Cell genomics最新文献_第2页

Ribonuclease activity undermines immune sensing of naked extracellular RNA. 核糖核酸酶活性破坏裸细胞外RNA的免疫感知。

IF 11.1

Cell genomics Pub Date : 2025-05-14 Epub Date: 2025-05-06 DOI: 10.1016/j.xgen.2025.100874

Mauricio Castellano, Valentina Blanco, Marco Li Calzi, Bruno Costa, Kenneth Witwer, Marcelo Hill, Alfonso Cayota, Mercedes Segovia, Juan Pablo Tosar

{"title":"Ribonuclease activity undermines immune sensing of naked extracellular RNA.","authors":"Mauricio Castellano, Valentina Blanco, Marco Li Calzi, Bruno Costa, Kenneth Witwer, Marcelo Hill, Alfonso Cayota, Mercedes Segovia, Juan Pablo Tosar","doi":"10.1016/j.xgen.2025.100874","DOIUrl":"10.1016/j.xgen.2025.100874","url":null,"abstract":"Cell membranes are thought of as barriers to extracellular RNA (exRNA) uptake. While naked exRNAs can be spontaneously internalized by certain cells, functional cytosolic delivery has been rarely observed. Here, we show that extracellular ribonucleases (RNases)-primarily from cell culture supplements-have obscured the study of exRNA functionality. When ribonuclease inhibitor (RI) is added to cell cultures, naked exRNAs can trigger pro-inflammatory responses in dendritic cells and macrophages, largely via endosomal Toll-like receptors (TLRs). Moreover, naked exRNAs can escape endosomes, engaging cytosolic RNA sensors. In addition, naked extracellular mRNAs can be spontaneously internalized and translated by various cell types in an RI-dependent manner. In vivo, RI co-injection amplifies naked-RNA-induced activation of splenic lymphocytes and myeloid leukocytes. Furthermore, naked RNA is inherently pro-inflammatory in RNase-poor compartments like the peritoneal cavity. These findings demonstrate that naked RNA is bioactive without requiring vesicular encapsulation, making a case for nonvesicular-exRNA-mediated intercellular communication.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100874"},"PeriodicalIF":11.1,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced interpretation of immune cell phenotype and function through a rhesus macaque single-cell atlas. 通过恒河猴单细胞图谱增强免疫细胞表型和功能的解释。

IF 11.1

Cell genomics Pub Date : 2025-05-14 Epub Date: 2025-04-14 DOI: 10.1016/j.xgen.2025.100849

Eisa Mahyari, Gregory J Boggy, G W McElfresh, Maanasa Kaza, Sebastian Benjamin, Benjamin Varco-Merth, Sohita Ojha, Shana Feltham, William Goodwin, Candice Nkoy, Derick Duell, Andrea Selseth, Tyler Bennett, Aaron Barber-Axthelm, Jeremy V Smedley, Caralyn S Labriola, Michael K Axthelm, R Keith Reeves, Afam A Okoye, Scott G Hansen, Louis J Picker, Benjamin N Bimber

{"title":"Enhanced interpretation of immune cell phenotype and function through a rhesus macaque single-cell atlas.","authors":"Eisa Mahyari, Gregory J Boggy, G W McElfresh, Maanasa Kaza, Sebastian Benjamin, Benjamin Varco-Merth, Sohita Ojha, Shana Feltham, William Goodwin, Candice Nkoy, Derick Duell, Andrea Selseth, Tyler Bennett, Aaron Barber-Axthelm, Jeremy V Smedley, Caralyn S Labriola, Michael K Axthelm, R Keith Reeves, Afam A Okoye, Scott G Hansen, Louis J Picker, Benjamin N Bimber","doi":"10.1016/j.xgen.2025.100849","DOIUrl":"10.1016/j.xgen.2025.100849","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) allows cell classification using genome-wide transcriptional state; however, high-dimensional transcriptomic profiles, and the unsupervised analyses employed to interpret them, provide a systematically different view of biology than well-established functional/lineage definitions of immunocytes. Understanding these differences and limits is essential for accurate interpretation of these rich data. We present the Rhesus Immune Reference Atlas (RIRA), the first immune-focused macaque single-cell multi-tissue atlas. We contrasted transcriptional profiles against immune lineages, using surface protein and marker genes as ground truth. While the pattern of clustering can align with cell type, this is not always true. Especially within T and natural killer (NK) cells, many functionally distinct subsets lack defining markers, and strong shared expression programs, such as cytotoxicity, result in systematic intermingling by unsupervised clustering. We identified gene programs with high discriminatory/diagnostic value, including multi-gene signatures that model T/NK cell maturation. Directly measuring these diagnostic programs complements unsupervised analyses.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100849"},"PeriodicalIF":11.1,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144043867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved genetic discovery and fine-mapping resolution through multivariate latent factor analysis of high-dimensional traits. 通过高维性状的多变量潜在因子分析提高遗传发现和精细定位分辨率。

IF 11.1

Cell genomics Pub Date : 2025-05-14 Epub Date: 2025-04-11 DOI: 10.1016/j.xgen.2025.100847

Feng Zhou, William J Astle, Adam S Butterworth, Jennifer L Asimit

引用次数: 0

scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework. scPrediXcan将深度学习方法和单细胞数据集成到细胞类型特异性转录组关联研究框架中。

IF 11.1

Cell genomics Pub Date : 2025-05-14 DOI: 10.1016/j.xgen.2025.100875

Yichao Zhou, Temidayo Adeluwa, Lisha Zhu, Sofia Salazar-Magaña, Sarah Sumner, Hyunki Kim, Saideep Gona, Festus Nyasimi, Rohit Kulkarni, Joseph E Powell, Ravi Madduri, Boxiang Liu, Mengjie Chen, Hae Kyung Im

