Innate lymphoid cells (ILCs) are rare tissue-resident lymphocytes that functionally mirror cells of CD4[+] T helper lineage but lack antigen receptors. Type 3 ILCs (ILC3s) are enriched at barrier sites, regulating inflammation and promoting tissue integrity. Here we profile the promoter-anchored chromosomal contacts of primary human ILC3s using low-input, high-resolution targeted chromosome conformation capture and compare them with those in CD4[+] T cells. We use these data to link Crohn's disease genome-wide association study variants with target genes, implicating both known and unanticipated candidates, including CLN3, a causal gene for Batten disease. We show that Cln3 overexpression in a mouse ILC3-like cell line alters stimulation-induced transcriptional programs and cytokine secretion. Extending our approach to five additional immune genome-wide association study traits reveals enrichment for regulators of ILC3 activation. Our work develops methods, maps long-range gene regulation in ILC3s, and prioritizes immune disease risk genes with roles in this clinically relevant immune cell type.

Mapping enhancers and their target genes in specific cell types is crucial for understanding gene regulation and human disease genetics. However, accurately predicting enhancer-gene regulatory interactions from single-cell datasets has been challenging. Here we introduce a family of classification models, scE2G, to predict enhancer-gene regulation. These models use features from single-cell assay for transposase-accessible chromatin with sequencing (ATAC-seq) or multiomic RNA and ATAC-seq data, and are trained on a CRISPR perturbation dataset including >10,000 evaluated element-gene pairs. We benchmark scE2G models against CRISPR perturbations, fine-mapped expression quantitative trait loci and genome-wide association study variant-gene associations and demonstrate state-of-the-art performance at prediction tasks across several cell types and categories of perturbations. We apply scE2G to build maps of enhancer-gene regulatory interactions in heterogeneous tissues and interpret noncoding variants associated with complex traits, nominating regulatory interactions linking INPP4B and IL15 to lymphocyte count. The scE2G models will enable accurate mapping of enhancer-gene regulatory interactions across thousands of human cell types.

Histone post-translational modifications (hPTMs) are key regulators of chromatin states, influencing gene expression, epigenetic memory and transposable element repression across eukaryotic genomes. While many hPTMs are evolutionarily conserved, the extent to which the chromatin states they define are similarly preserved remains unclear. Here we developed a combinatorial indexing chromatin immunoprecipitation followed by sequencing method to simultaneously profile specific hPTMs across diverse eukaryotic lineages, including amoebozoans, rhizarians, discobans and cryptomonads. Our analyses revealed highly conserved euchromatin states at active gene promoters and gene bodies. In contrast, we observed diverse configurations of repressive heterochromatin states associated with silenced genes and transposable elements, characterized by various combinations of hPTMs such as H3K9me3, H3K27me3 and/or different H3K79 methylations. These findings suggest that, while core hPTMs are ancient and broadly conserved, their functional readout has diversified throughout eukaryotic evolution, shaping lineage-specific chromatin landscapes.

The interplay between somatic mutations and copy number alterations influences tumor evolution and prognosis. These alterations are often treated independently, overlooking gene mutant dosage (GMD)-a key property of their interaction. Here we develop a computational framework that infers mutation copy number and multiplicity from targeted sequencing panels without requiring matched normal samples. We derive GMD for over 500,000 mutations across 60,000 pan-cancer samples. By stratifying more than 20,000 patients according to GMD across multiple genes, we identify 46 tumor-type-specific biomarkers predictive of survival, 13 of which were undetectable using binary mutant/wild-type models, 26 were associated with metastatic spread and 20 predicted metastatic tropism. Our method reveals GMD patterns as independent predictors of disease prognosis, metastatic potential and site-specific dissemination across diverse tumor types. This augmented insight into genomic drivers enhances our understanding of cancer progression and metastasis and holds the potential to substantially enhance biomarker discovery.

In eukaryotes, transcription factors (TFs) must continuously compete with nucleosomes to access their binding sites, leading to cell-to-cell variability in chromatin accessibility at regulatory regions. Although critical to understand enhancer function in transcription, the mechanisms that define how frequently an enhancer is active in a cell population remain unclear. Here we used single-molecule footprinting to quantify the frequency at which chromatin is accessible at enhancers in response to TF perturbations and changes in their chromatin environment. We find that, individually, most TFs open chromatin in a small fraction of cells, and that cumulative TF binding controls enhancer activation frequency. Moreover, testing the functionality of hundreds of enhancers when inserted at an ectopic genomic location indicates that p300 activity is required for their full activation. Our data support a model in which enhancer activation frequency depends on the cumulative function of multiple TFs and is modulated by p300 activity.

Evolution has used cell-cell communication as a strategy to coordinate organ development, enabling the reproducible generation of intricate structures. Classically, these interactions have been studied one at a time in model organisms, limiting our understanding of how cellular interplay coordinates human development. We investigated human kidney development using single-cell RNA sequencing and spatial transcriptomics, analyzing over 700,000 cells. By mapping gene expression and differentiation trajectories in space, we define the spatial organization of kidney development. Our analysis revealed unrecognized plasticity, showing that cell fate established during early patterning can be later revised. This plasticity provides a potential mechanism for how cell fate is robustly established in complex patterned tissues. Additionally, through a genome-wide, spatially aware cell-cell interaction analysis, we link localized ligand signals to cell fate decisions. We also define biologically meaningful cellular neighborhoods based on aggregated extracellular cues, providing a blueprint to understand the coordination of human development at scale.

Autoimmune hypothyroidism (Hashimoto's thyroiditis) is common and has a strong genetic component. Here we performed multi-ancestry genome-wide association meta-analyses encompassing 48,694 Hashimoto's thyroiditis cases, using a precise case definition, and 1,044,134 controls. We identified 155 significant (P < 5 × 10[-8]) independent genetic associations, of which 45 variants and 19 loci were not previously associated with hypothyroidism. Six loci were specific for individuals of European ancestry reference populations. Functional enrichment analyses of Hashimoto's thyroiditis-associated genes highlighted immune cells and the spleen, underpinning the importance of T cells in Hashimoto's thyroiditis development. This observation was further supported by 161 significant colocalizations with expression quantitative trait loci in immune cells and 40 in thyroid tissue (for example, TG, VAV3, IRF5), highlighting the interplay between the immune system and the thyroid. Mendelian randomization indicated causal effects of Hashimoto's thyroiditis on cardiovascular traits and expected associations with thyroid hormone levels.

The Singapore National Precision Medicine (NPM) program is a three-phase whole-of-nation effort designed to develop scalable, evidence-based solutions for precision health tailored to Asia's diverse populations. Here we present NPM phase II (2020-2025), highlighting how large-scale precision medicine initiatives can drive new research insights, enable healthcare innovations and create economic value. Key achievements include the PRECISE-SG100K population dataset, which reflects Singapore's unique multi-ancestry Asian population; the successful translation of research findings into mainstream national healthcare using familial hypercholesterolemia as a use case; and the establishment of strategic public-private partnerships with diverse industry sectors. We also outline phase III (2025-2031), which aims to establish whole-genome sequencing as a foundational element of a patient's lifelong healthcare record for 10% of the population. NPM provides a model for how smaller countries, despite limited populations and finite resources, can contribute meaningfully to global scientific movements while preserving strategic independence and addressing national health challenges.