Cell Genomics细胞基因组学
Cell Genomics(英文缩写 CELL GENOM),ISSN 2666-979X,eISSN 2666-979X,中文译名:细胞基因组学 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-28 至 2026-09-28，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2023 | 11.100 | Q1 |
| 2024 | 9.000 | Q1 |
| 2025 | 8.400 | Q1 |
Cell Genomics 最新收录文献
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1. MOSHPIT: Accessible, reproducible metagenome data science on the QIIME 2 framework.
PMID:日期:2026-09-24Metagenome sequencing has revolutionized functional microbiome analysis across diverse ecosystems but is fraught with technical hurdles. We introduce MOSHPIT (MOdular SHotgun metagenome Pipelines with Integrated provenance Tracking; https://moshpit.qiime2.org)-software built on the QIIME 2/rachis framework (Q2F) that integrates best-in-class CAMI II- and LEMMI-validated metagenome tools with robust provenance tracking and multiple user interfaces-enabling streamlined, reproducible metagenome analysis for all expertise levels. By building on Q2F, MOSHPIT enhances scalability, interoperability, and reproducibility in complex workflows, democratizing and accelerating discovery at the frontiers of metagenomics.
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2. Intraspecific sequence variation and complete genomes refine the identification of rapidly evolved regions in humans.
PMID:日期:2026-09-23Humans exhibit significant phenotypic differences from other great apes, yet pinpointing the underlying genetic changes has been limited by incomplete reference genomes and a reliance on single assemblies to represent a species. We aligned 20 telomere-to-telomere (T2T) assemblies spanning great ape divergence and variation to define 1,596 Consensus HAQERs (consensus human ancestor quickly evolved regions), regions that diverged rapidly between the human-chimpanzee ancestor and an ancestral node of modern humans. Unlike prior HAQER sets, Consensus HAQERs incorporate population variation, thereby reducing the likelihood of intraspecies variation appearing as interspecies divergence. Consensus HAQERs exhibit signatures of elevated mutation rates, ancient positive selection, and bivalent regulatory function; are enriched in disease-linked loci; and often emerged in previously inaccessible repetitive DNA. Through multiplex, single-cell enhancer assays, we identify HAQERs as active enhancers in the developing brain and cardiomyocytes, and we highlight their potential contributions to human-specific gene regulation across multiple tissues.
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3. Pre-diagnosis plasma cell-free DNA reveals early signatures of prostate and breast cancer risk up to eight years prior to clinical detection.
PMID:日期:2026-09-21Genome-wide cell-free DNA (cfDNA) methylation profiling of 491 pre-diagnosis breast and prostate cancer plasma samples, some collected up to nine years before diagnosis, identifies early cancer-associated epigenetic alterations and predictive signatures. Differentially methylated regions were enriched in regulatory and repetitive elements and reflected cancer-tissue- and immune-cell-associated DNA methylation patterns. Logistic regression models trained on discovery set samples showed that cfDNA silencer-region methylation robustly predicted future prostate cancer, with high-risk individuals exhibiting a 3.55-fold increased hazard of developing prostate cancer. Enhancer hypermethylation modestly predicted incident breast cancer but strongly distinguished established late-stage breast cancers, with high-risk individuals showing a 2.3-fold increased hazard. These results highlight cfDNA methylation as a promising biomarker for early cancer risk prediction and surveillance.
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4. Concentrating cell-type-specific transcriptional signatures in bone marrow from interspecies comparisons.
PMID:日期:2026-09-21Cell-type definition is commonly achieved using marker genes. Because cell types are broadly conserved across evolution, marker genes are identifiable via interspecies comparisons. We generated single-cell RNA sequencing datasets of bone marrow niche and hematopoietic progenitor compartments from four mouse species. Using these data, we developed a strategy that adds conservation of transcriptional levels to existing approaches that identify marker genes using conserved cell-type specificity. The resulting "signature gene" lists contain both well-known and underexplored bone marrow markers. Signature genes capture cell identities and thus can robustly discern homologous cell types in diverse tissues of evolutionarily distant species. Unbiased benchmarking assessments demonstrated that our signature genes are comparable or superior to larger, less-conserved gene lists. Last, we confirm our framework's versatility and robustness using published datasets from another tissue and mammalian order. Thus, combining conserved cell-type specificity and transcriptional levels is a powerful, widely applicable strategy to distill profoundly descriptive signatures.
