Project description:Differentiation of hemopoietic stem cells into granulocytes is characterized by distinct changes in the transcriptome. We analyzed mRNA expression in primary murine myeloid cells at four successive stages of hemopoietic differentiation; Lin- Sca1+ cKit+ stem/progenitor cells (LSKs), promyelocytes, myelocytes and granulocytes.
Project description:Differentiation of hemopoietic stem cells into granulocytes is characterized by distinct changes in the transcriptome. We analyzed mRNA expression in primary murine myeloid cells at four successive stages of hemopoietic differentiation; Lin- Sca1+ cKit+ stem/progenitor cells (LSKs), promyelocytes, myelocytes and granulocytes. Using fluorescence–activated cell sorting, we isolated primary murine myeloid cells at four successive stages of hemopoietic differentiation; Lin- Sca1+ cKit+ stem/progenitor cells (LSK), promyelocytes, myelocytes and granulocytes.
Project description:This study sought to determine the dynamic changes of miRNA expression during mouse granulopoiesis. We not only performed analyses of miRNA expression levels in whole cells but also analyzed purified nuclear and cytoplasmic cell fractions to profile miRNA subcellular localization. qRT-PCR analysis of miRNAs was performed on whole cell, nuclear and cytoplasmic RNAs extracted from mouse hemopoietic stem cells (LSKs), promyelocytes, myelocytes and granulocytes. 100 ng of RNA was reversed transcribed using the Taqman miRNA Reverse Transcription Kit and Megaplex RT Primers rodent pool A and B (Life Technologies). Complementary DNA (cDNA) was amplified using a TaqMan rodent microRNA A and B Array v2.0 (Life Technologies) with TaqMan Universal PCR Master Mix on an ABI 7900HT Sequence Detection System.
Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes.