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Dataset View [GSE86982]

SeriesGSE86982
TitleREGION-SPECIFIC NEURAL STEM CELL LINEAGES REVEALED BY SINGLE-CELL RNA-SEQ FROM HUMAN EMBRYONIC STEM CELLS [Smart-seq]
Year2016
CountryUSA
ArticleNot set
PMIDNA
Bio ProjectBioProject: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA343288
SraSRA: https://www.ncbi.nlm.nih.gov/sra?term=SRP090061
Overall DesginThe transcriptomes of 1846 single cells were profiled by SmartSeq2 at different timepoints throughout a 54-day differentiation protocol that converted H1 human embryonic stem cells to a variety of brain cell types. Some cells were positively labeled by a expression of a barcoded viral transgene to help establish clonality (marked by an SK).
SummaryDuring development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development. During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development. During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development.
Experimental ProtocolTo generate single cell suspensions, hESC-derived cultures were dissociated from plates using Accutase (ThermoFisher) at 37°C. Light trituration using a P1000 pipette was done every 5 min until nearly all clumps had been dissociated (up to 1 h). Cell suspension was washed and filtered through a 40 μm cell strainer. Cells were washed in PBS with 1% FBS and stained with 0.5-1 μg/mL DAPI. Single-cell suspensions were loaded onto a FACSAria II SORP (Becton Dickinson) and sorted directly into PCR strip tubes or plates held in chilled aluminum blocks. Doublets and dead cells were excluded based on forward scatter, side scatter and DAPI fluorescence. Sorting was done using the 130 μm nozzle with the sort mode set to single cell. Accuracy of single-cell sorts was confirmed by sorting DAPI-stained fixed cells onto a dry well of a 96-well plate and analyzing by fluorescence microscopy.; SmartSeq2 protocol. After reverse transcription and template switching, we amplified cDNA with KAPA HotStart HIFI 2× ReadyMix (Kapa Biosystems) for 22 cycles for RNA from single primary cortical cells. We purified PCR products using Ampure XP beads (Beckman Coulter). We quantified cDNA using a High Sensitivity DNA Chip (Agilent) on a Bioanalyzer 2100 or with the Quant-iT PicoGreen dsDNA Assay Kit (Thermo Fisher) on an Enspire plate reader (PerkinElmer). We used 1 ng of cDNA to generate RNA-Seq libraries using the Nextera XT library prep system (Illumina). We carried out sequencing of human cortical cells the on Illumina HiSeq using 50 base paired-end reads
Data processingRead were aligned transcriptome by RSEM to RefSeq gene annotation (April 23, 2013), and unmapped reads were aligned to genome by Bowtie. The remaining reads were aligned to ERCC.; Genome_build: hg19; Supplementary_files_format_and_content: RSEM TPM gene expression matrix
PlatformGPL16791
Public OnPublic on Sep 30 2016

Cell Groups

Differential Expression Gene List

KEGG GO Others   

Gene SymbolEnsembl IDFDR
LOC4403000.00906582323006469
B3GNT6ENSG000001984880.00906987437125018
PPP1R2ENSG000001842030.00907480424142708
LOC344967ENSG000002057940.00908632993588889
STARD3NLENSG000000102700.00908632993588889
WDR19ENSG000001577960.00908632993588889
RPS10P70.00909457536416627
LOC4407040.00909723579478544
ZNF23ENSG000001673770.00909723579478544
ZNF524ENSG000001714430.00909723579478544
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