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5. Mutation timing, accumulation, and selection in the male germline shape inheritance risk for developmental disorders.
PMID:日期:2026-09-16De novo mutations (DNMs) in the paternal germline are a major cause of developmental disorders, but how mutation timing, paternal age, and spermatogonial selection jointly shape transmissible risk within individual fathers is unclear. We combined trio whole-genome sequencing from 167 families with deep targeted NanoSeq profiling of sperm from 127 fathers of children with confirmed pathogenic DNMs. Transmitted DNM burden and paternal sperm mutation burden, spectra, and selection landscape were indistinguishable from population reference cohorts. Six fathers carried pathogenic early mosaic variants detectable in sperm at variant allele fractions (VAFs) of 0.7%-14.8%, creating individual recurrence-risk outliers. However, early mosaics accounted for ∼8% of the cohort-aggregated pathogenic burden exome-wide, compared with ∼18% from known positively selected drivers and ∼74% from other rare variants accumulating with paternal age. Thus, paternal de novo disease risk is shaped primarily by universal age-associated mutation and selection, while early mosaicism creates uncommon but clinically important high-risk individuals.
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6. Jingjing Zhai and Edward S. Buckler.
PMID:日期:2026-09-09Dr. Laura Zahn asked the authors, Dr. Jingjing Zhai and Dr. Edward (Ed) S. Buckler, to tell us about their research relating to their Cell Genomics paper, "PlantCAD2: A DNA foundation model for interpreting genomes across flowering plants."
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7. Stressed-out immune cells.
PMID:日期:2026-09-09Connections between chronic stress, inflammation, and human diseases are well-established but poorly understood. In this issue of Cell Genomics, the effects of stress hormones on the immune system are investigated using single-cell RNA sequencing to better understand how stress-regulated immunological signaling contributes to disease.
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8. Pouria Salehi Nowbandegani.
PMID:日期:2026-09-09Dr. Laura Zahn asked Dr. Pouria Salehi Nowbandegani about their study, "Defining and cataloging variants in pangenome graphs," and how they came to study this aspect of genomics.
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9. Defining and cataloging variants in pangenome graphs.
PMID:日期:2026-09-09Structural variation causes some human haplotypes to align poorly with the linear reference genome, and this leads to "reference bias." A pangenome reference graph could ameliorate this bias by relating a sample to multiple reference assemblies. However, this approach requires a new definition of a "genetic variant." We define pangenome variants against a reference tree that includes all nodes (sequences) of the pangenome graph but only a subset of its edges; non-reference edges are variant edges. Analyzing the Minigraph-Cactus draft human pangenome reference graph, we identified 29.6 million genetic variants. 3.5 million variants (11.7%) have a reference allele that is not on GRCh38; these variants are difficult to detect without a pangenome reference and are found within tangled, multiallelic regions. We analyze the HLA-A and RHD gene regions and identify thousands of small variants entangled with several structural variants. We release the open-source pantree and a variant call format (VCF) variant catalog.
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10. Identifying independent causal cell types for human diseases and risk variants.
PMID:日期:2026-09-09Genome-wide association studies (GWASs) have shown that disease-associated variants are concentrated in candidate regulatory elements (cREs) from disease-relevant cell types. Here, we introduce cell-type fine-mapping (CT-FM) and CT-FM-SNP, probabilistic methods that account for cRE sharing across cell types to infer independent causal cell-type sets for complex traits and candidate causal variants. Applying CT-FM to 63 GWASs using 924 cRE annotations, we inferred 79 independent cell-type sets explaining 39.0% ± 1.8% of trait SNP heritability and identified 14 traits with multiple independent cellular mechanisms, including height, schizophrenia, and autoimmune diseases. Applying CT-FM-SNP to 39 UK Biobank traits, we assigned high-confidence causal cell types to 3,091 candidate non-coding variant-trait pairs. Most variants appeared to act through a single cell-type set, whereas pleiotropic variants often acted through different cell types depending on the phenotype context. Together, CT-FM and CT-FM-SNP provide a framework for dissecting the cellular architecture of complex traits.