We applied a combinatorial indexing assay, sci-ATAC-seq, to profile genome-wide chromatin accessibility in ∼100,000 single cells from 13 adult mouse tissues. We identify 85 distinct patterns of chromatin accessibility, most of which can be assigned to cell types, and ∼400,000 differentially accessible elements. We use these data to link regulatory elements to their target genes, to define the transcription factor grammar specifying each cell type, and to discover in vivo correlates of heterogeneity in accessibility within cell types. We develop a technique for mapping single cell gene expression data to single-cell chromatin accessibility data, facilitating the comparison of atlases. By intersecting mouse chromatin accessibility with human genome-wide association summary statistics, we identify cell-type-specific enrichments of the heritability signal for hundreds of complex traits. These data define the in vivo landscape of the regulatory genome for common mammalian cell types at single-cell resolution.

An individual's T cell repertoire dynamically encodes their pathogen exposure history. To determine whether pathogen exposure signatures can be identified by documenting public T cell receptors (TCRs), we profiled the T cell repertoire of 666 subjects with known cytomegalovirus (CMV) serostatus by immunosequencing. We developed a statistical classification framework that could diagnose CMV status from the resulting catalog of TCRβ sequences with high specificity and sensitivity in both the original cohort and a validation cohort of 120 different subjects. We also confirmed that three of the identified CMV-associated TCRβ molecules bind CMV in vitro, and, moreover, we used this approach to accurately predict the HLA-A and HLA-B alleles of most subjects in the first cohort. As all memory T cell responses are encoded in the common format of somatic TCR recombination, our approach could potentially be generalized to a wide variety of disease states, as well as other immunological phenotypes, as a highly parallelizable diagnostic strategy.

The vast diversity of B-cell receptors (BCR) and secreted antibodies enables the recognition of, and response to, a wide range of epitopes, but this diversity has also limited our understanding of humoral immunity. We present a public database of more than 37 million unique BCR sequences from three healthy adult donors that is many fold deeper than any existing resource, together with a set of online tools designed to facilitate the visualization and analysis of the annotated data. We estimate the clonal diversity of the naive and memory B-cell repertoires of healthy individuals, and provide a set of examples that illustrate the utility of the database, including several views of the basic properties of immunoglobulin heavy chain sequences, such as rearrangement length, subunit usage, and somatic hypermutation positions and dynamics.

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with high-resolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity.

A detailed characterization of the dynamics and breadth of the immune response to an acute viral infection, as well as the determinants of recruitment to immunological memory, can greatly contribute to our basic understanding of the mechanics of the human immune system and can ultimately guide the design of effective vaccines. In addition to neutralizing antibodies, T cells have been shown to be critical for the effective resolution of acute viral infections. We report the first in-depth analysis of the dynamics of the CD8 ؉ T cell repertoire at the level of individual T cell clonal lineages upon vaccination of human volunteers with a single dose of YF-17D. This live attenuated yellow fever virus vaccine yields sterile, long-term immunity and has been previously used as a model to understand the immune response to a controlled acute viral infection. We identified and enumerated unique CD8؉ T cell clones specifically induced by this vaccine through a combined experimental and statistical approach that included high-throughput sequencing of the CDR3 variable region of the T cell receptor ␤-chain and an algorithm that detected significantly expanded T cell clones. This allowed us to establish that (i) on average, ϳ2,000 CD8 ؉ T cell clones were induced by YF-17D, (ii) 5 to 6% of the responding clones were recruited to long-term memory 3 months postvaccination, (iii) the most highly expanded effector clones were preferentially recruited to the memory compartment, and (iv) a fraction of the YF-17D-induced clones could be identified from peripheral blood lymphocytes solely by measuring clonal expansion. IMPORTANCEThe exhaustive investigation of pathogen-induced effector T cells is essential to accurately quantify the dynamics of the human immune response. The yellow fever vaccine (YFV) has been broadly used as a model to understand how a controlled, self-resolving acute viral infection induces an effective and long-term protective immune response. Here, we extend this previous work by reporting the identity of activated effector T cell clones that expand in response to the YFV 2 weeks postvaccination (as defined by their unique T cell receptor gene sequence) and by tracking clones that enter the memory compartment 3 months postvaccination. This is the first study to use high-throughput sequencing of immune cells to characterize the breadth of the antiviral effector cell response and to determine the contribution of unique virus-induced clones to the long-lived memory T cell repertoire. Thus, this study establishes a benchmark against which future vaccines can be compared to predict their efficacy. D uring the acute response to a viral infection, viral antigen (Ag)-specific effector CD8ϩ T cell clones (also known as cytotoxic T lymphocytes, or CTLs) become activated and expand as they recognize and eliminate infected host cells (1, 2). The Ag specificity of a T cell clone is determined by the T cell receptor (TCR), which is encoded by random, RAG-mediated V(D)J recombination. Thus, each T cell clone may be iden...

Modern biological techniques enable very dense genetic sampling of unfolding evolutionary histories, and thus frequently sample some genotypes multiple times. This motivates strategies to incorporate genotype abundance information in phylogenetic inference. In this article, we synthesize a stochastic process model with standard sequence-based phylogenetic optimality, and show that tree estimation is substantially improved by doing so. Our method is validated with extensive simulations and an experimental single-cell lineage tracing study of germinal center B cell receptor affinity maturation.

Probabilistic models of adaptive immune repertoire sequence distributions can be used to infer the expansion of immune cells in response to stimulus, differentiate genetic from environmental factors that determine repertoire sharing, and evaluate the suitability of various target immune sequences for stimulation via vaccination. Classically, these models are defined in terms of a probabilistic V(D)J recombination model which is sometimes combined with a selection model. In this paper we take a different approach, fitting variational autoencoder (VAE) models parameterized by deep neural networks to T cell receptor (TCR) repertoires. We show that simple VAE models can perform accurate cohort frequency estimation, learn the rules of VDJ recombination, and generalize well to unseen sequences. Further, we demonstrate that VAE-like models can distinguish between real sequences and sequences generated according to a recombination-selection model, and that many characteristics of VAE-generated sequences are similar to those of real sequences.

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with highresolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity. 6