Cell type-specific transcriptional programs in mouse prefrontal cortex during adolescence and addiction

Bhattacherjee, Aritra; Djekidel, Mohamed Nadhir; Chen, Renchao; Chen, Wenqiang; Tuesta, Luis M.; Zhang, Yi

doi:10.1038/s41467-019-12054-3

Cited by 132 publications

(182 citation statements)

References 78 publications

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“…How do we reconcile these contrasting views? Our PFC single-cell dataset uncovered transcriptomic cell types consistent with those from studies that profiled the mouse brain exhaustively (Saunders et al, 2018;Zeisel et al, 2018), other parts of the neocortex , or PFC more specifically (Bhattacherjee et al, 2019), but we solely focused on using Layer 5 pyramidal neuron subtypes and their projection mapping as a case study to interrogate task encoding properties with a cell-type framework. Using PAG-projecting neurons as an example of molecular homogeneity due to our observation of its invariant clustering across multiple resolutions and methods (Figures 1E, S1B), we found that even a homogeneous transcriptomic class encodes diverse information.…”

Section: Discussionmentioning

confidence: 99%

Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks

Lui

Nguyen

Grutzner

et al. 2020

Preprint

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Single-cell transcriptomics has been widely applied to classify neurons in the mammalian brain, while systems neuroscience has historically analyzed the encoding properties of cortical neurons without considering cell types. Here we examine how specific transcriptomic types of mouse prefrontal cortex (PFC) projection neurons relate to axonal projections and encoding properties across multiple cognitive tasks. We found that most types projected to multiple targets, and most targets received projections from multiple types, except PFC→PAG (periaqueductal gray). By comparing Ca 2+ -activity of the molecularly homogeneous PFC→PAG type against two heterogeneous classes in several two-alternative choice tasks in freely-moving mice, we found that all task-related signals assayed were qualitatively present in all examined classes. However, PAG-projecting neurons most potently encoded choice in cued tasks, whereas contralateral PFC-projecting neurons most potently encoded reward context in an uncued task. Thus, task signals are organized redundantly, but with clear quantitative biases across cells of specific molecular-anatomical characteristics.

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Section: Discussionmentioning

confidence: 99%

Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks

Lui

Nguyen

Grutzner

et al. 2020

Preprint

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“…The PFC data set (Bhattacherjee et al 2019) consists of cells from the prefrontal cortex of an adult mouse, and was generated using 10x Genomics Chromium v2 chemistry. Since only limited dynamics is expected in this data set, it is used here as a negative control.…”

