51
|
Michielsen L, Reinders MJT, Mahfouz A. Predicting cell population-specific gene expression from genomic sequence. FRONTIERS IN BIOINFORMATICS 2024; 4:1347276. [PMID: 38501113 PMCID: PMC10944912 DOI: 10.3389/fbinf.2024.1347276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/23/2024] [Indexed: 03/20/2024] Open
Abstract
Most regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some computational models tackle this problem by predicting gene expression directly from the genomic sequence. These models are currently limited to predicting bulk measurements and mainly make tissue-specific predictions. Here, we present a model that leverages single-cell RNA-sequencing data to predict gene expression. We show that cell population-specific models outperform tissue-specific models, especially when the expression profile of a cell population and the corresponding tissue are dissimilar. Further, we show that our model can prioritize GWAS variants and learn motifs of transcription factor binding sites. We envision that our model can be useful for delineating cell population-specific regulatory elements.
Collapse
Affiliation(s)
- Lieke Michielsen
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Marcel J. T. Reinders
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Ahmed Mahfouz
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| |
Collapse
|
52
|
Wen X, Luo Z, Zhao W, Calandrelli R, Nguyen TC, Wan X, Richard JLC, Zhong S. Single-cell multiplex chromatin and RNA interactions in aging human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.28.546457. [PMID: 37425846 PMCID: PMC10326989 DOI: 10.1101/2023.06.28.546457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA (caRNA) 1-3. Chromatin complex compositions change during cellular differentiation and aging, and are expected to be highly heterogeneous among terminally differentiated single cells 4-7. Here we introduce the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei. Applied to 14 human frontal cortex samples from elderly donors, MUSIC delineates diverse cortical cell types and states. We observed the nuclei exhibiting fewer short-range chromatin interactions are correlated with an "older" transcriptomic signature and with Alzheimer's pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter tends to be the cell type where these cis eQTLs specifically affect their target gene's expression. Additionally, the female cortical cells exhibit highly heterogeneous interactions between the XIST non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.
Collapse
Affiliation(s)
- Xingzhao Wen
- Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA 92093, USA
| | - Zhifei Luo
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Wenxin Zhao
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Riccardo Calandrelli
- Institute of Engineering in Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Tri C. Nguyen
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Xueyi Wan
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | | | - Sheng Zhong
- Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA 92093, USA
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
- Institute of Engineering in Medicine, University of California San Diego, La Jolla, CA 92093, USA
| |
Collapse
|
53
|
Wainberg M, Forde NJ, Mansour S, Kerrebijn I, Medland SE, Hawco C, Tripathy SJ. Genetic architecture of the structural connectome. Nat Commun 2024; 15:1962. [PMID: 38438384 PMCID: PMC10912129 DOI: 10.1038/s41467-024-46023-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/12/2024] [Indexed: 03/06/2024] Open
Abstract
Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.
Collapse
Affiliation(s)
- Michael Wainberg
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
| | - Natalie J Forde
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Salim Mansour
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Isabel Kerrebijn
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Colin Hawco
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | - Shreejoy J Tripathy
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
- Department of Physiology, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
54
|
Khodosevich K, Dragicevic K, Howes O. Drug targeting in psychiatric disorders - how to overcome the loss in translation? Nat Rev Drug Discov 2024; 23:218-231. [PMID: 38114612 DOI: 10.1038/s41573-023-00847-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 12/21/2023]
Abstract
In spite of major efforts and investment in development of psychiatric drugs, many clinical trials have failed in recent decades, and clinicians still prescribe drugs that were discovered many years ago. Although multiple reasons have been discussed for the drug development deadlock, we focus here on one of the major possible biological reasons: differences between the characteristics of drug targets in preclinical models and the corresponding targets in patients. Importantly, based on technological advances in single-cell analysis, we propose here a framework for the use of available and newly emerging knowledge from single-cell and spatial omics studies to evaluate and potentially improve the translational predictivity of preclinical models before commencing preclinical and, in particular, clinical studies. We believe that these recommendations will improve preclinical models and the ability to assess drugs in clinical trials, reducing failure rates in expensive late-stage trials and ultimately benefitting psychiatric drug discovery and development.
Collapse
Affiliation(s)
- Konstantin Khodosevich
- Biotech Research and Innovation Centre, Faculty of Health, University of Copenhagen, Copenhagen, Denmark.
| | - Katarina Dragicevic
- Biotech Research and Innovation Centre, Faculty of Health, University of Copenhagen, Copenhagen, Denmark
| | - Oliver Howes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| |
Collapse
|
55
|
Ling E, Nemesh J, Goldman M, Kamitaki N, Reed N, Handsaker RE, Genovese G, Vogelgsang JS, Gerges S, Kashin S, Ghosh S, Esposito JM, Morris K, Meyer D, Lutservitz A, Mullally CD, Wysoker A, Spina L, Neumann A, Hogan M, Ichihara K, Berretta S, McCarroll SA. A concerted neuron-astrocyte program declines in ageing and schizophrenia. Nature 2024; 627:604-611. [PMID: 38448582 PMCID: PMC10954558 DOI: 10.1038/s41586-024-07109-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/23/2024] [Indexed: 03/08/2024]
Abstract
Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.
Collapse
Affiliation(s)
- Emi Ling
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
| | - James Nemesh
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Melissa Goldman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Nolan Kamitaki
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Nora Reed
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Robert E Handsaker
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Jonathan S Vogelgsang
- McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Sherif Gerges
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Seva Kashin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Sulagna Ghosh
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | | | | | - Daniel Meyer
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Alyssa Lutservitz
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Christopher D Mullally
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Alec Wysoker
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Liv Spina
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Anna Neumann
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Marina Hogan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Kiku Ichihara
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Sabina Berretta
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
- Program in Neuroscience, Harvard Medical School, Boston, MA, USA.
| | - Steven A McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
56
|
Parks TV, Szczupak D, Choi SH, Schaeffer DJ. Noninvasive focal transgene delivery with viral neuronal tracers in the marmoset monkey. CELL REPORTS METHODS 2024; 4:100709. [PMID: 38359822 PMCID: PMC10921014 DOI: 10.1016/j.crmeth.2024.100709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/14/2023] [Accepted: 01/23/2024] [Indexed: 02/17/2024]
Abstract
We establish a reliable method for selectively delivering adeno-associated viral vectors (AAVs) across the blood-brain barrier (BBB) in the marmoset without the need for neurosurgical injection. We focally perturbed the BBB (∼1 × 2 mm) in area 8aD of the frontal cortex in four adult marmoset monkeys using low-intensity transcranial focused ultrasound aided by microbubbles. Within an hour of opening the BBB, either AAV2 or AAV9 was delivered systemically via tail-vein injection. In all four marmosets, fluorescence-encoded neurons were observed at the site of BBB perturbation, with AAV2 showing a sparse distribution of transduced neurons when compared to AAV9. The results are compared to direct intracortical injections of anterograde tracers into area 8aD and similar (albeit sparser) long-range connectivity was observed. With evidence of transduced neurons specific to the region of BBB opening as well as long-distance tracing, we establish a framework for focal noninvasive transgene delivery to the marmoset brain.
Collapse
Affiliation(s)
- T Vincenza Parks
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Diego Szczupak
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sang-Ho Choi
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.
| |
Collapse
|
57
|
Harkany T, Tretiakov E, Varela L, Jarc J, Rebernik P, Newbold S, Keimpema E, Verkhratsky A, Horvath T, Romanov R. Molecularly stratified hypothalamic astrocytes are cellular foci for obesity. RESEARCH SQUARE 2024:rs.3.rs-3748581. [PMID: 38405925 PMCID: PMC10889077 DOI: 10.21203/rs.3.rs-3748581/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Astrocytes safeguard the homeostasis of the central nervous system1,2. Despite their prominent morphological plasticity under conditions that challenge the brain's adaptive capacity3-5, the classification of astrocytes, and relating their molecular make-up to spatially devolved neuronal operations that specify behavior or metabolism, remained mostly futile6,7. Although it seems unexpected in the era of single-cell biology, the lack of a major advance in stratifying astrocytes under physiological conditions rests on the incompatibility of 'neurocentric' algorithms that rely on stable developmental endpoints, lifelong transcriptional, neurotransmitter, and neuropeptide signatures for classification6-8 with the dynamic functional states, anatomic allocation, and allostatic plasticity of astrocytes1. Simplistically, therefore, astrocytes are still grouped as 'resting' vs. 'reactive', the latter referring to pathological states marked by various inducible genes3,9,10. Here, we introduced a machine learning-based feature recognition algorithm that benefits from the cumulative power of published single-cell RNA-seq data on astrocytes as a reference map to stepwise eliminate pleiotropic and inducible cellular features. For the healthy hypothalamus, this walk-back approach revealed gene regulatory networks (GRNs) that specified subsets of astrocytes, and could be used as landmarking tools for their anatomical assignment. The core molecular censuses retained by astrocyte subsets were sufficient to stratify them by allostatic competence, chiefly their signaling and metabolic interplay with neurons. Particularly, we found differentially expressed mitochondrial genes in insulin-sensing astrocytes and demonstrated their reciprocal signaling with neurons that work antagonistically within the food intake circuitry. As a proof-of-concept, we showed that disrupting Mfn2 expression in astrocytes reduced their ability to support dynamic circuit reorganization, a time-locked feature of satiety in the hypothalamus, thus leading to obesity in mice. Overall, our results suggest that astrocytes in the healthy brain are fundamentally more heterogeneous than previously thought and topologically mirror the specificity of local neurocircuits.
Collapse
Affiliation(s)
- Tibor Harkany
- Center for Brain Research, Medical University of Vienna
| | | | | | - Jasna Jarc
- Center for Brain Research, Medical University of Vienna
| | | | | | - Erik Keimpema
- Medical University of Vienna, Center for Brain Research
| | | | | | | |
Collapse
|
58
|
Rybnicek J, Chen Y, Milic M, Tio ES, McLaurin J, Hohman TJ, De Jager PL, Schneider JA, Wang Y, Bennett DA, Tripathy S, Felsky D, Lambe EK. CHRNA5 links chandelier cells to severity of amyloid pathology in aging and Alzheimer's disease. Transl Psychiatry 2024; 14:83. [PMID: 38331937 PMCID: PMC10853183 DOI: 10.1038/s41398-024-02785-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/09/2024] [Accepted: 01/16/2024] [Indexed: 02/10/2024] Open
Abstract
Changes in high-affinity nicotinic acetylcholine receptors are intricately connected to neuropathology in Alzheimer's Disease (AD). Protective and cognitive-enhancing roles for the nicotinic α5 subunit have been identified, but this gene has not been closely examined in the context of human aging and dementia. Therefore, we investigate the nicotinic α5 gene CHRNA5 and the impact of relevant single nucleotide polymorphisms (SNPs) in prefrontal cortex from 922 individuals with matched genotypic and post-mortem RNA sequencing in the Religious Orders Study and Memory and Aging Project (ROS/MAP). We find that a genotype robustly linked to increased expression of CHRNA5 (rs1979905A2) predicts significantly reduced cortical β-amyloid load. Intriguingly, co-expression analysis suggests CHRNA5 has a distinct cellular expression profile compared to other nicotinic receptor genes. Consistent with this prediction, single nucleus RNA sequencing from 22 individuals reveals CHRNA5 expression is disproportionately elevated in chandelier neurons, a distinct subtype of inhibitory neuron known for its role in excitatory/inhibitory (E/I) balance. We show that chandelier neurons are enriched in amyloid-binding proteins compared to basket cells, the other major subtype of PVALB-positive interneurons. Consistent with the hypothesis that nicotinic receptors in chandelier cells normally protect against β-amyloid, cell-type proportion analysis from 549 individuals reveals these neurons show amyloid-associated vulnerability only in individuals with impaired function/trafficking of nicotinic α5-containing receptors due to homozygosity of the missense CHRNA5 SNP (rs16969968A2). Taken together, these findings suggest that CHRNA5 and its nicotinic α5 subunit exert a neuroprotective role in aging and Alzheimer's disease centered on chandelier interneurons.
Collapse
Affiliation(s)
- Jonas Rybnicek
- Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Yuxiao Chen
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Milos Milic
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Earvin S Tio
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - JoAnne McLaurin
- Biological Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Timothy J Hohman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Julie A Schneider
- Department of Pathology, Rush University, Chicago, IL, USA
- Department of Neurological Sciences, Rush University, Chicago, IL, USA
| | - Yanling Wang
- Department of Neurological Sciences, Rush University, Chicago, IL, USA
| | - David A Bennett
- Department of Neurological Sciences, Rush University, Chicago, IL, USA
| | - Shreejoy Tripathy
- Department of Physiology, University of Toronto, Toronto, ON, Canada.
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| | - Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| | - Evelyn K Lambe
- Department of Physiology, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Department of OBGYN, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
59
|
Hong 洪卉 H, Moore LA, Apostolides PF, Trussell LO. Calcium-Sensitive Subthreshold Oscillations and Electrical Coupling in Principal Cells of Mouse Dorsal Cochlear Nucleus. J Neurosci 2024; 44:e0106202023. [PMID: 37968120 PMCID: PMC10860609 DOI: 10.1523/jneurosci.0106-20.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 11/02/2023] [Accepted: 11/08/2023] [Indexed: 11/17/2023] Open
Abstract
In higher sensory brain regions, slow oscillations (0.5-5 Hz) associated with quiet wakefulness and attention modulate multisensory integration, predictive coding, and perception. Although often assumed to originate via thalamocortical mechanisms, the extent to which subcortical sensory pathways are independently capable of slow oscillatory activity is unclear. We find that in the first station for auditory processing, the cochlear nucleus, fusiform cells from juvenile mice (of either sex) generate robust 1-2 Hz oscillations in membrane potential and exhibit electrical resonance. Such oscillations were absent prior to the onset of hearing, intrinsically generated by hyperpolarization-activated cyclic nucleotide-gated (HCN) and persistent Na+ conductances (NaP) interacting with passive membrane properties, and reflected the intrinsic resonance properties of fusiform cells. Cx36-containing gap junctions facilitated oscillation strength and promoted pairwise synchrony of oscillations between neighboring neurons. The strength of oscillations were strikingly sensitive to external Ca2+, disappearing at concentrations >1.7 mM, due in part to the shunting effect of small-conductance calcium-activated potassium (SK) channels. This effect explains their apparent absence in previous in vitro studies of cochlear nucleus which routinely employed high-Ca2+ extracellular solution. In contrast, oscillations were amplified in reduced Ca2+ solutions, due to relief of suppression by Ca2+ of Na+ channel gating. Our results thus reveal mechanisms for synchronous oscillatory activity in auditory brainstem, suggesting that slow oscillations, and by extension their perceptual effects, may originate at the earliest stages of sensory processing.
Collapse
Affiliation(s)
- Hui Hong 洪卉
- Oregon Hearing Research Center and Vollum Institute, Oregon Health & Science University, Portland 97239, Oregon
| | - Lucille A Moore
- Neuroscience Graduate Program, Oregon Health & Science University, Portland 97239, Oregon
| | - Pierre F Apostolides
- Neuroscience Graduate Program, Oregon Health & Science University, Portland 97239, Oregon
| | - Laurence O Trussell
- Oregon Hearing Research Center and Vollum Institute, Oregon Health & Science University, Portland 97239, Oregon
| |
Collapse
|
60
|
Wagstyl K, Adler S, Seidlitz J, Vandekar S, Mallard TT, Dear R, DeCasien AR, Satterthwaite TD, Liu S, Vértes PE, Shinohara RT, Alexander-Bloch A, Geschwind DH, Raznahan A. Transcriptional cartography integrates multiscale biology of the human cortex. eLife 2024; 12:RP86933. [PMID: 38324465 PMCID: PMC10945526 DOI: 10.7554/elife.86933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.
Collapse
Affiliation(s)
- Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Sophie Adler
- UCL Great Ormond Street Institute for Child HealthHolbornUnited Kingdom
| | - Jakob Seidlitz
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt UniversityNashvilleUnited States
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General HospitalBostonUnited States
- Department of Psychiatry, Harvard Medical SchoolBostonUnited States
| | - Richard Dear
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Alex R DeCasien
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of MedicinePhiladelphiaUnited States
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Petra E Vértes
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Daniel H Geschwind
- Center for Autism Research and Treatment, Semel Institute, Program in Neurogenetics, Department of Neurology and Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| |
Collapse
|
61
|
Wang X, Wu X, Hong N, Jin W. Progress in single-cell multimodal sequencing and multi-omics data integration. Biophys Rev 2024; 16:13-28. [PMID: 38495443 PMCID: PMC10937857 DOI: 10.1007/s12551-023-01092-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 06/27/2023] [Indexed: 03/19/2024] Open
Abstract
With the rapid advance of single-cell sequencing technology, cell heterogeneity in various biological processes was dissected at different omics levels. However, single-cell mono-omics results in fragmentation of information and could not provide complete cell states. In the past several years, a variety of single-cell multimodal omics technologies have been developed to jointly profile multiple molecular modalities, including genome, transcriptome, epigenome, and proteome, from the same single cell. With the availability of single-cell multimodal omics data, we can simultaneously investigate the effects of genomic mutation or epigenetic modification on transcription and translation, and reveal the potential mechanisms underlying disease pathogenesis. Driven by the massive single-cell omics data, the integration method of single-cell multi-omics data has rapidly developed. Integration of the massive multi-omics single-cell data in public databases in the future will make it possible to construct a cell atlas of multi-omics, enabling us to comprehensively understand cell state and gene regulation at single-cell resolution. In this review, we summarized the experimental methods for single-cell multimodal omics data and computational methods for multi-omics data integration. We also discussed the future development of this field.
Collapse
Affiliation(s)
- Xuefei Wang
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Xinchao Wu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Ni Hong
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Wenfei Jin
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| |
Collapse
|
62
|
Hao Y, Stuart T, Kowalski MH, Choudhary S, Hoffman P, Hartman A, Srivastava A, Molla G, Madad S, Fernandez-Granda C, Satija R. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat Biotechnol 2024; 42:293-304. [PMID: 37231261 PMCID: PMC10928517 DOI: 10.1038/s41587-023-01767-y] [Citation(s) in RCA: 168] [Impact Index Per Article: 168.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 03/28/2023] [Indexed: 05/27/2023]
Abstract
Mapping single-cell sequencing profiles to comprehensive reference datasets provides a powerful alternative to unsupervised analysis. However, most reference datasets are constructed from single-cell RNA-sequencing data and cannot be used to annotate datasets that do not measure gene expression. Here we introduce 'bridge integration', a method to integrate single-cell datasets across modalities using a multiomic dataset as a molecular bridge. Each cell in the multiomic dataset constitutes an element in a 'dictionary', which is used to reconstruct unimodal datasets and transform them into a shared space. Our procedure accurately integrates transcriptomic data with independent single-cell measurements of chromatin accessibility, histone modifications, DNA methylation and protein levels. Moreover, we demonstrate how dictionary learning can be combined with sketching techniques to improve computational scalability and harmonize 8.6 million human immune cell profiles from sequencing and mass cytometry experiments. Our approach, implemented in version 5 of our Seurat toolkit ( http://www.satijalab.org/seurat ), broadens the utility of single-cell reference datasets and facilitates comparisons across diverse molecular modalities.
Collapse
Affiliation(s)
- Yuhan Hao
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Tim Stuart
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Madeline H Kowalski
- New York Genome Center, New York, NY, USA
- Institute for System Genetics, NYU Langone Medical Center, New York, NY, USA
| | - Saket Choudhary
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Paul Hoffman
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Austin Hartman
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Avi Srivastava
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | | | - Shaista Madad
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Carlos Fernandez-Granda
- Center for Data Science, New York University, New York, NY, USA
- Courant Institute of Mathematical Sciences, New York University, New York, NY, USA
| | - Rahul Satija
- Center for Genomics and Systems Biology, New York University, New York, NY, USA.
- New York Genome Center, New York, NY, USA.
| |
Collapse
|
63
|
Balak CD, Han CZ, Glass CK. Deciphering microglia phenotypes in health and disease. Curr Opin Genet Dev 2024; 84:102146. [PMID: 38171044 DOI: 10.1016/j.gde.2023.102146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/30/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024]
Abstract
Microglia are the major immune cells of the central nervous system (CNS) that perform numerous adaptive functions required for normal CNS development and homeostasis but are also linked to neurodegenerative and behavioral diseases. Microglia development and function are strongly influenced by brain environmental signals that are integrated at the level of transcriptional enhancers to drive specific programs of gene expression. Here, we describe a conceptual framework for how lineage-determining and signal-dependent transcription factors interact to select and regulate the ensembles of enhancers that determine microglia development and function. We then highlight recent findings that advance these concepts and conclude with a consideration of open questions that represent some of the major hurdles to be addressed in the future.
Collapse
Affiliation(s)
- Christopher D Balak
- Department of Cellular and Molecular Medicine, University of California, San Diego, USA; Biomedical Sciences Graduate Program, University of California, San Diego, USA
| | - Claudia Z Han
- Department of Cellular and Molecular Medicine, University of California, San Diego, USA
| | - Christopher K Glass
- Department of Cellular and Molecular Medicine, University of California, San Diego, USA; Department of Medicine, University of California, San Diego, USA.
| |
Collapse
|
64
|
Camunas-Soler J. Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca 2+ imaging and electrophysiology. Biophys Rev 2024; 16:89-107. [PMID: 38495444 PMCID: PMC10937895 DOI: 10.1007/s12551-023-01174-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 11/29/2023] [Indexed: 03/19/2024] Open
Abstract
I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.
