Reproducible single-cell annotation of programs underlying T cell subsets, activation states and functions.

T cells recognize antigens and induce specialized gene expression programs (GEPs), enabling functions like proliferation, cytotoxicity and cytokine production. Traditionally, different T cell classes are thought to exhibit mutually exclusive responses, including T1, T2 and T17 programs. However, single-cell RNA sequencing has revealed a continuum of T cell states without clearly distinct subsets, necessitating new analytical frameworks.

Opportunities and considerations for using artificial intelligence in bioinformatics education.

Artificial intelligence (AI) tools and techniques are undoubtedly being used in bioinformatics education, reflecting broader trends in education. However, many instructors and learners may be unaware of the full scope of potential uses for these tools within bioinformatics education, as well as effective practices for using them. Building on discussions held at the 6th Global Bioinformatics Education Summit, this perspective article provides insights about ways that AI might be used to generate or adapt instructional content, provide personalized help for learners, and automate assessment and grading.

Precisely defining disease variant effects in CRISPR-edited single cells.

Genetic studies have identified thousands of individual disease-associated non-coding alleles, but the identification of the causal alleles and their functions remains a critical bottleneck. CRISPR-Cas editing has enabled targeted modification of DNA to introduce and test disease alleles. However, the combination of inefficient editing, heterogeneous editing outcomes in individual cells and nonspecific transcriptional changes caused by editing and culturing conditions limits the ability to detect the functional consequences of disease alleles.

Nonadherence to guidelines for genetic testing in families with ovarian cancer shows racial bias.

Purpose: The National Comprehensive Cancer Network (NCCN) recommends germline genetic testing for individuals at risk for hereditary ovarian cancer. We sought to determine the proportion and characteristics of individuals meeting testing criteria in a multicenter biobank who were appropriately offered testing.

Methods: In this retrospective cohort study, we identified Mass General Brigham Biobank participants meeting genetic testing criteria per NCCN guidelines.

Granzyme K activates the entire complement cascade.

Granzymes are a family of serine proteases that are mainly expressed by CD8 T cells, natural killer cells and innate-like lymphocytes. Although their primary function is thought to be the induction of cell death in virally infected cells and tumours, accumulating evidence indicates that some granzymes can elicit inflammation by acting on extracellular substrates. We previously found that most tissue CD8 T cells in rheumatoid arthritis synovium, and in inflamed organs for some other diseases, express granzyme K (GZMK), a tryptase-like protease with poorly defined function.

The T cell receptor sequence influences the likelihood of T cell memory formation.

The amino acid sequence of the T cell receptor (TCR) varies between T cells of an individual's immune system. Particular TCR residues nearly guarantee mucosal-associated invariant T (MAIT) and natural killer T (NKT) cell transcriptional fates. To define how the TCR sequence affects T cell fates, we analyze the paired αβTCR sequence and transcriptome of 961,531 single cells.

Identifying genetic variants that influence the abundance of cell states in single-cell data.

Disease risk alleles influence the composition of cells present in the body, but modeling genetic effects on the cell states revealed by single-cell profiling is difficult because variant-associated states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce Genotype-Neighborhood Associations (GeNA), a statistical tool to identify cell-state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians.

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs).

Clonal associations between lymphocyte subsets and functional states in rheumatoid arthritis synovium.

Rheumatoid arthritis (RA) is an autoimmune disease involving antigen-specific T and B cells. Here, we perform single-cell RNA and repertoire sequencing on paired synovial tissue and blood samples from 12 seropositive RA patients. We identify clonally expanded CD4 + T cells, including CCL5+ cells and T peripheral helper (Tph) cells, which show a prominent transcriptomic signature of recent activation and effector function.

The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis.

Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments.

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions.

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks.

The genetic basis of autoimmunity seen through the lens of T cell functional traits.

Autoimmune disease heritability is enriched in T cell-specific regulatory regions of the genome. Modern-day T cell datasets now enable association studies between single nucleotide polymorphisms (SNPs) and a myriad of molecular phenotypes, including chromatin accessibility, gene expression, transcriptional programs, T cell antigen receptor (TCR) amino acid usage, and cell state abundances. Such studies have identified hundreds of quantitative trait loci (QTLs) in T cells that colocalize with genetic risk for autoimmune disease.

High-dimensional phenotyping to define the genetic basis of cellular morphology.

The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs).

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues.

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis.

Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin.

Psoriasis is a chronic, systemic inflammatory condition primarily affecting skin. While the role of the immune compartment (e.g.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians.

A quarter of humanity is estimated to be latently infected with () with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs).

Methods and Insights from Single-Cell Expression Quantitative Trait Loci.

Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and cell states, single-cell assays capture the transcriptional states of individual cells, including fine-grained, transient, and difficult-to-isolate populations at unprecedented scale and resolution. Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary with cell states, including some that colocalize with disease variants identified in genome-wide association studies.

Single-cell genomics meets human genetics.

Single-cell genomic technologies are revealing the cellular composition, identities and states in tissues at unprecedented resolution. They have now scaled to the point that it is possible to query samples at the population level, across thousands of individuals. Combining single-cell information with genotype data at this scale provides opportunities to link genetic variation to the cellular processes underpinning key aspects of human biology and disease.

The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis.

Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments.