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Promoting reproducibility with Code Ocean. 使用代码海洋提高可再现性。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-19 DOI: 10.1186/s13059-021-02299-x
Barbara Cheifet
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引用次数: 8
iMAP: integration of multiple single-cell datasets by adversarial paired transfer networks. iMAP:通过对抗性配对转移网络整合多个单细胞数据集。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-18 DOI: 10.1186/s13059-021-02280-8
Dongfang Wang, Siyu Hou, Lei Zhang, Xiliang Wang, Baolin Liu, Zemin Zhang

The integration of single-cell RNA-sequencing datasets from multiple sources is critical for deciphering cell-to-cell heterogeneities and interactions in complex biological systems. We present a novel unsupervised batch effect removal framework, called iMAP, based on both deep autoencoders and generative adversarial networks. Compared with current methods, iMAP shows superior, robust, and scalable performance in terms of both reliably detecting the batch-specific cells and effectively mixing distributions of the batch-shared cell types. Applying iMAP to tumor microenvironment datasets from two platforms, Smart-seq2 and 10x Genomics, we find that iMAP can leverage the powers of both platforms to discover novel cell-cell interactions.

整合来自多个来源的单细胞 RNA 序列数据集对于破译复杂生物系统中细胞间的异质性和相互作用至关重要。我们基于深度自动编码器和生成式对抗网络,提出了一种新颖的无监督批量效应去除框架,称为 iMAP。与目前的方法相比,iMAP 在可靠地检测批特异性细胞和有效地混合批共享细胞类型的分布方面都表现出卓越、稳健和可扩展的性能。将 iMAP 应用于来自 Smart-seq2 和 10x Genomics 这两个平台的肿瘤微环境数据集,我们发现 iMAP 可以利用这两个平台的优势发现新的细胞-细胞相互作用。
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引用次数: 0
LINE retrotransposons characterize mammalian tissue-specific and evolutionarily dynamic regulatory regions. LINE 反转座子是哺乳动物组织特异性和进化动态调控区域的特征。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-18 DOI: 10.1186/s13059-021-02260-y
Maša Roller, Ericca Stamper, Diego Villar, Osagie Izuogu, Fergal Martin, Aisling M Redmond, Raghavendra Ramachanderan, Louise Harewood, Duncan T Odom, Paul Flicek

Background: To investigate the mechanisms driving regulatory evolution across tissues, we experimentally mapped promoters, enhancers, and gene expression in the liver, brain, muscle, and testis from ten diverse mammals.

Results: The regulatory landscape around genes included both tissue-shared and tissue-specific regulatory regions, where tissue-specific promoters and enhancers evolved most rapidly. Genomic regions switching between promoters and enhancers were more common across species, and less common across tissues within a single species. Long Interspersed Nuclear Elements (LINEs) played recurrent evolutionary roles: LINE L1s were associated with tissue-specific regulatory regions, whereas more ancient LINE L2s were associated with tissue-shared regulatory regions and with those switching between promoter and enhancer signatures across species.

Conclusions: Our analyses of the tissue-specificity and evolutionary stability among promoters and enhancers reveal how specific LINE families have helped shape the dynamic mammalian regulome.