Collapse
Affiliation(s)
- Joan Camunas-Soler
- Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, University of Gothenburg, 405 30 Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
| |
Collapse
|
65
|
Moore JR, Nemera MT, D’Souza RD, Hamagami N, Clemens AW, Beard DC, Urman A, Mendoza VR, Gabel HW. Non-CG DNA methylation and MeCP2 stabilize repeated tuning of long genes that distinguish closely related neuron types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.30.577861. [PMID: 38352532 PMCID: PMC10862856 DOI: 10.1101/2024.01.30.577861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
The extraordinary diversity of neuron types in the mammalian brain is delineated at the highest resolution by subtle gene expression differences that may require specialized molecular mechanisms to be maintained. Neurons uniquely express the longest genes in the genome and utilize neuron-enriched non-CG DNA methylation (mCA) together with the Rett syndrome protein, MeCP2, to control gene expression, but the function of these unique gene structures and machinery in regulating finely resolved neuron type-specific gene programs has not been explored. Here, we employ epigenomic and spatial transcriptomic analyses to discover a major role for mCA and MeCP2 in maintaining neuron type-specific gene programs at the finest scale of cellular resolution. We uncover differential susceptibility to MeCP2 loss in neuronal populations depending on global mCA levels and dissect methylation patterns and intragenic enhancer repression that drive overlapping and distinct gene regulation between neuron types. Strikingly, we show that mCA and MeCP2 regulate genes that are repeatedly tuned to differentiate neuron types at the highest cellular resolution, including spatially resolved, vision-dependent gene programs in the visual cortex. These repeatedly tuned genes display genomic characteristics, including long length, numerous intragenic enhancers, and enrichment for mCA, that predispose them to regulation by MeCP2. Thus, long gene regulation by the MeCP2 pathway maintains differential gene expression between closely-related neurons to facilitate the exceptional cellular diversity in the complex mammalian brain.
Collapse
Affiliation(s)
- J. Russell Moore
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Mati T. Nemera
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Rinaldo D. D’Souza
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Nicole Hamagami
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Adam W. Clemens
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Diana C. Beard
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Alaina Urman
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Victoria Rodriguez Mendoza
- Opportunities in Genomic Research Program, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Harrison W. Gabel
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| |
Collapse
|
66
|
Leng K, Cadwell CR, Patrick Devine W, Tihan T, Qi Z, Singhal N, Glenn O, Kamiya S, Wiita A, Berger A, Shieh JT, Titus EW, Paredes MF, Upadhyay V. Cell type specificity of mosaic chromosome 1q gain resolved by snRNA-seq in a case of epilepsy with hyaline protoplasmic astrocytopathy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.16.562560. [PMID: 38328093 PMCID: PMC10849466 DOI: 10.1101/2023.10.16.562560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Introduction Mosaic gain of chromosome 1q (chr1q) has been associated with malformation of cortical development (MCD) and epilepsy. Hyaline protoplasmic astrocytopathy (HPA) is a rare neuropathological finding seen in cases of epilepsy with MCD. The cell-type specificity of mosaic chr1q gain in the brain and the molecular signatures of HPA are unknown. Methods We present a child with pharmacoresistant epilepsy who underwent epileptic focus resections at age 3 and 5 years and was found to have mosaic chr1q gain and HPA. We performed single-nuclei RNA-sequencing (snRNA-seq) of brain tissue from the second resection. Results snRNA-seq showed increased expression of chr1q genes specifically in subsets of neurons and astrocytes. Differentially expressed genes associated with inferred chr1q gain included AKT3 and genes associated with cell adhesion or migration. A subpopulation of astrocytes demonstrated marked enrichment for synapse-associated transcripts, possibly linked to the astrocytic inclusions observed in HPA. Discussion snRNA-seq may be used to infer the cell type-specificity of mosaic chromosomal copy number changes and identify associated gene expression alterations, which in the case of chr1q gain may involve aberrations in cell migration. Future studies using spatial profiling could yield further insights on the molecular signatures of HPA.
Collapse
Affiliation(s)
- Kun Leng
- Medical Scientist Training Program, University of California, San Francisco
| | - Cathryn R. Cadwell
- Department of Pathology, University of California, San Francisco
- Department of Neurological Surgery, University of California San Francisco
- Weill Institute for Neuroscience, University of California, San Francisco
| | | | - Tarik Tihan
- Department of Pathology, University of California, San Francisco
| | - Zhongxia Qi
- Department of Laboratory Medicine, University of California, San Francisco
| | - Nilika Singhal
- Division of Epilepsy, Department of Neurology, University of California, San Francisco
| | - Orit Glenn
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Sherry Kamiya
- Department of Pathology, University of California, San Francisco
| | - Arun Wiita
- Department of Laboratory Medicine, University of California, San Francisco
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco
- Chan Zuckerberg Biohub, San Francisco
| | - Amy Berger
- Department of Medicine, University of California, San Francisco
- Current affiliation: Denali Therapeutics
| | - Joseph T. Shieh
- Medical Genetics, Department of Pediatrics, University of California, San Francisco
| | - Erron W. Titus
- Medical Scientist Training Program, University of California, San Francisco
- Department of Laboratory Medicine, University of California, San Francisco
| | - Mercedes F. Paredes
- Weill Institute for Neuroscience, University of California, San Francisco
- Division of Epilepsy, Department of Neurology, University of California, San Francisco
| | | |
Collapse
|
67
|
Huang S, Wu SJ, Sansone G, Ibrahim LA, Fishell G. Layer 1 neocortex: Gating and integrating multidimensional signals. Neuron 2024; 112:184-200. [PMID: 37913772 PMCID: PMC11180419 DOI: 10.1016/j.neuron.2023.09.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/23/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.
Collapse
Affiliation(s)
- Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Program in Neuroscience, Harvard University, Cambridge, MA 02138, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giulia Sansone
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Leena Ali Ibrahim
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| |
Collapse
|
68
|
Ling E, Nemesh J, Goldman M, Kamitaki N, Reed N, Handsaker RE, Genovese G, Vogelgsang JS, Gerges S, Kashin S, Ghosh S, Esposito JM, French K, Meyer D, Lutservitz A, Mullally CD, Wysoker A, Spina L, Neumann A, Hogan M, Ichihara K, Berretta S, McCarroll SA. Concerted neuron-astrocyte gene expression declines in aging and schizophrenia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.07.574148. [PMID: 38260461 PMCID: PMC10802483 DOI: 10.1101/2024.01.07.574148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron-and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.
Collapse
Affiliation(s)
- Emi Ling
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - James Nemesh
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Melissa Goldman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Nolan Kamitaki
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Nora Reed
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Robert E. Handsaker
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Jonathan S. Vogelgsang
- McLean Hospital, Belmont, MA 02478, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
| | - Sherif Gerges
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Seva Kashin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Sulagna Ghosh
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | | | | | - Daniel Meyer
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Alyssa Lutservitz
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Christopher D. Mullally
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Alec Wysoker
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Liv Spina
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Anna Neumann
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Marina Hogan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Kiku Ichihara
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Sabina Berretta
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- McLean Hospital, Belmont, MA 02478, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- Program in Neuroscience, Harvard Medical School, Boston, MA 02215, USA
| | - Steven A. McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| |
Collapse
|
69
|
Yang YT, Gan Z, Zhang J, Zhao X, Yang Y, Han S, Wu W, Zhao XM. STAB2: an updated spatio-temporal cell atlas of the human and mouse brain. Nucleic Acids Res 2024; 52:D1033-D1041. [PMID: 37904591 PMCID: PMC10767951 DOI: 10.1093/nar/gkad955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 09/30/2023] [Accepted: 10/13/2023] [Indexed: 11/01/2023] Open
Abstract
The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.
Collapse
Affiliation(s)
- Yucheng T Yang
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Ziquan Gan
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Jinglong Zhang
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Xingzhong Zhao
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Yifan Yang
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Shuwen Han
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
| | - Wei Wu
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
| | - Xing-Ming Zhao
- Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang 313000, China
- Key Laboratory of Multiomics Research and Clinical Transformation of Digestive Cancer of Huzhou, Huzhou, Zhejiang 313000, China
- Institute of Science and Technology for Brain‐Inspired Intelligence, and Department of Neurology of Zhongshan Hospital, Fudan University, 220 Handan Road, Shanghai 200433, China
- MOE Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai 200032, China
- International Human Phenome Institutes (Shanghai), Shanghai 200433, China
| |
Collapse
|
70
|
Song Y, Seward CH, Chen CY, LeBlanc A, Leddy AM, Stubbs L. Isolated loss of the AUTS2 long isoform, brain-wide or targeted to Calbindin-lineage cells, generates a specific suite of brain, behavioral, and molecular pathologies. Genetics 2024; 226:iyad182. [PMID: 37816306 PMCID: PMC10763537 DOI: 10.1093/genetics/iyad182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/25/2023] [Accepted: 09/22/2023] [Indexed: 10/12/2023] Open
Abstract
Rearrangements within the AUTS2 region are associated with a rare syndromic disorder with intellectual disability, developmental delay, and behavioral abnormalities as core features. In addition, smaller regional variants are linked to wide range of neuropsychiatric disorders, underscoring the gene's essential role in brain development. Like many essential neurodevelopmental genes, AUTS2 is large and complex, generating distinct long (AUTS2-l) and short (AUTS2-s) protein isoforms from alternative promoters. Although evidence suggests unique isoform functions, the contributions of each isoform to specific AUTS2-linked phenotypes have not been clearly resolved. Furthermore, Auts2 is widely expressed across the developing brain, but cell populations most central to disease presentation have not been determined. In this study, we focused on the specific roles of AUTS2-l in brain development, behavior, and postnatal brain gene expression, showing that brain-wide AUTS2-l ablation leads to specific subsets of the recessive pathologies associated with mutations in 3' exons (exons 8-19) that disrupt both major isoforms. We identify downstream genes that could explain expressed phenotypes including hundreds of putative direct AUTS2-l target genes. Furthermore, in contrast to 3' Auts2 mutations which lead to dominant hypoactivity, AUTS2-l loss-of-function is associated with dominant hyperactivity and repetitive behaviors, phenotypes exhibited by many human patients. Finally, we show that AUTS2-l ablation in Calbindin 1-expressing cell lineages is sufficient to yield learning/memory deficits and hyperactivity with abnormal dentate gyrus granule cell maturation, but not other phenotypic effects. These data provide new clues to in vivo AUTS2-l functions and novel information relevant to genotype-phenotype correlations in the human AUTS2 region.
Collapse
Affiliation(s)
- Yunshu Song
- Pacific Northwest Research Institute, Seattle WA 98122, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | | | - Chih-Ying Chen
- Pacific Northwest Research Institute, Seattle WA 98122, USA
| | - Amber LeBlanc
- Pacific Northwest Research Institute, Seattle WA 98122, USA
| | | | - Lisa Stubbs
- Pacific Northwest Research Institute, Seattle WA 98122, USA
- Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| |
Collapse
|
71
|
Miao Z, Kim J. Uniform quantification of single-nucleus ATAC-seq data with Paired-Insertion Counting (PIC) and a model-based insertion rate estimator. Nat Methods 2024; 21:32-36. [PMID: 38049698 PMCID: PMC10776405 DOI: 10.1038/s41592-023-02103-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 10/25/2023] [Indexed: 12/06/2023]
Abstract
Existing approaches to scoring single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) feature matrices from sequencing reads are inconsistent, affecting downstream analyses and displaying artifacts. We show that, even with sparse single-cell data, quantitative counts are informative for estimating the regulatory state of a cell, which calls for a consistent treatment. We propose Paired-Insertion Counting as a uniform method for snATAC-seq feature characterization and provide a probability model for inferring latent insertion dynamics from snATAC-seq count matrices.
