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Inference and applications of ancestral recombination graphs 祖先重组图的推断与应用
IF 42.7 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-30 DOI: 10.1038/s41576-024-00772-4
Rasmus Nielsen, Andrew H. Vaughn, Yun Deng

Ancestral recombination graphs (ARGs) summarize the complex genealogical relationships between individuals represented in a sample of DNA sequences. Their use is currently revolutionizing the field of population genetics and is leading to the development of powerful new methods to elucidate individual and population genetic processes, including population size history, migration, admixture, recombination, mutation and selection. In this Review, we introduce the readers to the structure of ARGs and discuss how they relate to processes such as recombination and genetic drift. We explore differences and similarities between methods of estimating ARGs and provide concrete illustrative examples of how ARGs can be used to elucidate population-level processes.

祖先重组图(ARGs)概括了 DNA 序列样本中个体之间复杂的系谱关系。目前,ARG 的使用正在给群体遗传学领域带来革命性的变化,并促使人们开发出功能强大的新方法来阐明个体和群体的遗传过程,包括群体规模历史、迁移、混杂、重组、变异和选择。在这篇综述中,我们将向读者介绍ARGs的结构,并讨论它们与重组和遗传漂变等过程的关系。我们探讨了 ARGs 估算方法的异同,并提供了具体的示例,说明如何利用 ARGs 阐明种群水平的过程。
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引用次数: 0
Selection on structural variation in the amylase locus 对淀粉酶基因座结构变异的选择
IF 39.1 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-27 DOI: 10.1038/s41576-024-00782-2
Kirsty Minton
Bolognini et al. report evidence of positive selection for human amylase gene duplications associated with the agricultural revolution.
Bolognini 等人报告了与农业革命有关的人类淀粉酶基因重复的正选择证据。
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引用次数: 0
The evolution of DNA sequencing with microfluidics 利用微流体技术进行 DNA 测序的发展历程
IF 42.7 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-27 DOI: 10.1038/s41576-024-00783-1
Camille L. G. Lambert, Guido van Mierlo, Johannes J. Bues, Orane J. Guillaume-Gentil, Bart Deplancke
The adoption of microfluidics was fundamental to the development of cost-effective, high-throughput DNA sequencing. As the field progresses towards multi-omics, we reflect on the key concepts underlying microfluidics and how resulting engineering advances at the microscale drove the evolution of genomic sequencing. The adoption of microfluidics was fundamental to the development of cost-effective, high-throughput DNA sequencing. As the field progresses towards multi-omics, Lambert et al. reflect on the key concepts underlying microfluidics and how resulting engineering advances at the microscale drove the evolution of genomic sequencing.
微流控技术的采用是开发具有成本效益的高通量 DNA 测序技术的基础。随着多组学领域的发展,我们思考了微流控技术的关键概念,以及由此产生的微尺度工程技术进步如何推动了基因组测序的发展。微流控技术的采用是开发具有成本效益的高通量 DNA 测序技术的基础。随着多组学领域的发展,Lambert 等人反思了微流控技术的关键概念,以及由此产生的微尺度工程技术进步如何推动了基因组测序的发展。
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引用次数: 0
Genome-scale models in human metabologenomics 人类代谢组学中的基因组尺度模型
IF 42.7 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-19 DOI: 10.1038/s41576-024-00768-0
Adil Mardinoglu, Bernhard Ø. Palsson

Metabologenomics integrates metabolomics with other omics data types to comprehensively study the genetic and environmental factors that influence metabolism. These multi-omics data can be incorporated into genome-scale metabolic models (GEMs), which are highly curated knowledge bases that explicitly account for genes, transcripts, proteins and metabolites. By including all known biochemical reactions catalysed by enzymes and transporters encoded in the human genome, GEMs analyse and predict the behaviour of complex metabolic networks. Continued advancements to the scale and scope of GEMs — from cells and tissues to microbiomes and the whole body — have helped to design effective treatments and develop better diagnostic tools for metabolic diseases. Furthermore, increasing amounts of multi-omics data are incorporated into GEMs to better identify the underlying mechanisms, biomarkers and potential drug targets of metabolic diseases.

