Pub Date : 2024-09-16DOI: 10.1038/s41588-024-01902-8
Isabel Guerreiro, Franka J. Rang, Yumiko K. Kawamura, Carla Kroon-Veenboer, Jeroen Korving, Femke C. Groenveld, Ramada E. van Beek, Silke J. A. Lochs, Ellen Boele, Antoine H. M. F. Peters, Jop Kind
In mammals, early embryonic development exhibits highly unusual spatial positioning of genomic regions at the nuclear lamina, but the mechanisms underpinning this atypical genome organization remain elusive. Here, we generated single-cell profiles of lamina-associated domains (LADs) coupled with transcriptomics, which revealed a striking overlap between preimplantation-specific LAD dissociation and noncanonical broad domains of H3K27me3. Loss of H3K27me3 resulted in a restoration of canonical LAD profiles, suggesting an antagonistic relationship between lamina association and H3K27me3. Tethering of H3K27me3 to the nuclear periphery showed that the resultant relocalization is partially dependent on the underlying DNA sequence. Collectively, our results suggest that the atypical organization of LADs in early developmental stages is the result of a tug-of-war between intrinsic affinity for the nuclear lamina and H3K27me3, constrained by the available space at the nuclear periphery. This study provides detailed insight into the molecular mechanisms regulating nuclear organization during early mammalian development. Single-cell profiling of lamina-associated domains (LADs) during early mouse development reveals an overlap between preimplantation-specific LAD dissociation and noncanonical broad H3K27me3 domains. Loss of H3K27me3 restores canonical LAD profiles.
在哺乳动物中，早期胚胎发育表现出基因组区域在核薄层极不寻常的空间定位，但这种非典型基因组组织的基础机制仍然难以捉摸。在这里，我们结合转录组学生成了薄层相关结构域（LADs）的单细胞图谱，发现胚胎植入前特异性LAD解离与H3K27me3的非典型宽域之间存在惊人的重叠。缺失H3K27me3会导致典型LAD图谱的恢复，这表明薄片关联与H3K27me3之间存在拮抗关系。将 H3K27me3 拴系到核外围表明，由此产生的重新定位部分依赖于底层 DNA 序列。总之，我们的研究结果表明，LADs 在早期发育阶段的非典型组织是核薄层固有亲和力与 H3K27me3 之间角力的结果，受到核外围可用空间的限制。这项研究详细揭示了哺乳动物早期发育过程中调节核组织的分子机制。
{"title":"Antagonism between H3K27me3 and genome–lamina association drives atypical spatial genome organization in the totipotent embryo","authors":"Isabel Guerreiro, Franka J. Rang, Yumiko K. Kawamura, Carla Kroon-Veenboer, Jeroen Korving, Femke C. Groenveld, Ramada E. van Beek, Silke J. A. Lochs, Ellen Boele, Antoine H. M. F. Peters, Jop Kind","doi":"10.1038/s41588-024-01902-8","DOIUrl":"10.1038/s41588-024-01902-8","url":null,"abstract":"In mammals, early embryonic development exhibits highly unusual spatial positioning of genomic regions at the nuclear lamina, but the mechanisms underpinning this atypical genome organization remain elusive. Here, we generated single-cell profiles of lamina-associated domains (LADs) coupled with transcriptomics, which revealed a striking overlap between preimplantation-specific LAD dissociation and noncanonical broad domains of H3K27me3. Loss of H3K27me3 resulted in a restoration of canonical LAD profiles, suggesting an antagonistic relationship between lamina association and H3K27me3. Tethering of H3K27me3 to the nuclear periphery showed that the resultant relocalization is partially dependent on the underlying DNA sequence. Collectively, our results suggest that the atypical organization of LADs in early developmental stages is the result of a tug-of-war between intrinsic affinity for the nuclear lamina and H3K27me3, constrained by the available space at the nuclear periphery. This study provides detailed insight into the molecular mechanisms regulating nuclear organization during early mammalian development. Single-cell profiling of lamina-associated domains (LADs) during early mouse development reveals an overlap between preimplantation-specific LAD dissociation and noncanonical broad H3K27me3 domains. Loss of H3K27me3 restores canonical LAD profiles.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":null,"pages":null},"PeriodicalIF":31.7,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01902-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142234446","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}
Pub Date : 2024-09-12DOI: 10.1038/s41588-024-01907-3
Yoav Voichek, Gabriela Hristova, Almudena Mollá-Morales, Detlef Weigel, Magnus Nordborg
