leondaritis, G. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.984655 · Cited by 18
The brain's dark transcriptome: Sequencing RNA in distal compartments of neurons and glia
Ament, S. A., & Poulopoulos, A. (2023) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2023.102725 · Cited by 14
Disease modification upon 2 weeks of tofacitinib treatment in a mouse model of chronic epilepsy
Hoffman, O. R., Koehler, J. L., Espina, J. E. C., Patterson, A. M., Gohar, E. S., Coleman, E. M., Schoenike, B. A., Espinosa‐García, C., Paredes, F., Varvel, N. H., et al. (2025) · Science Translational Medicine · doi:10.1126/scitranslmed.adt0527 · Cited by 20
An unsupervised map of excitatory neuron dendritic morphology in the mouse visual cortex
Weis, M. A., Papadopoulos, S., Hansel, L., Lüddecke, T., Celii, B., Fahey, P. G., Wang, E. Y., Bae, J. A., Bodor, A. L., Brittain, D., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58763-w · Cited by 28
Dopamine D1–D2 signalling in hippocampus arbitrates approach and avoidance
Godino, A., Salery, M., Minier-Toribio, A. M., Patel, V., Fullard, J. F., Kondev, V., Parise, E. M., Martínez-Rivera, F. J., Morel, C., Roussos, P., et al. (2025) · Nature · doi:10.1038/s41586-025-08957-5 · Cited by 34
Microglial replacement in a Sandhoff disease mouse model reveals myeloid-derived β-hexosaminidase is necessary for neuronal health
Tsourmas, K. I., Butler, C. A., Kwang, N. E., Sloane, Z. R., Dykman, K. J. G., Maloof, G. O., Choudhury, B., Paulchakrabarti, M., Prekopa, C. A., Tabaie, E. Z., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63237-0 · Cited by 25
A whole-brain single-cell atlas of circadian neural activity in mice
Yamashita, K., Kinoshita, F. L., Yoshida, S., Matsumoto, K., Mitani, T. T., Fujishima, H., Minami, Y., Morii, E., Yamada, R. G., Okada, S., et al. (2025) · Science · doi:10.1126/science.aea3381 · Cited by 24
How Universities Entrust Digital Literacy to Improve Student Learning Outcomes During the COVID-19 Disruption
Basir, A., Kamaliah, K., Harahap, A., Fauzi, A., & Karyanto, B. (2021) · JURNAL IQRA · doi:10.25217/ji.v6i1.1146 · Cited by 17
Further refining the boundaries of the hippocampus CA2 with gene expression and connectivity: Potential subregions and heterogeneous cell types
Bienkowski, M. S. (2023) · Hippocampus · doi:10.1002/hipo.23508 · Cited by 19
Activity‐regulated gene expression across cell types of the mouse hippocampus
Nelson, E. D., Maynard, K. R., Nicholas, K. R., Tran, M. N., Divecha, H. R., Collado‐Torres, L., Hicks, S. C., & Martinowich, K. (2023) · Hippocampus · doi:10.1002/hipo.23548 · Cited by 16
Laminar and dorsoventral organization of layer 1 interneuronal microcircuitry in superficial layers of the medial entorhinal cortex
Shi, Y., Cui, H. F., Li, X., Chen, L., Zhang, C., Zhao, X., Li, X., Shao, Q., Sun, Q., Yan, K., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112782 · Cited by 20
Hippocampome.org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits
Wheeler, D. W., Kopsick, J. D., Sutton, N. M., Tecuatl, C., Komendantov, A. O., Nadella, K., & Ascoli, G. A. (2023) · eLife · doi:10.7554/elife.90597 · Cited by 14
Psychiatric risk gene Transcription Factor 4 (TCF4) regulates the density and connectivity of distinct inhibitory interneuron subtypes
Chen, H.-Y., Phan, B. N., Shim, G., Hamersky, G. R., Sadowski, N., O’Donnell, T. S., Sripathy, S. R., Bohlen, J. F., Pfenning, A. R., & Maher, B. J. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02248-z · Cited by 17
Disruption of the autism gene and chromatin regulator KDM5A alters hippocampal cell identity
Hayek, L. E., DeVries, D., Gogate, A., Aiken, A., Kaur, K. J., & Chahrour, M. H. (2023) · Science Advances · doi:10.1126/sciadv.adi0074 · Cited by 19
Single-cell RNA sequencing uncovers the cell type-dependent transcriptomic changes in the retrosplenial cortex after peripheral nerve injury
Wang, J., Wu, C., Lian, Y., Cao, X., Wang, Z., Dong, J., Wu, Q., Liu, L., Sun, L., Chen, W., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113551 · Cited by 19
Drug targeting in psychiatric disorders — how to overcome the loss in translation?
