Biology subjects

Sonthalia, R.

Publications and source records attributed to Sonthalia, R..

4 recordsLinked to original sources

bioRxiv2026

A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease

Blood provides an accessible window into human health, yet the absence of a peripheral blood mononuclear cells (PBMCs) reference with standardized immune cell annotations has constrained comparisons between single-cell RNA sequencing (scRNAseq) studies. Here, we present HARP (Human Cell Atlas Reference for PBMCs), an integrated atlas of ~9 million PBMCs from >2,600 donors across 15 studies spanning four continents, encompassing diverse populations, neonates to 97 years, across health and diverse immune-related diseases. We developed optimized integration workflows, including novel label-free metrics to assess integration quality, and generated community-driven consensus annotations for 192 immune cell subsets, identifying rare populations representing as few as 0.004% of PBMCs. HARP reveals coordinated cellular modules associated with age, sex, and disease, identifies female-biased interferon and inflammatory gene programs and their perturbation by COVID-19, and uncovers a novel sexual dimorphism in prostaglandin signaling. Finally, we introduce scTiger, a hierarchical label-transfer framework that accurately projects these 192 cell annotations onto ~18 million additional PBMCs, providing a robust and transferable reference for harmonizing future PBMC studies. HARP provides a high-resolution community-driven reference atlas for PBMC annotation and analysis, as a basis for emerging clinical applications of single-cell genomics.

immunology↗

bioRxiv2025

Deep learning reveals functional archetypes in the adult human gut microbiome that underlie interindividual variability and confound disease signals

Understanding the functional diversity of the gut microbiome is essential for decoding its roles in health and disease. Using a deep-learning framework, we identified three functional archetypes defining healthy adult gut microbiomes, each characterized by specific metabolic potentials: sugar metabolism with branched-chain amino acid and cell wall synthesis (Archetype 1), fatty acid and TCA cycle metabolism (Archetype 2), and amino acid and nitrogen metabolism (Archetype 3). Archetype proximity is linked to stability, with Archetype 2 representing the most resilient state, likely due to its metabolic flexibility. Functional diversity emerged as a confounder in disease-associated microbial signatures. In inflammatory bowel disease, we observed archetype-specific shifts, including increased carbohydrate metabolism in Archetype 1-dominant samples and inflammatory pathways in Archetype 3-dominant samples, suggesting distinct opportunities for microbiome-targeted interventions. This framework addresses key challenges in microbiome research, including inter-individual variability and confounding, while providing robust insights into disease-associated functional shifts and microbial ecosystem dynamics. HighlightsO_LIAdult gut microbiomes are defined by three functional archetypes C_LIO_LIArchetypes reveal distinct metabolic potentials and inform on microbiome stability C_LIO_LIArchetype-specific functional profiles confound disease associations and reveal therapeutic targets C_LIO_LIA deep-learning framework enables robust characterization of microbial functional ecosystems C_LI

microbiology↗

bioRxiv2024

Single-cell analysis of human diversity in circulating immune cells

Lack of diversity and proportionate representation in genomics datasets and databases contributes to inequity in healthcare outcomes globally1,2. The relationships of human diversity with biological and biomedical phenotypes are pervasive3, yet remain understudied, particularly in a single-cell genomics context. Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 healthy donors and 6 controls, spanning 7 population groups across 5 countries. AIDA is one of the largest healthy blood datasets in terms of number of cells, and also the most diverse in terms of number of population groups. Though population groups are frequently compared at the continental level, we identified a pervasive impact of sub-continental diversity on cellular and molecular properties of immune cells. These included cell populations and genes implicated in disease risk and pathogenesis as well as those relevant for diagnostics. We detected single-cell signatures of human diversity not apparent at the level of cell types, as well as modulation of the effects of age and sex by self-reported ethnicity. We discovered functional genetic variants influencing cell type-specific gene expression, including context-dependent effects, which were under-represented in analyses of non-Asian population groups, and which helped contextualise disease-associated variants. We validated our findings using multiple independent datasets and cohorts. AIDA provides fundamental insights into the relationships of human diversity with immune cell phenotypes, enables analyses of multi-ancestry disease datasets, and facilitates the development of precision medicine efforts in Asia and beyond.

genomics↗

bioRxiv2023

Quantification of the escape from X chromosome inactivation with the million cell-scale human single-cell omics datasets reveals heterogeneity of escape across cell types and tissues

One of the two X chromosomes of females is silenced through X chromosome inactivation (XCI) to compensate for the difference in the dosage between sexes. Among the X-linked genes, several genes escape from XCI, which could contribute to the differential gene expression between the sexes. However, the differences in the escape across cell types and tissues are still poorly characterized because no methods could directly evaluate the escape under a physiological condition at the cell-cluster resolution with versatile technology. Here, we developed a method, single-cell Level inactivated X chromosome mapping (scLinaX), which directly quantifies relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA-sequencing (scRNA-seq) data. The scLinaX and differentially expressed genes analyses with the scRNA-seq datasets of [~]1,000,000 blood cells consistently identified the relatively strong degree of escape in lymphocytes compared to myeloid cells. An extension of scLinaX for multi-modal datasets, scLinaX-multi, suggested a stronger degree of escape in lymphocytes than myeloid cells at the chromatin-accessibility level with a 10X multiome dataset. The scLinaX analysis with the human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes identified the larger effect sizes of the PRKX gene locus-lymphocyte counts association in females than males. This could suggest evidence of the underlying impact of escape on the genotype-phenotype association in humans. Overall, scLinaX and the quantified catalog of escape identified the heterogeneity of escape across cell types and tissues and would contribute to expanding the current understanding of the XCI, escape, and sex differences in gene regulation.

genomics↗