Cell genomics最新文献_第3页

CSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data. CSI-GEP：一种基于gpu的无监督机器学习方法，用于恢复atlas级单细胞RNA-seq数据中的基因表达程序。

IF 11.1

Cell genomics Pub Date : 2025-01-08 DOI: 10.1016/j.xgen.2024.100739

Xueying Liu, Richard H Chapple, Declan Bennett, William C Wright, Ankita Sanjali, Erielle Culp, Yinwen Zhang, Min Pan, Paul Geeleher

{"title":"CSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data.","authors":"Xueying Liu, Richard H Chapple, Declan Bennett, William C Wright, Ankita Sanjali, Erielle Culp, Yinwen Zhang, Min Pan, Paul Geeleher","doi":"10.1016/j.xgen.2024.100739","DOIUrl":"10.1016/j.xgen.2024.100739","url":null,"abstract":"Exploratory analysis of single-cell RNA sequencing (scRNA-seq) typically relies on hard clustering over two-dimensional projections like uniform manifold approximation and projection (UMAP). However, such methods can severely distort the data and have many arbitrary parameter choices. Methods that can model scRNA-seq data as non-discrete \"gene expression programs\" (GEPs) can better preserve the data's structure, but currently, they are often not scalable, not consistent across repeated runs, and lack an established method for choosing key parameters. Here, we developed a GPU-based unsupervised learning approach, \"consensus and scalable inference of gene expression programs\" (CSI-GEP). We show that CSI-GEP can recover ground truth GEPs in real and simulated atlas-scale scRNA-seq datasets, significantly outperforming cutting-edge methods, including GPT-based neural networks. We applied CSI-GEP to a whole mouse brain atlas of 2.2 million cells, disentangling endothelial cell types missed by other methods, and to an integrated scRNA-seq atlas of human tumors and cell lines, discovering mesenchymal-like GEPs unique to cancer cells growing in culture.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 1","pages":"100739"},"PeriodicalIF":11.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Double or nothing: Ancient duplications in the amylase locus drove human adaptation. 要么加倍，要么一无所有：古代淀粉酶位点的复制驱动着人类的适应。

IF 11.1

Cell genomics Pub Date : 2025-01-08 DOI: 10.1016/j.xgen.2024.100741

Shahar Silverman, Diyendo Massilani

引用次数: 0

The trait-specific timing of accelerated genomic change in the human lineage. 人类谱系中加速基因组变化的特征特异性时间。

IF 11.1

Cell genomics Pub Date : 2025-01-08 DOI: 10.1016/j.xgen.2024.100740

Eucharist Kun, Mashaal Sohail, Vagheesh M Narasimhan

{"title":"The trait-specific timing of accelerated genomic change in the human lineage.","authors":"Eucharist Kun, Mashaal Sohail, Vagheesh M Narasimhan","doi":"10.1016/j.xgen.2024.100740","DOIUrl":"10.1016/j.xgen.2024.100740","url":null,"abstract":"Humans exhibit distinct characteristics compared to our primate and ancient hominin ancestors. To investigate genomic bursts in the evolution of these traits, we use two complementary approaches to examine enrichment among genome-wide association study loci spanning diseases and AI-based image-derived brain, heart, and skeletal tissue phenotypes with genomic regions reflecting four evolutionary divergence points. These regions cover epigenetic differences among humans and rhesus macaques, human accelerated regions (HARs), ancient selective sweeps, and Neanderthal-introgressed alleles. Skeletal traits such as pelvic width and limb proportions showed enrichment in evolutionary annotations that mirror morphological changes in the primate fossil record. Additionally, we observe enrichment of loci associated with the longitudinal fasciculus in human-gained epigenetic elements since macaques, the visual cortex in HARs, and the thalamus proper in Neanderthal-introgressed alleles, implying that associated cognitive functions such as language processing, decision-making, sensory signaling, and motor control are enriched at different evolutionary depths.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 1","pages":"100740"},"PeriodicalIF":11.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk. 应答qtl、染色质可及性和软骨细胞中的三维染色质结构为骨关节炎风险提供了机制洞察。

IF 11.1

Cell genomics Pub Date : 2025-01-08 DOI: 10.1016/j.xgen.2024.100738

Nicole E Kramer, Seyoun Byun, Philip Coryell, Susan D'Costa, Eliza Thulson, HyunAh Kim, Sylvie M Parkus, Marielle L Bond, Emma R Klein, Jacqueline Shine, Susanna Chubinskaya, Michael I Love, Karen L Mohlke, Brian O Diekman, Richard F Loeser, Douglas H Phanstiel

