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Microorganisms as architects of a sustainable future 微生物是可持续未来的建筑师。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-10-16 DOI: 10.1038/s41576-025-00906-2
Nicole S. Webster
Microorganisms are central to climate stability, food security and biodiversity, yet they remain absent from global sustainability frameworks. Recognizing and mobilizing their power is essential if we are to meet the challenges of the coming decades. Microorganisms are central to climate stability, food security and biodiversity, yet they remain absent from global sustainability frameworks. In this Comment, Nicole Webster highlights the power of eco-evolutionary genomics in transforming sustainability science and calls for the inclusion of microbes in global policies.
微生物对气候稳定、粮食安全和生物多样性至关重要,但它们仍然没有出现在全球可持续性框架中。如果我们要迎接未来几十年的挑战,就必须认识到并调动它们的力量。微生物对气候稳定、粮食安全和生物多样性至关重要,但它们仍然没有出现在全球可持续性框架中。在这篇评论中,Nicole Webster强调了生态进化基因组学在改变可持续性科学方面的力量,并呼吁将微生物纳入全球政策。
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引用次数: 0
Clinical use of polygenic risk scores: current status, barriers and future directions. 多基因风险评分的临床应用现状、障碍及未来发展方向。
IF 42.7 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-10-10 DOI: 10.1038/s41576-025-00900-8
Iftikhar J Kullo
Genome-wide association studies have identified thousands of single-nucleotide variants that are associated with complex traits, including cardiometabolic diseases, cancers and neurological disorders. Polygenic risk scores (PRSs), which aggregate the effects of these variants, can help to identify individuals who are at increased risk of developing such diseases. As PRSs are typically only weakly associated with conventional risk factors for these diseases, they have incremental predictive value and are beginning to be incorporated into clinical practice to guide early detection and preventive strategies. However, challenges to their use - such as suboptimal precision, poor transferability across diverse populations and low familiarity among patients and providers with the concept of polygenic risk - must be addressed before their broader clinical adoption. This Review explores the current state of the field, highlights key challenges and outlines future directions for the use of PRSs to improve risk prediction and to advance personalized prevention in clinical care.
全基因组关联研究已经确定了数千种与复杂特征相关的单核苷酸变异,包括心脏代谢疾病、癌症和神经系统疾病。多基因风险评分(PRSs)可以汇总这些变异的影响,有助于识别患此类疾病风险增加的个体。由于prs通常与这些疾病的传统危险因素仅弱相关,因此它们具有逐渐增加的预测价值,并开始纳入临床实践,以指导早期发现和预防策略。然而,在其广泛的临床应用之前,必须解决其使用所面临的挑战,例如精度欠佳,不同人群之间的可移植性差以及患者和提供者对多基因风险概念的熟悉程度低。本综述探讨了该领域的现状,强调了主要挑战,并概述了使用prs来改进风险预测和推进临床护理中的个性化预防的未来方向。
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引用次数: 0
Forensic genetics in the omics era 组学时代的法医遗传学。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-10-08 DOI: 10.1038/s41576-025-00896-1
Manfred Kayser
Recent advances in forensic genetics, driven by technological innovation coupled with the use of an expanding range of nucleic acid markers, have markedly improved the scope, accuracy and reliability of evidential information obtainable from human biological traces recovered at crime scenes. The majority of these biomarkers have been identified using non-targeted omics approaches, including genomics, transcriptomics, epigenomics and microbiome profiling. Moreover, targeted massively parallel sequencing, in some cases non-targeted whole-genome sequencing, are being applied to the analyses of biological trace material. These approaches and methods are being used for the identification of perpetrators (including monozygotic twins), their relatives or victims of criminal activities; the prediction of phenotypic and behavioural traits of unknown individuals; and the determination of trace characteristics, including tissue type and time of deposition. Recent advances in forensic genetics have improved the range, precision and reliability of forensic information obtainable from biological trace material. The author reviews how non-targeted and targeted omics approaches and methods are improving crime scene analyses being applied for the identification of perpetrators and their relatives or victims, the prediction of phenotypic traits, and the determination of trace characteristics.
