Exploring tissue architecture using spatial transcriptomics.
Exploring tissue architecture using spatial transcriptomics.
复制标题
利用空间转录组学探索组织结构。
DOI：
10.1038/s41586-021-03634-9
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发表时间：
2021-08
期刊：
影响因子：
64.8
通讯作者：
Yanai I
中科院分区：
文献类型：
--
作者：
Rao A;Barkley D;França GS;Yanai I
破译多细胞生物中基因活动协调复杂细胞排列的原理和机制对于生命科学研究具有深远的影响。下一代基于测序和基于成像的方法的最新技术进步已经确立了空间转录组学的潜力，可以系统地测量整个组织空间中所有或大多数基因的表达水平，并已被用来产生神经科学、发育、植物生物学和包括癌症在内的一系列疾病的生物学见解。与基因组测序和人口健康调查产生的数据集类似，该技术生成的大规模地图集有助于探索性数据分析以生成假设。在这里，我们回顾了空间转录组技术，并描述了可用于结果数据分析路径的操作清单。空间转录组学还可以用于使用比较时间点或条件（包括遗传或环境扰动）的实验设计进行假设检验。最后，空间转录组数据自然适合与其他数据模式集成，为洞察组织组织提供可扩展的框架。
Deciphering the principles and mechanisms by which gene activity orchestrates complex cellular arrangements in multicellular organisms has far-reaching implications for research in the life sciences. Recent technological advancements in next-generation sequencing-based and imaging-based approaches have established the potential of spatial transcriptomics to measure expression levels of all or most genes systematically throughout tissue space, and have been adopted to generate biological insight in neuroscience, development, plant biology, and a range of diseases including cancer. Similar to datasets made possible by genomic sequencing and population health surveys, the large-scale atlases generated by this technology lend themselves to exploratory data analysis for hypothesis generation. Here, we review spatial transcriptomic technologies and describe the repertoire of operations available for paths of analysis of the resulting data. Spatial transcriptomics can also be deployed for hypothesis testing using experimental designs comparing timepoints or conditions - including genetic or environmental perturbations. Finally, spatial transcriptomic data is naturally amenable to integration with other data modalities providing an expandable framework for insight into tissue organization.
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影响因子：
64.8
作者：
Boyd DF;Allen EK;Randolph AG;Guo XJ;Weng Y;Sanders CJ;Bajracharya R;Lee NK;Guy CS;Vogel P;Guan W;Li Y;Liu X;Novak T;Newhams MM;Fabrizio TP;Wohlgemuth N;Mourani PM;PALISI Pediatric Intensive Care Influenza (PICFLU) Investigators;Wight TN;Schultz-Cherry S;Cormier SA;Shaw-Saliba K;Pekosz A;Rothman RE;Chen KF;Yang Z;Webby RJ;Zhong N;Crawford JC;Thomas PG
通讯作者：
Thomas PG
影响因子：
46.9
作者：
Becht, Etienne;McInnes, Leland;Newell, Evan W.
通讯作者：
Newell, Evan W.
影响因子：
5.9
作者：
Andersson A;Bergenstråhle J;Asp M;Bergenstråhle L;Jurek A;Fernández Navarro J;Lundeberg J
通讯作者：
Lundeberg J
影响因子：
64.5
作者：
Asp, Michaela;Giacomello, Stefania;Lundeberg, Joakim
通讯作者：
Lundeberg, Joakim
影响因子：
48
作者：
Browaeys, Robin;Saelens, Wouter;Saeys, Yvan
通讯作者：
Saeys, Yvan