Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA240837 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We isolated by fluorescence-activated cell sorting highly purified populations (long term hematopoietic stem cells (LT-HSCs), short term hematopoietic stem cells (ST-HSCs), multipotent progenitors (MPPs), common myeloid progenitor (CMPs), granulocyte and monocyte progenitors (GMPs), multilymphoid progenitors (MLPs), Myeloid-erythorid Progenitor (MEP), Granulocytes, Monocytes, B cells, T cells, Dendritic cells, Natural Killer cells and Erythrocyte Progenitors from 3 to 4 cord blood pools. We extracted RNA from 5K cells of each population and performed RNA-sequencing.
| EGAS00001004968 | EGA
Project description:Aged hematopoietic stem cells (HSCs) display myeloid-biased differentiation and reduced regenerative potential. In this study, we uncover that P-selectin (Selp) marks a subset of aged HSCs with reduced repopulation capacity. This population of HSCs expresses a prominent aging transcriptome. Overexpression of Selp in young HSCs impaired long-term reconstitution potential and repressed erythropoiesis. We show that IL-1β is elevated in aged bone marrow and administration of IL-1β induces expression of Selp and other aging-associated genes in HSCs. Finally, we demonstrate that transplantation of aged HSCs into young recipients restores a young-like transcriptome, specifically by repressing pro-inflammatory pathways, highlighting the important role of the bone marrow microenvironment in HSC aging.
2023-01-02 | GSE194273 | GEO
Project description:The transcriptome of Ctrl and Vitamin A-deficient longterm hematopoietic stem cells (LT-HSC) and multipotant progenitors (MPP3/4) was assessed by RNAseq.
2021-11-02 | E-MTAB-9729 | biostudies-arrayexpress
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.
2009-05-20 | GSE16139 | GEO
Project description:Introgressed variants from other species can be an important source of genetic variation because they may arise rapidly, can include multiple mutations on a single haplotype, and have often been pretested by selection in the species of origin. Although introgressed alleles are generally deleterious, several studies have reported introgression as the source of adaptive alleles-including the rodenticide-resistant variant of Vkorc1 that introgressed from Mus spretus into European populations of Mus musculus domesticus. Here, we conducted bidirectional genome scans to characterize introgressed regions into one wild population of M. spretus from Spain and three wild populations of M. m. domesticus from France, Germany, and Iran. Despite the fact that these species show considerable intrinsic postzygotic reproductive isolation, introgression was observed in all individuals, including in the M. musculus reference genome (GRCm38). Mus spretus individuals had a greater proportion of introgression compared with M. m. domesticus, and within M. m. domesticus, the proportion of introgression decreased with geographic distance from the area of sympatry. Introgression was observed on all autosomes for both species, but not on the X-chromosome in M. m. domesticus, consistent with known X-linked hybrid sterility and inviability genes that have been mapped to the M. spretus X-chromosome. Tract lengths were generally short with a few outliers of up to 2.7 Mb. Interestingly, the longest introgressed tracts were in olfactory receptor regions, and introgressed tracts were significantly enriched for olfactory receptor genes in both species, suggesting that introgression may be a source of functional novelty even between species with high barriers to gene flow.
| S-EPMC8784167 | biostudies-literature
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. Mouse hematopoietic stem cells were purified from bone marrow cells using negative and positive selection with a Magnetic-Activated Cell Sorter (MACS). total RNA and mRNA were purified from the purified cells using Trizol reagent and magnetic oligo dT beads. Double strand cDNAs were synthesized using a cDNA synthesis kit and anchored oligo dT primers. After NlaIII digestion, 3’ cDNAs were isolated and amplified through 16-cycle PCR. SAGE tags were released from the 3’ cDNA after linker ligation. Ditags were formed, concatemerized and cloned into a pZERO vector. Sequencing reactions were performed with the ET sequencing terminator kit. Sequences were collected using a Megabase 1000 sequencer. SAGE tag sequences were extracted using SAGE 2000 software.
