Cell genomics最新文献

Tumor-specific antigens (TSAs) are crucial for activating T cells against cancer, but traditional discovery methods focusing on exonic mutations overlook non-canonical TSAs from non-coding regions. We employed an integrative proteogenomic strategy combining whole-genome and RNA sequencing with immunoprecipitation mass spectrometry to comprehensively explore TSA generation in colorectal cancer patients. Analysis of 10 paired tumor samples identified 96 mutated major histocompatibility complex class I-presented neo-epitopes, with 80.21% originating from non-coding regions. In hypermutated tumors with high mutational burden, neo-epitopes predominantly arose from intergenic and intronic areas, while in non-hypermutated tumors with low mutational burden, they mainly stemmed from coding variations and alternative splicing events. Functional validation in mouse models demonstrated that mutated non-canonical neo-epitopes effectively activated CD8⁺ T cells and significantly suppressed tumor growth. These findings underscore the importance of considering the entire genomic landscape in TSA discovery, suggesting new avenues for personalized immunotherapy.

Only one-third of immune-associated genome-wide association study (GWAS) loci colocalize with expression quantitative trait loci (eQTLs), leaving most mechanisms unresolved. To address this, we created a unified single-cell chromatin accessibility (scATAC) map of ∼280,000 peripheral immune cells from 48 individuals, including 20 COVID-19 patients. Topic modeling of scATAC data identified continuous cell states and revealed disease-relevant cellular contexts. We identified 37,390 chromatin accessibility QTLs (caQTLs) at 10% false discovery rate and observed extensive sharing of caQTLs, with <20% confined to a single context. Notably, caQTLs explained ∼50% more GWAS loci compared to eQTLs, nominating putative causal genes for some unexplained loci. Yet most GWAS-colocalizing caQTLs lacked eQTL support, limiting causal inference from chromatin data alone. Thus, while caQTLs can improve GWAS interpretation, robust mechanistic insights require integration with gene expression and other functional evidence. Our work underscores that cellular context is critical for regulatory variant interpretation and emphasizes the need to map genetic effects in disease-relevant cell states.

The human complement of chromosomes differs from our closest primate relatives by virtue of a unique chromosome fusion event. In this issue of Cell Genomics, Yang et al. provide the first detailed analysis of the site of chromosome fusion and reconstruct the complex evolutionary relationships among the genomic elements within the human fusion site and their related sequences in our great ape relatives.

Sex differences in behaviors arise from variations in female and male nervous systems, yet the cellular and molecular bases of these differences remain poorly defined. Here, we employ an unbiased, single-cell transcriptomic approach to investigate how sex influences the adult Drosophila melanogaster brain. We demonstrate that sex differences do not result from large-scale transcriptional reprogramming, but rather from selective modifications within shared developmental lineages mediated by the sex-differentiating transcription factors Doublesex and Fruitless. We reveal, with unprecedented resolution, the extraordinary genetic diversity within these sexually dimorphic cell types and find that birth order represents a novel axis of sexual differentiation. Neuronal identity in the adult reflects spatiotemporal patterning and sex-specific survival, with female-biased neurons emerging early and male-biased neurons arising later. This pattern reframes dimorphic neurons as "paralogous" rather than "orthologous," suggesting sex leverages distinct developmental windows to build behavioral circuits, and highlights a role for exaptation in diversifying the brain.

Mapping the impact of genomic variation on gene expression provides insight into the molecular basis of complex phenotypic traits and disease predisposition. Mouse models offer a controlled framework to capture genomic diversity across tissues. As part of the IGVF consortium, we profiled the transcriptomes of eight tissues from each founder strain of the Collaborative Cross using single-nucleus RNA sequencing. The resulting "8-cube" dataset contains 5.2 million nuclei across 106 cell types and cell states. Transcriptome variation correlated with genetic divergence, highest in the wild-derived strains. Heart and brain were relatively similar, whereas gonads, adrenal gland, skeletal muscle, kidney, and liver showed greater divergence. Variation often concentrated in specific cell types and states, especially those linked to immune and metabolic traits. The founder 8-cube dataset provides rich transcriptome signatures to help explain strain-specific traits and disease states and serves as a foundation for deeper analysis of these tissues across diverse mouse genotypes.