在技术创新的推动下,加上核酸标记的使用范围不断扩大,法医遗传学取得了最新进展,显著提高了从犯罪现场恢复的人类生物痕迹中获得的证据信息的范围、准确性和可靠性。这些生物标记物中的大多数是用非靶向组学方法鉴定的,包括基因组学、转录组学、表观基因组学和微生物组分析。此外,靶向大规模平行测序,在某些情况下,非靶向全基因组测序,正在应用于生物痕量物质的分析。正在使用这些办法和方法来查明犯罪者(包括同卵双胞胎)、其亲属或犯罪活动的受害者;未知个体的表型和行为特征预测;并测定微量特征,包括组织类型和沉积时间。
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引用次数: 0
Host–pathogen interactions shape human evolution and future pandemics 宿主-病原体相互作用影响着人类进化和未来的流行病。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-10-07 DOI: 10.1038/s41576-025-00902-6
Tzachi Hagai
In this Journal Club, Tzachi Hagai highlights a 2005 paper by Sawyer et al. that tested the functional relationship of evolutionary changes in immune genes with infection outcomes.
在这个杂志俱乐部中,Tzachi Hagai强调了Sawyer等人2005年的一篇论文,该论文测试了免疫基因的进化变化与感染结果的功能关系。
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引用次数: 0
The evolution of Mycobacterium tuberculosis as humans migrated out of Africa 人类迁出非洲时结核分枝杆菌的进化。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-10-01 DOI: 10.1038/s41576-025-00901-7
Sara Suliman
Sara Suliman describes a seminal 2013 publication by Comas et al. that investigated the origins of the tuberculosis-causing bacteria and its coevolution with diverse human populations.
Sara Suliman描述了Comas等人在2013年发表的一篇开创性论文,该论文调查了导致结核病的细菌的起源及其与不同人群的共同进化。
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引用次数: 0
Spatial architecture of development and disease 发展和疾病的空间建筑。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-09-30 DOI: 10.1038/s41576-025-00892-5
Enikő Lázár, Joakim Lundeberg
Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect disease processes. Recent advances in high-throughput spatial omics technologies have enabled the investigation of this complexity in stunning detail, providing groundbreaking insights into how spatial molecular organization shapes health and disease. Spatial analysis empowers the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. This Review examines spatially resolved pathological molecular alterations in a wide range of disease processes, such as developmental disorders, tumorigenesis, fibrosis and injury responses, neurodegeneration, infection and inflammation, through the lens of these universal biological frameworks. We discuss challenges, opportunities and promising examples in advancing these technologies to clinical applications, including the increasing importance of artificial intelligence. Finally, we explore possible avenues for a more comprehensive, multidimensional assessment of tissues. Spatial omics has empowered the discovery of developmental and disease-associated molecular signatures, cell states and multicellular niches, as well as the evaluation of disease heterogeneity within and across organs. The authors review spatially resolved molecular changes across diseases and discuss the potential of spatial multi-omics for clinical applications, including the recent impact of artificial intelligence.
组织结构是多层分子景观的产物,即使是空间环境中细微的破坏也可能引发或反映疾病过程。高通量空间组学技术的最新进展使得对这种复杂性的研究能够以惊人的细节进行,为空间分子组织如何塑造健康和疾病提供了开创性的见解。空间分析有助于发现发育和疾病相关的分子特征、细胞状态和多细胞生态位,以及评估器官内和器官间的疾病异质性。本综述通过这些普遍的生物学框架,研究了在广泛的疾病过程中空间解决的病理分子改变,如发育障碍、肿瘤发生、纤维化和损伤反应、神经变性、感染和炎症。我们讨论了将这些技术推进临床应用的挑战、机遇和有希望的例子,包括人工智能日益增长的重要性。最后,我们探讨了对组织进行更全面、多维度评估的可能途径。
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引用次数: 0
A clinical milestone for CRISPR in sickle-cell disease CRISPR治疗镰状细胞病的临床里程碑。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-09-26 DOI: 10.1038/s41576-025-00898-z
Gerald Mboowa
Gerald Mboowa reflects on the dual legacy of a 2021 study by Frangoul et al., which demonstrated safe and effective CRISPR-based editing to treat sickle-cell disease and β-thalassemia, as both a triumph of modern science and a call to action for global health.