背景:为了研究跨组织调控进化的驱动机制,我们通过实验绘制了十种不同哺乳动物肝脏、大脑、肌肉和睾丸中的启动子、增强子和基因表达图谱:基因周围的调控格局包括组织共享调控区和组织特异性调控区,其中组织特异性启动子和增强子的进化最为迅速。在启动子和增强子之间切换的基因组区域在不同物种之间更为常见,而在同一物种的不同组织之间则不太常见。长互套核元素(LINEs)在进化过程中反复发挥作用:LINE L1与组织特异性调控区相关,而更古老的LINE L2则与组织共享调控区以及在启动子和增强子之间跨物种切换的调控区相关:我们对启动子和增强子的组织特异性和进化稳定性的分析揭示了特定的LINE家族是如何帮助形成动态的哺乳动物调控组的。
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引用次数: 0
Author Correction: Assembly of hundreds of novel bacterial genomes from the chicken caecum. 作者更正:来自鸡盲肠的数百种新型细菌基因组的组装。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-12 DOI: 10.1186/s13059-021-02284-4
Laura Glendinning, Robert D Stewart, Mark J Pallen, Kellie A Watson, Mick Watson
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引用次数: 4
The data-hypothesis relationship. 数据-假设关系。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-10 DOI: 10.1186/s13059-021-02276-4
Teppo Felin, Jan Koenderink, Joachim I Krueger, Denis Noble, George F R Ellis
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引用次数: 10
Data bias. 数据偏差。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-10 DOI: 10.1186/s13059-021-02278-2
Teppo Felin, Jan Koenderink, Joachim I Krueger, Denis Noble, George F R Ellis
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引用次数: 7
3 '-5 ' crosstalk contributes to transcriptional bursting. 3 '-5 '串扰有助于转录突变。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-04 DOI: 10.1186/s13059-020-02227-5
Massimo Cavallaro, Mark D Walsh, Matt Jones, James Teahan, Simone Tiberi, Bärbel Finkenstädt, Daniel Hebenstreit

Background: Transcription in mammalian cells is a complex stochastic process involving shuttling of polymerase between genes and phase-separated liquid condensates. It occurs in bursts, which results in vastly different numbers of an mRNA species in isogenic cell populations. Several factors contributing to transcriptional bursting have been identified, usually classified as intrinsic, in other words local to single genes, or extrinsic, relating to the macroscopic state of the cell. However, some possible contributors have not been explored yet. Here, we focus on processes at the 3 ' and 5 ' ends of a gene that enable reinitiation of transcription upon termination.

Results: Using Bayesian methodology, we measure the transcriptional bursting in inducible transgenes, showing that perturbation of polymerase shuttling typically reduces burst size, increases burst frequency, and thus limits transcriptional noise. Analysis based on paired-end tag sequencing (PolII ChIA-PET) suggests that this effect is genome wide. The observed noise patterns are also reproduced by a generative model that captures major characteristics of the polymerase flux between the ends of a gene and a phase-separated compartment.

Conclusions: Interactions between the 3 ' and 5 ' ends of a gene, which facilitate polymerase recycling, are major contributors to transcriptional noise.

背景:哺乳动物细胞中的转录是一个复杂的随机过程,涉及聚合酶在基因和相分离的液体凝结物之间的穿梭。转录以突变的形式发生,这导致同源细胞群中的 mRNA 种类数量大相径庭。导致转录猝灭的几个因素已经确定,通常分为内在因素(换句话说,单个基因的局部因素)和外在因素(与细胞的宏观状态有关)。然而,一些可能的促成因素尚未得到探讨。在此,我们重点研究了基因3'端和5'端使转录终止后重新启动的过程:结果:我们使用贝叶斯方法测量了可诱导转基因的转录猝灭,结果表明干扰聚合酶穿梭通常会减少猝灭大小,增加猝灭频率,从而限制转录噪音。基于成对末端标签测序(PolII ChIA-PET)的分析表明,这种效应是全基因组的。一个生成模型也再现了观察到的噪音模式,该模型捕捉到了基因末端与相分离区室之间聚合酶通量的主要特征:结论:基因3'端和5'端之间的相互作用促进了聚合酶的循环,是转录噪音的主要成因。
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引用次数: 0
GeneWalk identifies relevant gene functions for a biological context using network representation learning. GeneWalk 利用网络表征学习技术识别生物背景下的相关基因功能。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-02-02 DOI: 10.1186/s13059-021-02264-8
Robert Ietswaart, Benjamin M Gyori, John A Bachman, Peter K Sorger, L Stirling Churchman

A bottleneck in high-throughput functional genomics experiments is identifying the most important genes and their relevant functions from a list of gene hits. Gene Ontology (GO) enrichment methods provide insight at the gene set level. Here, we introduce GeneWalk ( github.com/churchmanlab/genewalk ) that identifies individual genes and their relevant functions critical for the experimental setting under examination. After the automatic assembly of an experiment-specific gene regulatory network, GeneWalk uses representation learning to quantify the similarity between vector representations of each gene and its GO annotations, yielding annotation significance scores that reflect the experimental context. By performing gene- and condition-specific functional analysis, GeneWalk converts a list of genes into data-driven hypotheses.

