PT  - JOURNAL ARTICLE
AU  - Peng Hu
AU  - Emily Fabyanic
AU  - Zhaolan Zhou
AU  - Hao Wu
TI  - sNucDrop-Seq: Dissecting cell-type composition and neuronal activity state in mammalian brains by massively parallel single-nucleus RNA-Seq
AID  - 10.1101/154476
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 154476
4099  - http://biorxiv.org/content/early/2017/07/02/154476.short
4100  - http://biorxiv.org/content/early/2017/07/02/154476.full
AB  - Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues, such as adult mammalian brains, is challenging. Here, we integrate sucrose-gradient assisted nuclear purification with droplet microfluidics to develop a highly scalable single-nucleus RNA-Seq approach (sNucDrop-Seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼11,000 nuclei isolated from adult mouse cerebral cortex, we demonstrate that sNucDrop-Seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity, but also enables analysis of long non-coding RNAs and transient states such as neuronal activity-dependent transcription at single-cell resolution in vivo.