Collapse
Affiliation(s)
- Zhen Miao
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Junhyong Kim
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
| |
Collapse
|
72
|
Sepp M, Leiss K, Murat F, Okonechnikov K, Joshi P, Leushkin E, Spänig L, Mbengue N, Schneider C, Schmidt J, Trost N, Schauer M, Khaitovich P, Lisgo S, Palkovits M, Giere P, Kutscher LM, Anders S, Cardoso-Moreira M, Sarropoulos I, Pfister SM, Kaessmann H. Cellular development and evolution of the mammalian cerebellum. Nature 2024; 625:788-796. [PMID: 38029793 PMCID: PMC10808058 DOI: 10.1038/s41586-023-06884-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programmes underlying the development of the cerebellum in mammals. In this study we generated single-nucleus RNA-sequencing data for around 400,000 cells to trace the development of the cerebellum from early neurogenesis to adulthood in human, mouse and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell-type generation, except for Purkinje cells, for which we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell-state markers and gene-expression trajectories across neuronal differentiation show that cerebellar cell-type-defining programmes have been overall preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell-type level. In sum, our study unveils shared and lineage-specific gene-expression programmes governing the development of cerebellar cells and expands our understanding of mammalian brain evolution.
Collapse
Affiliation(s)
- Mari Sepp
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
| | - Kevin Leiss
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
| | - Florent Murat
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- INRAE, LPGP, Rennes, France
| | - Konstantin Okonechnikov
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Piyush Joshi
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
- Developmental Origins of Pediatric Cancer Junior Group, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Evgeny Leushkin
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Lisa Spänig
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
- Developmental Origins of Pediatric Cancer Junior Group, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Noe Mbengue
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Céline Schneider
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Julia Schmidt
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Nils Trost
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Maria Schauer
- Museum für Naturkunde Berlin, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Philipp Khaitovich
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Steven Lisgo
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - Miklós Palkovits
- Human Brain Tissue Bank, Semmelweis University, Budapest, Hungary
| | - Peter Giere
- Museum für Naturkunde Berlin, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Lena M Kutscher
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Developmental Origins of Pediatric Cancer Junior Group, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Simon Anders
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- BioQuant, Heidelberg University, Heidelberg, Germany
| | | | - Ioannis Sarropoulos
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
- Wellcome Sanger Institute, Cambridge, UK.
| | - Stefan M Pfister
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.
- Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), Heidelberg, Germany.
| | - Henrik Kaessmann
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
| |
Collapse
|
73
|
Wallace JL, Pollen AA. Human neuronal maturation comes of age: cellular mechanisms and species differences. Nat Rev Neurosci 2024; 25:7-29. [PMID: 37996703 DOI: 10.1038/s41583-023-00760-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2023] [Indexed: 11/25/2023]
Abstract
The delayed and prolonged postmitotic maturation of human neurons, compared with neurons from other species, may contribute to human-specific cognitive abilities and neurological disorders. Here we review the mechanisms of neuronal maturation, applying lessons from model systems to understand the specific features of protracted human cortical maturation and species differences. We cover cell-intrinsic features of neuronal maturation, including transcriptional, epigenetic and metabolic mechanisms, as well as cell-extrinsic features, including the roles of activity and synapses, the actions of glial cells and the contribution of the extracellular matrix. We discuss evidence for species differences in biochemical reaction rates, the proposed existence of an epigenetic maturation clock and the contributions of both general and modular mechanisms to species-specific maturation timing. Finally, we suggest approaches to measure, improve and accelerate the maturation of human neurons in culture, examine crosstalk and interactions among these different aspects of maturation and propose conceptual models to guide future studies.
Collapse
Affiliation(s)
- Jenelle L Wallace
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
74
|
Russell AJC, Weir JA, Nadaf NM, Shabet M, Kumar V, Kambhampati S, Raichur R, Marrero GJ, Liu S, Balderrama KS, Vanderburg CR, Shanmugam V, Tian L, Iorgulescu JB, Yoon CH, Wu CJ, Macosko EZ, Chen F. Slide-tags enables single-nucleus barcoding for multimodal spatial genomics. Nature 2024; 625:101-109. [PMID: 38093010 PMCID: PMC10764288 DOI: 10.1038/s41586-023-06837-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 11/06/2023] [Indexed: 12/17/2023]
Abstract
Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed1-6. However, missing from these measurements is the ability to routinely and easily spatially localize these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are tagged with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as an input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 μm spatial resolution and delivered whole-transcriptome data that are indistinguishable in quality from ordinary single-nucleus RNA-sequencing data. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualized receptor-ligand interactions driving B cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to almost any single-cell measurement technology. As a proof of principle, we performed multiomic measurements of open chromatin, RNA and T cell receptor (TCR) sequences in the same cells from metastatic melanoma, identifying transcription factor motifs driving cancer cell state transitions in spatially distinct microenvironments. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.
Collapse
Affiliation(s)
- Andrew J C Russell
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Jackson A Weir
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Biological and Biomedical Sciences Program, Harvard University, Cambridge, MA, USA
| | - Naeem M Nadaf
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Vipin Kumar
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Sandeep Kambhampati
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard University, Boston, MA, USA
| | - Ruth Raichur
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Sophia Liu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Biophysics Program, Harvard University, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | | | - Vignesh Shanmugam
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Luyi Tian
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Guangzhou Laboratory, Guangdong, China
| | - J Bryan Iorgulescu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Stem Cell Transplantation and Cellular Therapies, Dana-Farber Cancer Institute, Boston, MA, USA
- Molecular Diagnostics Laboratory, Department of Hematopathology, Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Charles H Yoon
- Department of Surgical Oncology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Catherine J Wu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Stem Cell Transplantation and Cellular Therapies, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Evan Z Macosko
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
| | - Fei Chen
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
| |
Collapse
|
75
|
Afshar-Saber W, Teaney NA, Winden KD, Jumo H, Shi X, McGinty G, Hubbs J, Chen C, Tokatly Latzer I, Gasparoli F, Ebrahimi-Fakhari D, Buttermore ED, Roullet JB, Pearl PL, Sahin M. ALDH5A1-deficient iPSC-derived excitatory and inhibitory neurons display cell type specific alterations. Neurobiol Dis 2024; 190:106386. [PMID: 38110041 PMCID: PMC10843729 DOI: 10.1016/j.nbd.2023.106386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/14/2023] [Accepted: 12/15/2023] [Indexed: 12/20/2023] Open
Abstract
Succinic semialdehyde dehydrogenase deficiency (SSADHD) is a neurometabolic disorder caused by ALDH5A1 mutations presenting with autism and epilepsy. SSADHD leads to impaired GABA metabolism and results in accumulation of GABA and γ-hydroxybutyrate (GHB), which alter neurotransmission and are thought to lead to neurobehavioral symptoms. However, why increased inhibitory neurotransmitters lead to seizures remains unclear. We used induced pluripotent stem cells from SSADHD patients (one female and two male) and differentiated them into GABAergic and glutamatergic neurons. SSADHD iGABA neurons show altered GABA metabolism and concomitant changes in expression of genes associated with inhibitory neurotransmission. In contrast, glutamatergic neurons display increased spontaneous activity and upregulation of mitochondrial genes. CRISPR correction of the pathogenic variants or SSADHD mRNA expression rescue various metabolic and functional abnormalities in human neurons. Our findings uncover a previously unknown role for SSADHD in excitatory human neurons and provide unique insights into the cellular and molecular basis of SSADHD and potential therapeutic interventions.
Collapse
Affiliation(s)
- Wardiya Afshar-Saber
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicole A Teaney
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kellen D Winden
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hellen Jumo
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Xutong Shi
- Washington State University, Department of Pharmacotherapy, Spokane, WA, USA
| | - Gabrielle McGinty
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jed Hubbs
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cidi Chen
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA
| | - Itay Tokatly Latzer
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | | | - Darius Ebrahimi-Fakhari
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth D Buttermore
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Human Neuron Core, Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA
| | | | - Phillip L Pearl
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mustafa Sahin
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; FM Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
76
|
Libé-Philippot B, Lejeune A, Wierda K, Louros N, Erkol E, Vlaeminck I, Beckers S, Gaspariunaite V, Bilheu A, Konstantoulea K, Nyitrai H, De Vleeschouwer M, Vennekens KM, Vidal N, Bird TW, Soto DC, Jaspers T, Dewilde M, Dennis MY, Rousseau F, Comoletti D, Schymkowitz J, Theys T, de Wit J, Vanderhaeghen P. LRRC37B is a human modifier of voltage-gated sodium channels and axon excitability in cortical neurons. Cell 2023; 186:5766-5783.e25. [PMID: 38134874 PMCID: PMC10754148 DOI: 10.1016/j.cell.2023.11.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/28/2023] [Accepted: 11/27/2023] [Indexed: 12/24/2023]
Abstract
The enhanced cognitive abilities characterizing the human species result from specialized features of neurons and circuits. Here, we report that the hominid-specific gene LRRC37B encodes a receptor expressed in human cortical pyramidal neurons (CPNs) and selectively localized to the axon initial segment (AIS), the subcellular compartment triggering action potentials. Ectopic expression of LRRC37B in mouse CPNs in vivo leads to reduced intrinsic excitability, a distinctive feature of some classes of human CPNs. Molecularly, LRRC37B binds to the secreted ligand FGF13A and to the voltage-gated sodium channel (Nav) β-subunit SCN1B. LRRC37B concentrates inhibitory effects of FGF13A on Nav channel function, thereby reducing excitability, specifically at the AIS level. Electrophysiological recordings in adult human cortical slices reveal lower neuronal excitability in human CPNs expressing LRRC37B. LRRC37B thus acts as a species-specific modifier of human neuron excitability, linking human genome and cell evolution, with important implications for human brain function and diseases.
