转录组
生物
计算生物学
基因表达谱
细胞
DNA微阵列
单细胞分析
基因
基因表达
遗传学
作者
Alexander Rosenberg,Charles M. Roco,Richard A. Muscat,Anna Kuchina,Paul Sample,Zizhen Yao,Lucas T. Graybuck,David J. Peeler,Sumit Mukherjee,Wei Chen,Suzie H. Pun,Drew L. Sellers,Bosiljka Tasic,Georg Seelig
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:2018-03-15
卷期号:360 (6385): 176-182
被引量:1142
标识
DOI:10.1126/science.aam8999
摘要
Identifying single-cell types in the mouse brain The recent development of single-cell genomic techniques allows us to profile gene expression at the single-cell level easily, although many of these methods have limited throughput. Rosenberg et al. describe a strategy called split-pool ligation-based transcriptome sequencing, or SPLiT-seq, which uses combinatorial barcoding to profile single-cell transcriptomes without requiring the physical isolation of each cell. The authors used their method to profile >100,000 single-cell transcriptomes from mouse brains and spinal cords at 2 and 11 days after birth. Comparisons with in situ hybridization data on RNA expression from Allen Institute atlases linked these transcriptomes with spatial mapping, from which developmental lineages could be identified. Science , this issue p. 176
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