Mouse Erythroid Differentiation Research Articles

WDR82-binding long noncoding RNA lncEry controls mouse erythroid differentiation and maturation.

Hematopoietic differentiation is controlled by both genetic and epigenetic regulators. Long noncoding RNAs (lncRNAs) have been demonstrated to be important for normal hematopoiesis, but their function in erythropoiesis needs to be further explored. We profiled the transcriptomes of 16 murine hematopoietic cell populations by deep RNA sequencing and identified a novel lncRNA, Gm15915, that was highly expressed in erythroid-related progenitors and erythrocytes. For this reason, we named it lncEry. We also identified a novel lncEry isoform, which was the principal transcript that has not been reported before. lncEry depletion impaired erythropoiesis, indicating the important role of the lncRNA in regulating erythroid differentiation and maturation. Mechanistically, we found that lncEry interacted with WD repeat-containing protein 82 (WDR82) to promote the transcription of Klf1 and globin genes and thus control the early and late stages of erythropoiesis, respectively. These findings identified lncEry as an important player in the transcriptional regulation of erythropoiesis.

Dynamics of the 4D genome during in vivo lineage specification and differentiation

Mammalian gene expression patterns are controlled by regulatory elements, which interact within topologically associating domains (TADs). The relationship between activation of regulatory elements, formation of structural chromatin interactions and gene expression during development is unclear. Here, we present Tiled-C, a low-input chromosome conformation capture (3C) technique. We use this approach to study chromatin architecture at high spatial and temporal resolution through in vivo mouse erythroid differentiation. Integrated analysis of chromatin accessibility and single-cell expression data shows that regulatory elements gradually become accessible within pre-existing TADs during early differentiation. This is followed by structural re-organization within the TAD and formation of specific contacts between enhancers and promoters. Our high-resolution data show that these enhancer-promoter interactions are not established prior to gene expression, but formed gradually during differentiation, concomitant with progressive upregulation of gene activity. Together, these results provide new insight into the close, interdependent relationship between chromatin architecture and gene regulation during development.

Comparison of Expression and Epigenetic Profiles in Human and Mouse Erythropoiesis and Megakaryopoiesis Using a Systems Biology Model

To date numerous datasets of gene expression and epigenetic profiles for mouse and human hematopoietic cells have been generated. While individual data sets for a particular cell type have been correlated, no approach exists to harness all expression and epigenetic profiles for the different types of hematopoietic cells. Our goal is to develop a systems biology platform to compare epigenetic profiles of hematopoietic cells towards a better understanding of epigenetic mechanisms governing hematopoiesis. To provide the necessary foundation to support systematic studies of hematopoiesis, we have developed the Systems Biology Repository (SBR, http://sbrblood.nhgri.nih.gov), a data "ranch" for organizing and analyzing transcriptome and epigenome data cells throughout differentiation.To populate SBR, we extracted, curated, annotated, and integrated all human and mouse hematopoietic datasets available through the Encyclopedia of DNA Elements (ENCODE), the Gene Expression Omnibus (GEO) and the Short Read Repository (SRR). These include genome-wide profiles of DNA methylation, histone methylation and acetylation, transcription factor occupancy (ChIPSeq), chromatin accessibility (DNaseISeq, ATACSeq, FAIRESeq), and coding as well as non-coding transcriptional profiles (RNASeq).To demonstrate the utility of SBR, we conducted three different analyses. The first was a vertical study of HistoneSeq (H3K4me1, H3K4me2, H3K4me3, and H3K27ac), DNA methylation and RNASeq profiles during mouse erythroid differentiation. We found a global decrease in DNA methylation from hematopoietic stem and progenitor cells (HSC) through common myeloid progenitors (CMP), erythroid progenitor cells (MEP) and erythroblasts (ERY; 92936 peaks in HSC to 14422 in ERY). The number of expressed genes (using a tags per million cutoff of 10) increased in erythroid progenitors (8901 in HSC to 10778 in CMP and 10670 in MEP) before decreasing in ERY (8654). 62% of histone marks delineating active enhancers (H3K27ac, H3K4me1) are present in both HSC and ERY, while 48% arise de novo during differentiation. In contrast, only 16% of active promoter specific histone marks (H3K4me2, H3K4me3) are present in both HSC and ERY.For a horizontal analysis we compared the DNA methylation, RNASeq, histone modification (H3K4me1, H3K4me2, H3K4me3, and H3K27ac) and transcription factor binding (GATA1 and NFE2) profiles of erythroblasts (ERY) and megakaryocytes (MEG). We found a similar relationship between gene expression and the histone and DNA methylation profiles in each cell type but differences between expression and in transcription factor occupancy. DNA methylation and H3K4me3 was enriched in the gene body of expressed genes (>36%) for both ERY (p ≤ 0.001) and MEG (p ≤ 0.01). In contrast DNA methylation was enriched in the upstream and downstream regions of non-coding RNA genes (p ≤ 0.001). Transcription factor occupancy was cell type specific: 79% of GATA1 sites are in ERY and 72% of NFE2 sites are in MEG. In erythroblasts, DNA methylation and GATA1 binding in the gene body are associated with gene silencing (4 fold difference, p ≤ 0.001), while in megakaryocytes, DNA methylation and NFE2 binding in the gene body are associated with gene activation (8 fold difference, p ≤ 0.001).We used the Mouse Genome Informatics homology map data to perform a cross-species comparison of the expression profiles of mouse and human multipotent progenitors (MPP), proerythroblasts and orthochromatic erythroblasts. We found a total of 5247 genes expressed at significantly different levels (p ≤ 0.001) between human and mouse MPP, while only 2010 genes were expressed at significantly similar levels (p ≤ 0.001). At the proerythroblast and orthochromatic erythroblast stages 7696 genes and 6571 genes were expressed at significantly different levels (p ≤ 0.001) between human and mouse respectively, while 2024 and 2560 genes were expressed at significantly similar levels (p ≤ 0.001). These data are consistent with previous studies showing differences in the transcriptional profiles of mouse and human hematopoietic cells.In summary, SBR provides a foundation to model the genetic and epigenetic landscape in both the mouse and human hematopoietic system, and enables functional correlations to be made between the species. As SBR is expanded to include data from patient cells, it will be possible to model epigenetic changes associated with disease. DisclosuresNo relevant conflicts of interest to declare.

