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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
TSR1ENSG000001677210.00990530639361717
GABPB2ENSG000001434580.009909309260328
ZNF320ENSG000001829860.00991177251182177
CDT1ENSG000001675130.00991833907033997
FZD7ENSG000001557600.00991833907033997
POLR2AENSG000001812220.00992385848212512
ZNF251ENSG000001981690.00994273309041656
BCKDHAENSG000002480980.00994513733870111
CTDSPL2ENSG000001377700.00994825061902732
LYPLA2ENSG000000110090.00995011528824581
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