The development of single-cell multimodal assays provides a powerful tool for investigating multiple dimensions of cellular heterogeneity, enabling new insights into development, tissue homeostasis and disease. A key challenge in the analysis of single-cell multimodal data is to devise appropriate strategies for tying together data across different modalities. The term ‘data integration’ has been used to describe this task, encompassing a broad collection of approaches ranging from batch correction of individual omics datasets to association of chromatin accessibility and genetic variation with transcription. Although existing integration strategies exploit similar mathematical ideas, they typically have distinct goals and rely on different principles and assumptions. Consequently, new definitions and concepts are needed to contextualize existing methods and to enable development of new methods. As the number of single-cell experiments with multiple data modalities increases, Argelaguet and colleagues review the concepts and challenges of data integration.

Computational principles and challenges in single-cell data integration.

Where Are the Disease-Associated eQTLs?

Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

/pdf/a-compendium-of-uniformly-processed-human-gene-expression-gr4axmfptk.pdf

A compendium of uniformly processed human gene expression and splicing quantitative trait loci.

Recent advances in single-cell technologies and integration algorithms make it possible to construct large, comprehensive reference atlases from multiple datasets encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map new query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony, a novel algorithm for building compressed, integrated reference atlases of ≥106 cells and enabling efficient query mapping within seconds. Based on a linear mixture model framework, Symphony precisely localizes query cells within a low-dimensional reference embedding without the need to reintegrate the reference cells, facilitating the downstream transfer of many types of reference-defined annotations to the query cells. We demonstrate the power of Symphony by (1) mapping a query containing multiple levels of experimental design to predict pancreatic cell types in human and mouse, (2) localizing query cells along a smooth developmental trajectory of human fetal liver hematopoiesis, and (3) harnessing a multimodal CITE-seq reference atlas to infer query surface protein expression in memory T cells. Symphony will enable the sharing of comprehensive integrated reference atlases in a convenient, portable format that powers fast, reproducible querying and downstream analyses.

https://biorxiv.org/content/10.1101/2020.11.18.389189v1.full.pdf

Efficient and precise single-cell reference atlas mapping with Symphony

An increasing number of gene expression quantitative trait locus (QTL) studies have made summary statistics publicly available, which can be used to gain insight into human complex traits by downstream analyses such as fine-mapping and colocalisation. However, differences between these datasets in their variants tested, allele codings, and in the transcriptional features quantified are a barrier to their widespread use. Here, we present the eQTL Catalogue, a resource which contains quality controlled, uniformly re-computed QTLs from 19 eQTL publications. In addition to gene expression QTLs, we have also identified QTLs at the level of exon expression, transcript usage, and promoter, splice junction and 3ʹ end usage. Our summary statistics can be downloaded by FTP or accessed via a REST API and are also accessible via the Open Targets Genetics Portal. We demonstrate how the eQTL Catalogue and GWAS Catalog APIs can be used to perform colocalisation analysis between GWAS and QTL results without downloading and reformatting summary statistics. New datasets will continuously be added to the eQTL Catalogue, enabling systematic interpretation of human GWAS associations across a large number of cell types and tissues. The eQTL Catalogue is available at https://www.ebi.ac.uk/eqtl/.

/pdf/eqtl-catalogue-a-compendium-of-uniformly-processed-human-5dca04hxev.pdf

eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs

Studying the function of common genetic variants in primary human tissues and during development is challenging. To address this, we use an efficient multiplexing strategy to differentiate 215 human induced pluripotent stem cell (iPSC) lines toward a midbrain neural fate, including dopaminergic neurons, and use single-cell RNA sequencing (scRNA-seq) to profile over 1 million cells across three differentiation time points. The proportion of neurons produced by each cell line is highly reproducible and is predictable by robust molecular markers expressed in pluripotent cells. Expression quantitative trait loci (eQTL) were characterized at different stages of neuronal development and in response to rotenone-induced oxidative stress. Of these, 1,284 eQTL colocalize with known neurological trait risk loci, and 46% are not found in the Genotype-Tissue Expression (GTEx) catalog. Our study illustrates how coupling scRNA-seq with long-term iPSC differentiation enables mechanistic studies of human trait-associated genetic variants in otherwise inaccessible cell states.

Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation

Common genetic variants can have profound effects on cellular function, but studying these effects in primary human tissue samples and during development is challenging. Human induced pluripotent stem cell (iPSC) technology holds great promise for assessing these effects across different differentiation contexts. Here, we use an efficient pooling strategy to differentiate 215 iPS cell lines towards a midbrain neural fate, including dopaminergic neurons, and profile over 1 million cells sampled across three differentiation timepoints using single cell RNA sequencing. We find that the proportion of neuronal cells produced by each cell line is highly reproducible over different experimental batches, and identify robust molecular markers in pluripotent cells that predict line-to-line differences in cell fate. We identify expression quantitative trait loci (eQTL) that manifest at different stages of neuronal development, and in response to oxidative stress, by exposing cells to rotenone. We find over one thousand eQTL that colocalise with a known risk locus for a neurological trait, nearly half of which are not found in GTEx. Our study illustrates how coupling single cell transcriptomics with long-term iPSC differentiation can profile mechanistic effects of human trait-associated genetic variants in otherwise inaccessible cell states.

https://www.biorxiv.org/content/biorxiv/early/2020/05/22/2020.05.21.103820.full.pdf

OBJECTIVE The lack of pro-opiomelanocortin (POMC)-derived melanocortin peptides results in hypoadrenalism and severe obesity in both humans and rodents that is treatable with synthetic melanocortins. However, there are significant differences in POMC processing between humans and rodents, and little is known about the relative physiological importance of POMC products in the human brain. The aim of this study was to determine which POMC-derived peptides are present in the human brain, to establish their relative concentrations, and to test if their production is dynamically regulated. METHODS We analysed both fresh post-mortem human hypothalamic tissue and hypothalamic neurons derived from human pluripotent stem cells (hPSCs) using liquid chromatography tandem mass spectrometry (LC-MS/MS) to determine the sequence and quantify the production of hypothalamic neuropeptides, including those derived from POMC. RESULTS In both in vitro and in vivo hypothalamic cells, LC-MS/MS revealed the sequence of hundreds of neuropeptides as a resource for the field. Although the existence of β-melanocyte stimulating hormone (MSH) is controversial, we found that both this peptide and desacetyl α-MSH (d-α-MSH) were produced in considerable excess of acetylated α-MSH. In hPSC-derived hypothalamic neurons, these POMC derivatives were appropriately trafficked, secreted, and their production was significantly (P < 0.0001) increased in response to the hormone leptin. CONCLUSIONS Our findings challenge the assumed pre-eminence of α-MSH and suggest that in humans, d-α-MSH and β-MSH are likely to be the predominant physiological products acting on melanocortin receptors.

Quantitative mass spectrometry for human melanocortin peptides in vitro and in vivo suggests prominent roles for β-MSH and desacetyl α-MSH in energy homeostasis.

Julie Jerber

Papers

Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation

Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation

Quantitative mass spectrometry for human melanocortin peptides in vitro and in vivo suggests prominent roles for β-MSH and desacetyl α-MSH in energy homeostasis.