Much of what we know about eukaryotic transcription stems from animals and yeast; however, plants evolved separately for over a billion years, leaving ample time for divergence in transcriptional regulation. Here we set out to elucidate fundamental properties of cis-regulatory sequences in plants. Using massively parallel reporter assays across four plant species, we demonstrate the central role of sequences downstream of the transcription start site (TSS) in transcriptional regulation. Unlike animal enhancers that are position independent, plant regulatory elements depend on their position, as altering their location relative to the TSS significantly affects transcription. We highlight the importance of the region downstream of the TSS in regulating transcription by identifying a DNA motif that is conserved across vascular plants and is sufficient to enhance gene expression in a dose-dependent manner. The identification of a large number of position-dependent enhancers points to fundamental differences in gene regulation between plants and animals. Massively parallel reporter assays in four plant species show that transcriptional regulatory elements are position dependent with enrichment downstream of the transcription start site, particularly GATC motifs with strong effects in vascular plants.
我们对真核生物转录的了解大多源自动物和酵母；然而，植物单独进化了十多亿年，这为转录调控的分化留下了充足的时间。在这里，我们着手阐明植物顺式调控序列的基本特性。通过对四种植物进行大规模并行报告分析，我们证明了转录起始位点（TSS）下游序列在转录调控中的核心作用。与位置无关的动物增强子不同，植物调控元件取决于它们的位置，因为改变它们相对于 TSS 的位置会显著影响转录。我们通过鉴定一种在维管束植物中保守且足以以剂量依赖性方式增强基因表达的 DNA 基序，强调了 TSS 下游区域在转录调控中的重要性。大量位置依赖性增强子的鉴定指出了植物和动物基因调控的根本差异。
{"title":"Widespread position-dependent transcriptional regulatory sequences in plants","authors":"Yoav Voichek, Gabriela Hristova, Almudena Mollá-Morales, Detlef Weigel, Magnus Nordborg","doi":"10.1038/s41588-024-01907-3","DOIUrl":"10.1038/s41588-024-01907-3","url":null,"abstract":"Much of what we know about eukaryotic transcription stems from animals and yeast; however, plants evolved separately for over a billion years, leaving ample time for divergence in transcriptional regulation. Here we set out to elucidate fundamental properties of cis-regulatory sequences in plants. Using massively parallel reporter assays across four plant species, we demonstrate the central role of sequences downstream of the transcription start site (TSS) in transcriptional regulation. Unlike animal enhancers that are position independent, plant regulatory elements depend on their position, as altering their location relative to the TSS significantly affects transcription. We highlight the importance of the region downstream of the TSS in regulating transcription by identifying a DNA motif that is conserved across vascular plants and is sufficient to enhance gene expression in a dose-dependent manner. The identification of a large number of position-dependent enhancers points to fundamental differences in gene regulation between plants and animals. Massively parallel reporter assays in four plant species show that transcriptional regulatory elements are position dependent with enrichment downstream of the transcription start site, particularly GATC motifs with strong effects in vascular plants.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":null,"pages":null},"PeriodicalIF":31.7,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01907-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170997","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}
Pub Date : 2024-09-12DOI: 10.1038/s41588-024-01899-0
Joseph Usset, Axel Rosendahl Huber, Maria A. Andrianova, Eduard Batlle, Joan Carles, Edwin Cuppen, Elena Elez, Enriqueta Felip, Marina Gómez-Rey, Deborah Lo Giacco, Francisco Martinez-Jimenez, Eva Muñoz-Couselo, Lillian L. Siu, Josep Tabernero, Ana Vivancos, Ferran Muiños, Abel Gonzalez-Perez, Nuria Lopez-Bigas
Only a subset of patients treated with immune checkpoint inhibitors (CPIs) respond to the treatment, and distinguishing responders from non-responders is a major challenge. Many proposed biomarkers of CPI response and survival probably represent alternative measurements of the same aspects of the tumor, its microenvironment or the host. Thus, we currently ignore how many truly independent biomarkers there are. With an unbiased analysis of genomics, transcriptomics and clinical data of a cohort of patients with metastatic tumors (n = 479), we discovered five orthogonal latent factors: tumor mutation burden, T cell effective infiltration, transforming growth factor-beta activity in the microenvironment, prior treatment and tumor proliferative potential. Their association with CPI response and survival was observed across all tumor types and validated across six independent cohorts (n = 1,491). These five latent factors constitute a frame of reference to organize current and future knowledge on biomarkers of CPI response and survival. Analysis of human tumor datasets shows that all features that appear significantly associated with immunotherapy response and survival may be collapsed into five latent factors: tumor mutation burden, T cell effective infiltration, TGF-β activity in the microenvironment, prior treatment and tumor proliferative potential.