Section: Methodsmentioning

confidence: 99%

Preprocessing choices affect RNA velocity results for droplet scRNA-seq data

Soneson

Srivastava

Patro

et al. 2020

Preprint

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12Experimental single-cell approaches are becoming widely used for many purposes, including inves-13 tigation of the dynamic behaviour of developing biological systems. Consequently, a large number 14 of computational methods for extracting dynamic information from such data have been developed. 15 One example is RNA velocity analysis, in which spliced and unspliced RNA abundances are jointly 16 modeled in order to infer a 'direction of change' and thereby a future state for each cell in the gene 17 expression space. 18 Naturally, the accuracy and interpretability of the inferred RNA velocities depend crucially on the 19 correctness of the estimated abundances. Here, we systematically compare four widely used quan-20 tification tools, in total yielding twelve different quantification approaches, in terms of their estimates 21 of spliced and unspliced RNA abundances in four experimental droplet scRNA-seq data sets. We 22show that there are substantial differences between the quantifications obtained from different tools, 23 and identify typical genes for which such discrepancies are observed. We further show that these 24 abundance differences propagate to the downstream analysis, and can have a large effect on estimated 25 velocities as well as the biological interpretation. 26Our results highlight that abundance quantification is a crucial aspect of the RNA velocity anal-27 ysis workflow, and that both the definition of the genomic features of interest and the quantification 28 algorithm itself require careful consideration. 29 Single-cell RNA-seq (scRNA-seq) enables high-throughput profiling of gene expression on a transcriptome-31 wide scale in individual cells. The increased resolution compared to bulk RNA-seq, where only average 32 expression profiles of populations of cells are obtained, provides vastly improved potential to study 33 a variety of biological questions. One such question concerns the dynamics of biological systems, re-34 flected in, e.g., cellular differentiation and development. While such dynamical processes would ideally 35 be studied via repeated transcriptome-wide expression profiling of the same cells over time, this is not 36 possible with current scRNA-seq protocols. Existing analysis methods for so called trajectory inference 37 are instead applied to one or several snapshots of a population of cells, assumed to comprise all stages 38 of the trajectory of interest. Many computational methods for trajectory inference from scRNA-seq have 39 been presented in the literature (reviewed by Saelens et al. (2019)). These methods typically use the 40 similarity of the gene expression profiles between cells to construct a (possibly branching) path through 41 the observed set of cells, representing the trajectory of interest. Projecting the cells onto this path then 42 provides an ordering of the cells by so called pseudotime. 43 A different approach to the investigation of developmental processes in scRNA-seq data instead 44 exploits the underlying molecular dynamics. The feasibility of ...

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“…Different neuronal subtypes in mPFC play various roles in encoding and regulating behaviors 24 . To examine what are the specific types of neurons that involve in impulsive behaviors, we performed double-immunofluorescent staining of CaMKIIα and c-Fos (Fig.…”

Section: Postnatal Sevoflurane Exposure Showed Adhd-like Impulsive Bementioning

confidence: 99%

Neonatal sevoflurane exposure induces impulsive behavioral deficit through disrupting excitatory neurons in the medial prefrontal cortex in mice

Xie

Liu

et al. 2020

Transl Psychiatry

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Sevoflurane, in particular multiple exposures, has been reported to cause the abnormal neurological development including attention-deficit/hyperactivity disorder (ADHD). This study is to investigate ADHD-like impulsivity in adult mice after repeated sevoflurane exposures at the neonatal stage. Six-day-old pups were exposed to 60% oxygen in the presence or absence of 3% sevoflurane for 2 h and the treatment was administrated once daily for three consecutive days. To assess the impulsivity, the cliff avoidance reaction (CAR) was carried out at the 8th week. Our results showed that repeated sevoflurane treatment increased the number of jumps and shortened the jumping latency in the CAR test. The cortices were harvested for immunostaining to detect c-Fos and calmodulin-dependent protein kinase IIα (CaMKIIα) expression in the medial prefrontal cortex (mPFC). We found that mPFC neurons, especially excitatory neurons, were highly activated and related to impulsive behavior. The activation viruses (AAV-CaMKIIα-hM3Dq) were injected to evaluate the effects of specific activation of mPFC excitatory neurons on impulsive behavior in the presence of clozapine-N-oxide (CNO). Likewise, the inhibitory viruses (AAV-CaMKIIα-hM4Di) were injected in the sevoflurane group to explore whether the mPFC excitatory neuronal inhibition reduced the impulsivity. Our results revealed that chemogenetic activation of mPFC excitatory neurons induced impulsive behavior whereas inhibition of mPFC excitatory neurons partially rescued the deficit. These results indicate that repeated sevoflurane exposures at the critical time induce impulsive behavior accompanied with overactivation of mPFC excitatory neurons in adult stages. This work may further extend to understand the ADHD-like impulsive behavior of the anesthetic neurotoxicity.

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Cell type-specific transcriptional programs in mouse prefrontal cortex during adolescence and addiction

Cited by 132 publications

References 78 publications

Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks

Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks

Preprocessing choices affect RNA velocity results for droplet scRNA-seq data

Neonatal sevoflurane exposure induces impulsive behavioral deficit through disrupting excitatory neurons in the medial prefrontal cortex in mice

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