Ectopic expression of Hmgn2 antagonizes mouse erythroid differentiation in vitro

Hmgn2 (high mobility group nucleosomal 2), a ubiquitous nucleosome-binding protein that unfolds chromatin fibres and enhances DNA replication, reportedly regulates differentiation of epithelial and mesenchymal cells. To investigate how Hmgn2 regulates HC (haemopoietic cell) differentiation, we quantified Hmgn2 expression in HCs of mouse FL (fetal liver) during erythroid differentiation. Hmgn2 expression levels were >10-fold higher in immature erythroid progenitors than in mature erythroid cells, suggesting that Hmgn2 antagonizes erythroid differentiation. To address this issue, Hmgn2 were transfected into both Friend erythroleukaemia cells and FL HCs. There was a 3.3-fold decrease in relatively mature c-Kit(+)/CD71(+) erythroid cells, a 2.9-fold increase in immature c-Kit(+)/CD71(-) erythroid cells in transfected Friend cells, a 1.1-fold decrease in relatively mature CD71(+)/Ter119(+) erythroid cells, and a 1.7-fold increase in relatively immature c-Kit(+)/CD71(+) erythroid cells in FL HCs accompanied by down-regulation of genes encoding the erythroid transcription factors, Gata1 and Klf1. Two days after Hmgn2 transfection of Friend erythroleukaemia cells, the number of S-phase cells increased, whereas the number of cells in G(1) decreased, while that of mitotic cells remained unchanged. We conclude that ectopic expression of Hmgn2 antagonizes mouse erythroid differentiation in vitro, which may be due to enhancement of DNA replication and/or blocking entry of mitosis at S-phase.

Identification of MicroRNAs Associated with Erythropoiesis Through Deep Sequencing of Red Blood Cells,

Abstract 3164We have recently found that human mature red blood cells (RBCs), though lacking large RNAs, possess a diverse and abundant set of microRNAs (miRNAs). MiRNAs are a class of small RNAs that inhibit translation and/or promote degradation of target mRNAs. Red blood cells are an ideal model for small RNA identification due to the relatively low amount of contaminating mRNA, tRNA, and rRNA fragments.We performed deep sequencing of small RNAs in human RBCs to provide an unbiased set of both known and novel microRNAs, and to gain insight into the process of erythropoiesis. Small RNA libraries were applied to the Illumina GAII deep sequencing platform from both HbAA and HbSS individuals, as microRNAs have also been shown to be genetic determinants of sickle cell phenotypes (Sangokoya 2010). A modified version of the probabilistic modeling algorithm, miRDeep (Friedländer 2008), was used to identify several novel and known microRNAs. Genomic loci that overlapped with miRNAs described in miRBase were identified as known miRNAs. The remaining genomic loci were identified as encoding candidate novel miRNAs. Collectively, we identified 253 predicted miRNA precursor loci from the two samples. 226 miRNA precursor loci annotated in miRBase were identified as known miRNAs, whereas the remaining 27 precursor loci were identified as candidate novel miRNAs. In addition to miRNAs, we identified other small RNAs that did not pass miRDeep criteria. One of the most abundant sequences consisted of a distinct fragment of Ro-associated Y4 RNA (hY4). Y RNAs are involved in chromosomal DNA replication and cell proliferation, and specifically, RNAs hY1 and hY4 have been shown to be present in mature human erythrocytes (O’Brien 1990).In addition, we also identified the relative expression of both novel and known microRNAs during erythropoiesis using both human and mouse erythroid differentiation models. We are currently investigating the relevant targets and regulatory functions of these microRNAs during erythropoiesis, as well as experimental validation of authentic microRNA fuction of novel microRNAs. This global analysis will enhance our understanding of events dictating red cell maintenance and development. Disclosures:No relevant conflicts of interest to declare.

