The ANTsX Ecosystem for Mapping the Mouse Brain.

Precision mapping techniques coupled with high resolution image acquisition of the mouse brain permit the study of the spatial organization of gene expression and their mutual interaction for a comprehensive view of salient structural/functional relationships. Such research is facilitated by standardized anatomical coordinate systems, such as the well-known Allen Common Coordinate Framework (AllenCCFv3), and the ability to spatially map to such standardized spaces. The Advanced Normalization Tools Ecosystem is a comprehensive open-source software toolkit for generalized quantitative imaging with applicability to multiple organ systems, modalities, and animal species. Herein, we illustrate the utility of ANTsX for generating precision spatial mappings of the mouse brain and potential subsequent quantitation. We describe ANTsX-based workflows for mapping domain-specific image data to AllenCCFv3 accounting for common artefacts and other confounds. Novel contributions include ANTsX functionality for velocity flow-based mapping spanning the spatiotemporal domain of a longitudinal trajectory which we apply to the Developmental Common Coordinate Framework. Additionally, we present an automated structural morphological pipeline for determining volumetric and cortical thickness measurements analogous to the well-utilized ANTsX pipeline for human neuroanatomical structural morphology which illustrates a general open-source framework for tailored brain parcellations.

Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections.

This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging technology remain sparse and conventional image representations cannot efficiently model the high dimensions from subcellular detection of thousands of genes. We address these challenges by representing spatial transcriptomics data as generalized functions encoding position and high-dimensional feature (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling regions as homogeneous random fields with unknown transcriptomic feature distribution. We solve simultaneously for the minimizing geodesic diffeomorphism of coordinates through LDDMM and for these latent feature densities. We map tissue-scale mouse brain atlases to gene-based and cell-based transcriptomics data from MERFISH and BARseq technologies and to histopathology and cross-species atlases to illustrate integration of diverse molecular and cellular datasets into a single coordinate system as a means of comparison and further atlas construction.

A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons.

The brain controls nearly all bodily functions via spinal projecting neurons (SPNs) that carry command signals from the brain to the spinal cord. However, a comprehensive molecular characterization of brain-wide SPNs is still lacking. Here we transcriptionally profiled a total of 65,002 SPNs, identified 76 region-specific SPN types, and mapped these types into a companion atlas of the whole mouse brain1. This taxonomy reveals a three-component organization of SPNs: (1) molecularly homogeneous excitatory SPNs from the cortex, red nucleus and cerebellum with somatotopic spinal terminations suitable for point-to-point communication; (2) heterogeneous populations in the reticular formation with broad spinal termination patterns, suitable for relaying commands related to the activities of the entire spinal cord; and (3) modulatory neurons expressing slow-acting neurotransmitters and/or neuropeptides in the hypothalamus, midbrain and reticular formation for 'gain setting' of brain-spinal signals. In addition, this atlas revealed a LIM homeobox transcription factor code that parcellates the reticulospinal neurons into five molecularly distinct and spatially segregated populations. Finally, we found transcriptional signatures of a subset of SPNs with large soma size and correlated these with fast-firing electrophysiological properties. Together, this study establishes a comprehensive taxonomy of brain-wide SPNs and provides insight into the functional organization of SPNs in mediating brain control of bodily functions.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain.

The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties1-3. Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present an online platform, Allen Brain Cell Atlas, to visualize the mouse whole-brain cell-type atlas along with the single-cell RNA-sequencing and MERFISH datasets. We systematically analysed the neuronal and non-neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell-type organization in different brain regions-in particular, a dichotomy between the dorsal and ventral parts of the brain. The dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. Our study also uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types. Finally, we found that transcription factors are major determinants of cell-type classification and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole mouse brain transcriptomic and spatial cell-type atlas establishes a benchmark reference atlas and a foundational resource for integrative investigations of cellular and circuit function, development and evolution of the mammalian brain.

Enhancer-AAVs allow genetic access to oligodendrocytes and diverse populations of astrocytes across species.

Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and our astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their roles across species, disease states, and behavioral epochs.

Transcriptomic cytoarchitecture reveals principles of human neocortex organization.

