five

Transcriptome Profiling and Sequencing of differentiated Human Hematopoietic Stem cells Reveal Lineage Specific Expression and Alternative Splicing of Genes

收藏
NIAID Data Ecosystem2026-03-08 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29989
下载链接
链接失效反馈
官方服务:
资源简介:
Hematopoietic differentiation is strictly regulated by complex network of transcription factors that are controlled by ligands binding to cell surface receptors. Disruptions of the intricate sequences of transcriptional activation and suppression of multiple genes cause hematological diseases, such as leukemias, myelodysplastic syndromes or myeloproliferative syndromes. From a clinical standpoint, deciphering the pattern of gene expression during hematopoiesis may help unravel disease-specific mechanisms in hematopoietic malignancies. Herein, we describe a human in vitro hematopoietic model system where lineage specific differentiation of CD34+ cells was accomplished using specific cytokines. Microarray and RNAseq based whole transcriptome and exome analysis was performed on the differentiated erythropoietic, granulopoietic and megakaryopoietic cells to delineate changes in expression of whole transcripts and exons. Analysis on the Human 1.0 ST exon arrays indicated differential expression of 172 genes (P< 0.0000001) and significant splicing of 86 genes during differentiation. Pathway analysis identified these genes to be involved in Rac/RhoA signaling, Wnt/B-catenin signaling and alanine/aspartate metabolism. Comparison of the microarray data to next generation RNAseq analysis during erythroid differentiation demonstrated a high degree of correlation in gene (R= 0.72) and exon (R=0. 62) expression. Our data provides a molecular portrait of events that regulate differentiation of hematopoietic cells. Knowledge of molecular processes by which the cells acquire their cell specific fate would be beneficial in developing cell-based therapies for human diseases. Comparison of gene expression patterns between CD34, E, M and G groups
创建时间:
2014-07-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作