Erythron Database: Gene Expression From Primary Murine Embryonic, Fetal and Adult Erythroid Cell Precursors.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 780-780
Author(s):  
Paul D Kingsley ◽  
Jenna M Frame ◽  
Emily Greenfest-Allen ◽  
Jeffrey Malik ◽  
Kathleen E. McGrath ◽  
...  

Abstract Abstract 780 Gene expression analyses of mammalian erythroid precursors have been limited to time series generated from in vitro maturation model systems, one or two time point analyses from in vivo-derived samples, or pairwise comparisons of grouped precursors compared with a mutant phenotype. Despite the fact that erythroid cells comprise >25% of the cells of the mammalian fetus and adult, there have been no analyses of gene expression 1) of multiple stages of primary erythroid precursors, or 2) of similar maturational stages derived from primitive, fetal definitive and adult definitive erythroid lineages. Erythroid precursors have classically been defined using morphological characteristics following Wright-Giemsa staining, including cell size, nuclear condensation, nuclear to cytoplasmic ratio, and loss of cytoplasmic basophilia due to decreased ribosomes and increased hemoglobin. Recently, progressive stages of erythroid precursors have been defined by cell surface expression of glycophorin A/Ter-119, CD71 and CD44. It has been difficult to compare and interpret data derived from these two different approaches. We devised a cell sorting strategy utilizing a combination of cell surface expression and scatter related to size with stains for RNA and DNA to purify progressive stages of erythroid precursors (proerythroblast, ProE; basophilic erythroblast, BasoE; polychromatophilic/orthochromatic erythroblast, Poly/OrthoE; reticulocyte, Retic) that correlate well with the morphological series identified by Wright-Giemsa staining. RNA was isolated from four maturational stages (ProE, BasoE, Poly/OrthoE, and Retic) derived from three erythroid lineages: 1) “primitive” erythroid, from yolk sac and embryonic bloodstream, 2) “fetal definitive” erythroid, from E14.5 liver, and 3) “adult definitive” erythroid, from the bone marrow. Gene expression data from these samples were obtained using Affymetrix Genechip arrays. Initial analysis of the dataset indicates robust, reproducible clustering of samples within replicates of each stage/lineage. Hierarchical clustering analysis reveals both stage- and lineage-specific gene sets. A large number of genes are differentially expressed in the reticulocyte stage, regardless of lineage. Intriguingly, initial analysis also indicates that of the 12 stage/lineage data sets, the adult ProE and primitive Poly/OrthoE had the most divergent gene expression patterns distinguishing them from the other samples. Genes representing different expression patterns predicted by abundance data were confirmed using qPCR analysis. Cluster analysis as well as gene ontology mapping indicate a diverse set of expression patterns and molecular functions are present during erythroid maturation. Lineage-specific gene-interaction networks have been constructed and we are analyzing their topology to determine those most essential to erythroid maturation. Gene interactions were determined based on ranked co-expression of genes across our cell stages. These interactions are annotated by known and computationally predicted transcription factor targets, pathways (e.g., metabolic, cellular process, cell-signaling), and known erythroid-specific interactions and can be filtered according to cell-stage specific gene expression and gene function. We are developing a public access website that will aid in the analyses of these data through a searchable database of predicted and known gene-interactions. The site will facilitate comparison of gene-expression and function among the erythropoietic lineages by allowing the visualization and annotation of lineage-specific local-gene interaction networks. These studies provide the first gene expression data from defined stages of normal, primary erythroid precursors that constitute a significant portion of the embryonic, fetal and adult erythron. Disclosures: No relevant conflicts of interest to declare.

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 156-156
Author(s):  
Craig M Forester ◽  
Gun Woo-Byeon ◽  
Juan Oses-Prieto ◽  
Al Burlingame ◽  
Maria Barna ◽  
...  

Erythropoiesis is an intricately orchestrated process responsible for rapidly responding to an array of signaling cues to direct cell fates. While gene expression during erythropoiesis has mainly been studied at the transcription level, regulation of gene expression at the level of translation is still poorly understood. As translational control is one of the fastest steps to regulate protein abundance in the cell, we hypothesize that this mechanism plays an important role to rapidly control protein levels in response to extracellular cues during erythroid differentiation. However, outstanding questions remain on how translational control regulates specific gene programs in early erythroid states including 1.) how mRNA are selected for translation in normal erythropoiesis and 2.) how components of the translational machinery are regulated by upstream signaling pathways to orchestrate the translational landscape. In addressing these questions, we have nuncovered a dynamic interplay between Eukaryotic Initiation Factor 4E (eIF4E), the major mRNA cap binding protein that controls translation initiation and its repressor protein, 4EBP1 in erythropoiesis. Specifically, using in vivo phospho-flow cytometry analysis of the eIF4E-4EBP1 axis, eIF4E activity is high in early erythroid phases and is repressed by 4EBP1 in order to allow erythroid maturation. Surprisingly, high eIF4E activity in early erythroid precursors occurs without an increase in global protein synthesis. Utilizing a model of CD34+ human cord blood cells (HUDEP-2), we show that constitutive overexpression of eIF4E impaired erythropoietic maturation. To capture the specific proteins potentially regulated by eIF4E activity during erythropoiesis, we performed quantitative TMT mass spectrometry during HUDEP-2 erythroid differentiation. Our results revealed that eIF4E controls a specific key network of genes necessary for maintenance of early erythroid precursors. By analyzing the 5' untranslated region (5'UTR) of the eIF4E-dependent mRNA network, we identify a highly conserved, CT-rich motif which is required for these mRNAs to be more efficiently translated with increasing eIF4E levels. These results demonstrate wide-spread translational control of CT-rich mRNAs by eIF4E during early erythropoiesis. We are currently employing DMS-MaPseq to understand whether these motifs are also part of structured RNA elements that confer sensitivity to eIF4E levels. We have further extended these findings to a novel transgenic mouse model we have developed that allows in vivo assessment of increased eIF4E temporally at concise phases of erythroid maturation. Understanding this balance of eIF4E activity provides a novel insight into how of translational control dictates gene expression to determine phases of maturation in a crucial differentiation process. Disclosures No relevant conflicts of interest to declare.


