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The recent development of single-cell genomic techniques allows us to profile gene expression at the single-cell level easily, although many of these methods have limited throughput. Rosenberg et al. describe a strategy called split-pool ligation-based transcriptome sequencing, or SPLiT-seq, which uses combinatorial barcoding to profile single-cell transcriptomes without requiring the physical isolation of each cell. The authors used their method to profile >100,000 single-cell transcriptomes from mouse brains and spinal cords at 2 and 11 days after birth. Comparisons with in situ hybridization data on RNA expression from Allen Institute atlases linked these transcriptomes with spatial mapping, from which developmental lineages could be identified. Science , this issue p. 176 Single-cell analyses with SPLiT-seq (split-pool ligation-based transcriptome sequencing) elucidate development of the mouse nervous system. To facilitate scalable profiling of single cells, we developed split-pool ligation-based transcriptome sequencing (SPLiT-seq), a single-cell RNA-seq (scRNA-seq) method that labels the cellular origin of RNA through combinatorial barcoding. SPLiT-seq is compatible with fixed cells or nuclei, allows efficient sample multiplexing, and requires no customized equipment. We used SPLiT-seq to analyze 156,049 single-nucleus transcriptomes from postnatal day 2 and 11 mouse brains and spinal cords. More than 100 cell types were identified, with gene expression patterns corresponding to cellular function, regional specificity, and stage of differentiation. Pseudotime analysis revealed transcriptional programs driving four developmental lineages, providing a snapshot of early postnatal development in the murine central nervous system. SPLiT-seq provides a path toward comprehensive single-cell transcriptomic analysis of other similarly complex multicellular systems.

Multiplexed fluorescence in situ hybridization techniques have enabled cell-type identification, linking transcriptional heterogeneity with spatial heterogeneity of cells. However, inaccurate cell segmentation reduces the efficacy of cell-type identification and tissue characterization. Here, we present a method called Spot-based Spatial cell-type Analysis by Multidimensional mRNA density estimation (SSAM), a robust cell segmentation-free computational framework for identifying cell-types and tissue domains in 2D and 3D. SSAM is applicable to a variety of in situ transcriptomics techniques and capable of integrating prior knowledge of cell types. We apply SSAM to three mouse brain tissue images: the somatosensory cortex imaged by osmFISH, the hypothalamic preoptic region by MERFISH, and the visual cortex by multiplexed smFISH. Here, we show that SSAM detects regions occupied by known cell types that were previously missed and discovers new cell types. 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.

Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

Brain circuits comprise vast numbers of interconnected neurons with diverse molecular, anatomical and physiological properties. To allow targeting of individual neurons for structural and functional studies, we created light-inducible site-specific DNA recombinases based on Cre, Dre and Flp (RecVs). RecVs can induce genomic modifications by one-photon or two-photon light induction in vivo. They can produce targeted, sparse and strong labeling of individual neurons by modifying multiple loci within mouse and zebrafish genomes. In combination with other genetic strategies, they allow intersectional targeting of different neuronal classes. In the mouse cortex they enable sparse labeling and whole-brain morphological reconstructions of individual neurons. Furthermore, these enzymes allow single-cell two-photon targeted genetic modifications and can be used in combination with functional optical indicators with minimal interference. In summary, RecVs enable spatiotemporally precise optogenomic modifications that can facilitate detailed single-cell analysis of neural circuits by linking genetic identity, morphology, connectivity and function. Light-dependent variants of Cre, Dre and Flp enable targeted sparse or single-cell labeling in mouse and zebrafish.

Cortical circuit tracing using modified rabies virus can identify input neurons making direct monosynaptic connections onto neurons of interest. However, challenges remain in our ability to establish the cell type identity of rabies-labeled input neurons. While transcriptomics may offer an avenue to characterize inputs, the extent of rabies-induced transcriptional changes in distinct neuronal cell types remains unclear, and whether these changes preclude characterization of rabies-infected neurons according to established transcriptomic cell types is unknown. We used single-nucleus RNA sequencing to survey the gene expression profiles of rabies-infected neurons and assessed their correspondence with established transcriptomic cell types. We demonstrated that when using transcriptome-wide RNA profiles, rabies-infected cortical neurons can be transcriptomically characterized despite global and cell-type-specific rabies-induced transcriptional changes. Notably, we found differential modulation of neuronal marker gene expression, suggesting that caution should be taken when attempting to characterize rabies-infected cells with single genes or small gene sets.