Dynamics of the epigenetic landscape during erythroid differentiation after GATA1 restoration

Interplays among lineage-specific nuclear proteins, chromatin modifying enzymes, and the basal transcription machinery govern cellular differentiation, but their dynamics of action and coordination with transcriptional control are not fully understood. Alterations in chromatin structure appear to establish a permissive state for gene activation at some loci, but they play an integral role in activation at other loci. To determine the predominant roles of chromatin states and factor occupancy in directing gene regulation during differentiation, we mapped chromatin accessibility, histone modifications, and nuclear factor occupancy genome-wide during mouse erythroid differentiation dependent on the master regulatory transcription factor GATA1. Notably, despite extensive changes in gene expression, the chromatin state profiles (proportions of a gene in a chromatin state dominated by activating or repressive histone modifications) and accessibility remain largely unchanged during GATA1-induced erythroid differentiation. In contrast, gene induction and repression are strongly associated with changes in patterns of transcription factor occupancy. Our results indicate that during erythroid differentiation, the broad features of chromatin states are established at the stage of lineage commitment, largely independently of GATA1. These determine permissiveness for expression, with subsequent induction or repression mediated by distinctive combinations of transcription factors.

Massive translational repression of gene expression during mouse erythroid differentiation

We took advantage of a mouse erythroid differentiation system to determine the relative contribution of transcriptional and translational control during this process. Comparison of expression data obtained with total cytoplasmic mRNAs or polysome-bound mRNAs (actively translated mRNAs) on Affymetrix high-density oligonucleotide microarrays revealed different characteristics of the two regulatory mechanisms. Indeed, mRNA expression from a vast majority of genes was affected, albeit most changes were relatively small and occurred at a low pace. Translational control, however, affected a smaller fraction of genes but was effective at earlier time-points. This analysis unravels six clusters of genes showing no significant variation in mRNA expression levels whereas they are submitted to translational regulation. Their involvement in terminal mouse erythropoiesis may prove to be highly relevant. Furthermore, the data from specific and functional categories of genes emphasize that translational control, not only reinforces the transcriptional effect, but allows the cell to increase the complexity in gene expression regulation patterns.

Isolation and characterization of a novel mouse erythroid differentiation-denucleation related gene (MEDDF)

Using subtractive cDNA cloning method, a series of cDNA fragments have been isolated. One of them has been selected, that expressed differentially in the mouse intermediatelate erythroblasts, as a probe for the screening of mouse erythroid differentiation related gene from a cDNA library constructed from mouse mid-late erythroids. A positive cDNA clone has been obtained using phagein situ hybridization coupled with PCR technique. Sequencing of this cDNA by utilizing the Bluescript-SK (+) phage vector system demonstrates that it has a full length of 505 bp with an open reading frame of 309 bp (from 53 to 359 bp) encoded a protein of 102 amino acids. There is a tailing signal AATAA at 462 bp and a 26-bp long poly A tail terminal at the 3′UTR. Searches of GenBank databases failed to find any homologous sequences (Gen-Bank Accession Number: Banklt 180846 AF 060220) and it was proved to be a novel gene designated mouse erythroid differentiation-denucleation related gene (MEDDF). Northern blot analysis petformed with the MEDDF revealed that a 500-bp mRNA transcript was expressed markedly In RNA prepared from mouse mid-late erythroblasts as well as hematopoietic tissues, such as bone marrow and spleen, but not in RNA from other tissues, such as brain, heart, liver, lung, kidney and testes. The results suggest that it is a tissue specific novel gene associated with mouse erythroid terminal differentiation.

G-actin and F-actin levels at different stages of mouse erythroid differentiation

Monomeric (G-) actin and filamentous (F-) actin levels were determined in Triton X-100 extracts prepared from mouse erythroid cells at various stages of differentiation. G-actin and F-actin were found in the Triton-soluble fraction and in the Triton-insoluble fraction, respectively. G-actin levels in untreated and dimethyl sulfoxide-treated (differentiated) erythroleukemia cells, reticulocytes, and erythrocytes were 48, 33, 2.8, and 0.37 ug/mg protein, respectively, and F-actin levels were 17, 35, 45, and 59 ug/mg protein, respectively. G-actin/F-actin ratios were successively lower in cells representing the more mature stages of development.