Collapse
Affiliation(s)
- Baptiste Libé-Philippot
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Amélie Lejeune
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Keimpe Wierda
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Electrophysiology Unit, VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium
| | - Nikolaos Louros
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Emir Erkol
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Ine Vlaeminck
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Electrophysiology Unit, VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium
| | - Sofie Beckers
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Vaiva Gaspariunaite
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Angéline Bilheu
- Université Libre de Bruxelles (ULB), Institute for Interdisciplinary Research (IRIBHM), 1070 Brussels, Belgium
| | - Katerina Konstantoulea
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Hajnalka Nyitrai
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Matthias De Vleeschouwer
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Kristel M Vennekens
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Niels Vidal
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Thomas W Bird
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand
| | - Daniela C Soto
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, Davis, CA 95616, USA
| | - Tom Jaspers
- Laboratory for Therapeutic and Diagnostic Antibodies, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Maarten Dewilde
- Laboratory for Therapeutic and Diagnostic Antibodies, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Megan Y Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, Davis, CA 95616, USA
| | - Frederic Rousseau
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Davide Comoletti
- School of Biological Sciences, Victoria University of Wellington, Wellington 6012, New Zealand; Child Health Institute of New Jersey, Rutgers University, New Brunswick, NJ 08901, USA
| | - Joost Schymkowitz
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; Department of Cellular and Molecular Medicine, KUL, 3000 Leuven, Belgium
| | - Tom Theys
- KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium; Research Group Experimental Neurosurgery and Neuroanatomy, KUL, 3000 Leuven, Belgium
| | - Joris de Wit
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium.
| | - Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KUL, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium; Université Libre de Bruxelles (ULB), Institute for Interdisciplinary Research (IRIBHM), 1070 Brussels, Belgium.
| |
Collapse
|
77
|
Shao M, Zhang W, Li Y, Tang L, Hao ZZ, Liu S. Patch-seq: Advances and Biological Applications. Cell Mol Neurobiol 2023; 44:8. [PMID: 38123823 DOI: 10.1007/s10571-023-01436-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/24/2023] [Indexed: 12/23/2023]
Abstract
Multimodal analysis of gene-expression patterns, electrophysiological properties, and morphological phenotypes at the single-cell/single-nucleus level has been arduous because of the diversity and complexity of neurons. The emergence of Patch-sequencing (Patch-seq) directly links transcriptomics, morphology, and electrophysiology, taking neuroscience research to a multimodal era. In this review, we summarized the development of Patch-seq and recent applications in the cortex, hippocampus, and other nervous systems. Through generating multimodal cell type atlases, targeting specific cell populations, and correlating transcriptomic data with phenotypic information, Patch-seq has provided new insight into outstanding questions in neuroscience. We highlight the challenges and opportunities of Patch-seq in neuroscience and hope to shed new light on future neuroscience research.
Collapse
Affiliation(s)
- Mingting Shao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Wei Zhang
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Ye Li
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Lei Tang
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, 510080, China.
| |
Collapse
|
78
|
Lam M, Lee D, Kosater I, Khairallah A, Taga M, Zhang Y, Fujita M, Nag S, Bennett DA, De Jager P, Menon V. Human disease-specific cell signatures in non-lesional tissue in Multiple Sclerosis detected by single-cell and spatial transcriptomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.20.572491. [PMID: 38187779 PMCID: PMC10769298 DOI: 10.1101/2023.12.20.572491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Recent investigations of cell type changes in Multiple Sclerosis (MS) using single-cell profiling methods have focused on active lesional and peri-lesional brain tissue, and have implicated a number of peripheral and central nervous system cell types. However, an important question is the extent to which so-called "normal-appearing" non-lesional tissue in individuals with MS accumulate changes over the lifespan. Here, we compared post-mortem non-lesional brain tissue from donors with a pathological or clinical diagnosis of MS from the Religious Orders Study or Rush Memory and Aging Project (ROSMAP) cohorts to age- and sex-matched brains from persons without MS (controls). We profiled three brain regions using single-nucleus RNA-seq: dorsolateral prefrontal cortex (DLPFC), normal appearing white matter (NAWM) and the pulvinar in thalamus (PULV), from 15 control individuals, 8 individuals with MS, and 5 individuals with other detrimental pathologies accompanied by demyelination, resulting in a total of 78 samples. We identified region- and cell type-specific differences in non-lesional samples from individuals diagnosed with MS and/or exhibiting secondary demyelination with other neurological conditions, as compared to control donors. These differences included lower proportions of oligodendrocytes with expression of myelination related genes MOBP, MBP, PLP1, as well as higher proportions of CRYAB+ oligodendrocytes in all three brain regions. Among microglial signatures, we identified subgroups that were higher in both demyelination (TMEM163+/ERC2+), as well as those that were specifically higher in MS donors (HIF1A+/SPP1+) and specifically in donors with secondary demyelination (SOCS6+/MYO1E+), in both white and grey matter. To validate our findings, we generated Visium spatial transcriptomics data on matched tissue from 13 donors, and recapitulated our observations of gene expression differences in oligodendrocytes and microglia. Finally, we show that some of the differences observed between control and MS donors in NAWM mirror those previously reported between control WM and active lesions in MS donors. Overall, our investigation sheds additional light on cell type- and disease-specific differences present even in non-lesional white and grey matter tissue, highlighting widespread cellular signatures that may be associated with downstream pathological changes.
Collapse
Affiliation(s)
- Matti Lam
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Dylan Lee
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Ivy Kosater
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Anthony Khairallah
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Mariko Taga
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Ya Zhang
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Masashi Fujita
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Sukriti Nag
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL
| | - Philip De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| | - Vilas Menon
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center
| |
Collapse
|
79
|
Mukamel EA, Liu H, Behrens MM, Ecker JR. Cell type-specific enrichment of somatic aneuploidy in the mammalian brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.18.572285. [PMID: 38187559 PMCID: PMC10769240 DOI: 10.1101/2023.12.18.572285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Somatic mutations alter the genomes of a subset of an individual's brain cells1-3, impacting gene regulation and contributing to disease processes4,5. Mosaic single nucleotide variants have been characterized with single-cell resolution in the brain2,3, but we have limited information about large-scale structural variation, including whole-chromosome duplication or loss1,6,7. We used a dataset of over 415,000 single-cell DNA methylation and chromatin conformation profiles across the adult mouse brain to identify aneuploid cells comprehensively. Whole-chromosome loss or duplication occurred in <1% of cells, with rates up to 1.8% in non-neuronal cell types, including oligodendrocyte precursors and pericytes. Among all aneuploidies, we observed a strong enrichment of trisomy on chromosome 16, which is syntenic with human chromosome 21 and constitutively trisomic in Down syndrome. Chromosome 16 trisomy occurred in multiple cell types and across brain regions, suggesting that nondisjunction is a recurrent feature of somatic variation in the brain.
Collapse
Affiliation(s)
- Eran A. Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, University of California, San Diego, La Jolla, CA 92037, USA
| | - M. Margarita Behrens
- Computational Neurobiology Laboratory, University of California, San Diego, La Jolla, CA 92037, USA
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, University of California, San Diego, La Jolla, CA 92037, USA
- Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| |
Collapse
|
80
|
Akula SK, Exposito-Alonso D, Walsh CA. Shaping the brain: The emergence of cortical structure and folding. Dev Cell 2023; 58:2836-2849. [PMID: 38113850 PMCID: PMC10793202 DOI: 10.1016/j.devcel.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 04/08/2023] [Accepted: 11/10/2023] [Indexed: 12/21/2023]
Abstract
The cerebral cortex-the brain's covering and largest region-has increased in size and complexity in humans and supports higher cognitive functions such as language and abstract thinking. There is a growing understanding of the human cerebral cortex, including the diversity and number of cell types that it contains, as well as of the developmental mechanisms that shape cortical structure and organization. In this review, we discuss recent progress in our understanding of molecular and cellular processes, as well as mechanical forces, that regulate the folding of the cerebral cortex. Advances in human genetics, coupled with experimental modeling in gyrencephalic species, have provided insights into the central role of cortical progenitors in the gyrification and evolutionary expansion of the cerebral cortex. These studies are essential for understanding the emergence of structural and functional organization during cortical development and the pathogenesis of neurodevelopmental disorders associated with cortical malformations.
Collapse
Affiliation(s)
- Shyam K Akula
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
| | - David Exposito-Alonso
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
| | - Christopher A Walsh
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA; Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, Maryland, USA.
| |
Collapse
|
81
|
Moffitt TB, Atcherson S, Padberg J. Auditory brainstem responses in the nine-banded armadillo ( Dasypus novemcinctus). PeerJ 2023; 11:e16602. [PMID: 38107579 PMCID: PMC10725177 DOI: 10.7717/peerj.16602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 11/15/2023] [Indexed: 12/19/2023] Open
Abstract
The auditory brainstem response (ABR) to tone burst stimuli of thirteen frequencies ranging from 0.5 to 48 kHz was recorded in the nine-banded armadillo (Dasypus novemcinctus), the only extant member of the placental mammal superorder Xenarthra in North America. The armadillo ABR consisted of five main peaks that were visible within the first 10 ms when stimuli were presented at high intensities. The latency of peak I of the armadillo ABR increased as stimulus intensity decreased by an average of 20 μs/dB. Estimated frequency-specific thresholds identified by the ABR were used to construct an estimate of the armadillo audiogram describing the mean thresholds of the eight animals tested. The majority of animals tested (six out of eight) exhibited clear responses to stimuli from 0.5 to 38 kHz, and two animals exhibited responses to stimuli of 48 kHz. Across all cases, the lowest thresholds were observed for frequencies from 8 to 12 kHz. Overall, we observed that the armadillo estimated audiogram bears a similar pattern as those observed using ABR in members of other mammalian clades, including marsupials and later-derived placental mammals.
Collapse
Affiliation(s)
| | - Samuel Atcherson
- Department of Audiology and Speech Pathology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | | |
Collapse
|
82
|
Pelkey KA, Vargish GA, Pellegrini LV, Calvigioni D, Chapeton J, Yuan X, Hunt S, Cummins AC, Eldridge MAG, Pickel J, Chittajallu R, Averbeck BB, Tóth K, Zaghloul K, McBain CJ. Evolutionary conservation of hippocampal mossy fiber synapse properties. Neuron 2023; 111:3802-3818.e5. [PMID: 37776852 PMCID: PMC10841147 DOI: 10.1016/j.neuron.2023.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 07/03/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
Various specialized structural/functional properties are considered essential for contextual memory encoding by hippocampal mossy fiber (MF) synapses. Although investigated to exquisite detail in model organisms, synapses, including MFs, have undergone minimal functional interrogation in humans. To determine the translational relevance of rodent findings, we evaluated MF properties within human tissue resected to treat epilepsy. Human MFs exhibit remarkably similar hallmark features to rodents, including AMPA receptor-dominated synapses with small contributions from NMDA and kainate receptors, large dynamic range with strong frequency facilitation, NMDA receptor-independent presynaptic long-term potentiation, and strong cyclic AMP (cAMP) sensitivity of release. Array tomography confirmed the evolutionary conservation of MF ultrastructure. The astonishing congruence of rodent and human MF core features argues that the basic MF properties delineated in animal models remain critical to human MF function. Finally, a selective deficit in GABAergic inhibitory tone onto human MF postsynaptic targets suggests that unrestrained detonator excitatory drive contributes to epileptic circuit hyperexcitability.
