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Inaccurate cell segmentation has been the major problem for cell-type identification and tissue characterization of the in situ spatially resolved transcriptomics data. Here we show a robust cell segmentation-free computational framework (SSAM), for identifying cell types and tissue domains in 2D and 3D.

RNA-sequencing analysis of cells in the human cortex enabled identification of diverse cell types, revealing well-conserved architecture and homologous cell types as well as extensive differences when compared with datasets covering the analogous region of the mouse brain.

Transcriptional profiling and axonal reconstructions identify two types of pyramidal tract neuron in the motor cortex: one type projects to thalamic regions and produces early and persistent preparatory activity, and the other type projects to motor centres in the medulla and produces motor commands.

A comprehensive single-cell RNA sequencing study delineates cell-type-specific transcriptomic changes in the brain associated with normal ageing that will inform the investigation into functional changes and the interaction of ageing and disease.

Although single-cell gene expression profiling has been possible for the past two decades, a number of recent technological advances in microfluidic and sequencing technology have recently made the procedure much easier and less expensive. Awatramani and colleagues discuss the use of single-cell gene expression profiling for classifying neuronal cell types.

 A transcriptomic cell-type atlas of the whole adult mouse brain with ~5,300 clusters built from single-cell and spatial transcriptomic datasets with more than eight million cells reveals remarkable cell type diversity across the brain and unique cell type characteristics of different brain regions. 

This paper discusses how experimental and computational studies integrating multimodal data, such as RNA expression, connectivity and neural activity, are advancing our understanding of the architecture, mechanisms and function of cortical circuits.

Methylome-based clustering and cross-modality integration with companion datasets from the BRAIN Initiative Cell Census Network enabled the construction of a 3D multi-omic genome atlas of the adult mouse brain featuring thousands of cell-type-specific profiles.

In this study, the authors develop a comprehensive taxonomy of brain-wide SPNs, identifying several novel subsets via their transcriptional signatures.

An atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain unravels the transcriptional regulatory programs that drive the heterogeneity and complexity of brain structure and function.

A comprehensive cell atlas of the whole mouse brain with high molecular and spatial resolution is generated.

This study uses epi-retro-seq to link single-cell epigenomes and cell types to long-distance projections for neurons dissected from different regions projecting to different targets across the whole mouse brain.

Combined patch clamp recording, biocytin staining and single-cell RNA-sequencing of human neurocortical neurons shows an expansion of glutamatergic neuron types relative to mouse that characterizes the greater complexity of the human neocortex.

Cell type epigenetic and topographic information of primate brain is lacking. Here, authors identified transcriptional regulatory network, gradient expression pattern and disease vulnerability at cell type level in PFC, M1 and V1 of monkey brain by snRNAseq, snATAC-seq and Stereo-seq.

Sparse labelling and whole-brain imaging are used to reconstruct and classify brain-wide complete morphologies of 1,741 individual neurons in the mouse brain, revealing a dependence on both brain region and transcriptomic profile.

An examination of motor cortex in humans, marmosets and mice reveals a generally conserved cellular makeup that is likely to extend to many mammalian species, but also differences in gene expression, DNA methylation and chromatin state that lead to species-dependent specializations.

The authors describe an integrated atlas of the diverse cell types in the mouse primary motor cortex.

Mammalian cortex comprises a variety of cells, but the extent of this cellular diversity is unknown. The authors defined cell types in the primary visual cortex of adult mice using single-cell transcriptomics. This revealed 49 cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types.

Single-cell transcriptomics of more than 20,000 cells from two functionally distinct areas of the mouse neocortex identifies 133 transcriptomic types, and provides a foundation for understanding the diversity of cortical cell types.

Light-dependent variants of Cre, Dre and Flp enable targeted sparse or single-cell labeling in mouse and zebrafish.

Gouwens et al. established a morpho-electrical taxonomy of cell types for the mouse visual cortex via unsupervised clustering analysis of multiple quantitative features from 1,938 neurons available online at the Allen Cell Types Database.

The authors developed an optimized rabies tracing system for generating brain-wide monosynaptic input connectomes, and applied it in mouse visual cortex to reveal topographically organized subnetworks co-defined by visual areas, layers and cell classes.

Aligning multimodal data for cell type research is a challenging problem in neuroscience. Coupled autoencoders, a deep neural network-based methodology, can be used to effectively address this task.

David Kingsley and colleagues functionally investigate a previously identified GWAS region in an enhancer of the KITLG gene (encoding KIT ligand) that is significantly associated with blond hair color in northern European populations. They show that a single regulatory SNP, located 350,000 bp upstream of the human gene, reduces the activity of a tissue-specific hair follicle enhancer and is sufficient to alter hair color in mice.

Identification of sleep-active and sleep-promoting neurons in the preoptic area of the hypothalamus using neural projection tracing tools to target this population among a group of intermingled neurons, all with various functions.

The BRAIN Initiative Cell Census Network has constructed a multimodal cell census and atlas of the mammalian primary motor cortex in a landmark effort towards understanding brain cell-type diversity, neural circuit organization and brain function.

In order to identify receptors that may serve as therapeutic targets in the treatment of impulse control disorders, van der Veen et al developed a systematic target discovery approach combining behavioural chemogenetics and gene expression analysis. In doing so, they identified Gi-coupled receptors in layer-5 pyramidal cells of the anterior cingulate cortex as potential therapeutic targets, which could pave the way for the development of treatments.