Variation in cytoarchitecture is the basis for the histological definition of cortical areas. We used single cell transcriptomics and performed cellular characterization of the human cortex to better understand cortical areal specialization. Single-nucleus RNA-sequencing of 8 areas spanning cortical structural variation showed a highly consistent cellular makeup for 24 cell subclasses. However, proportions of excitatory neuron subclasses varied substantially, likely reflecting differences in connectivity across primary sensorimotor and association cortices. Laminar organization of astrocytes and oligodendrocytes also differed across areas. Primary visual cortex showed characteristic organization with major changes in the excitatory to inhibitory neuron ratio, expansion of layer 4 excitatory neurons, and specialized inhibitory neurons. These results lay the groundwork for a refined cellular and molecular characterization of human cortical cytoarchitecture and areal specialization.

Morphoelectric and transcriptomic divergence of the layer 1 interneuron repertoire in human versus mouse neocortex.

Neocortical layer 1 (L1) is a site of convergence between pyramidal-neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neurons with extensive L1 branching, but whether L1 interneurons are similarly diverse is underexplored. Using Patch-seq recordings from human neurosurgical tissue, we identified four transcriptomic subclasses with mouse L1 homologs, along with distinct subtypes and types unmatched in mouse L1. Subclass and subtype comparisons showed stronger transcriptomic differences in human L1 and were correlated with strong morphoelectric variability along dimensions distinct from mouse L1 variability. Accompanied by greater layer thickness and other cytoarchitecture changes, these findings suggest that L1 has diverged in evolution, reflecting the demands of regulating the expanded human neocortical circuit.

Signature morphoelectric properties of diverse GABAergic interneurons in the human neocortex.

Human cortex transcriptomic studies have revealed a hierarchical organization of γ-aminobutyric acid-producing (GABAergic) neurons from subclasses to a high diversity of more granular types. Rapid GABAergic neuron viral genetic labeling plus Patch-seq (patch-clamp electrophysiology plus single-cell RNA sequencing) sampling in human brain slices was used to reliably target and analyze GABAergic neuron subclasses and individual transcriptomic types. This characterization elucidated transitions between PVALB and SST subclasses, revealed morphological heterogeneity within an abundant transcriptomic type, identified multiple spatially distinct types of the primate-specialized double bouquet cells (DBCs), and shed light on cellular differences between homologous mouse and human neocortical GABAergic neuron types. These results highlight the importance of multimodal phenotypic characterization for refinement of emerging transcriptomic cell type taxonomies and for understanding conserved and specialized cellular properties of human brain cell types.

Integrated multimodal cell atlas of Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types. We used image-based quantitative neuropathology to place 84 donors spanning the spectrum of AD pathology along a continuous disease pseudoprogression score and multiomic technologies to profile single nuclei from each donor, mapping their transcriptomes, epigenomes, and spatial coordinates to a common cell type reference with unprecedented resolution. Temporal analysis of cell-type proportions indicated an early reduction of Somatostatin-expressing neuronal subtypes and a late decrease of supragranular intratelencephalic-projecting excitatory and Parvalbumin-expressing neurons, with increases in disease-associated microglial and astrocytic states. We found complex gene expression differences, ranging from global to cell type-specific effects. These effects showed different temporal patterns indicating diverse cellular perturbations as a function of disease progression. A subset of donors showed a particularly severe cellular and molecular phenotype, which correlated with steeper cognitive decline. We have created a freely available public resource to explore these data and to accelerate progress in AD research at SEA-AD.org.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain.

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

A Universal Method for Crossing Molecular and Atlas Modalities using Simplex-Based Image Varifolds and Quadratic Programming.

This paper explicates a solution to the problem of building correspondences between molecular-scale transcriptomics and tissue-scale atlases. The central model represents spatial transcriptomics as generalized functions encoding molecular position and high-dimensional transcriptomic-based (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling each atlas compartment as a homogeneous random field with unknown transcriptomic feature distribution. The algorithm presented solves simultaneously for the minimizing geodesic diffeomorphism of coordinates and latent atlas transcriptomic feature fractions by alternating LDDMM optimization for coordinate transformations and quadratic programming for the latent transcriptomic variables. We demonstrate the universality of the algorithm in mapping tissue atlases to gene-based and cell-based MERFISH datasets as well as to other tissue scale atlases. The joint estimation of diffeomorphisms and latent feature distributions allows integration of diverse molecular and cellular datasets into a single coordinate system and creates an avenue of comparison amongst atlas ontologies for continued future development.