Collapse
Affiliation(s)
- Kenneth A Pelkey
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Geoffrey A Vargish
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leonardo V Pellegrini
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Brain and Mind Research Institute, Ottawa, ON K1H 8M5, Canada
| | - Daniela Calvigioni
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio Chapeton
- National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaoqing Yuan
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steven Hunt
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Alex C Cummins
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mark A G Eldridge
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - James Pickel
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ramesh Chittajallu
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Bruno B Averbeck
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katalin Tóth
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Brain and Mind Research Institute, Ottawa, ON K1H 8M5, Canada
| | - Kareem Zaghloul
- National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Chris J McBain
- Eunice Kennedy Shriver National Institute of Child Health and Human Development Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA.
| |
Collapse
|
83
|
Maimaitili M, Chen M, Febbraro F, Ucuncu E, Kelly R, Niclis JC, Christiansen JR, Mermet-Joret N, Niculescu D, Lauritsen J, Iannielli A, Klæstrup IH, Jensen UB, Qvist P, Nabavi S, Broccoli V, Nykjær A, Romero-Ramos M, Denham M. Enhanced production of mesencephalic dopaminergic neurons from lineage-restricted human undifferentiated stem cells. Nat Commun 2023; 14:7871. [PMID: 38052784 DOI: 10.1038/s41467-023-43471-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 11/10/2023] [Indexed: 12/07/2023] Open
Abstract
Current differentiation protocols for generating mesencephalic dopaminergic (mesDA) neurons from human pluripotent stem cells result in grafts containing only a small proportion of mesDA neurons when transplanted in vivo. In this study, we develop lineage-restricted undifferentiated stem cells (LR-USCs) from pluripotent stem cells, which enhances their potential for differentiating into caudal midbrain floor plate progenitors and mesDA neurons. Using a ventral midbrain protocol, 69% of LR-USCs become bona fide caudal midbrain floor plate progenitors, compared to only 25% of human embryonic stem cells (hESCs). Importantly, LR-USCs generate significantly more mesDA neurons under midbrain and hindbrain conditions in vitro and in vivo. We demonstrate that midbrain-patterned LR-USC progenitors transplanted into 6-hydroxydopamine-lesioned rats restore function in a clinically relevant non-pharmacological behavioral test, whereas midbrain-patterned hESC-derived progenitors do not. This strategy demonstrates how lineage restriction can prevent the development of undesirable lineages and enhance the conditions necessary for mesDA neuron generation.
Collapse
Affiliation(s)
- Muyesier Maimaitili
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | - Muwan Chen
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | - Fabia Febbraro
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Clinical Genetics, Aarhus University Hospital, 8200, Aarhus, Denmark
| | - Ekin Ucuncu
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | - Rachel Kelly
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | | | | | - Noëmie Mermet-Joret
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Molecular Biology and Genetics, Aarhus University, 8000C, Aarhus, Denmark
- Center of Excellence PROMEMO, Aarhus University, Aarhus, Denmark
| | - Dragos Niculescu
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
- Center of Excellence PROMEMO, Aarhus University, Aarhus, Denmark
| | - Johanne Lauritsen
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | - Angelo Iannielli
- Stem Cell and Neurogenesis Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132, Milan, Italy
- CNR Institute of Neuroscience, 20129, Milan, Italy
| | - Ida H Klæstrup
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | - Uffe Birk Jensen
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Clinical Genetics, Aarhus University Hospital, 8200, Aarhus, Denmark
| | - Per Qvist
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8000C, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, 8000C, Aarhus, Denmark
- Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, 8000C, Aarhus, Denmark
| | - Sadegh Nabavi
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Molecular Biology and Genetics, Aarhus University, 8000C, Aarhus, Denmark
- Center of Excellence PROMEMO, Aarhus University, Aarhus, Denmark
| | - Vania Broccoli
- Stem Cell and Neurogenesis Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132, Milan, Italy
- CNR Institute of Neuroscience, 20129, Milan, Italy
| | - Anders Nykjær
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
- Center of Excellence PROMEMO, Aarhus University, Aarhus, Denmark
| | - Marina Romero-Ramos
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark
| | - Mark Denham
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, 8000C, Aarhus, Denmark.
- Department of Biomedicine, Aarhus University, 8000C, Aarhus, Denmark.
| |
Collapse
|
84
|
Kenwood MM, Souaiaia T, Kovner R, Fox AS, French DA, Oler JA, Roseboom PH, Riedel MK, Mueller SAL, Kalin NH. Gene expression in the primate orbitofrontal cortex related to anxious temperament. Proc Natl Acad Sci U S A 2023; 120:e2305775120. [PMID: 38011550 DOI: 10.1073/pnas.2305775120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/13/2023] [Indexed: 11/29/2023] Open
Abstract
Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.
Collapse
Affiliation(s)
- Margaux M Kenwood
- Neuroscience Training Program, University of Wisconsin, Madison, WI 53705
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | - Tade Souaiaia
- Department of Cell Biology, State University of New York Downstate, New York, NY 11228
| | - Rothem Kovner
- Yale School of Medicine, Yale University, New Haven, CT 06510
| | - Andrew S Fox
- Department of Psychology and California National Primate Research Center, University of California, Davis, CA 95616
| | - Delores A French
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | | | - Marissa K Riedel
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | | | - Ned H Kalin
- Neuroscience Training Program, University of Wisconsin, Madison, WI 53705
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715
| |
Collapse
|
85
|
Liu S, Zheng P, Wang CY, Jia BB, Zemke NR, Ren B, Zhuang X. Cell-type-specific 3D-genome organization and transcription regulation in the brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.04.570024. [PMID: 38105994 PMCID: PMC10723369 DOI: 10.1101/2023.12.04.570024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
3D organization of the genome plays a critical role in regulating gene expression. However, it remains unclear how chromatin organization differs among different cell types in the brain. Here we used genome-scale DNA and RNA imaging to investigate 3D-genome organization in transcriptionally distinct cell types in the primary motor cortex of the mouse brain. We uncovered a wide spectrum of differences in the nuclear architecture and 3D-genome organization among different cell types, ranging from the physical size of the cell nucleus to the active-inactive chromatin compartmentalization and radial positioning of chromatin loci within the nucleus. These cell-type-dependent variations in nuclear architecture and chromatin organization exhibited strong correlation with both total transcriptional activity of the cell and transcriptional regulation of cell-type-specific marker genes. Moreover, we found that the methylated-DNA-binding protein MeCP2 regulates transcription in a divergent manner, depending on the nuclear radial positions of chromatin loci, through modulating active-inactive chromatin compartmentalization.
Collapse
Affiliation(s)
- Shiwei Liu
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Pu Zheng
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Cosmos Yuqi Wang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Bojing Blair Jia
- Bioinformatics and Systems Biology Graduate Program, Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA
| | - Nathan R. Zemke
- Department of Cellular and Molecular Medicine and Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine and Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| |
Collapse
|
86
|
Jin P, Zhu B, Jia Y, Zhang Y, Wang W, Shen Y, Zhong Y, Zheng Y, Wang Y, Tong Y, Zhang W, Li S. Single-cell transcriptomics reveals the brain evolution of web-building spiders. Nat Ecol Evol 2023; 7:2125-2142. [PMID: 37919396 PMCID: PMC10697844 DOI: 10.1038/s41559-023-02238-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 09/29/2023] [Indexed: 11/04/2023]
Abstract
Spiders are renowned for their efficient capture of flying insects using intricate aerial webs. How the spider nervous systems evolved to cope with this specialized hunting strategy and various environmental clues in an aerial space remains unknown. Here we report a brain-cell atlas of >30,000 single-cell transcriptomes from a web-building spider (Hylyphantes graminicola). Our analysis revealed the preservation of ancestral neuron types in spiders, including the potential coexistence of noradrenergic and octopaminergic neurons, and many peptidergic neuronal types that are lost in insects. By comparing the genome of two newly sequenced plesiomorphic burrowing spiders with three aerial web-building spiders, we found that the positively selected genes in the ancestral branch of web-building spiders were preferentially expressed (42%) in the brain, especially in the three mushroom body-like neuronal types. By gene enrichment analysis and RNAi experiments, these genes were suggested to be involved in the learning and memory pathway and may influence the spiders' web-building and hunting behaviour. Our results provide key sources for understanding the evolution of behaviour in spiders and reveal how molecular evolution drives neuron innovation and the diversification of associated complex behaviours.
Collapse
Affiliation(s)
- Pengyu Jin
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Bingyue Zhu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yinjun Jia
- School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- Tsinghua-Peking Center for Life Sciences, Beijing, China
| | - Yiming Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wei Wang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Guangxi Normal University, Guilin, China
| | - Yunxiao Shen
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yu Zhong
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yami Zheng
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yang Wang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yan Tong
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wei Zhang
- School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
- Tsinghua-Peking Center for Life Sciences, Beijing, China
| | - Shuqiang Li
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
| |
Collapse
|
87
|
Zemke NR, Armand EJ, Wang W, Lee S, Zhou J, Li YE, Liu H, Tian W, Nery JR, Castanon RG, Bartlett A, Osteen JK, Li D, Zhuo X, Xu V, Chang L, Dong K, Indralingam HS, Rink JA, Xie Y, Miller M, Krienen FM, Zhang Q, Taskin N, Ting J, Feng G, McCarroll SA, Callaway EM, Wang T, Lein ES, Behrens MM, Ecker JR, Ren B. Conserved and divergent gene regulatory programs of the mammalian neocortex. Nature 2023; 624:390-402. [PMID: 38092918 PMCID: PMC10719095 DOI: 10.1038/s41586-023-06819-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Divergence of cis-regulatory elements drives species-specific traits1, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains unclear. Here we investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset and mouse using single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome and chromosomal conformation profiles from a total of over 200,000 cells. From these data, we show evidence that divergence of transcription factor expression corresponds to species-specific epigenome landscapes. We find that conserved and divergent gene regulatory features are reflected in the evolution of the three-dimensional genome. Transposable elements contribute to nearly 80% of the human-specific candidate cis-regulatory elements in cortical cells. Through machine learning, we develop sequence-based predictors of candidate cis-regulatory elements in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Finally, we show that epigenetic conservation combined with sequence similarity helps to uncover functional cis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits.
Collapse
Affiliation(s)
- Nathan R Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
| | - Wenliang Wang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Jingtian Zhou
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rosa G Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia K Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Xiaoyu Zhuo
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Vincent Xu
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Keyi Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Hannah S Indralingam
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Jonathan A Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Michael Miller
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Fenna M Krienen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Genetics, Harvard Medical School, Boston, USA
| | - Qiangge Zhang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Naz Taskin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Guoping Feng
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven A McCarroll
- Department of Genetics, Harvard Medical School, Boston, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Edward M Callaway
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - M Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA.