{"title":"Five latent factors underlie response to immunotherapy","authors":"Joseph Usset, Axel Rosendahl Huber, Maria A. Andrianova, Eduard Batlle, Joan Carles, Edwin Cuppen, Elena Elez, Enriqueta Felip, Marina Gómez-Rey, Deborah Lo Giacco, Francisco Martinez-Jimenez, Eva Muñoz-Couselo, Lillian L. Siu, Josep Tabernero, Ana Vivancos, Ferran Muiños, Abel Gonzalez-Perez, Nuria Lopez-Bigas","doi":"10.1038/s41588-024-01899-0","DOIUrl":"10.1038/s41588-024-01899-0","url":null,"abstract":"Only a subset of patients treated with immune checkpoint inhibitors (CPIs) respond to the treatment, and distinguishing responders from non-responders is a major challenge. Many proposed biomarkers of CPI response and survival probably represent alternative measurements of the same aspects of the tumor, its microenvironment or the host. Thus, we currently ignore how many truly independent biomarkers there are. With an unbiased analysis of genomics, transcriptomics and clinical data of a cohort of patients with metastatic tumors (n = 479), we discovered five orthogonal latent factors: tumor mutation burden, T cell effective infiltration, transforming growth factor-beta activity in the microenvironment, prior treatment and tumor proliferative potential. Their association with CPI response and survival was observed across all tumor types and validated across six independent cohorts (n = 1,491). These five latent factors constitute a frame of reference to organize current and future knowledge on biomarkers of CPI response and survival. Analysis of human tumor datasets shows that all features that appear significantly associated with immunotherapy response and survival may be collapsed into five latent factors: tumor mutation burden, T cell effective infiltration, TGF-β activity in the microenvironment, prior treatment and tumor proliferative potential.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":null,"pages":null},"PeriodicalIF":31.7,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01899-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170845","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}
Pub Date : 2024-09-11DOI: 10.1038/s41588-024-01898-1
Manik Garg, Marcin Karpinski, Dorota Matelska, Lawrence Middleton, Oliver S. Burren, Fengyuan Hu, Eleanor Wheeler, Katherine R. Smith, Margarete A. Fabre, Jonathan Mitchell, Amanda O’Neill, Euan A. Ashley, Andrew R. Harper, Quanli Wang, Ryan S. Dhindsa, Slavé Petrovski, Dimitrios Vitsios
The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank’s longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10−8) gene–disease relationships alongside 182 gene–disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene–disease prioritization. All extracted gene–disease associations and incident disease predictive biomarkers are publicly available ( http://milton.public.cgr.astrazeneca.com ). MILTON uses phenotype information in the UK Biobank to identify clinical biomarkers and other quantitative traits that characterize diseases. It then constructs augmented cohorts by predicting undiagnosed individuals, improving power to discover gene–disease relationships.