A single-cell resolution gene expression atlas of the larval zebrafish brain.

The advent of multimodal brain atlases promises to accelerate progress in neuroscience by allowing in silico queries of neuron morphology, connectivity, and gene expression. We used multiplexed fluorescent in situ RNA hybridization chain reaction (HCR) technology to generate expression maps across the larval zebrafish brain for a growing set of marker genes. The data were registered to the Max Planck Zebrafish Brain (mapzebrain) atlas, thus allowing covisualization of gene expression, single-neuron tracings, and expertly curated anatomical segmentations. Using post hoc HCR labeling of the immediate early gene cfos, we mapped responses to prey stimuli and food ingestion across the brain of freely swimming larvae. This unbiased approach revealed, in addition to previously described visual and motor areas, a cluster of neurons in the secondary gustatory nucleus, which express the marker calb2a, as well as a specific neuropeptide Y receptor, and project to the hypothalamus. This discovery exemplifies the power of this new atlas resource for zebrafish neurobiology.

Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity.

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet, it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here, we recorded the activity from ∼40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven generative model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine (cRBM), unveils ∼200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. We then performed in silico perturbation experiments to determine the interregional functional connectivity, which is conserved across individual animals and correlates well with structural connectivity. Our results showcase how cRBMs can capture the coarse-grained organization of the zebrafish brain. Notably, this generative model can readily be deployed to parse neural data obtained by other large-scale recording techniques.

Rapid Effects of Selection on Brain-wide Activity and Behavior.

Interindividual variation in behavior and brain activity is universal and provides substrates for natural selection [1-9]. Selective pressures shift the expression of behavioral traits at the population level [10, 11], but the accompanying changes of the underlying neural circuitry have rarely been identified [12, 13]. Selection likely acts through the genetic and/or epigenetic underpinnings of neural activity controlling the selected behavior [14]. Endocrine and neuromodulatory systems participate in behavioral diversity and could provide the substrate for evolutionary modifications [15-21]. Here, we examined brain-wide patterns of activity in larval zebrafish selectively bred over two generations for extreme differences in habituation of the acoustic startle response (ASR) [22]. The ASR is an evolutionarily conserved defensive behavior induced by strong acoustic/vibrational stimuli. ASR habituation shows great individual variability that is stable over days and heritable [4, 22]. Selection for high ASR habituation leads to stronger sound-evoked activation of ASR-processing brain areas. In contrast, animals selected for low habituation displayed stronger spontaneous activity in ASR-processing centers. Ablation of dopaminergic tyrosine hydroxylase (TH) neurons decreased ASR sensitivity. Independently selected ASR habituation lineages link the effect of behavioral selection to dopaminergic caudal hypothalamus (HC) neurons [23]. High ASR habituation co-segregated with decreased spontaneous swimming phenotypes, but visual startle responses were unaffected. Furthermore, high- and low-habituation larvae differed in stress responses as adults. Thus, selective pressure over a couple of generations on ASR habituation behavior is able to induce substantial differences in brain activity, carrying along additional behaviors as piggyback traits that might further affect fitness in the wild. VIDEO ABSTRACT.

A Cellular-Resolution Atlas of the Larval Zebrafish Brain.

Understanding brain-wide neuronal dynamics requires a detailed map of the underlying circuit architecture. We built an interactive cellular-resolution atlas of the zebrafish brain at 6 days post-fertilization (dpf) based on the reconstructions of over 2,000 individually GFP-labeled neurons. We clustered our dataset in "morphotypes," establishing a unique database of quantitatively described neuronal morphologies together with their spatial coordinates in vivo. Over 100 transgene expression patterns were imaged separately and co-registered with the single-neuron atlas. By annotating 72 non-overlapping brain regions, we generated from our dataset an inter-areal wiring diagram of the larval brain, which serves as ground truth for synapse-scale, electron microscopic reconstructions. Interrogating our atlas by "virtual tract tracing" has already revealed previously unknown wiring principles in the tectum and the cerebellum. In conclusion, we present here an evolving computational resource and visualization tool, which will be essential to map function to structure in a vertebrate brain. VIDEO ABSTRACT.

