Cell genomics最新文献

To trace the history of human-cat interactions and the arrival of domestic cats (Felis catus) in East Asia, we analyzed 22 small felid bones excavated from 14 archaeological sites across China spanning 5,000 years. Genomic and radiocarbon evidence revealed that commensal leopard cats (Prionailurus bengalensis) appeared in anthropogenic environments at least 5,400 years ago and persisted until 150 CE. After a gap of several centuries, the earliest known domestic cat in China (c. 730 CE), reconstructed as a fully or partially white cat, was identified in Shaanxi during the Tang Dynasty. Genomic analysis combining 130 modern and ancient Eurasian cat specimens suggested an origin of Chinese domestic cats from the Levant and a likely merchant-mediated dispersal via the Silk Road. Commensal leopard cats and domestic cats once independently inhabited ancient human settlements in China but followed divergent sociocultural paths with only domestic cats becoming fully domesticated and globally introduced.

According to the current paradigm, human monogenic disorders underlying immunological phenotypes are due to rare (frequency <1%) as opposed to common (>1%) alleles. However, as reviewed here, an increasing number of studies have reported monogenic disorders of immunity, recessive or dominant, involving alleles that are currently common in specific small or large populations. Examples range from IFNAR1 and IFNAR2 null alleles in the Arctic and Pacific to PTCRA hypomorphic alleles in South Asia. This situation may be explained by a history of (1) population bottlenecks followed by expansion; (2) genetic drift before the advent of an environmental trigger; (3) slow purging, especially for recessive, mild, or incompletely penetrant conditions; and/or (4) balancing selection with a heterozygous advantage. In patients with suspected monogenic immunological conditions, a role for alleles common in the corresponding population should not be excluded. At odds with the prevailing view, common alleles may underlie monogenic disorders of immunity and should therefore be considered.

Tracking clonal evolution is critical to fully define the mechanisms of normal physiology and the disruptions of these processes in disease. In this issue of Cell Genomics, Pak and Saurty-Seerunghen et al. describe the development of Genotyping of Transcriptomes for multiple targets and sample types (GoT-Multi) and show how this new technology enables insights into cellular states that mediate clonal evolution in diseases, such as the Richter transformation of chronic lymphocytic leukemia, while also revealing convergence of cell states, even with distinct driver mutations.

The advent of long-read sequencing and telomere-to-telomere (T2T) assemblies has transformed studies of eukaryotic genomic variation. Pangenomes now leverage these advances to generate comprehensive catalogs of structural variants (SVs) and gene presence-absence polymorphisms across populations. Here, we review how pangenomes improve the identification, classification, and large-scale analysis of SVs and gene families, yielding insights into genome organization, functional gene evolution, and the architecture of phenotypic traits. We discuss mechanisms of SV formation, their uneven genomic distribution, and their roles in trait diversity. Examples from humans, plants, animals, and fungi highlight the importance of SVs in adaptation, domestication, and disease. We also consider the integration of pangenome graphs into genome-wide association studies, the challenges of applying T2T pangenomes at the population scale, and the need for new computational tools. Together, pangenomes represent a transformative framework for decoding genomic diversity and its consequences.

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.

Generative genomic models hold immense potential for creating intricate biological systems, yet designing precise functional sequences remains challenging. Merchant et al. in Nature present semantic design, which employs the Evo genomic language model to generate novel functional genes based solely on genomic context. Moreover, SynGenome database houses over 120 billion sequences generated through semantic design, spanning a diverse range of functions.

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.