Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons
Open accessAbstract
Single-cell RNA sequencing (RNA-Seq) provides rich information about cell types and states. However, it is difficult to capture rare dynamic processes, such as adult neurogenesis, because isolation of rare neurons from adult tissue is challenging and markers for each phase are limited. Here, we develop Div-Seq, which combines scalable single-nucleus RNA-Seq (sNuc-Seq) with pulse labeling of proliferating cells by 5-ethynyl-2'-deoxyuridine (EdU) to profile individual dividing cells. sNuc-Seq and Div-Seq can sensitively identify closely related hippocampal cell types and track transcriptional dynamics of newborn neurons within the adult hippocampal neurogenic niche, respectively. We also apply Div-Seq to identify and profile rare newborn neurons in the adult spinal cord, a noncanonical neurogenic region. sNuc-Seq and Div-Seq open the way for unbiased analysis of diverse complex tissues.
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Recent advances in single-nucleus RNA sequencing (snRNA-Seq) have extended transcriptomic analysis to frozen or archived post-mortem brain tissues.
“Recent advances in single-nucleus RNA sequencing (snRNA-Seq) have extended transcriptomic analysis to frozen or archived post-mortem brain tissues.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [165]
The paper’s main text (indexed under Abstract; page unavailable) says sNuc-Seq is compatible with frozen or fixed tissue and reports transcriptomic analysis of adult mouse hippocampal nuclei. It does not establish its use on archived post-mortem brain tissue, so that part of the claim is unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measuredsnRNA-Seq has enabled detailed profiling of vulnerable neuronal subtypes and glial populations.
“This technique has enabled detailed profiling of vulnerable neuronal subtypes and glial populations.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [165]
The paper’s Abstract reports detailed profiling of closely related hippocampal neuronal types and rare newborn GABAergic neurons, and identifies oligodendrocyte precursor cells among newborn spinal-cord cells. It does not characterize those neurons as vulnerable or establish detailed profiling of glial populations more broadly. (LLM, conf=0.84)
Experimental — accuracy not yet measuredBy isolating nuclei rather than whole cells, snRNA-Seq retains transcriptional fidelity while avoiding cell dissociation artifacts.
“By isolating nuclei rather than whole cells, snRNA-Seq retains transcriptional fidelity while avoiding cell dissociation artifacts155,165.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [165]
Existing snRNA-seq methods use FACS sorting into plates or C1 microfluidics, which are not scalable to tens of thousands of nuclei or many samples.
“However, these methods either rely on sorting nuclei by FACS into plates (96 or 384 wells)3,5 or on C1 microfluidics4, neither of which are scalable, precluding profiling tens of thousands of nuclei”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
DroNc-seq GABAergic sub-clusters matched nearly one-to-one with sNuc-Seq hippocampus sub-clusters and satisfactorily with fine-resolution visual cortex scRNA-seq sub-clusters.
“the DroNc-seq sub-clusters matched with a nearly one-to-one mapping to sub-clusters defined by sNuc-Seq3 on the hippocampus, and with a satisfactory match to sets of fine-resolution sub-clusters defined by scRNA-seq of a distinct brain region, the visual cortex17”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
Human GABAergic sub-clusters showed good congruence with previously defined clusters in mouse hippocampus, mouse visual cortex, and human cortex, including the same canonical marker assignments.
“we found good congruence between our GABAergic sub-clusters and those previously defined3,4,17 in mouse and human”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
The higher intronic read fraction in nuclei reflects enrichment of nascent transcripts in the nucleus.
“reflecting the enrichment of nascent transcripts in the nucleus3,13–16”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
Cell types and signatures from DroNc-seq were comparable to those from sNuc-Seq of mouse hippocampus and scRNA-seq of visual cortex.
“the cell types and their signatures from DroNc-seq are comparable to those obtained previously with sNuc-Seq of mouse hippocampus3 and scRNA-seq of the visual cortex17”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
Human cell-type gene signatures agreed well with previously defined signatures in mouse hippocampus and cortex.
“The cell-type specific gene signatures we determined for each human cell-type cluster (Fig. 2d, Supplementary Table 8) agreed well with previously defined signatures in mouse hippocampus3 and cortex17”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
Single-nucleus RNA-seq was developed to analyze RNA in nuclei from fresh, frozen, or lightly fixed tissues.
“To address this challenge, we3 and others4–6 developed single nucleus RNA-seq (snRNA-seq) for analysis of RNA in single nuclei from fresh, frozen or lightly fixed tissues.”
From Massively parallel single-nucleus RNA-seq with DroNc-seq (2017) · cites this paper as [3]
Differentiation trajectories of newborn neurons and oligodendrocytes in adults can also be reconstructed.
“Differentiation trajectories of newborn neurons and oligodendrocytes in adults can also be reconstructed (Habib et al., 2016; Marques et al., 2016).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Habib et al., 2016
Continuous trajectories appear in brain development and in adult differentiating populations, including oligodendrocyte lineage cells and newborn dentate gyrus granule cells.
“Continuous trajectories occur during brain development (Nowakowski et al., 2017) and in differentiating cell populations in the adult, such as oligodendrocyte lineage cells (Marques et al., 2016) or newborn granule cells in the dentate gyrus of the hippocampus (Habib et al., 2016).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Habib et al., 2016
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“Single-cell approaches allow us to study cell-to-cell heterogeneity (Habib et al., 2017).”
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- Authors
- Habib, N., Li, Y., Heidenreich, M., Swiech, L., Avraham-Davidi, I., Trombetta, J. J., Hession, C., Zhang, F., & Regev, A.
- Affiliations
- Broad Institute (US)
- Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA.
- Corresponding author
- Habib, Naomi
- Li, Yinqing
- Zhang, Feng
- Regev, Aviv
- Venue
- Science
- Published
- 2016-08-26
- Volume
- 353
- Issue
- 6302
- Pages
- 925-928
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC5480621
- OpenAlex
- W2486882743
- Cited by
- 601
- References
- 63
- Citations by year
- 2026: 30 · 2025: 51 · 2024: 71 · 2023: 59 · 2022: 63 · 2021: 75 · 2020: 67 · 2019: 58 · 2018: 73 · 2017: 46 · 2016: 7
- FWCI
- 31.89
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Funders
- Howard Hughes Medical Institute
- Helen Hay Whitney Foundation
- Human Frontier Science Program
- Klarman Cell Observatory at the Broad Institute
- National Institute of Mental Health (U01MH105960)
- NIMH (5DP1-MH100706, 1R01-MH110049)
- NSF
- New York Stem Cell
- Simons
- Paul G. Allen Family
- Vallee Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- single-nucleus RNA sequencing, adult neurogenesis, newborn neurons, cell proliferation, transcriptional dynamics, rare cell types
- MeSH terms
- Animals, Cell Division, Cell Nucleus, Deoxyuridine, Hippocampus, Isotope Labeling, Neurons, Spinal Cord, Transcription, Genetic, Sequence Analysis, RNA, Mice, Neurogenesis, Single-Cell Analysis, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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