高通量功能基因组学实验的一个瓶颈是从基因命中列表中识别出最重要的基因及其相关功能。基因本体(GO)富集方法提供了基因组水平的洞察力。在这里,我们介绍 GeneWalk(github.com/churchmanlab/genewalk),它能识别对实验环境至关重要的单个基因及其相关功能。在自动组装特定于实验的基因调控网络之后,GeneWalk 利用表征学习量化每个基因的向量表征与其 GO 注释之间的相似性,从而得出反映实验背景的注释意义分数。通过进行特定基因和条件的功能分析,GeneWalk将基因列表转化为数据驱动的假设。
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引用次数: 0
A comprehensive enhancer screen identifies TRAM2 as a key and novel mediator of YAP oncogenesis. 一项全面的增强子筛选确定了TRAM2是YAP肿瘤发生的关键和新的介质。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-01-29 DOI: 10.1186/s13059-021-02272-8
Li Li, Alejandro P Ugalde, Colinda L G J Scheele, Sebastian M Dieter, Remco Nagel, Jin Ma, Abhijeet Pataskar, Gozde Korkmaz, Ran Elkon, Miao-Ping Chien, Li You, Pin-Rui Su, Onno B Bleijerveld, Maarten Altelaar, Lyubomir Momchev, Zohar Manber, Ruiqi Han, Pieter C van Breugel, Rui Lopes, Peter Ten Dijke, Jacco van Rheenen, Reuven Agami

Background: Frequent activation of the co-transcriptional factor YAP is observed in a large number of solid tumors. Activated YAP associates with enhancer loci via TEAD4-DNA-binding protein and stimulates cancer aggressiveness. Although thousands of YAP/TEAD4 binding-sites are annotated, their functional importance is unknown. Here, we aim at further identification of enhancer elements that are required for YAP functions.

Results: We first apply genome-wide ChIP profiling of YAP to systematically identify enhancers that are bound by YAP/TEAD4. Next, we implement a genetic approach to uncover functions of YAP/TEAD4-associated enhancers, demonstrate its robustness, and use it to reveal a network of enhancers required for YAP-mediated proliferation. We focus on EnhancerTRAM2, as its target gene TRAM2 shows the strongest expression-correlation with YAP activity in nearly all tumor types. Interestingly, TRAM2 phenocopies the YAP-induced cell proliferation, migration, and invasion phenotypes and correlates with poor patient survival. Mechanistically, we identify FSTL-1 as a major direct client of TRAM2 that is involved in these phenotypes. Thus, TRAM2 is a key novel mediator of YAP-induced oncogenic proliferation and cellular invasiveness.

Conclusions: YAP is a transcription co-factor that binds to thousands of enhancer loci and stimulates tumor aggressiveness. Using unbiased functional approaches, we dissect YAP enhancer network and characterize TRAM2 as a novel mediator of cellular proliferation, migration, and invasion. Our findings elucidate how YAP induces cancer aggressiveness and may assist diagnosis of cancer metastasis.