代谢组学将代谢组学与其他 omics 数据类型相结合,全面研究影响代谢的遗传和环境因素。这些多组学数据可被纳入基因组规模的代谢模型(GEMs)中,GEMs 是经过高度编辑的知识库,明确记录了基因、转录本、蛋白质和代谢物。通过纳入人类基因组中编码的酶和转运体催化的所有已知生化反应,GEMs 可以分析和预测复杂代谢网络的行为。从细胞和组织到微生物组和全身,GEMs 的规模和范围不断扩大,有助于设计有效的治疗方法和开发更好的代谢疾病诊断工具。此外,越来越多的多组学数据被纳入 GEM,以更好地确定代谢疾病的潜在机制、生物标志物和潜在药物靶点。
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引用次数: 0
Gene synthesis from a non-coding RNA 非编码 RNA 的基因合成
IF 39.1 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-18 DOI: 10.1038/s41576-024-00781-3
Linda Koch
A study in Science investigating bacterial defence mechanisms against phages reports a novel mode of gene regulation through reverse transcription of a non-coding RNA template, leading to the formation of a toxic repetitive gene.
科学》(Science)杂志上的一项研究调查了细菌对噬菌体的防御机制,报告了一种新的基因调控模式,即通过反转录非编码 RNA 模板,形成有毒的重复基因。
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引用次数: 0
Tumbling bacteria and non-genetic individuality 翻滚细菌和非遗传个体性
IF 39.1 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-18 DOI: 10.1038/s41576-024-00779-x
Alejo E. Rodriguez-Fraticelli
In this Journal Club, Alejo Rodriguez-Fratelli discusses a paper by Spudich and Koshland Jr that characterized non-genetic cell individuality in bacteria, a concept with emerging relevance to cancer progression.
在本期 "期刊俱乐部 "中,Alejo Rodriguez-Fratelli 讨论了 Spudich 和 Koshland Jr 发表的一篇论文,该论文描述了细菌中非遗传细胞个体性的特征,这一概念与癌症进展密切相关。
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引用次数: 0
Identifying off-target effects of genome editing with Tracking-seq 利用跟踪-测序技术识别基因组编辑的脱靶效应
IF 39.1 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-17 DOI: 10.1038/s41576-024-00775-1
Ming Zhu
In this Tools of the Trade article, Ming Zhu describes Tracking-seq, a versatile method for detecting off-target effects of genome-editing tools across a range of experimental conditions.
在这篇 "贸易工具 "文章中,Ming Zhu 介绍了 Tracking-seq,这是一种在各种实验条件下检测基因组编辑工具脱靶效应的多功能方法。
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引用次数: 0
Reshaping Waddington’s developmental landscape 重塑瓦丁顿的发展格局
IF 39.1 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-17 DOI: 10.1038/s41576-024-00777-z
Yimiao Qu, Kyle M. Loh
Yimiao Qu and Kyle Loh discuss a 2004 paper by Xie et al., who demonstrated that B cells can be reprogrammed into macrophages through the enforced expression of a single transcription factor, providing insights into cellular plasticity and lineage conversion.
Yimiao Qu 和 Kyle Loh 讨论了 Xie 等人 2004 年发表的一篇论文,他们证明了 B 细胞可以通过强制表达单一转录因子重编程为巨噬细胞,为细胞的可塑性和品系转换提供了深入的见解。
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引用次数: 0
Why geneticists should care about male infertility 遗传学家为何要关注男性不育问题
IF 39.1 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-16 DOI: 10.1038/s41576-024-00773-3
Joris A. Veltman, Frank Tüttelmann
The widespread use of medically assisted reproduction fosters the false impression that the underlying causes of male infertility are not important to know. However, to improve men’s reproductive and long-term health, as well as the health of their offspring, large-scale genetic studies are essential. Thus, reproductive genomics should be implemented in diagnostics as soon as possible. In this Comment, Veltman and Tüttelmann call on geneticists to further study male infertility and help to develop diagnostic strategies using state-of-the-art genomic approaches.
医学辅助生殖的广泛使用助长了一种错误印象,即男性不育的根本原因并不重要。然而,为了改善男性的生殖健康和长期健康,以及他们后代的健康,大规模的基因研究是必不可少的。因此,生殖基因组学应尽快应用于诊断中。在这篇评论中,Veltman 和 Tüttelmann 呼吁遗传学家进一步研究男性不育症,并利用最先进的基因组学方法帮助制定诊断策略。
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引用次数: 0
Progress in toxicogenomics to protect human health 毒物基因组学在保护人类健康方面的进展
IF 42.7 1区 生物学 Q1 GENETICS & HEREDITY Pub Date : 2024-09-02 DOI: 10.1038/s41576-024-00767-1
Matthew J. Meier, Joshua Harrill, Kamin Johnson, Russell S. Thomas, Weida Tong, Julia E. Rager, Carole L. Yauk

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose–response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

毒物基因组学测量分子特征,如转录本、蛋白质、代谢物和表观基因组修饰,以了解和预测环境和药物暴露的毒理效应。由于基因表达谱分析技术的创新,转录组学已成为当代毒理学研究中不可或缺的工具,可提供大规模的机理和定量信息。通过使用转录组生物标志物、网络推断分析、模式匹配方法和人工智能,这些数据可用于预测毒理学危害。此外,新兴的方法,如高通量剂量-反应模型,可以利用毒物基因组数据保护人类健康,即使不能预测具体的危害。最后,单细胞转录组学和多组学提供了对毒理学机制的详细了解。在此,我们回顾了毒物基因组学自诞生以来在将转录组学应用于毒理学测试方面所取得的进展,并重点介绍了正在改变风险评估的进展。
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引用次数: 0
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