Cell genomics最新文献

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.

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.

In this issue of Cell Genomics, Xihao Li (X.L.), Zilin Li (Z.L.), and colleagues present the annotated genomic data structure (aGDS) format to streamline genomic analyses that use biobank-scale whole-genome sequencing data. Both authors have a research focus in statistical genetics/genomics, and here they highlight their latest work and the benefits of their aGDS approach.

Ribosomal RNA (rRNA) genes are organized in tandem arrays known as ribosomal DNA (rDNA) on multiple chromosomes in Hominidae genomes. We measured copy number and transcriptional activity status of rRNA gene arrays across multiple individual genomes, revealing an identifiable fingerprint of rDNA copy number and activity. In some cases, entire arrays were transcriptionally silent, characterized by high DNA methylation across the rRNA gene, inaccessible chromatin, and the absence of transcription factors and transcripts. Silent arrays showed reduced association with the nucleolus and decreased interchromosomal interactions, consistent with the model that nucleolar organizer function depends on transcriptional activity. Removing rDNA methylation activated silent arrays. Array activity status remained stable through induced pluripotent stem cell reprogramming and differentiation into cerebral and intestinal organoids. Haplotype tracing in two unrelated family trios showed paternal transmission of silent arrays. We propose that the epigenetic state buffers rRNA gene dosage, specifies nucleolar organizer function, and can propagate transgenerationally.

Aging is the main determinant of chronic diseases and mortality, yet organ-specific aging trajectories vary, and the molecular basis underlying this heterogeneity remains unclear. To elucidate this, we integrated genomic, epigenomic, transcriptomic, proteomic, and metabolomic data, employing post-genome-wide association study methodologies to systematically investigate the molecular mechanisms of nine organ-specific aging clocks and four blood-based epigenetic clocks. We uncovered genetic correlations and specific phenotypic clusters among these aging-related traits, identified prioritized genetic drug targets for heterogeneous aging, and elucidated downstream proteomic and metabolomic effects mediated by heterogeneous aging. We constructed a cross-layer molecular interaction network of heterogeneous aging across multiple organ systems and characterized detectable biomarkers of this heterogeneity. Integrating these findings, we developed an R/Shiny-based framework that provides a comprehensive multi-omic molecular landscape of heterogeneous aging, thereby advancing the understanding of aging heterogeneity and informing precision medicine strategies to delay organ-specific aging and prevent or treat its associated chronic diseases.

Most genetic polymorphisms associated with complex traits are found in non-coding regions of the genome. Characterizing their effect presents a formidable challenge, and expression quantitative trait locus (eQTLs) mapping has been a key approach to do so. As comprehensive eQTL maps are available only for a few species, here we developed the Drosophila outbred synthetic population (Dros-OSP) and used it to characterize the landscape of transcriptional regulation in Drosophila melanogaster. We collected head and body transcriptomes and genomes from 1,286 outbred flies and mapped local and distant eQTLs for 98% of the genes. We characterized the network organization of the transcriptome across tissues and described the properties of local and distal eQTLs in terms of genetic diversity, heritability, connectivity, and pleiotropy. These results provide new insights into the genetic basis of transcriptional regulation in the fruit fly and offer a new mapping resource that will expand the possibilities currently available for the Drosophila community.

In this issue of Cell Genomics, McKeever et al.¹ generate a single-nucleus transcriptomic atlas of ALS/FTLD brain and reveal widespread alternative polyadenylation changes. Their findings highlight 3' end RNA processing as a central integrator of stress responses, cell-type specificity, and disease susceptibility, offering new mechanistic insight and potential therapeutic directions.

Though there has been substantial progress in the development of anti-human epidermal growth factor receptor 2 (HER2) therapies to treat HER2-positive metastatic breast cancer (MBC) within the past two decades, most patients still experience disease progression and cancer-related death. HER2-directed tyrosine kinase inhibitors can be highly effective therapies for patients with HER2-positive MBC; however, an understanding of resistance mechanisms is needed to better inform treatment approaches. We performed whole-exome sequencing on 111 patients with 73 tumor biopsies and 120 cell-free DNA samples to assess mechanisms of resistance. In 11 of 26 patients with acquired resistance, we identified alterations in previously characterized genes, such as PIK3CA and ERBB2, that could explain treatment resistance. Mutations in growing subclones identified potential mechanisms of resistance in 5 of 26 patients and included alterations in ESR1, FGFR2, and FGFR4. Additional studies are needed to assess the functional role and clinical utility of these alterations in driving resistance.