背景:在大量实体肿瘤中观察到频繁激活的共转录因子YAP。激活的YAP通过tead4 - dna结合蛋白与增强子位点结合,刺激肿瘤侵袭性。虽然数以千计的YAP/TEAD4结合位点被标注,但它们的功能重要性尚不清楚。在这里,我们的目标是进一步确定YAP功能所需的增强元件。结果:我们首先应用YAP的全基因组ChIP分析来系统地识别与YAP/TEAD4结合的增强子。接下来,我们实施了一种遗传学方法来揭示YAP/ tead4相关增强子的功能,证明其稳健性,并使用它来揭示YAP介导的增殖所需的增强子网络。我们专注于EnhancerTRAM2,因为其靶基因TRAM2在几乎所有肿瘤类型中与YAP活性的表达相关性最强。有趣的是,TRAM2表型与yap诱导的细胞增殖、迁移和侵袭表型相关,并与较差的患者生存率相关。在机制上,我们确定FSTL-1是参与这些表型的TRAM2的主要直接客户。因此,TRAM2是yap诱导的癌性增殖和细胞侵袭的关键新介质。结论:YAP是一种结合数千个增强子位点并刺激肿瘤侵袭性的转录辅助因子。使用无偏倚的功能方法,我们剖析了YAP增强子网络,并将TRAM2描述为细胞增殖、迁移和侵袭的新介质。我们的研究结果阐明了YAP如何诱导癌症侵袭性,并可能有助于癌症转移的诊断。
{"title":"A comprehensive enhancer screen identifies TRAM2 as a key and novel mediator of YAP oncogenesis.","authors":"Li Li, Alejandro P Ugalde, Colinda L G J Scheele, Sebastian M Dieter, Remco Nagel, Jin Ma, Abhijeet Pataskar, Gozde Korkmaz, Ran Elkon, Miao-Ping Chien, Li You, Pin-Rui Su, Onno B Bleijerveld, Maarten Altelaar, Lyubomir Momchev, Zohar Manber, Ruiqi Han, Pieter C van Breugel, Rui Lopes, Peter Ten Dijke, Jacco van Rheenen, Reuven Agami","doi":"10.1186/s13059-021-02272-8","DOIUrl":"10.1186/s13059-021-02272-8","url":null,"abstract":"<p><strong>Background: </strong>Frequent activation of the co-transcriptional factor YAP is observed in a large number of solid tumors. Activated YAP associates with enhancer loci via TEAD4-DNA-binding protein and stimulates cancer aggressiveness. Although thousands of YAP/TEAD4 binding-sites are annotated, their functional importance is unknown. Here, we aim at further identification of enhancer elements that are required for YAP functions.</p><p><strong>Results: </strong>We first apply genome-wide ChIP profiling of YAP to systematically identify enhancers that are bound by YAP/TEAD4. Next, we implement a genetic approach to uncover functions of YAP/TEAD4-associated enhancers, demonstrate its robustness, and use it to reveal a network of enhancers required for YAP-mediated proliferation. We focus on Enhancer<sup>TRAM2</sup>, as its target gene TRAM2 shows the strongest expression-correlation with YAP activity in nearly all tumor types. Interestingly, TRAM2 phenocopies the YAP-induced cell proliferation, migration, and invasion phenotypes and correlates with poor patient survival. Mechanistically, we identify FSTL-1 as a major direct client of TRAM2 that is involved in these phenotypes. Thus, TRAM2 is a key novel mediator of YAP-induced oncogenic proliferation and cellular invasiveness.</p><p><strong>Conclusions: </strong>YAP is a transcription co-factor that binds to thousands of enhancer loci and stimulates tumor aggressiveness. Using unbiased functional approaches, we dissect YAP enhancer network and characterize TRAM2 as a novel mediator of cellular proliferation, migration, and invasion. Our findings elucidate how YAP induces cancer aggressiveness and may assist diagnosis of cancer metastasis.</p>","PeriodicalId":48922,"journal":{"name":"Genome Biology","volume":"22 1","pages":"54"},"PeriodicalIF":12.3,"publicationDate":"2021-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13059-021-02272-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25310983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Evolutionary conservation and divergence of the human brain transcriptome. 人脑转录组的进化保护和分化。
IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Pub Date : 2021-01-29 DOI: 10.1186/s13059-020-02257-z
William G Pembroke, Christopher L Hartl, Daniel H Geschwind

Background: Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological, and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human- or primate-specific and therefore which components can be faithfully recapitulated in mouse models.

Results: We compare conservation of co-expression in 116 independent data sets derived from human, mouse, and non-human primate representing more than 15,000 total samples. We observe greater changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Glia, notably microglia, astrocytes, and oligodendrocytes are the most divergent cell type, three times more on average than neurons. We show that cis-regulatory sequence divergence explains a significant fraction of co-expression divergence. Moreover, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We identify dozens of human neuropsychiatric and neurodegenerative disease risk genes, such as COMT, PSEN-1, LRRK2, SHANK3, and SNCA, with highly divergent co-expression between mouse and human and show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types.