{"title":"Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank","authors":"Manik Garg, Marcin Karpinski, Dorota Matelska, Lawrence Middleton, Oliver S. Burren, Fengyuan Hu, Eleanor Wheeler, Katherine R. Smith, Margarete A. Fabre, Jonathan Mitchell, Amanda O’Neill, Euan A. Ashley, Andrew R. Harper, Quanli Wang, Ryan S. Dhindsa, Slavé Petrovski, Dimitrios Vitsios","doi":"10.1038/s41588-024-01898-1","DOIUrl":"10.1038/s41588-024-01898-1","url":null,"abstract":"The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank’s longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10−8) gene–disease relationships alongside 182 gene–disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene–disease prioritization. All extracted gene–disease associations and incident disease predictive biomarkers are publicly available ( http://milton.public.cgr.astrazeneca.com ). MILTON uses phenotype information in the UK Biobank to identify clinical biomarkers and other quantitative traits that characterize diseases. It then constructs augmented cohorts by predicting undiagnosed individuals, improving power to discover gene–disease relationships.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":null,"pages":null},"PeriodicalIF":31.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01898-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142166305","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}
X chromosome inactivation triggers a dramatic reprogramming of transcription and chromosome architecture. However, how the chromatin organization of inactive X chromosome is established de novo in vivo remains elusive. Here, we identified an Xist-separated megadomain structure (X-megadomains) on the inactive X chromosome in mouse extraembryonic lineages and extraembryonic endoderm (XEN) cell lines, and transiently in the embryonic lineages, before Dxz4-delineated megadomain formation at later stages in a strain-specific manner. X-megadomain boundary coincides with strong enhancer activities and cohesin binding in an Xist regulatory region required for proper Xist activation in early embryos. Xist regulatory region disruption or cohesin degradation impaired X-megadomains in extraembryonic endoderm cells and caused ectopic activation of regulatory elements and genes near Xist, indicating that cohesin loading at regulatory elements promotes X-megadomains and confines local gene activities. These data reveal stepwise X chromosome folding and transcriptional regulation to achieve both essential gene activation and global silencing during the early stages of X chromosome inactivation. Hi-C analysis identifies Xist-separated megadomains (X-megadomains) on the inactive X chromosome in mouse early embryos. Cohesin loading at Xist regulatory elements promotes X-megadomain formation and restricts nearby gene activity.
X 染色体失活会引发转录和染色体结构的急剧重塑。然而，非活性 X 染色体的染色质组织是如何在体内从头建立起来的，仍然是一个未知数。在这里，我们在小鼠胚外系和胚外内胚层（XEN）细胞系中鉴定出了非活性 X 染色体上的 Xist 分离巨域结构（X-megadomains），并在胚胎系中鉴定出了瞬时结构，然后在后期以株系特异性的方式鉴定出了 Dxz4 划线的巨域形成。X-巨域边界与早期胚胎中适当激活 Xist 所需的 Xist 调节区中的强增强子活动和粘合素结合相吻合。Xist调控区的破坏或内聚素降解损害了胚外内胚层细胞中的X-megadomains，并导致调控元件和Xist附近基因的异位激活，这表明内聚素在调控元件上的负载促进了X-megadomains并限制了局部基因的活动。这些数据揭示了在X染色体失活的早期阶段，X染色体逐步折叠和转录调控实现了重要基因激活和全局沉默。
{"title":"Stepwise de novo establishment of inactive X chromosome architecture in early development","authors":"Zhenhai Du, Liangjun Hu, Zhuoning Zou, Meishuo Liu, Zihan Li, Xukun Lu, Clair Harris, Yunlong Xiang, Fengling Chen, Guang Yu, Kai Xu, Feng Kong, Qianhua Xu, Bo Huang, Ling Liu, Qiang Fan, Haifeng Wang, Sundeep Kalantry, Wei Xie","doi":"10.1038/s41588-024-01897-2","DOIUrl":"10.1038/s41588-024-01897-2","url":null,"abstract":"X chromosome inactivation triggers a dramatic reprogramming of transcription and chromosome architecture. However, how the chromatin organization of inactive X chromosome is established de novo in vivo remains elusive. Here, we identified an Xist-separated megadomain structure (X-megadomains) on the inactive X chromosome in mouse extraembryonic lineages and extraembryonic endoderm (XEN) cell lines, and transiently in the embryonic lineages, before Dxz4-delineated megadomain formation at later stages in a strain-specific manner. X-megadomain boundary coincides with strong enhancer activities and cohesin binding in an Xist regulatory region required for proper Xist activation in early embryos. Xist regulatory region disruption or cohesin degradation impaired X-megadomains in extraembryonic endoderm cells and caused ectopic activation of regulatory elements and genes near Xist, indicating that cohesin loading at regulatory elements promotes X-megadomains and confines local gene activities. These data reveal stepwise X chromosome folding and transcriptional regulation to achieve both essential gene activation and global silencing during the early stages of X chromosome inactivation. Hi-C analysis identifies Xist-separated megadomains (X-megadomains) on the inactive X chromosome in mouse early embryos. Cohesin loading at Xist regulatory elements promotes X-megadomain formation and restricts nearby gene activity.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":null,"pages":null},"PeriodicalIF":31.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-10DOI: 10.1038/s41588-024-01906-4