Survival of Late Pleistocene Hunter-Gatherer Ancestry in the Iberian Peninsula.

The Iberian Peninsula in southwestern Europe represents an important test case for the study of human population movements during prehistoric periods. During the Last Glacial Maximum (LGM), the peninsula formed a periglacial refugium [1] for hunter-gatherers (HGs) and thus served as a potential source for the re-peopling of northern latitudes [2]. The post-LGM genetic signature was previously described as a cline from Western HG (WHG) to Eastern HG (EHG), further shaped by later Holocene expansions from the Near East and the North Pontic steppes [3-9]. Western and central Europe were dominated by ancestry associated with the ∼14,000-year-old individual from Villabruna, Italy, which had largely replaced earlier genetic ancestry, represented by 19,000-15,000-year-old individuals associated with the Magdalenian culture [2]. However, little is known about the genetic diversity in southern European refugia, the presence of distinct genetic clusters, and correspondence with geography. Here, we report new genome-wide data from 11 HGs and Neolithic individuals that highlight the late survival of Paleolithic ancestry in Iberia, reported previously in Magdalenian-associated individuals. We show that all Iberian HGs, including the oldest, a ∼19,000-year-old individual from El Mirón in Spain, carry dual ancestry from both Villabruna and the Magdalenian-related individuals. Thus, our results suggest an early connection between two potential refugia, resulting in a genetic ancestry that survived in later Iberian HGs. Our new genomic data from Iberian Early and Middle Neolithic individuals show that the dual Iberian HG genomic legacy pertains in the peninsula, suggesting that expanding farmers mixed with local HGs. VIDEO ABSTRACT.

Achilles is a circadian clock-controlled gene that regulates immune function in Drosophila.

The circadian clock is a transcriptional/translational feedback loop that drives the rhythmic expression of downstream mRNAs. Termed "clock-controlled genes," these molecular outputs of the circadian clock orchestrate cellular, metabolic, and behavioral rhythms. As part of our on-going work to characterize key upstream regulators of circadian mRNA expression, we have identified a novel clock-controlled gene in Drosophila melanogaster, Achilles (Achl), which is rhythmic at the mRNA level in the brain and which represses expression of antimicrobial peptides in the immune system. Achilles knock-down in neurons dramatically elevates expression of crucial immune response genes, including IM1 (Immune induced molecule 1), Mtk (Metchnikowin), and Drs (Drosomysin). As a result, flies with knocked-down Achilles expression are resistant to bacterial challenges. Meanwhile, no significant change in core clock gene expression and locomotor activity is observed, suggesting that Achilles influences rhythmic mRNA outputs rather than directly regulating the core timekeeping mechanism. Notably, Achilles knock-down in the absence of immune challenge significantly diminishes the fly's overall lifespan, indicating a behavioral or metabolic cost of constitutively activating this pathway. Together, our data demonstrate that (1) Achilles is a novel clock-controlled gene that (2) regulates the immune system, and (3) participates in signaling from neurons to immunological tissues.

Drosophila DH31 Neuropeptide and PDF Receptor Regulate Night-Onset Temperature Preference.