Conclusions: We identify robust co-expression modules reflecting whole-brain and regional patterns of gene expression. Compared with those that represent basic metabolic processes, cell-type-specific modules, most prominently glial modules, are the most divergent between species. These data and analyses serve as a foundational resource to guide human disease modeling and its interpretation.

背景:小鼠模型允许直接询问遗传对分子、生理和行为脑表型的影响。然而,在多大程度上神经或精神特征可能是人类或灵长类动物特有的,因此哪些成分可以在小鼠模型中忠实地再现,这是未知的。结果:我们比较了来自人类、小鼠和非人类灵长类动物的116个独立数据集的共表达保守性,这些数据集代表了超过15,000个总样本。我们观察到人类谱系发生了比小鼠更大的变化,并且显著的区域差异突出表明大脑皮层是分化最大的区域。胶质细胞,尤其是小胶质细胞、星形胶质细胞和少突胶质细胞是分化程度最高的细胞类型,平均是神经元的三倍。我们发现顺式调控序列的差异解释了共表达差异的重要部分。此外,蛋白质编码序列约束与共表达保护相似,因此功能不耐受丧失的基因在神经元模块而不是胶质模块中富集。我们鉴定了数十种人类神经精神和神经退行性疾病风险基因,如COMT、PSEN-1、LRRK2、SHANK3和SNCA,它们在小鼠和人类之间具有高度不同的共表达,并表明3D人脑类器官概括了代表几种人类细胞类型的体内共表达模块。结论:我们确定了反映全脑和区域基因表达模式的鲁棒共表达模块。与那些代表基本代谢过程的模块相比,细胞类型特异性模块,最突出的是胶质模块,在物种之间的差异最大。这些数据和分析是指导人类疾病建模及其解释的基础资源。
{"title":"Evolutionary conservation and divergence of the human brain transcriptome.","authors":"William G Pembroke,&nbsp;Christopher L Hartl,&nbsp;Daniel H Geschwind","doi":"10.1186/s13059-020-02257-z","DOIUrl":"https://doi.org/10.1186/s13059-020-02257-z","url":null,"abstract":"<p><strong>Background: </strong>Mouse models have allowed for the direct interrogation of genetic effects on molecular, physiological, and behavioral brain phenotypes. However, it is unknown to what extent neurological or psychiatric traits may be human- or primate-specific and therefore which components can be faithfully recapitulated in mouse models.</p><p><strong>Results: </strong>We compare conservation of co-expression in 116 independent data sets derived from human, mouse, and non-human primate representing more than 15,000 total samples. We observe greater changes occurring on the human lineage than mouse, and substantial regional variation that highlights cerebral cortex as the most diverged region. Glia, notably microglia, astrocytes, and oligodendrocytes are the most divergent cell type, three times more on average than neurons. We show that cis-regulatory sequence divergence explains a significant fraction of co-expression divergence. Moreover, protein coding sequence constraint parallels co-expression conservation, such that genes with loss of function intolerance are enriched in neuronal, rather than glial modules. We identify dozens of human neuropsychiatric and neurodegenerative disease risk genes, such as COMT, PSEN-1, LRRK2, SHANK3, and SNCA, with highly divergent co-expression between mouse and human and show that 3D human brain organoids recapitulate in vivo co-expression modules representing several human cell types.</p><p><strong>Conclusions: </strong>We identify robust co-expression modules reflecting whole-brain and regional patterns of gene expression. Compared with those that represent basic metabolic processes, cell-type-specific modules, most prominently glial modules, are the most divergent between species. These data and analyses serve as a foundational resource to guide human disease modeling and its interpretation.</p>","PeriodicalId":48922,"journal":{"name":"Genome Biology","volume":"22 1","pages":"52"},"PeriodicalIF":12.3,"publicationDate":"2021-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13059-020-02257-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25311054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 26
期刊
Genome Biology
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