The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.

Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

Understanding the function of genes and their regulation in tissue homeostasis and disease requires knowing the cellular context in which genes are expressed in tissues across the body. Single cell genomics allows the generation of detailed cellular atlases in human tissues, but most efforts are focused on single tissue types. Here, we establish a framework for profiling multiple tissues across the human body at single-cell resolution using single nucleus RNA-Seq (snRNA-seq), and apply it to 8 diverse, archived, frozen tissue types (three donors per tissue). We apply four snRNA-seq methods to each of 25 samples from 16 donors, generating a cross-tissue atlas of 209,126 nuclei profiles, and benchmark them vs. scRNA-seq of comparable fresh tissues. We use a conditional variational autoencoder (cVAE) to integrate an atlas across tissues, donors, and laboratory methods. We highlight shared and tissue-specific features of tissue-resident immune cells, identifying tissue-restricted and non-restricted resident myeloid populations. These include a cross-tissue conserved dichotomy between LYVE1- and HLA class II-expressing macrophages, and the broad presence of LAM-like macrophages across healthy tissues that is also observed in disease. For rare, monogenic muscle diseases, we identify cell types that likely underlie the neuromuscular, metabolic, and immune components of these diseases, and biological processes involved in their pathology. For common complex diseases and traits analyzed by GWAS, we identify the cell types and gene modules that potentially underlie disease mechanisms. The experimental and analytical frameworks we describe will enable the generation of large-scale studies of how cellular and molecular processes vary across individuals and populations.

We conducted a large multi-ethnic meta-analysis of genome-wide association studies for primary open-angle glaucoma (POAG) on a total of 34,179 cases vs 349,321 controls, and identified 127 independent risk loci, almost doubling the number of known loci for POAG. The majority of loci have broadly consistent effect across European, Asian and African ancestries. We identify a link, both genome-wide and at specific loci, between POAG and Alzheimer's disease. Gene expression data and bioinformatic functional analyses provide further support for the functional relevance of the POAG risk genes. Several drug compounds target these risk genes and may be potential candidates for developing novel POAG treatments.Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness worldwide 1,2 . The disease is characterized by progressive optic nerve degeneration that is usually accompanied by elevated intraocular pressure (IOP). Neuroprotective therapies are not available and current treatments are limited to lowering IOP which can slow disease progression at early disease stages. However over 50% of glaucoma is not diagnosed until irreversible optic nerve damage has occurred 2,3 .

SummaryECLIPSER was developed to identify pathogenic cell types and cell type-specific genes that may affect complex disease susceptibility and trait variation by integrating single cell data with known GWAS loci. ECLIPSER maps genes to GWAS loci for a given complex trait based on expression and splicing quantitative trait loci (e/sQTLs) and other functional data, and tests whether the mapped genes are enriched for cell type-specific expression in particular cell types using single-cell/nucleus RNA-seq data from one or more tissues of interest. A Bayesian Fisher’s exact test is used to compute fold-enrichment significance. We demonstrate the application of ECLIPSER on various skin diseases and traits using snRNA-seq of healthy human skin samples.Availability and ImplementationThe source code and documentation for ECLIPSER and a Jupyter notebook for generating output tables and figures are available at https://github.com/segrelabgenomics/ECLIPSER. The source code for GWASvar2gene that maps genes to GWAS loci based on e/sQTLs is available at https://github.com/segrelabgenomics/GWASvar2gene. The analysis presented here used data from GTEx (https://gtexportal.org/home/datasets) and Open Targets Genetics (https://genetics-docs.opentargets.org/data-access/graphql-api), but can also be applied to other GWAS variant lists and QTL studies. Data used to reproduce the results of the paper are available in Supplementary data.

Streptococcus pneumoniae is a leading cause of ocular infections including serious and sight-threatening conditions. The use of pneumococcal conjugate vaccines (PCV) has substantially reduced the incidence of pneumonia and invasive pneumococcal diseases, but has had limited impact on ocular infections. Additionally, widespread vaccine use has resulted in ongoing selective pressure and serotype replacement in carriage and disease. To gain insight into the population structure of pneumococcal isolates causing ocular infections in a post-PCV-13 time period, we investigated the genomic epidemiology of ocular S. pneumoniae isolates (n=45) collected at Massachusetts Eye and Ear between 2014 and 2017. By performing a series of molecular typing methods from draft genomes, we found that the population structure of ocular S. pneumoniae is highly diverse with 27 sequence types (grouped into 18 clonal complexes) and 17 serotypes being identified. Distribution of these lineages diverged according to the site of isolation, with conjunctivitis being commonly caused by isolates grouped in the Epidemic Conjunctivitis Cluster-ECC (60 %), and ST448 (53.3 %) being most frequently identified. Conversely, S. pneumoniae keratitis cases were caused by a highly diverse population of isolates grouping within 15 different clonal complexes. Serotyping inference demonstrated that 95.5 % of the isolates were non-PCV-13 vaccine types. Most of the conjunctivitis isolates (80 %) were unencapsulated, with the remaining belonging to serotypes 15B, 3 and 23B. On the other hand, S. pneumoniae causing keratitis were predominantly encapsulated (95.2 %) with 13 different serotypes identified, mostly being non-vaccine types. Carriage of macrolide resistance genes was common in our ocular S. pneumoniae population (42.2 %), and usually associated with the mefA +msrD genotype (n=15). These genes were located in the Macrolide Efflux Genetic Assembly cassette and were associated with low-level in vitro resistance to 14- and 15-membered macrolides. Less frequently, macrolide-resistant isolates carried an ermB gene (n=4), which was co-located with the tetM gene in a Tn-916-like transposon. Our study demonstrates that the population structure of ocular S. pneumoniae is highly diverse, mainly composed by isolates that escape the PCV-13 vaccine, with patterns of tissue/niche segregation, adaptation and specialization. These findings suggest that the population structure of ocular pneumococcus may be shaped by multiple factors including PCV-13 selective pressure, microbial-related and niche-specific host-associated features.

Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide; however the molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization analysis of >130 POAG and 112 IOP GWAS loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina proposed causal genes for 60% of the loci, that were enriched in extracellular matrix organization, cell adhesion, and vascular development. Analyzing single-nucleus RNA-seq of glaucoma-relevant eye tissues, we found that the colocalizing genes were enriched in known and less well-characterized cell types, including fibroblasts in the conventional and unconventional aqueous outflow pathways; vascular cells in the anterior segment; astrocytes and Müller glia in retina and optic nerve head (ONH); and smooth muscle and vascular endothelial cells in ONH. This study nominated IOP- dependent and independent regulatory mechanisms, genes, and cell types that may underlie POAG pathogenesis.