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Mus musculus

ABSTRACT: Single-cell and bulk RNA-seq of sorted and micro-dissected mouse bone marrow and fetal liver cells

PROVIDER: PRJNA352039 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR4778530_1.fastq.gz	Fastqsanger.gz
	SRR4778530_2.fastq.gz	Fastqsanger.gz
	SRR4778531_1.fastq.gz	Fastqsanger.gz
	SRR4778531_2.fastq.gz	Fastqsanger.gz
	SRR4778532_1.fastq.gz	Fastqsanger.gz

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Transcriptomics of single-cell and bulk sorted and micro-dissected mouse bone marrow, fetal liver and small intestine crypt cells

Project description:Transcriptomics of single-cell and bulk sorted and micro-dissected mouse bone marrow, fetal liver and small intestine crypt cells

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Single-cell RNA-seq of sorted and micro-dissected mouse bone marrow cells

Project description:We here systematically studied the interaction network of bone marrow cells. To this end, we micro-dissected many small interacting structures (cell doublets, triplets etc.) into single cells, and sequenced their mRNAs, to infer cell identity. After grouping the cells into cell types (based on the single-cell transcriptomes), we identified actual physical interactions that occurred more, or less, than what would be expected by chance. We compared the micro-dissected data to sorted hematopoietic stem cells. After mild dissociation of the bone marrow, we micro-dissected many small interacting structures (cell doublets, triplets etc.) into single cells, and sequenced their mRNAs. In addition, single hematopoietic stem cells were sorted (Lineage- Kit+ Sca1+ CD150+ CD48-) to sequence their transcriptome. In detail, the bone marrow was mildly flushed. Structures composed of about 10 to 20 cells were set apart. With needles and a micro-dissection microscope, we trimmed of smaller structures from these big structure. These smaller structures are mainly two to four cells attached together. These small structures were then further micro-dissected to single cells. The goal of doing these sequential dissections was to keep track of which cells were interacting with which. Each micro-dissected cell sample contains RNA-seq data for 96 single cells. Each single cells received a different barcode that allow us to entangle them, and to produce the processed .coutt.csv file. Each sorted hematopoietic stem cell sample represents a single cell. The processed data file expdata_BMJhscC.csv contains transcript counts for all analyzed cells.

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Project description:Ter-119 is a better murine erythroid selection marker than CD71 for bulk immunomics, murine bone marrow and fetal liver erythroid cells have different antimicrobial immune transcriptome signatures, murine bone marrow erythropoiesis is comprised of two branches In this study, we decided to benchmark erythroid cells’ selection and enrichment markers – CD71 and Ter-119 via bulk immune transcriptomics by Nanostring and perform bulk immune transcriptome profiling of Ter-119+ erythroid cells from the bone marrow and the fetal liver by Nanostring.

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Project description:We used the NanoString mouse nCounter miRNA expression platform to compare the miRNA expression profiles of pro-B cells sorted from fetal liver and adult bone marrow in order to gain insight into changes in miRNA expression during B cell ontogeny. Fetal liver and adult bone marrow cells were harvested and FACS sorted for pro-B cells (B220+CD43+IgM-veCD19+CD24+). Total RNA was extracted and used for sample preparation and hybridization per manufacturer's instructions.

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Project description:Various blood lineages, including lymphoid cells and myeloid cells, are produced from hematopoietic stem cells (HSCs) in the bone marrow. However, HSCs aren’t developed in the bone marrow during mouse embryogenesis. The first HSCs are found in the aorta-gonad-mesonephros region, the yolk sac, and the fetal liver, although the number is very few at embryonic day (E) 11. Most HSCs are observed in the fetal liver at E12. To understand the specific genes of nascent HSCs, we performed single-cell RNA-seq analysis of KIT-expressing cells sorted from the fetal liver at E12. We identified the nascent HSC population and found some feature genes in those cells. Therefore, our data will help us understand the nascent HSCs.

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