{"title":"Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk.","authors":"Nicole E Kramer, Seyoun Byun, Philip Coryell, Susan D'Costa, Eliza Thulson, HyunAh Kim, Sylvie M Parkus, Marielle L Bond, Emma R Klein, Jacqueline Shine, Susanna Chubinskaya, Michael I Love, Karen L Mohlke, Brian O Diekman, Richard F Loeser, Douglas H Phanstiel","doi":"10.1016/j.xgen.2024.100738","DOIUrl":"10.1016/j.xgen.2024.100738","url":null,"abstract":"Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWASs) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. To address this gap, we mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA sequencing in chondrocytes from 101 donors across two conditions uncovered 3,782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 6 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"5 1","pages":"100738"},"PeriodicalIF":11.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical modeling of single-cell epitranscriptomics enabled trajectory and regulatory inference of RNA methylation. 单细胞表转录组学的统计建模使RNA甲基化的轨迹和调控推理成为可能。

IF 11.1

Cell genomics Pub Date : 2025-01-08 Epub Date: 2024-12-05 DOI: 10.1016/j.xgen.2024.100702

Haozhe Wang, Yue Wang, Jingxian Zhou, Bowen Song, Gang Tu, Anh Nguyen, Jionglong Su, Frans Coenen, Zhi Wei, Daniel J Rigden, Jia Meng

{"title":"Statistical modeling of single-cell epitranscriptomics enabled trajectory and regulatory inference of RNA methylation.","authors":"Haozhe Wang, Yue Wang, Jingxian Zhou, Bowen Song, Gang Tu, Anh Nguyen, Jionglong Su, Frans Coenen, Zhi Wei, Daniel J Rigden, Jia Meng","doi":"10.1016/j.xgen.2024.100702","DOIUrl":"10.1016/j.xgen.2024.100702","url":null,"abstract":"As a fundamental mechanism for gene expression regulation, post-transcriptional RNA methylation plays versatile roles in various biological processes and disease mechanisms. Recent advances in single-cell technology have enabled simultaneous profiling of transcriptome-wide RNA methylation in thousands of cells, holding the promise to provide deeper insights into the dynamics, functions, and regulation of RNA methylation. However, it remains a major challenge to determine how to best analyze single-cell epitranscriptomics data. In this study, we developed SigRM, a computational framework for effectively mining single-cell epitranscriptomics datasets with a large cell number, such as those produced by the scDART-seq technique from the SMART-seq2 platform. SigRM not only outperforms state-of-the-art models in RNA methylation site detection on both simulated and real datasets but also provides rigorous quantification metrics of RNA methylation levels. This facilitates various downstream analyses, including trajectory inference and regulatory network reconstruction concerning the dynamics of RNA methylation.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100702"},"PeriodicalIF":11.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cell type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures. 在异质分化培养中，细胞类型和动态状态控制着基因表达的遗传调控。

IF 11.1

Cell genomics Pub Date : 2024-12-11 Epub Date: 2024-12-02 DOI: 10.1016/j.xgen.2024.100701

Joshua M Popp, Katherine Rhodes, Radhika Jangi, Mingyuan Li, Kenneth Barr, Karl Tayeb, Alexis Battle, Yoav Gilad

引用次数: 0

Genome-wide chromosome architecture prediction reveals biophysical principles underlying gene structure. 全基因组染色体结构预测揭示了基因结构的生物物理原理。

IF 11.1

Cell genomics Pub Date : 2024-12-11 Epub Date: 2024-11-25 DOI: 10.1016/j.xgen.2024.100698

Michael Chiang, Chris A Brackley, Catherine Naughton, Ryu-Suke Nozawa, Cleis Battaglia, Davide Marenduzzo, Nick Gilbert

{"title":"Genome-wide chromosome architecture prediction reveals biophysical principles underlying gene structure.","authors":"Michael Chiang, Chris A Brackley, Catherine Naughton, Ryu-Suke Nozawa, Cleis Battaglia, Davide Marenduzzo, Nick Gilbert","doi":"10.1016/j.xgen.2024.100698","DOIUrl":"10.1016/j.xgen.2024.100698","url":null,"abstract":"Classical observations suggest a connection between 3D gene structure and function, but testing this hypothesis has been challenging due to technical limitations. To explore this, we developed epigenetic highly predictive heteromorphic polymer (e-HiP-HoP), a model based on genome organization principles to predict the 3D structure of human chromatin. We defined a new 3D structural unit, a \"topos,\" which represents the regulatory landscape around gene promoters. Using GM12878 cells, we predicted the 3D structure of over 10,000 active gene topoi and stored them in the 3DGene database. Data mining revealed folding motifs and their link to Gene Ontology features. We computed a structural diversity score and identified influential nodes-chromatin sites that frequently interact with gene promoters, acting as key regulators. These nodes drive structural diversity and are tied to gene function. e-HiP-HoP provides a framework for modeling high-resolution chromatin structure and a mechanistic basis for chromatin contact networks that link 3D gene structure with function.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100698"},"PeriodicalIF":11.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142735179","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

A combined deep learning framework for mammalian m6A site prediction. 哺乳动物 m6A 位点预测的深度学习组合框架。

IF 11.1

Cell genomics Pub Date : 2024-12-11 Epub Date: 2024-11-20 DOI: 10.1016/j.xgen.2024.100697