{"title":"scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework.","authors":"Yichao Zhou, Temidayo Adeluwa, Lisha Zhu, Sofia Salazar-Magaña, Sarah Sumner, Hyunki Kim, Saideep Gona, Festus Nyasimi, Rohit Kulkarni, Joseph E Powell, Ravi Madduri, Boxiang Liu, Mengjie Chen, Hae Kyung Im","doi":"10.1016/j.xgen.2025.100875","DOIUrl":"10.1016/j.xgen.2025.100875","url":null,"abstract":"Transcriptome-wide association studies (TWASs) help identify disease-causing genes but often fail to pinpoint disease mechanisms at the cellular level because of the limited sample sizes and sparsity of cell-type-specific expression data. Here, we propose scPrediXcan, which integrates state-of-the-art deep learning approaches that predict epigenetic features from DNA sequences with the canonical TWAS framework. Our prediction approach, ctPred, predicts cell-type-specific expression with high accuracy and captures complex gene-regulatory grammar that linear models overlook. Applied to type 2 diabetes (T2D) and systemic lupus erythematosus (SLE), scPrediXcan outperformed the canonical TWAS framework by identifying more candidate causal genes, explaining more genome-wide association study (GWAS) loci and providing insights into the cellular specificity of TWAS hits. Overall, our results demonstrate that scPrediXcan represents a significant advance, promising to deepen our understanding of the cellular mechanisms underlying complex diseases.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 5","pages":"100875"},"PeriodicalIF":11.1,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ethics choices during the Human Genome Project reflected their policy world, not ours. 人类基因组计划中的伦理选择反映了他们的政策世界，而不是我们的。

IF 11.1

Cell genomics Pub Date : 2025-05-14 DOI: 10.1016/j.xgen.2025.100841

Jonathan E LoTempio, Christopher R Donohue, Jonathan D Moreno, Robert Cook-Deegan

引用次数: 0

Variant-to-function approaches for adipose tissue: Insights into cardiometabolic disorders. 脂肪组织的变异-功能方法：对心脏代谢紊乱的见解。

IF 11.1

Cell genomics Pub Date : 2025-05-14 Epub Date: 2025-04-03 DOI: 10.1016/j.xgen.2025.100844

Sophia Metz, Jonathan Robert Belanich, Melina Claussnitzer, Tuomas Oskari Kilpeläinen

引用次数: 0

Genome-wide allele-specific expression in multi-tissue samples from healthy male baboons reveals the transcriptional complexity of mammals. 健康雄性狒狒多组织样本的全基因组等位基因特异性表达揭示了哺乳动物转录的复杂性。

IF 11.1

Cell genomics Pub Date : 2025-05-14 Epub Date: 2025-04-04 DOI: 10.1016/j.xgen.2025.100823

Ramesh Ramasamy, Muthuswamy Raveendran, R Alan Harris, Hiep D Le, Ludovic S Mure, Giorgia Benegiamo, Ouria Dkhissi-Benyahya, Howard Cooper, Jeffrey Rogers, Satchidananda Panda

{"title":"Genome-wide allele-specific expression in multi-tissue samples from healthy male baboons reveals the transcriptional complexity of mammals.","authors":"Ramesh Ramasamy, Muthuswamy Raveendran, R Alan Harris, Hiep D Le, Ludovic S Mure, Giorgia Benegiamo, Ouria Dkhissi-Benyahya, Howard Cooper, Jeffrey Rogers, Satchidananda Panda","doi":"10.1016/j.xgen.2025.100823","DOIUrl":"10.1016/j.xgen.2025.100823","url":null,"abstract":"Allele-specific expression (ASE) is pivotal in understanding the genetic underpinnings of phenotypic variation within species, differences in disease susceptibility, and responses to environmental factors. We processed 11 different tissue types collected from 12 age-matched healthy olive baboons (Papio anubis) for genome-wide ASE analysis. By sequencing their genomes at a minimum depth of 30×, we identified over 16 million single-nucleotide variants (SNVs). We also generated long-read sequencing data, enabling the phasing of all variants present within the coding regions of 96.5% of assayable protein-coding genes as a single haplotype block. Given the extensive heterozygosity of baboons relative to humans, we could quantify ASE across 72% of the total annotated protein-coding gene set. We identified genes that exhibit ASE and affect specific tissues and genotypes. We discovered ASE SNVs that also exist in human populations with identical alleles and that are designated as pathogenic by both the PrimateAI-3D and AlphaMissense models.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100823"},"PeriodicalIF":11.1,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Readdressing the role of ADRA2A in Raynaud's phenomenon: Methodological concerns and implications. 重新定位ADRA2A在雷诺现象中的作用：方法论关注和启示。

IF 11.1

Cell genomics Pub Date : 2025-05-14 DOI: 10.1016/j.xgen.2025.100883

Ali H Eid

引用次数: 0

Single-cell meta-analysis of T cells reveals clonal dynamics of response to checkpoint immunotherapy. T细胞的单细胞荟萃分析揭示了对检查点免疫治疗反应的克隆动力学。

IF 11.1

Cell genomics Pub Date : 2025-05-14 Epub Date: 2025-04-04 DOI: 10.1016/j.xgen.2025.100842

Ofir Shorer, Asaf Pinhasi, Keren Yizhak

引用次数: 0

Meet the author: Hae Kyung Im. 认识一下作者：海京任。