Khodosevich, K., Dragičević, K., & Howes, O. D. (2023) · Nature Reviews Drug Discovery · doi:10.1038/s41573-023-00847-7 · Cited by 17
Connecting single-cell transcriptomes to projectomes in the mouse visual cortex
Sorensen, S. A., Gouwens, N. W., Wang, Y., Mallory, M., Budzillo, A., Dalley, R. A., Lee, B., Gliko, O., Kuo, H.-C., Kuang, X., et al. (2026) · Nature · doi:10.1038/s41586-026-10424-8 · Cited by 13
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Hypnotic treatment improves sleep architecture and EEG disruptions and rescues memory deficits in a mouse model of fragile X syndrome
Martinez, J. D., Wilson, L. G., Brancaleone, W. P., Peterson, K. G., Popke, D. S., Caicedo-Garzón, V., Perez‐Tremble, R., Donnelly, M. J., Ortega, S., Torres, D., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114266 · Cited by 17
Imaging the endocannabinoid signaling system
Dudok, B., & Soltész, I. (2021) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2021.109451 · Cited by 18
A comparative atlas of single-cell chromatin accessibility in the human brainPreprint
Li, Y. E., Preißl, S., Miller, M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.09.515833 · Cited by 17
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Spatially Exploring RNA Biology in Archival Formalin-Fixed Paraffin-Embedded TissuesPreprint
Bai, Z., Zhang, D., Gao, Y. P., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.06.579143 · Cited by 17
Neural xenografts contribute to long-term recovery in stroke via molecular graft-host crosstalkPreprint
Weber, R., Buil, B. A., Rentsch, N. H., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.03.588020 · Cited by 17
Inhibitory and disinhibitory VIP IN-mediated circuits in neocortexPreprint
Dellal, S. S., Zurita, H., Kruglikov, I., Valero, M., Abad-Perez, P., Geron, E., Meng, J. H., Prönneke, A., Hanson, J. L., Mir, E., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.26.640383 · Cited by 24
Exploring the influence of age and diet on gut microbiota development in children during the first 5 years: a study from Yaoundé, Cameroon
Adjele, J. J. B., Devi, P., Kumari, P., Yadav, A., Tchuenchieu, A. K., Mouafo, H. T., Medoua, G. N., Essia, J. J. N., Chauhan, N. S., & Pandey, R. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1512111 · Cited by 17
A spatial single-cell atlas of the claustro-insular region uncovers key regulators of neuronal identity and excitability
Fodoulian, L., Boillat, M., Moulinier, M., Carleton, A., & Rodríguez, I. (2025) · Nature Communications · doi:10.1038/s41467-025-63138-2 · Cited by 17
Cell type-specific mechanisms of information transfer in data-driven biophysical models of hippocampal CA3 principal neurons
Linaro, D., Levy, M. J., & Hunt, D. L. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010071 · Cited by 22
Convergent cerebrospinal fluid proteomes and metabolic ontologies in humans and animal models of Rett syndrome
Zlatic, S. A., Duong, D. M., Gadalla, K. K. E., Murage, B., Ping, L., Shah, R., Fink, J. J., Khwaja, O., Swanson, L. C., Şahin, M., et al. (2022) · iScience · doi:10.1016/j.isci.2022.104966 · Cited by 17
Recent advances in deciphering hippocampus complexity using single-cell transcriptomics
Chang, C., Zuo, H., & Li, Y. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106062 · Cited by 16
scTOP: physics-inspired order parameters for cellular identification and visualization
Yampolskaya, M., Herriges, M. J., Ikonomou, L., Kotton, D. N., & Mehta, P. (2023) · Development · doi:10.1242/dev.201873 · Cited by 15
Protocol for Xenium spatial transcriptomics studies using fixed frozen mouse brain sections