Rui Fan, Chunmei Cui, Boming Kang, Zecheng Chang, Guoqing Wang, Qinghua Cui

引用次数: 0

Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes. 基因剂量对认知能力的影响：一项基于功能的脑和非脑过程关联研究。

IF 11.1

Cell genomics Pub Date : 2024-12-11 DOI: 10.1016/j.xgen.2024.100721

Guillaume Huguet, Thomas Renne, Cécile Poulain, Alma Dubuc, Kuldeep Kumar, Sayeh Kazem, Worrawat Engchuan, Omar Shanta, Elise Douard, Catherine Proulx, Martineau Jean-Louis, Zohra Saci, Josephine Mollon, Laura M Schultz, Emma E M Knowles, Simon R Cox, David Porteous, Gail Davies, Paul Redmond, Sarah E Harris, Gunter Schumann, Guillaume Dumas, Aurélie Labbe, Zdenka Pausova, Tomas Paus, Stephen W Scherer, Jonathan Sebat, Laura Almasy, David C Glahn, Sébastien Jacquemont

{"title":"Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes.","authors":"Guillaume Huguet, Thomas Renne, Cécile Poulain, Alma Dubuc, Kuldeep Kumar, Sayeh Kazem, Worrawat Engchuan, Omar Shanta, Elise Douard, Catherine Proulx, Martineau Jean-Louis, Zohra Saci, Josephine Mollon, Laura M Schultz, Emma E M Knowles, Simon R Cox, David Porteous, Gail Davies, Paul Redmond, Sarah E Harris, Gunter Schumann, Guillaume Dumas, Aurélie Labbe, Zdenka Pausova, Tomas Paus, Stephen W Scherer, Jonathan Sebat, Laura Almasy, David C Glahn, Sébastien Jacquemont","doi":"10.1016/j.xgen.2024.100721","DOIUrl":"10.1016/j.xgen.2024.100721","url":null,"abstract":"Copy-number variants (CNVs) that increase the risk for neurodevelopmental disorders also affect cognitive ability. However, such CNVs remain challenging to study due to their scarcity, limiting our understanding of gene-dosage-sensitive biological processes linked to cognitive ability. We performed a genome-wide association study (GWAS) in 258,292 individuals, which identified-for the first time-a duplication at 2q12.3 associated with higher cognitive performance. We developed a functional-burden analysis, which tested the association between cognition and CNVs disrupting 6,502 gene sets biologically defined across tissues, cell types, and ontologies. Among those, 864 gene sets were associated with cognition, and effect sizes of deletion and duplication were negatively correlated. The latter suggested that functions across all biological processes were sensitive to either deletions (e.g., subcortical regions, postsynaptic) or duplications (e.g., cerebral cortex, presynaptic). Associations between non-brain tissues and cognition were driven partly by constrained genes, which may shed light on medical comorbidities in neurodevelopmental disorders.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 12","pages":"100721"},"PeriodicalIF":11.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11701252/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142820147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deciphering proteins in Alzheimer's disease: A new Mendelian randomization method integrated with AlphaFold3 for 3D structure prediction. 解码阿尔茨海默病中的蛋白质：一种新的孟德尔随机化方法与AlphaFold3相结合，用于3D结构预测。

IF 11.1

Cell genomics Pub Date : 2024-12-11 Epub Date: 2024-12-04 DOI: 10.1016/j.xgen.2024.100700

Minhao Yao, Gary W Miller, Badri N Vardarajan, Andrea A Baccarelli, Zijian Guo, Zhonghua Liu

{"title":"Deciphering proteins in Alzheimer's disease: A new Mendelian randomization method integrated with AlphaFold3 for 3D structure prediction.","authors":"Minhao Yao, Gary W Miller, Badri N Vardarajan, Andrea A Baccarelli, Zijian Guo, Zhonghua Liu","doi":"10.1016/j.xgen.2024.100700","DOIUrl":"10.1016/j.xgen.2024.100700","url":null,"abstract":"Hidden confounding biases hinder identifying causal protein biomarkers for Alzheimer's disease in non-randomized studies. While Mendelian randomization (MR) can mitigate these biases using protein quantitative trait loci (pQTLs) as instrumental variables, some pQTLs violate core assumptions, leading to biased conclusions. To address this, we propose MR-SPI, a novel MR method that selects valid pQTL instruments using Leo Tolstoy's Anna Karenina principle and performs robust post-selection inference. Integrating MR-SPI with AlphaFold3, we developed a computational pipeline to identify causal protein biomarkers and predict 3D structural changes. Applied to genome-wide proteomics data from 54,306 UK Biobank participants and 455,258 subjects (71,880 cases and 383,378 controls) for a genome-wide association study of Alzheimer's disease, we identified seven proteins (TREM2, PILRB, PILRA, EPHA1, CD33, RET, and CD55) with structural alterations due to missense mutations. These findings offer insights into the etiology and potential drug targets for Alzheimer's disease.","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100700"},"PeriodicalIF":11.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142787878","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