Gerald Mboowa回顾了2021年Frangoul等人的一项研究的双重遗产,该研究证明了基于crispr的编辑技术可以安全有效地治疗镰状细胞病和β-地中海贫血,这既是现代科学的胜利,也是为全球健康采取行动的呼吁。
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引用次数: 0
Advances in haplotype phasing and genotype imputation 单倍型分期和基因型插入的研究进展。
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-09-24 DOI: 10.1038/s41576-025-00895-2
Quan Sun, Yun Li
Haplotype phasing — to determine which genetic variants reside on the same chromosome — and genotype imputation — to infer unobserved genotypes — have become indispensable steps to improve genome coverage for genomic analyses such as genome-wide association studies. Several tools exist for haplotype phasing and genotype imputation, all of which have continuously evolved to accommodate the increasing sample sizes of genomic studies and rapidly improving sequencing technologies. To fully leverage these recent advances, researchers must deliberate several practical considerations, including tool choice, quality control filters, data privacy concerns and reference panel choice. Looking ahead, long-read sequencing technologies are poised to bring novel opportunities to this field and drive methodological development. Haplotype phasing and genotype imputation improve genomic analyses by determining which variants occur together on a chromosome and inferring unobserved varants, respectively. In this Review, Sun and Li describe how tools for haplotype phasing and genotype imputation have evolved to accommodate increasingly larger genomic datasets and new sequencing technologies.
单倍型分期——确定哪些遗传变异驻留在同一染色体上——和基因型插入——推断未观察到的基因型——已经成为提高基因组分析(如全基因组关联研究)的基因组覆盖率必不可少的步骤。目前已有几种工具用于单倍型分期和基因型插入,所有这些工具都在不断发展,以适应不断增加的基因组研究样本量和快速改进的测序技术。为了充分利用这些最新进展,研究人员必须考虑几个实际问题,包括工具选择、质量控制过滤器、数据隐私问题和参考面板选择。展望未来,长读测序技术有望为这一领域带来新的机遇,并推动方法的发展。
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引用次数: 0
Predicting the regulatory genome 预测调控基因组
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-09-16 DOI: 10.1038/s41576-025-00887-2
Sarthak Tiwari, Alireza Karbalayghareh, Christina S. Leslie
Deep learning models have made impressive strides in decoding the regulatory genome, but key challenges remain unsolved. In this Comment, the authors overview the latest deep learning models for predicting regulatory function from genomic sequence and highlight key topics going forward, including the trade-off between specialized and general models, multitasking across cell types, and training on genetic variation and diverse species.
深度学习模型在解码调控基因组方面取得了令人印象深刻的进展,但关键挑战仍未解决。在这篇评论中,作者概述了用于预测基因组序列调控功能的最新深度学习模型,并强调了未来的关键主题,包括专业模型和通用模型之间的权衡,跨细胞类型的多任务处理,以及遗传变异和物种多样性的训练。
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引用次数: 0
Cis-regulatory elements at cellular resolution 细胞分辨率的顺式调控元件
IF 52 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2025-09-16 DOI: 10.1038/s41576-025-00882-7
Yi Xiang See, Tim Stuart, Jay W. Shin
Recent advances in single-cell profiling technologies now enable routine and scalable measurements of cis-regulatory element activity across diverse cell types, disease states and genetic backgrounds. It is time to coordinate a global effort to systematically map cis-regulatory element function at single-cell resolution. In this Comment, the authors outline some key next steps to advance our understanding of cis-regulatory elements at single-cell resolution, which includes harmonizing global efforts to construct a comprehensive single-cell atlas of gene regulation.
单细胞分析技术的最新进展现在可以在不同的细胞类型、疾病状态和遗传背景下常规和可扩展地测量顺式调节元件的活性。现在是时候协调全球的努力,系统地绘制单细胞分辨率的顺式调控元件功能。在这篇评论中,作者概述了一些关键的下一步,以提高我们对单细胞分辨率顺式调控元件的理解,其中包括协调全球努力构建一个全面的单细胞基因调控图谱。
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Nature Reviews Genetics
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