Ma, X., Chen, P., Wei, J., Zhang, Y., Chen, C.-E., Zhao, H., Ferguson, D., McGee, A. W., Dai, Z., & Qiu, S. (2024) · STAR Protocols · doi:10.1016/j.xpro.2024.103420 · Cited by 16
Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex
Johansen, N., Kempynck, N., Zemke, N. R., Somasundaram, S., Winter, S. D., Hooper, M. J., Dwivedi, D., Lohia, R., Wehbe, F., Li, B., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100879 · Cited by 22
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PsiNorm: a scalable normalization for single-cell RNA-seq data
Borella, M., Martello, G., Risso, D., & Romualdi, C. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab641 · Cited by 19
An independent regulator of global release pathways in astrocytes generates a subtype of extracellular vesicles required for postsynaptic function
Levy-Myers, R., Daudelin, D., Na, C. H., & Sockanathan, S. (2023) · Science Advances · doi:10.1126/sciadv.adg2067 · Cited by 15
Connectivity of single neurons classifies cell subtypes in mouse brains
Liu, L., Yun, Z., Manubens-Gil, L., Chen, H., Xiong, F., Dong, H., Zeng, H., Hawrylycz, M., Ascoli, G. A., & Peng, H. (2025) · Nature Methods · doi:10.1038/s41592-025-02621-6 · Cited by 24
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A time window for memory consolidation during NREM sleep revealed by cAMP oscillation
Deng, Z., Fei, X., Zhang, S., & Xu, M. (2025) · Neuron · doi:10.1016/j.neuron.2025.03.020 · Cited by 19
MeCP2 and non-CG DNA methylation stabilize the expression of long genes that distinguish closely related neuron types
Moore, J. R., Nemera, M. T., D’Souza, R. D., Hamagami, N., Clemens, A. W., Beard, D. C., Urman, A., Razia, Y., Mendoza, V. R., Law, T. E., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01947-w · Cited by 21
Charting the spatial transcriptome of the human cerebral cortex at single-cell resolution
Wei, S., Luo, M., Wang, P., Chen, R., Jin, X., Xu, C., Li, C., Lin, X., Xu, Z., Liu, H., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62793-9 · Cited by 20
Cell-type specific molecular architecture for mu opioid receptor function in pain and addiction circuits
Ochandarena, N. E., Niehaus, J. K., Tassou, A., & Scherrer, G. (2023) · Neuropharmacology · doi:10.1016/j.neuropharm.2023.109597 · Cited by 20
Cell-type-specific cis-regulatory divergence in gene expression and chromatin accessibility revealed by human-chimpanzee hybrid cells
Wang, B., Starr, A. L., & Fraser, H. B. (2023) · eLife · doi:10.7554/elife.89594 · Cited by 30
The alpha2 nicotinic acetylcholine receptor, a subunit with unique and selective expression in inhibitory interneurons associated with principal cells
Hilscher, M. M., Mikulovic, S., Perry, S. E., Lundberg, S., & Kullander, K. (2023) · Pharmacological Research · doi:10.1016/j.phrs.2023.106895 · Cited by 15
Contribution of Oligodendrocytes, Microglia, and Astrocytes to Myelin Debris Uptake in an Explant Model of Inflammatory Demyelination in Rats
Cammarota, M., & Boscia, F. (2023) · Cells · doi:10.3390/cells12172203 · Cited by 17
Targeted blockade of aberrant sodium current in a stem cell-derived neuron model of SCN3A encephalopathy
Qu, G., Merchant, J. P., Clatot, J., DeFlitch, L., Frederick, D. J., Tang, S., Salvatore, M., Zhang, X., Li, J., Anderson, S. A., et al. (2023) · Brain · doi:10.1093/brain/awad376 · Cited by 15
Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections
Liu, S., Gao, L., Chen, J., & Yan, J. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113590 · Cited by 15
A brief history of somatostatin interneuron taxonomy or: how many somatostatin subtypes are there, really?