Protein domains are fundamental units determining protein functions. This study identified all protein domains and domain combinations from 446 genomes across all major plant lineages. We discovered more domains and domain combinations in land plants than in algae. Many novel "core" protein domains were acquired in the early evolution of streptophytes, substantially enriching the genomic toolkit that enabled plants to shift from unicellular to multicellular organization and to adapt to terrestrial life. After conquering the land, the number of ancestral core domains kept decreasing in land plants; in contrast, an increasing number of non-core domains were acquired, which, together with enhanced activity of domain shuffling, generated various novel domain combinations and expanded protein diversity. We speculate that losing existing genetic elements (core domains) is not always detrimental, as it may have reduced evolutionary constraint upon species, paving the way for biological innovation (speciation) and adaptation to changing environments.

The ecological persistence of Bifidobacterium breve across life stages reflects adaptive strategies beyond the classical infant- versus adult-type dichotomy, historically attributed to differential nutrient utilization. Here, comparative genomics revealed no major differences in shared carbohydrate-related genes or accessory genome content between infant- and adult-derived strains. Instead, a distinct type III lanthipeptide bacteriocin cluster, lanKC, was specifically detected in adult-derived isolates. Functional assays combining gene knockout, in vitro co-cultivation, and human intervention demonstrated that lanKC enhances strain-level competitive fitness and promotes community stability. Phylogenetic and metagenomic analyses of 5,475 lanKC homologs and 6,122 infant gut metagenomes further suggested a possible early-life acquisition via intra-genus horizontal gene transfer. These findings uncover a previously unrecognized genetic basis underlying B. breve adaptation to the gut environment and support a multi-factorial model in which metabolic flexibility and interference competition jointly sustain bifidobacterial persistence and host-microbe symbiosis throughout life.

Gene expression shapes the nervous system at every biological level, from molecular and cellular processes defining neuronal identity and function to systems-level wiring and circuit dynamics underlying behavior. Here, we generate the first high-resolution, single-cell transcriptomic atlas of the adult Drosophila melanogaster central brain by integrating multiple datasets, achieving an unprecedented 10-fold coverage of every neuron in this complex tissue. We show that a neuron's genetic identity overwhelmingly reflects its developmental origin, preserving a genetic address based on both lineage and birth order. We reveal foundational rules linking neurogenesis to transcriptional identity and provide a framework for systematically defining neuronal types. This atlas provides a powerful resource for mapping the cellular substrates of behavior by integrating annotations of hemilineage, cell types/subtypes, and molecular signatures of underlying physiological properties. It lays the groundwork for a long-sought bridge between developmental processes and the functional circuits that give rise to behavior.

We developed a benchmark set of subclonal variants in the Genome in a Bottle (GIAB) Consortium HG002 reference material (RM) DNA for evaluating lower-frequency variant callsets. We used a somatic variant caller with high-coverage (300×) whole-genome sequencing data from the GIAB Ashkenazi Jewish trio to identify potential subclonal variants in the HG002 RM DNA. Using orthogonal sequencing data and manual curation, we defined a benchmark set with 85 high-confidence subclonal single-nucleotide variants (SNVs) (allele frequency [AF] > 5%) and a benchmark region covering 2.45 Gbp of the autosomes. External validation supported that it can be used to reliably identify both false negatives and false positives for a variety of sequencing technologies and variant callers. By adding our characterization of mosaic SNVs in this widely used cell line, we have expanded the scope of bioinformatic and sequencing applications for which the HG002 GIAB RM can be used to include benchmarking subclonal SNVs.

Cellular identity emerges from the dynamic coordination of context-aware gene programs that encode biological functions across molecular layers. To decode this complexity, we present SSpMosaic, a computational framework that establishes metaprograms (higher-order, cross-dataset aligned gene program representations) as universal anchors for biological state representation. Leveraging these metaprograms, SSpMosaic enables consistent, accurate integration across batches, modalities, and species. Critically, SSpMosaic accurately annotates cell types within query datasets, enabling discovery and annotation of novel cell states through metaprogram-based transfer learning. The framework achieves resolution-agnostic spatial transcriptomics deconvolution, precisely mapping cell-type distributions from spot-level (Visium) to subcellular scales (CosMx/Visium HD). As a paradigm-shifting application, we integrate single-nucleus transcriptomics, chromatin accessibility, and spatial transcriptomics to resolve multi-stage spatial domain dynamics across tissue slices. Finally, SSpMosaic enables reference-free spatial characterization, identifying conserved spatial ecotypes across tissue slices and annotating cellular niches without requiring matched single-cell data.