Analysis Of Differentially Expressed Genes From Hematopoietic Stem Cell Based On Transcriptome Data

Objective:Hematopoietic stem cells (HSCs) are a class of adult stem cells from the blood system, which have the ability of long-term self-renewal and the capability of giving rise to all the other blood cells. Research of the mechanism involved in the maintain and transformation of HSCs holds a great promise for blood disease prevention, diagnosis and treatment. However, the mechanism has not yet been elucidated. Here, we analyzed the gene expression microarray data of HSC, and found some key genes and pathways related to the biological process of differentiation, aging and disease. And the results lay the foundation for the further exploration on the mechanism of HSC’s maintain and transformation, as well as, the looking for a new therapeutic targets.Methods:(1) Choose datasets of HSC expression profiling by array from GEO database.(2) Get effective value of probe expression data through preprocessing the original picture signal by programming methodology.(3) Use the Rankprod arithmetic, which is based on the fold change arithmetic, to get the significantly differentially expressed genes (DEGs).(4) Make functional annotation and pathway enrichment of DEGs by using a network tool-DAVID.(5)Use GeneMANIA, a network tool, to build co-expression network and physical interaction network of functional genes, which are noted with DEGs.(6) Find genes that may related to sternness through a network tool-StemCellNet.Results:(1) Obtained applicable datasets respectively.(2) Successfully preprocessed the original picture-signal data and got all the effective probe expression value.(3) Gained abundant interested differentially expressed genes. Differentially expressed genes were obtained respectively from the HSCs biological process-related datasets by analysis of gene differential expression. In the comparative analysis, young HSCs and old HSCs, normal HSCs and progenitor cells, healthy HSCs and AML-HSCs were respectively compared, and found54genes disturbed in all the bioprocesses mentioned above.(4) Successfully achieved the gene ontology and gained interested pathways.(5) Successfully gained co-expression network, physical interaction network, and also, obtained several novel unreported genes related to sternness, HERC5, MIR15B and MIR302A, for example.Conclusion:In this research, as has been mentioned above, via differential expression spectrum research combined with functional network analysis, we found a lot of interested genes and pathways. Furthermore, the interaction between system genes lays the foundation of revealing the molecular mechanism of HSCs and HSCs-related diseases. We also found some HSC DEGs, which are unreported and may related to cell sternness, and the further research of these genes will help people to reveal hematopoietic stem cells differentiation and related molecular mechanism of diseases, and also provides certain guiding significance to the other stem cells research.