Efficient method for the differentiation of human pluripotent stem cells (hPSCs) into functional brain microvascular endothelial (BME)-like cells
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ABSTRACT:
PROVIDER: PRJNA624900 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11539339_1.fastq.gz | Fastqsanger.gz | |||
| SRR11539339_2.fastq.gz | Fastqsanger.gz | |||
| SRR11539340_1.fastq.gz | Fastqsanger.gz | |||
| SRR11539340_2.fastq.gz | Fastqsanger.gz | |||
| SRR11539341_1.fastq.gz | Fastqsanger.gz |
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Project description:We developed an efficient method for the differentiation of human pluripotent stem cells (hPSCs) into functional brain microvascular endothelial (BME)-like cells. Here, we compared the whole-gene expression pattern of BME-like cells differentiated from hPSCs with primary BMECs (pBMECs). Comparison of expressed genes in the purified BME-like cells and pBMECs indicated a high degree of similarity. Furthermore, brain ECs related gene, including BBB membrane specific proteins, transporters, and channels, showed similar levels between BME-like cells and pBMECs. This study reveals that hPSC-derived BME-like cells have similar character with pBMECs.
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Project description:Next-generation sequencing (NGS) has significantly facilitated the analysis of the gene profile and elucidated the molecular mechanisms important for specific cell lineage differentiated from human pluripotent stem cells (hPSCs). Here we report the application of RNA-sequencing technology for transcriptome profile of primary human brain microvascular endothelial cells (BMECs) and hPSC-derived BMECs, and comparison of transcriptomes among cells, including hPSCs, mesodermal progenitors, ectodermal progenitors, endodermal progenitors, hBMECs and hPSC-derived BMECs from hPSCs. Four different BMEC samples differentiated from hPSCs by two different methods and hBMECs were performed in IIIumina HiSeq2500. The resulting sequence reads (about 20 million reads per sample) were mapped to human genome (hg19) using HISAT, and the RefSeq transcript levels (FPKMs) were quantified using the python script rpkmforgenes.py. We next analyzed the expression of a subset of genes that regulate key BBB attributes, including tight junctions and molecular transporters. The gene set comprises 20 tight junction-related genes and an unbiased list of all 25 CLDN genes, all 407 solute carrier (SLC) transporters, and all 53 ATP-binding cassette (ABC) transporters regardless of prior knowledge of BBB association. Primary human BMECs expressed 234 of these genes. BMECs differentiated from hPSCs via the defined method expressed many of these same genes (206 of 234 (88%)) as did BMECs differentiated via the UM method (208 of 234 (89%), indicating a close similarity between hPSC-derived BMECs and primary human BMECs with respect to transcripts having likely relevance to BBB function. RNA sequencing was used to compare global gene expression profiles in the hPSC-derived BMECs with BMECs generated from our previously reported co-differentiation system and primary human BMECs. As expected, hPSC-derived BMECs from three independent differentiations clustered closely and were similar to those generated from the undefined UM platform. Moreover, the hPSC-derived BMECs clustered with primary human BMECs and were distinct from undifferentiated hPSCs and hPSC-derived ectoderm, endoderm and mesodermThis study provides detailed transcriptome comparison between hBMECs and hPSC-derived BMECs and unveils important genes related BMEC phenotypes.
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