Junjie Zhu, Kun Pang, Beiyu Hu, Ruiqiao He, Ning Wang, Zewen Jiang, Peifeng Ji, Fangqing Zhao
Spatial transcriptomic techniques offer unprecedented insights into the molecular organization of complex tissues. However, integrating cost-effectiveness, high throughput, a wide field of view and compatibility with three-dimensional (3D) volumes has been challenging. Here we introduce microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq), a new method that combines carbodiimide chemistry, spatial combinatorial indexing and innovative microfluidics design. This technique allows sensitive and reproducible profiling of diverse tissue types, achieving an eightfold increase in throughput, minimal cost and reduced batch effects. MAGIC-seq breaks conventional microfluidics limits by enhancing barcoding efficiency and enables analysis of whole postnatal mouse sections, providing comprehensive cellular structure elucidation at near single-cell resolution, uncovering transcriptional variations and dynamic trajectories of mouse organogenesis. Our 3D transcriptomic atlas of the developing mouse brain, consisting of 93 sections, reveals the molecular and cellular landscape, serving as a valuable resource for neuroscience and developmental biology. Overall, MAGIC-seq is a high-throughput, cost-effective, large field of view and versatile method for spatial transcriptomic studies. Microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq) is a spatial transcriptomics method combining multiple-grid microfluidic design and prefabricated DNA arrays for increased throughput and reduced cost, with applications for large fields of view and 3D spatial mapping.
{"title":"Custom microfluidic chip design enables cost-effective three-dimensional spatiotemporal transcriptomics with a wide field of view","authors":"Junjie Zhu, Kun Pang, Beiyu Hu, Ruiqiao He, Ning Wang, Zewen Jiang, Peifeng Ji, Fangqing Zhao","doi":"10.1038/s41588-024-01906-4","DOIUrl":"10.1038/s41588-024-01906-4","url":null,"abstract":"Spatial transcriptomic techniques offer unprecedented insights into the molecular organization of complex tissues. However, integrating cost-effectiveness, high throughput, a wide field of view and compatibility with three-dimensional (3D) volumes has been challenging. Here we introduce microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq), a new method that combines carbodiimide chemistry, spatial combinatorial indexing and innovative microfluidics design. This technique allows sensitive and reproducible profiling of diverse tissue types, achieving an eightfold increase in throughput, minimal cost and reduced batch effects. MAGIC-seq breaks conventional microfluidics limits by enhancing barcoding efficiency and enables analysis of whole postnatal mouse sections, providing comprehensive cellular structure elucidation at near single-cell resolution, uncovering transcriptional variations and dynamic trajectories of mouse organogenesis. Our 3D transcriptomic atlas of the developing mouse brain, consisting of 93 sections, reveals the molecular and cellular landscape, serving as a valuable resource for neuroscience and developmental biology. Overall, MAGIC-seq is a high-throughput, cost-effective, large field of view and versatile method for spatial transcriptomic studies. Microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq) is a spatial transcriptomics method combining multiple-grid microfluidic design and prefabricated DNA arrays for increased throughput and reduced cost, with applications for large fields of view and 3D spatial mapping.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":null,"pages":null},"PeriodicalIF":31.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01906-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160458","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}
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