- Institute of Genomic Medicine, Moores Cancer Center, School of Medicine, University of California San Diego, La Jolla, CA, USA.
| |
Collapse
|
88
|
Nevue AA, Zemel BM, Friedrich SR, von Gersdorff H, Mello CV. Cell type specializations of the vocal-motor cortex in songbirds. Cell Rep 2023; 42:113344. [PMID: 37910500 PMCID: PMC10752865 DOI: 10.1016/j.celrep.2023.113344] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/30/2023] [Accepted: 10/10/2023] [Indexed: 11/03/2023] Open
Abstract
Identifying molecular specializations in cortical circuitry supporting complex behaviors, like learned vocalizations, requires understanding of the neuroanatomical context from which these circuits arise. In songbirds, the robust arcopallial nucleus (RA) provides descending cortical projections for fine vocal-motor control. Using single-nuclei transcriptomics and spatial gene expression mapping in zebra finches, we have defined cell types and molecular specializations that distinguish RA from adjacent regions involved in non-vocal motor and sensory processing. We describe an RA-specific projection neuron, differential inhibitory subtypes, and glia specializations and have probed predicted GABAergic interneuron subtypes electrophysiologically within RA. Several cell-specific markers arise developmentally in a sex-dependent manner. Our interactive apps integrate cellular data with developmental and spatial distribution data from the gene expression brain atlas ZEBrA. Users can explore molecular specializations of vocal-motor neurons and support cells that likely reflect adaptations key to the physiology and evolution of vocal control circuits and refined motor skills.
Collapse
Affiliation(s)
- Alexander A Nevue
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA; Vollum Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Benjamin M Zemel
- Vollum Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Samantha R Friedrich
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | | | - Claudio V Mello
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA.
| |
Collapse
|
89
|
Sorensen SA, Gouwens NW, Wang Y, Mallory M, Budzillo A, Dalley R, Lee B, Gliko O, Kuo HC, Kuang X, Mann R, Ahmadinia L, Alfiler L, Baftizadeh F, Baker K, Bannick S, Bertagnolli D, Bickley K, Bohn P, Brown D, Bomben J, Brouner K, Chen C, Chen K, Chvilicek M, Collman F, Daigle T, Dawes T, de Frates R, Dee N, DePartee M, Egdorf T, El-Hifnawi L, Enstrom R, Esposito L, Farrell C, Gala R, Glomb A, Gamlin C, Gary A, Goldy J, Gu H, Hadley K, Hawrylycz M, Henry A, Hill D, Hirokawa KE, Huang Z, Johnson K, Juneau Z, Kebede S, Kim L, Lee C, Lesnar P, Li A, Glomb A, Li Y, Liang E, Link K, Maxwell M, McGraw M, McMillen DA, Mukora A, Ng L, Ochoa T, Oldre A, Park D, Pom CA, Popovich Z, Potekhina L, Rajanbabu R, Ransford S, Reding M, Ruiz A, Sandman D, Siverts L, Smith KA, Stoecklin M, Sulc J, Tieu M, Ting J, Trinh J, Vargas S, Vumbaco D, Walker M, Wang M, Wanner A, Waters J, Williams G, Wilson J, Xiong W, Lein E, Berg J, Kalmbach B, Yao S, Gong H, Luo Q, Ng L, Sümbül U, Jarsky T, Yao Z, Tasic B, Zeng H. Connecting single-cell transcriptomes to projectomes in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.25.568393. [PMID: 38168270 PMCID: PMC10760188 DOI: 10.1101/2023.11.25.568393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.
Collapse
Affiliation(s)
| | | | - Yun Wang
- Allen Institute for Brain Science
| | | | | | | | | | | | | | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | | | - Chao Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Kai Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | - Nick Dee
- Allen Institute for Brain Science
| | | | | | | | | | | | | | | | | | | | | | | | - Hong Gu
- Allen Institute for Brain Science
| | | | | | | | | | | | - Zili Huang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | - Lisa Kim
- Allen Institute for Brain Science
| | | | | | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | | | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | - Zoran Popovich
- University of Washington, Dept. of Computer Science and Engineering
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Wei Xiong
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Ed Lein
- Allen Institute for Brain Science
| | - Jim Berg
- Allen Institute for Brain Science
| | | | | | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Qingming Luo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Lydia Ng
- Allen Institute for Brain Science
| | | | | | | | | | | |
Collapse
|
90
|
He S, Shi Y, Ye J, Yin J, Yang Y, Liu D, Shen T, Zeng D, Zhang M, Li S, Xu F, Cai Y, Zhao F, Li H, Peng D. Does decreased autophagy and dysregulation of LC3A in astrocytes play a role in major depressive disorder? Transl Psychiatry 2023; 13:362. [PMID: 38001115 PMCID: PMC10673997 DOI: 10.1038/s41398-023-02665-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 10/23/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023] Open
Abstract
Astrocytic dysfunction contributes to the molecular pathogenesis of major depressive disorder (MDD). However, the astrocytic subtype that mainly contributes to MDD etiology and whether dysregulated autophagy in astrocytes is associated with MDD remain unknown. Using a single-nucleus RNA sequencing (snRNA-seq) atlas, three astrocyte subtypes were identified in MDD, while C2 State-1Q astrocytes showed aberrant changes in both cell proportion and most differentially expressed genes compared with other subtypes. Moreover, autophagy pathways were commonly inhibited in astrocytes in the prefrontal cortices (PFCs) of patients with MDD, especially in C2 State-1Q astrocytes. Furthermore, by integrating snRNA-seq and bulk transcriptomic data, we found significant reductions in LC3A expression levels in the PFC region of CUMS-induced depressed mice, as well as in postmortem PFC tissues and peripheral blood samples from patients with MDD. These results were further validated by qPCR using whole-blood samples from patients with MDD and healthy controls. Finally, LC3A expression in the whole blood of patients with MDD was negatively associated with the severity of depressive symptoms. Overall, our results underscore autophagy inhibition in PFC astrocytes as a common molecular characteristic in MDD and might reveal a novel potential diagnostic marker LC3A.
Collapse
Affiliation(s)
- Shen He
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yue Shi
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinmei Ye
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiahui Yin
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yufang Yang
- School of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Dan Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ting Shen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Duan Zeng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Siyuan Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feikang Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiyun Cai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Faming Zhao
- Key Laboratory of Environmental Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Huafang Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Daihui Peng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| |
Collapse
|
91
|
Li P, Wei J, Zhu Y. CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation. Brief Bioinform 2023; 25:bbad417. [PMID: 37995133 PMCID: PMC10790717 DOI: 10.1093/bib/bbad417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/09/2023] [Accepted: 10/29/2023] [Indexed: 11/25/2023] Open
Abstract
Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this limitation, we introduced CellGO. CellGO tackles this challenge by leveraging the visible neural network (VNN) and single-cell gene expressions to mimic cell-type-specific signaling propagation along the Gene Ontology tree within a cell. This design enables a novel scoring system to calculate the cell-type-specific gene-pathway paired active scores, based on which, CellGO is able to identify cell-type-specific active pathways associated with single genes. In addition, by aggregating the activities of single genes, CellGO extends its capability to identify cell-type-specific active pathways for a given gene set. To enhance biological interpretation, CellGO offers additional features, including the identification of significantly active cell types and driver genes and community analysis of pathways. To validate its performance, CellGO was assessed using a gene set comprising mixed cell-type markers, confirming its ability to discern active pathways across distinct cell types. Subsequent benchmarking analyses demonstrated CellGO's superiority in effectively identifying cell types and their corresponding cell-type-specific pathways affected by gene knockouts, using either single genes or sets of genes differentially expressed between knockout and control samples. Moreover, CellGO demonstrated its ability to infer cell-type-specific pathogenesis for disease risk genes. Accessible as a Python package, CellGO also provides a user-friendly web interface, making it a versatile and accessible tool for researchers in the field.
Collapse
Affiliation(s)
- Peilong Li
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200032, China
| | - Junfeng Wei
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200032, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200032, China
| |
Collapse
|
92
|
Herb BR, Glover HJ, Bhaduri A, Colantuoni C, Bale TL, Siletti K, Hodge R, Lein E, Kriegstein AR, Doege CA, Ament SA. Single-cell genomics reveals region-specific developmental trajectories underlying neuronal diversity in the human hypothalamus. SCIENCE ADVANCES 2023; 9:eadf6251. [PMID: 37939194 PMCID: PMC10631741 DOI: 10.1126/sciadv.adf6251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 10/24/2023] [Indexed: 11/10/2023]
Abstract
The development and diversity of neuronal subtypes in the human hypothalamus has been insufficiently characterized. To address this, we integrated transcriptomic data from 241,096 cells (126,840 newly generated) in the prenatal and adult human hypothalamus to reveal a temporal trajectory from proliferative stem cell populations to mature hypothalamic cell types. Iterative clustering of the adult neurons identified 108 robust transcriptionally distinct neuronal subtypes representing 10 hypothalamic nuclei. Pseudotime trajectories provided insights into the genes driving formation of these nuclei. Comparisons to single-cell transcriptomic data from the mouse hypothalamus suggested extensive conservation of neuronal subtypes despite certain differences in species-enriched gene expression. The uniqueness of hypothalamic neuronal lineages was examined developmentally by comparing excitatory lineages present in cortex and inhibitory lineages in ganglionic eminence, revealing both distinct and shared drivers of neuronal maturation across the human forebrain. These results provide a comprehensive transcriptomic view of human hypothalamus development through gestation and adulthood at cellular resolution.
Collapse
Affiliation(s)
- Brian R. Herb
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD, USA
- UM-MIND, University of Maryland School of Medicine, Baltimore, MD, USA
- Kahlert Institute for Addiction Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hannah J. Glover
- Naomi Berrie Diabetes Center, Columbia Stem Cell Initiative, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Aparna Bhaduri
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Carlo Colantuoni
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tracy L. Bale
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO, USA
| | - Kimberly Siletti
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Rebecca Hodge
- Allen Institute for Brain Science, Seattle, WA 98109
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA 98109
| | - Arnold R. Kriegstein
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, USA
| | - Claudia A. Doege
- Naomi Berrie Diabetes Center, Columbia Stem Cell Initiative, Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Seth A. Ament
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- UM-MIND, University of Maryland School of Medicine, Baltimore, MD, USA
- Kahlert Institute for Addiction Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| |
Collapse
|
93
|
Kim SN, Viswanadham VV, Doan RN, Dou Y, Bizzotto S, Khoshkhoo S, Huang AY, Yeh R, Chhouk B, Truong A, Chappell KM, Beaudin M, Barton A, Akula SK, Rento L, Lodato M, Ganz J, Szeto RA, Li P, Tsai JW, Hill RS, Park PJ, Walsh CA. Cell lineage analysis with somatic mutations reveals late divergence of neuronal cell types and cortical areas in human cerebral cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565899. [PMID: 37986891 PMCID: PMC10659282 DOI: 10.1101/2023.11.06.565899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The mammalian cerebral cortex shows functional specialization into regions with distinct neuronal compositions, most strikingly in the human brain, but little is known in about how cellular lineages shape cortical regional variation and neuronal cell types during development. Here, we use somatic single nucleotide variants (sSNVs) to map lineages of neuronal sub-types and cortical regions. Early-occurring sSNVs rarely respect Brodmann area (BA) borders, while late-occurring sSNVs mark neuron-generating clones with modest regional restriction, though descendants often dispersed into neighboring BAs. Nevertheless, in visual cortex, BA17 contains 30-70% more sSNVs compared to the neighboring BA18, with clones across the BA17/18 border distributed asymmetrically and thus displaying different cortex-wide dispersion patterns. Moreover, we find that excitatory neuron-generating clones with modest regional restriction consistently share low-mosaic sSNVs with some inhibitory neurons, suggesting significant co-generation of excitatory and some inhibitory neurons in the dorsal cortex. Our analysis reveals human-specific cortical cell lineage patterns, with both regional inhomogeneities in progenitor proliferation and late divergence of excitatory/inhibitory lineages.