2009-05-20 | E-GEOD-16139 | biostudies-arrayexpress
Project description:Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs)
| PRJNA766036 | ENA
Project description:Translational research is commonly performed in the C57B6/J mouse strain, chosen for its genetic homogeneity and phenotypic uniformity. Here, we evaluate the suitability of the white-footed deer mouse (Peromyscus leucopus) as a model organism for aging research, offering a comparative analysis against C57B6/J and diversity outbred (DO) Mus musculus strains. Our study includes comparisons of body composition, skeletal muscle function, and cardiovascular parameters, shedding light on potential applications and limitations of P. leucopus in aging studies. Notably, P. leucopus exhibits distinct body composition characteristics, emphasizing reduced muscle force exertion and a unique metabolism, particularly in fat mass. Cardiovascular assessments showed changes in arterial stiffness, challenging conventional assumptions and highlighting the need for a nuanced interpretation of aging-related phenotypes. Our study also highlights inherent challenges associated with maintaining and phenotyping P. leucopus cohorts. Behavioral considerations, including anxiety-induced responses during handling and phenotyping assessment, pose obstacles in acquiring meaningful data. Moreover, the unique anatomy of P. leucopus necessitates careful adaptation of protocols designed for Mus musculus. While showcasing potential benefits, further extensive analyses across broader age ranges and larger cohorts are necessary to establish the reliability of P. leucopus as a robust and translatable model for aging studies.
| S-EPMC11335981 | biostudies-literature
Project description:Hamey2017 - Blood stem cell regulatory
network
This model is described in the article:
Reconstructing blood stem
cell regulatory network models from single-cell molecular
profiles
Fiona K. Hamey, Sonia Nestorowa,
Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold
Göttgens
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Adult blood contains a mixture of mature cell types, each
with specialized functions. Single hematopoietic stem cells
(HSCs) have been functionally shown to generate all mature cell
types for the lifetime of the organism. Differentiation of HSCs
toward alternative lineages must be balanced at the population
level by the fate decisions made by individual cells.
Transcription factors play a key role in regulating these
decisions and operate within organized regulatory programs that
can be modeled as transcriptional regulatory networks. As
dysregulation of single HSC fate decisions is linked to fatal
malignancies such as leukemia, it is important to understand
how these decisions are controlled on a cell-by-cell basis.
Here we developed and applied a network inference method,
exploiting the ability to infer dynamic information from
single-cell snapshot expression data based on expression
profiles of 48 genes in 2,167 blood stem and progenitor cells.
This approach allowed us to infer transcriptional regulatory
network models that recapitulated differentiation of HSCs into
progenitor cell types, focusing on trajectories toward
megakaryocyte–erythrocyte progenitors and lymphoid-primed
multipotent progenitors. By comparing these two models, we
identified and subsequently experimentally validated a
difference in the regulation of nuclear factor, erythroid 2
(Nfe2) and core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 homolog (Cbfa2t3h) by the transcription
factor Gata2. Our approach confirms known aspects of
hematopoiesis, provides hypotheses about regulation of HSC
differentiation, and is widely applicable to other hierarchical
biological systems to uncover regulatory relationships.
This model is hosted on
BioModels Database
and identified by:
MODEL1610060000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-06-09 | MODEL1610060000 | BioModels
Project description:Hamey2017 - Blood stem cell regulatory
network (LMPP network)
This model is described in the article:
Reconstructing blood stem
cell regulatory network models from single-cell molecular
profiles
Fiona K. Hamey, Sonia Nestorowa,
Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold
Göttgens
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Adult blood contains a mixture of mature cell types, each
with specialized functions. Single hematopoietic stem cells
(HSCs) have been functionally shown to generate all mature cell
types for the lifetime of the organism. Differentiation of HSCs
toward alternative lineages must be balanced at the population
level by the fate decisions made by individual cells.
Transcription factors play a key role in regulating these
decisions and operate within organized regulatory programs that
can be modeled as transcriptional regulatory networks. As
dysregulation of single HSC fate decisions is linked to fatal
malignancies such as leukemia, it is important to understand
how these decisions are controlled on a cell-by-cell basis.
Here we developed and applied a network inference method,
exploiting the ability to infer dynamic information from
single-cell snapshot expression data based on expression
profiles of 48 genes in 2,167 blood stem and progenitor cells.
This approach allowed us to infer transcriptional regulatory
network models that recapitulated differentiation of HSCs into
progenitor cell types, focusing on trajectories toward
megakaryocyte–erythrocyte progenitors and lymphoid-primed
multipotent progenitors. By comparing these two models, we
identified and subsequently experimentally validated a
difference in the regulation of nuclear factor, erythroid 2
(Nfe2) and core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 homolog (Cbfa2t3h) by the transcription
factor Gata2. Our approach confirms known aspects of
hematopoiesis, provides hypotheses about regulation of HSC
differentiation, and is widely applicable to other hierarchical
biological systems to uncover regulatory relationships.
This model is hosted on
BioModels Database
and identified by:
MODEL1610060001.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-06-09 | MODEL1610060001 | BioModels