Agmon, A., & Barth, A. L. (2024) · Frontiers in Neural Circuits · doi:10.3389/fncir.2024.1436915 · Cited by 13
Loss of TREM2 diminishes CAA despite an overall increase of amyloid load in Tg‐SwDI mice
Zhong, R., Xu, Y., Williams, J. W., & Li, L. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14222 · Cited by 16
Sex-specific single cell-level transcriptomic signatures of Rett syndrome disease progression
Sharifi, O., Haghani, V., Neier, K. E., Fraga, K. J., Korf, I. F., Hakam, S. M., Quon, G., Johansen, N., Yasui, D. H., & LaSalle, J. M. (2024) · Communications Biology · doi:10.1038/s42003-024-06990-0 · Cited by 17
Sex-specific GABAergic microcircuits that switch vulnerability into resilience to stress and reverse the effects of chronic stress exposure
Jiang, T., Feng, M., Hutsell, A., & Lüscher, B. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02835-8 · Cited by 14
Gene expression changes in the brain of a Cushing's syndrome mouse model
Amaya, J. M., Viho, E. M. G., Sips, H. C. M., Lalai, R. A., Sahut‐Barnola, I., Dumontet, T., Montanier, N., Pereira, A. M., Martinez, A., & Meijer, O. C. (2022) · Journal of Neuroendocrinology · doi:10.1111/jne.13125 · Cited by 14
Cell type matching in single-cell RNA-sequencing data using FR-Match
Zhang, Y., Aevermann, B. D., Gala, R., & Scheuermann, R. H. (2022) · Scientific Reports · doi:10.1038/s41598-022-14192-z · Cited by 9
Transcriptomic cytoarchitecture reveals principles of human neocortex organizationPreprint
Jorstad, N. L., Close, J., Johansen, N., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.06.515349 · Cited by 15
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Pyramidal neurons proportionately alter the identity and survival of specific cortical interneuron subtypesPreprint
Wu, S. J., Dai, M., Yang, S.-P., McCann, C., Qiu, Y., Kumar, V., Marrero, G. J., Tsyporin, J., Huang, S., Shin, D., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.20.604399 · Cited by 17
A single-nucleus transcriptomic atlas of medium spiny neurons in the rat nucleus accumbens
Reiner, B. C., Chehimi, S. N., Merkel, R., Toikumo, S., Berrettini, W. H., Kranzler, H. R., Sanchez‐Roige, S., Kember, R. L., Schmidt, H. D., & Crist, R. C. (2024) · Scientific Reports · doi:10.1038/s41598-024-69255-0 · Cited by 14
Molecular Signatures in Cortical Development
Steyert, M. R., Li, T., Piao, X., & Nowakowski, T. J. (2025) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-091823-014001 · Cited by 15
Neural xenografts contribute to long-term recovery in stroke via molecular graft-host crosstalk
Weber, R., Buil, B. A., Rentsch, N. H., Perron, P., Halliday, S., Bosworth, A., Zhang, M., Kisler, K., Bodenmann, C., Zürcher, K. J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63725-3 · Cited by 32
STAB2: an updated spatio-temporal cell atlas of the human and mouse brain
Yang, Y., Gan, Z., Zhang, J., Zhao, X., Yang, Y., Han, S., Wu, W., & Zhao, X. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad955 · Cited by 15
ZEBRA: a hierarchically integrated gene expression atlas of the murine and human brain at single-cell resolution
Flotho, M., Amand, J., Hirsch, P., Grandke, F., Wyss‐Coray, T., Keller, A., & Kern, F. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad990 · Cited by 18
Differential usage of DNA modifications in neurons, astrocytes, and microglia
Tooley, K. B., Chucair‐Elliott, A. J., Ocañas, S. R., Machalinski, A. H., Pham, K. D., Hoolehan, W., Kulpa, A. M., Stanford, D. R., & Freeman, W. M. (2023) · Epigenetics & Chromatin · doi:10.1186/s13072-023-00522-6 · Cited by 13
Spatial transcriptomic brain imaging reveals the effects of immunomodulation therapy on specific regional brain cells in a mouse dementia model
Lee, E. J., Bae, S., Suh, M., Choi, Y., Choi, Y., Hwang, D. W., & Lee, D. S. (2024) · BMC Genomics · doi:10.1186/s12864-024-10434-8 · Cited by 15