Collapse
Affiliation(s)
- Sonia Nan Kim
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, 02115, MA, USA
| | - Vinayak V. Viswanadham
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA
- Bioinformatics and Integrative Genomics Program, Harvard Medical School, Boston, 02115, MA, USA
| | - Ryan N. Doan
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
| | - Yanmei Dou
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA
| | - Sara Bizzotto
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Sattar Khoshkhoo
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, 02115, MA, USA
| | - August Yue Huang
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Rebecca Yeh
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
| | - Brian Chhouk
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
| | - Alex Truong
- Research Computing, Harvard Medical School, Boston, 02115, MA, USA
| | | | - Marc Beaudin
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
| | - Alison Barton
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA
- Bioinformatics and Integrative Genomics Program, Harvard Medical School, Boston, 02115, MA, USA
| | - Shyam K. Akula
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
| | - Lariza Rento
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
| | - Michael Lodato
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Javier Ganz
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Ryan A. Szeto
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, 02115, MA, USA
| | - Pengpeng Li
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Jessica W. Tsai
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
| | - Robert Sean Hill
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Peter J. Park
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA
| | - Christopher A. Walsh
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, 02115, MA, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, 02115, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, 02115, MA, USA
| |
Collapse
|
94
|
Zhang R, Quan H, Wang Y, Luo F. Neurogenesis in primates versus rodents and the value of non-human primate models. Natl Sci Rev 2023; 10:nwad248. [PMID: 38025664 PMCID: PMC10659238 DOI: 10.1093/nsr/nwad248] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/21/2023] [Accepted: 09/10/2023] [Indexed: 12/01/2023] Open
Abstract
Neurogenesis, the process of generating neurons from neural stem cells, occurs during both embryonic and adult stages, with each stage possessing distinct characteristics. Dysfunction in either stage can disrupt normal neural development, impair cognitive functions, and lead to various neurological disorders. Recent technological advancements in single-cell multiomics and gene-editing have facilitated investigations into primate neurogenesis. Here, we provide a comprehensive overview of neurogenesis across rodents, non-human primates, and humans, covering embryonic development to adulthood and focusing on the conservation and diversity among species. While non-human primates, especially monkeys, serve as valuable models with closer neural resemblance to humans, we highlight the potential impacts and limitations of non-human primate models on both physiological and pathological neurogenesis research.
Collapse
Affiliation(s)
- Runrui Zhang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Hongxin Quan
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Yinfeng Wang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Fucheng Luo
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| |
Collapse
|
95
|
Konopka G, Bhaduri A. Functional genomics and systems biology in human neuroscience. Nature 2023; 623:274-282. [PMID: 37938705 DOI: 10.1038/s41586-023-06686-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 09/27/2023] [Indexed: 11/09/2023]
Abstract
Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena.
Collapse
Affiliation(s)
- Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, USA.
- Peter O'Donnell Jr Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Aparna Bhaduri
- Department of Biological Chemistry, University of California, Los Angeles, CA, USA.
| |
Collapse
|
96
|
De Donno C, Hediyeh-Zadeh S, Moinfar AA, Wagenstetter M, Zappia L, Lotfollahi M, Theis FJ. Population-level integration of single-cell datasets enables multi-scale analysis across samples. Nat Methods 2023; 20:1683-1692. [PMID: 37813989 PMCID: PMC10630133 DOI: 10.1038/s41592-023-02035-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 09/05/2023] [Indexed: 10/11/2023]
Abstract
The increasing generation of population-level single-cell atlases has the potential to link sample metadata with cellular data. Constructing such references requires integration of heterogeneous cohorts with varying metadata. Here we present single-cell population level integration (scPoli), an open-world learner that incorporates generative models to learn sample and cell representations for data integration, label transfer and reference mapping. We applied scPoli on population-level atlases of lung and peripheral blood mononuclear cells, the latter consisting of 7.8 million cells across 2,375 samples. We demonstrate that scPoli can explain sample-level biological and technical variations using sample embeddings revealing genes associated with batch effects and biological effects. scPoli is further applicable to single-cell sequencing assay for transposase-accessible chromatin and cross-species datasets, offering insights into chromatin accessibility and comparative genomics. We envision scPoli becoming an important tool for population-level single-cell data integration facilitating atlas use but also interpretation by means of multi-scale analyses.
Collapse
Affiliation(s)
- Carlo De Donno
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
| | | | - Amir Ali Moinfar
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- School of Computing, Information and Technology, Technical University of Munich, Munich, Germany
| | - Marco Wagenstetter
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
| | - Luke Zappia
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- School of Computing, Information and Technology, Technical University of Munich, Munich, Germany
| | - Mohammad Lotfollahi
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany.
- School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.
- School of Computing, Information and Technology, Technical University of Munich, Munich, Germany.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| |
Collapse
|
97
|
Suresh H, Crow M, Jorstad N, Hodge R, Lein E, Dobin A, Bakken T, Gillis J. Comparative single-cell transcriptomic analysis of primate brains highlights human-specific regulatory evolution. Nat Ecol Evol 2023; 7:1930-1943. [PMID: 37667001 PMCID: PMC10627823 DOI: 10.1038/s41559-023-02186-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 08/02/2023] [Indexed: 09/06/2023]
Abstract
Enhanced cognitive function in humans is hypothesized to result from cortical expansion and increased cellular diversity. However, the mechanisms that drive these phenotypic innovations remain poorly understood, in part because of the lack of high-quality cellular resolution data in human and non-human primates. Here, we take advantage of single-cell expression data from the middle temporal gyrus of five primates (human, chimp, gorilla, macaque and marmoset) to identify 57 homologous cell types and generate cell type-specific gene co-expression networks for comparative analysis. Although orthologue expression patterns are generally well conserved, we find 24% of genes with extensive differences between human and non-human primates (3,383 out of 14,131), which are also associated with multiple brain disorders. To assess the functional significance of gene expression differences in an evolutionary context, we evaluate changes in network connectivity across meta-analytic co-expression networks from 19 animals. We find that a subset of these genes has deeply conserved co-expression across all non-human animals, and strongly divergent co-expression relationships in humans (139 out of 3,383, <1% of primate orthologues). Genes with human-specific cellular expression and co-expression profiles (such as NHEJ1, GTF2H2, C2 and BBS5) typically evolve under relaxed selective constraints and may drive rapid evolutionary change in brain function.
Collapse
Affiliation(s)
- Hamsini Suresh
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | | | | | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Alexander Dobin
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Jesse Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada.
| |
Collapse
|
98
|
Kogan E, Lu J, Zuo Y. Cortical circuit dynamics underlying motor skill learning: from rodents to humans. Front Mol Neurosci 2023; 16:1292685. [PMID: 37965043 PMCID: PMC10641381 DOI: 10.3389/fnmol.2023.1292685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 10/11/2023] [Indexed: 11/16/2023] Open
Abstract
Motor learning is crucial for the survival of many animals. Acquiring a new motor skill involves complex alterations in both local neural circuits in many brain regions and long-range connections between them. Such changes can be observed anatomically and functionally. The primary motor cortex (M1) integrates information from diverse brain regions and plays a pivotal role in the acquisition and refinement of new motor skills. In this review, we discuss how motor learning affects the M1 at synaptic, cellular, and circuit levels. Wherever applicable, we attempt to relate and compare findings in humans, non-human primates, and rodents. Understanding the underlying principles shared by different species will deepen our understanding of the neurobiological and computational basis of motor learning.
Collapse
Affiliation(s)
| | | | - Yi Zuo
- Department of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, Santa Cruz, CA, United States
| |
Collapse
|
99
|
Zhang R, Yang M, Schreiber J, O'Day DR, Turner JMA, Shendure J, Disteche CM, Deng X, Noble WS. Cross-species imputation and comparison of single-cell transcriptomic profiles. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.19.563173. [PMID: 37905060 PMCID: PMC10614954 DOI: 10.1101/2023.10.19.563173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.
Collapse
Affiliation(s)
- Ran Zhang
- Department of Genome Sciences, University of Washington
- eScience Institute, University of Washington
| | - Mu Yang
- Department of Biomedical Informatics and Medical Education, University of Washington
| | | | - Diana R O'Day
- Brotman Baty Institute for Precision Medicine, University of Washington
| | | | - Jay Shendure
- Department of Genome Sciences, University of Washington
- Brotman Baty Institute for Precision Medicine, University of Washington
- Howard Hughes Medical Institute
- Allen Center for Cell Lineage Tracing
| | - Christine M Disteche
- Department of Laboratory Medicine and Pathology, University of Washington
- Department of Medicine, University of Washington
| | - Xinxian Deng
- Department of Laboratory Medicine and Pathology, University of Washington
| | - William Stafford Noble
- Department of Genome Sciences, University of Washington
- Paul G. Allen School of Computer Science and Engineering, University of Washington
| |
Collapse
|
100
|
Lodge DJ, Elam HB, Boley AM, Donegan JJ. Discrete hippocampal projections are differentially regulated by parvalbumin and somatostatin interneurons. Nat Commun 2023; 14:6653. [PMID: 37863893 PMCID: PMC10589277 DOI: 10.1038/s41467-023-42484-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 10/12/2023] [Indexed: 10/22/2023] Open
Abstract
People with schizophrenia show hyperactivity in the ventral hippocampus (vHipp) and we have previously demonstrated distinct behavioral roles for vHipp cell populations. Here, we test the hypothesis that parvalbumin (PV) and somatostatin (SST) interneurons differentially innervate and regulate hippocampal pyramidal neurons based on their projection target. First, we use eGRASP to show that PV-positive interneurons form a similar number of synaptic connections with pyramidal cells regardless of their projection target while SST-positive interneurons preferentially target nucleus accumbens (NAc) projections. To determine if these anatomical differences result in functional changes, we used in vivo opto-electrophysiology to show that SST cells also preferentially regulate the activity of NAc-projecting cells. These results suggest vHipp interneurons differentially regulate that vHipp neurons that project to the medial prefrontal cortex (mPFC) and NAc. Characterization of these cell populations may provide potential molecular targets for the treatment schizophrenia and other psychiatric disorders associated with vHipp dysfunction.
Collapse
Affiliation(s)
- Daniel J Lodge
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, Audie L. Murphy Division, San Antonio, TX, USA
| | - Hannah B Elam
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, Audie L. Murphy Division, San Antonio, TX, USA
| | - Angela M Boley
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, Audie L. Murphy Division, San Antonio, TX, USA
| | - Jennifer J Donegan
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA.
- Department of Psychiatry and Behavioral Sciences and Center for Early Life Adversity, Department of Neuroscience, Dell Medical School at the University of Texas at Austin, Austin, TX, 78712, USA.
| |
Collapse
|