Body temperature exhibits rhythmic fluctuations over a 24 h period (Refinetti and Menaker, 1992) and decreases during the night, which is associated with sleep initiation (Gilbert et al., 2004; Kräuchi, 2007a,b). However, the underlying mechanism of this temperature decrease is largely unknown. We have previously shown that Drosophila exhibit a daily temperature preference rhythm (TPR), in which their preferred temperatures increase during the daytime and then decrease at the transition from day to night (night-onset) (Kaneko et al., 2012). Because Drosophila are small ectotherms, their body temperature is very close to that of the ambient temperature (Stevenson, 1985), suggesting that their TPR generates their body temperature rhythm. Here, we demonstrate that the neuropeptide diuretic hormone 31 (DH31) and pigment-dispersing factor receptor (PDFR) contribute to regulate the preferred temperature decrease at night-onset. We show that PDFR and tethered-DH31 expression in dorsal neurons 2 (DN2s) restore the preferred temperature decrease at night-onset, suggesting that DH31 acts on PDFR in DN2s. Notably, we previously showed that the molecular clock in DN2s is important for TPR. Although PDF (another ligand of PDFR) is a critical factor for locomotor activity rhythms, Pdf mutants exhibit normal preferred temperature decreases at night-onset. This suggests that DH31-PDFR signaling specifically regulates a preferred temperature decrease at night-onset. Thus, we propose that night-onset TPR and locomotor activity rhythms are differentially controlled not only by clock neurons but also by neuropeptide signaling in the brain. SIGNIFICANCE STATEMENT: Body temperature rhythm (BTR) is fundamental for the maintenance of functions essential for homeostasis, such as generating metabolic energy and sleep. One major unsolved question is how body temperature decreases dramatically during the night. Previously, we demonstrated that a BTR-like mechanism, referred to as temperature preference rhythm (TPR), exists in Drosophila Here, we demonstrate that the diuretic hormone 31 (DH31) neuropeptide and pigment-dispersing factor receptor (PDFR) regulate preferred temperature decreases at night-onset via dorsal neurons 2. This is the first in vivo evidence that DH31 could function as a ligand of PDFR. Although both DH31 and PDF are ligands of PDFR, we show that DH31 regulates night-onset TPR, but PDF does not, suggesting that night-onset TPR and locomotor activity rhythms are controlled by different neuropeptides via different clock cells.

Presynaptic GABA Receptors Mediate Temporal Contrast Enhancement in Drosophila Olfactory Sensory Neurons and Modulate Odor-Driven Behavioral Kinetics.

Contrast enhancement mediated by lateral inhibition within the nervous system enhances the detection of salient features of visual and auditory stimuli, such as spatial and temporal edges. However, it remains unclear how mechanisms for temporal contrast enhancement in the olfactory system can enhance the detection of odor plume edges during navigation. To address this question, we delivered to Drosophila melanogaster flies pulses of high odor intensity that induce sustained peripheral responses in olfactory sensory neurons (OSNs). We use optical electrophysiology to directly measure electrical responses in presynaptic terminals and demonstrate that sustained peripheral responses are temporally sharpened by the combined activity of two types of inhibitory GABA receptors to generate contrast-enhanced voltage responses in central OSN axon terminals. Furthermore, we show how these GABA receptors modulate the time course of innate behavioral responses after odor pulse termination, demonstrating an important role for temporal contrast enhancement in odor-guided navigation.

Massive migration from the steppe was a source for Indo-European languages in Europe.

We generated genome-wide data from 69 Europeans who lived between 8,000-3,000 years ago by enriching ancient DNA libraries for a target set of almost 400,000 polymorphisms. Enrichment of these positions decreases the sequencing required for genome-wide ancient DNA analysis by a median of around 250-fold, allowing us to study an order of magnitude more individuals than previous studies and to obtain new insights about the past. We show that the populations of Western and Far Eastern Europe followed opposite trajectories between 8,000-5,000 years ago. At the beginning of the Neolithic period in Europe, ∼8,000-7,000 years ago, closely related groups of early farmers appeared in Germany, Hungary and Spain, different from indigenous hunter-gatherers, whereas Russia was inhabited by a distinctive population of hunter-gatherers with high affinity to a ∼24,000-year-old Siberian. By ∼6,000-5,000 years ago, farmers throughout much of Europe had more hunter-gatherer ancestry than their predecessors, but in Russia, the Yamnaya steppe herders of this time were descended not only from the preceding eastern European hunter-gatherers, but also from a population of Near Eastern ancestry. Western and Eastern Europe came into contact ∼4,500 years ago, as the Late Neolithic Corded Ware people from Germany traced ∼75% of their ancestry to the Yamnaya, documenting a massive migration into the heartland of Europe from its eastern periphery. This steppe ancestry persisted in all sampled central Europeans until at least ∼3,000 years ago, and is ubiquitous in present-day Europeans. These results provide support for a steppe origin of at least some of the Indo-European languages of Europe.