A global transcriptional atlas of the effect of acute sleep deprivation in the mouse frontal cortex
Ford, K., Zuin, E., Righelli, D., Medina, E., Schoch, H., Singletary, K. G., Muheim, C., Frank, M. G., Hicks, S. C., Risso, D., et al. (2024) · iScience · doi:10.1016/j.isci.2024.110752 · Cited by 16
Interaction of methyl-CpG-binding protein 2 (MeCP2) with distinct enhancers in the mouse cortex
Mishra, G. P., Sun, E. X., Chin, T., Eckhardt, M., Greenberg, M. E., & Stroud, H. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01808-y · Cited by 15
Atypical hippocampal excitatory neurons express and govern object memory
Kinman, A. I., Merryweather, D. N., Erwin, S. R., Campbell, R. E., Sullivan, K. E., Kraus, L., Kapustina, M., Bristow, B. N., Zhang, M. Y., Elder, M. W., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56260-8 · Cited by 18
Orderly specification and precise laminar deployment of cortical glutamatergic projection neuron types through intermediate progenitors
Huilgol, D., Levine, J. M., Galbavy, W., Wang, B., & Huang, Z. J. (2024) · Developmental Cell · doi:10.1016/j.devcel.2025.02.009 · Cited by 17
Transcriptomic evidence for dense peptidergic networks within forebrains of four widely divergent tetrapods
Smith, S. J. (2021) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2021.09.011 · Cited by 12
Cortical control of chandelier cells in neural codes
Jung, K., Choi, Y., & Kwon, H. (2022) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2022.992409 · Cited by 10
Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing
Xing, Y., Zan, C., & Liu, L. (2023) · Frontiers in Neural Circuits · doi:10.3389/fncir.2023.1007755 · Cited by 14
Loss or gain of function? Effects of ion channel mutations on neuronal firing depend on the neuron type
Koch, N. A., Sonnenberg, L., Hedrich, U. B. S., Lauxmann, S., & Benda, J. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1194811 · Cited by 13
Single-cell long-read mRNA isoform regulation is pervasive across mammalian brain regions, cell types, and developmentPreprint
Joglekar, A., Hu, W., Zhang, B., Narykov, O., Diekhans, M., Balacco, J., Ndhlovu, L. C., Milner, T. A., Fedrigo, O. D., Jarvis, E. D., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.02.535281 · Cited by 13
An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampusPreprint
Thompson, J. R., Nelson, E. D., Tippani, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.26.590643 · Cited by 14
Long-term intermittent theta burst stimulation enhanced hippocampus-dependent memory by regulating hippocampal theta oscillation and neurotransmitter levels in healthy rats
Xiang, W., Liu, J., Hui, Y., Wu, Z., Wang, L., Wang, Y., Bai, Y., Li, J., Zhang, L., Xi, Y., et al. (2023) · Neurochemistry International · doi:10.1016/j.neuint.2023.105671 · Cited by 13
Transcriptomic and spatial GABAergic neuron subtypes in zona incerta mediate distinct innate behaviors
Zhu, M., Peng, J., Wang, M., Lin, S., Zhang, H., Zhou, Y., Dai, X., Zhao, H., Yu, Y., Shen, L., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-57896-2 · Cited by 17
Inhibiting 15-PGDH blocks blood–brain barrier deterioration and protects mice from Alzheimer’s disease and traumatic brain injury
Koh, Y., Vázquez‐Rosa, E., Gao, F., Li, H., Chakraborty, S., Tripathi, S. J., Barker, S., Bud, Z., Bangalore, A., Kandjoze, U. P., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2417224122 · Cited by 17
Noncanonical circuits, states, and computations of the hippocampus
Farrell, J. S., & Soltész, I. (2025) · Science · doi:10.1126/science.adv4420 · Cited by 14
A Molecular Landscape of Mouse Hippocampal Neuromodulation
Smith, S. J., & von Zastrow, M. (2022) · Frontiers in Neural Circuits · doi:10.3389/fncir.2022.836930 · Cited by 13