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. Hair color differences are among the most obvious examples of phenotypic variation in humans. Although genome-wide association studies (GWAS) have implicated multiple loci in human pigment variation, the causative base-pair changes are still largely unknown 1 . Here we dissect a regulatory region of the KITLG gene (encoding KIT ligand) that is significantly associated with common blond hair color in northern Europeans 2 . Functional tests demonstrate that the region contains a regulatory enhancer that drives expression in developing hair follicles. This enhancer contains a common SNP (rs12821256) that alters a binding site for the lymphoid enhancer-binding factor 1 (LEF1) transcription factor, reducing LEF1 responsiveness and enhancer activity in cultured human keratinocytes. Mice carrying ancestral or derived variants of the human KITLG enhancer exhibit significant differences in hair pigmentation, confirming that altered regulation of an essential growth factor contributes to the classic blond hair phenotype found in northern Europeans.

Defining cell types in situ connects gene expression, anatomy, and function during certain behaviors A full understanding of a complex system is difficult, perhaps impossible, to accomplish without an inventory of the components involved. When that system is an organ in an organism, the parts list becomes a census of cell types, including their identity, number, location, and function. On page 792 of this issue, Moffitt et al. ( 1 ) demonstrate an advanced method for in situ profiling of gene expression within the preoptic region of the intact mouse hypothalamus. Their approach not only yields a census of cell types in this region of the brain, but also assesses which cell types are activated during certain behaviors. This region of the brain is involved in the regulation of homeostasis and social behaviors such as aggression, sex, and parenting.

Abundant evidence supports the presence of at least three distinct types of thalamocortical (TC) neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex (V1). Different types of TC neurons in mice, humans, and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of TC neurons in the primate dLGN: magnocellular (M) neurons, parvocellular (P) neurons, and two types of koniocellular (K) neurons. Despite extensively documented morphological and physiological differences between M and P neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. Likewise, the dominant feature of TC neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to the observed differences in morphology and cortical projection targets. Finally, alignment of transcriptome profiles across species highlights expanded diversity of GABAergic neurons in primate versus mouse dLGN and homologous types of TC neurons in primates that are distinct from TC neurons in mouse.

The protein coding sequences of most eukaryotic messenger RNA precursors (pre-mRNAs) are interrupted by non-coding sequences called introns. Pre-mRNA splicing is the process by which introns are removed and the protein coding elements assembled into mature mRNAs. Alternative pre-mRNA splicing selectively joins different protein coding elements to form mRNAs that encode proteins with distinct functions, and is therefore an important source of protein diversity. The elaboration of this mechanism may have had a significant role in the expansion of metazoan proteomes during evolution.

In the mouse, each class of olfactory receptor neurons expressing a given odorant receptor has convergent axonal projections to two specific glomeruli in the olfactory bulb, thereby creating an odour map. However, it is unclear how this map is represented in the olfactory cortex. Here we combine rabies-virus-dependent retrograde mono-trans-synaptic labelling with genetics to control the location, number and type of ‘starter’ cortical neurons, from which we trace their presynaptic neurons. We find that individual cortical neurons receive input from multiple mitral cells representing broadly distributed glomeruli. Different cortical areas represent the olfactory bulb input differently. For example, the cortical amygdala preferentially receives dorsal olfactory bulb input, whereas the piriform cortex samples the whole olfactory bulb without obvious bias. These differences probably reflect different functions of these cortical areas in mediating innate odour preference or associative memory. The trans-synaptic labelling method described here should be widely applicable to mapping connections throughout the mouse nervous system. Scent tracking In the mouse, glomeruli in the olfactory bulb receive projections from single classes of olfactory neurons, thereby forming an odour map. Information from the glomeruli is then relayed to the cortex but the projection patterns from individual glomeruli are not known. Three papers now examine the details of this projection. Luo and colleagues use a combination of genetics and retrograde mono-trans-synaptic rabies virus labelling. They trace the presynaptic connections of individual cortical neurons and find no evidence of connections supporting a stereotyped odour map in the cortex, but see systematic topographical differences in amygdala connectivity. The lack of stereotypical cortical projection is corroborated, both at the level of bulk axonal patterning and in projections of individually labelled neurons, by two papers — one from the Axel laboratory, and one from the Baldwin laboratory — that examine the anterograde projections from individual glomeruli. Together, these findings provide anatomical evidence for combinatorial processing of information from diverse glomeruli by cortical neurons and may also reflect different functions of various areas in mediating innate or learned odour preferences.