Generation of single-cell and single-nuclei suspensions from embryonic and adult mouse brains
Lee, D. R., Zhang, Y., Rhodes, C. T., & Petros, T. J. (2022) · STAR Protocols · doi:10.1016/j.xpro.2022.101944 · Cited by 11
sc BrainMap: a landscape for cell types and associated genetic markers in the brain
Chi, Y., Qi, R., Zhou, Y., Tong, H., Jin, H., Turck, C. W., Chen, W., & Wang, G. (2023) · Database · doi:10.1093/database/baad035 · Cited by 12
The evolving definition of plant cell type
Amini, S., Doyle, J. J., & Libault, M. (2023) · Frontiers in Plant Science · doi:10.3389/fpls.2023.1271070 · Cited by 13
Transcriptional maintenance of cortical somatostatin interneuron subtype identity during migration
Munguba, H., Nikouei, K., Hochgerner, H., Oberst, P., Kouznetsova, A., Ryge, J., Muñoz‐Manchado, A. B., Close, J., Batista‐Brito, R., Linnarsson, S., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.07.018 · Cited by 20
SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis
Gonzalez-Ferrer, J., Lehrer, J., O’Farrell, A., Paten, B., Teodorescu, M., Haussler, D. H., Jönsson, V. D., & Mostajo-Radji, M. A. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100581 · Cited by 16
Detection of allele-specific expression in spatial transcriptomics with spASE
Zou, L. S., Cable, D. M., Barrera, I., Zhao, T., Murray, E. M., Aryee, M. J., Chen, F., & Irizarry, R. A. (2024) · Genome biology · doi:10.1186/s13059-024-03317-4 · Cited by 10
Sex-biasing influence of autism-associated Ube3a gene overdosage at connectomic, behavioral, and transcriptomic levels
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Authors: Yao, Z., van Velthoven, C. T. J., Nguyen, T. N., Goldy, J., Sedeno-Cortes, A. E., Baftizadeh, F., Bertagnolli, D., Casper, T., Chiang, M., Crichton, K., Ding, S.-L., Fong, O., Garren, E., Glandon, A., Gouwens, N. W., Gray, J., Graybuck, L. T., Hawrylycz, M. J., Hirschstein, D., Kroll, M., Lathia, K., Lee, C., Levi, B., McMillen, D., Mok, S., Pham, T., Ren, Q., Rimorin, C., Shapovalova, N., Sulc, J., Sunkin, S. M., Tieu, M., Torkelson, A., Tung, H., Ward, K., Dee, N., Smith, K. A., Tasic, B., & Zeng, H.
Affiliations: Allen Institute for Brain Science (US)
Corresponding author: Zeng, Hongkui
ORCID: Yao, Zizhen
Nguyen, Thuc Nghi
Goldy, Jeff
Baftizadeh, Fahimeh
Bertagnolli, Darren
Casper, Tamara
Chiang, Megan
Crichton, Kirsten
Ding, Song-Lin
Fong, Olivia
Glandon, Alexandra
Gouwens, Nathan W.
Graybuck, Lucas T.
Hawrylycz, Michael J.
Hirschstein, Daniel
Kroll, Matthew
Lathia, Kanan
Lee, Changkyu
Levi, Boaz
McMillen, Delissa
Mok, Stephanie
Ren, Qingzhong
Rimorin, Christine
Shapovalova, Nadiya
Sunkin, Susan M.
Tieu, Michael
Torkelson, Amy
Tung, Herman
Ward, Katelyn
Dee, Nick
Smith, Kimberly A.
Tasic, Bosiljka
Zeng, Hongkui
Venue: Cell
Publisher: Elsevier BV
Published: 2021-06
Volume: 184
Issue: 12
Pages: 3222-3241.e26
ISSN: 0092-8674 (ISSN-L)
DOI: 10.1016/j.cell.2021.04.021
PMC: PMC8195859
OpenAlex: W3162218953
Semantic Scholar: c60f04ef990c1f8b8d4c22e7ace44a70cc4bca3f
Cited by: 1,065
References: 85
Citations by year: 2026: 189 · 2025: 223 · 2024: 243 · 2023: 186 · 2022: 122 · 2021: 83
FWCI: 50.70
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 374 d)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: Cell (publishedVersion)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
SSRN Electronic Journal (acceptedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords: neocortex, hippocampal formation, glutamatergic neurons, GABAergic neurons, neuronal cell types, subiculum, mouse brain, single-cell transcriptomics
MeSH terms: Animals, Hippocampus, Mice, Inbred C57BL, Mice, Transgenic, Glutamic Acid, Neocortex, Mice, GABAergic Neurons, Transcriptome

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A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation

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