2021 ◽  
Vol 12 ◽  
Author(s):  
Seung-Joon Ahn ◽  
Steven J. Marygold

UDP-glycosyltransferases (UGTs) are important conjugation enzymes found in all kingdoms of life, catalyzing a sugar conjugation with small lipophilic compounds and playing a crucial role in detoxification and homeostasis. The UGT gene family is defined by a signature motif in the C-terminal domain where the uridine diphosphate (UDP)-sugar donor binds. UGTs have been identified in a number of insect genomes over the last decade and much progress has been achieved in characterizing their expression patterns and molecular functions. Here, we present an update of the complete repertoire of UGT genes in Drosophila melanogaster and provide a brief overview of the latest research in this model insect. A total of 35 UGT genes are found in the D. melanogaster genome, localized to chromosomes 2 and 3 with a high degree of gene duplications on the chromosome arm 3R. All D. melanogaster UGT genes have now been named in FlyBase according to the unified UGT nomenclature guidelines. A phylogenetic analysis of UGT genes shows lineage-specific gene duplications. Analysis of anatomical and induced gene expression patterns demonstrate that some UGT genes are differentially expressed in various tissues or after environmental treatments. Extended searches of UGT orthologs from 18 additional Drosophila species reveal a diversity of UGT gene numbers and composition. The roles of Drosophila UGTs identified to date are briefly reviewed, and include xenobiotic metabolism, nicotine resistance, olfaction, cold tolerance, sclerotization, pigmentation, and immunity. Together, the updated genomic information and research overview provided herein will aid further research in this developing field.


2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.


2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.


Blood ◽  
1987 ◽  
Vol 70 (6) ◽  
pp. 1959-1961
Author(s):  
MR Loken ◽  
CI Civin ◽  
WL Bigbee ◽  
RG Langlois ◽  
RH Jensen

The expression of two epitopes on glycophorin A (GPA) during erythroid development was examined on normal human bone marrow using quantitative flow cytometry. The highly correlated binding of two monoclonal antibodies, one sensitive and the other insensitive to glycosylation, indicated that the two epitopes were coordinately expressed during erythroid development. Both antigens reached a maximum expression during the early normoblast stage and were maintained at a constant amount per cell throughout further maturation to erythrocytes. These data suggest that glycosylation of GPA, as detected by antibodies recognizing blood group (M) and (N) antigens, does not increase during erythroid maturation.


1992 ◽  
Vol 4 (11) ◽  
pp. 1383-1404 ◽  
Author(s):  
G N Drews ◽  
T P Beals ◽  
A Q Bui ◽  
R B Goldberg

2019 ◽  
Vol 104 (11) ◽  
pp. 5225-5237 ◽  
Author(s):  
Mariam Haffa ◽  
Andreana N Holowatyj ◽  
Mario Kratz ◽  
Reka Toth ◽  
Axel Benner ◽  
...  

Abstract Context Adipose tissue inflammation and dysregulated energy homeostasis are key mechanisms linking obesity and cancer. Distinct adipose tissue depots strongly differ in their metabolic profiles; however, comprehensive studies of depot-specific perturbations among patients with cancer are lacking. Objective We compared transcriptome profiles of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) from patients with colorectal cancer and assessed the associations of different anthropometric measures with depot-specific gene expression. Design Whole transcriptomes of VAT and SAT were measured in 233 patients from the ColoCare Study, and visceral and subcutaneous fat area were quantified via CT. Results VAT compared with SAT showed elevated gene expression of cytokines, cell adhesion molecules, and key regulators of metabolic homeostasis. Increased fat area was associated with downregulated lipid and small molecule metabolism and upregulated inflammatory pathways in both compartments. Comparing these patterns between depots proved specific and more pronounced gene expression alterations in SAT and identified unique associations of integrins and lipid metabolism–related enzymes. VAT gene expression patterns that were associated with visceral fat area poorly overlapped with patterns associated with self-reported body mass index (BMI). However, subcutaneous fat area and BMI showed similar associations with SAT gene expression. Conclusions This large-scale human study demonstrates pronounced disparities between distinct adipose tissue depots and reveals that BMI poorly correlates with fat mass–associated changes in VAT. Taken together, these results provide crucial evidence for the necessity to differentiate between distinct adipose tissue depots for a correct characterization of gene expression profiles that may affect metabolic health of patients with colorectal cancer.


Blood ◽  
2019 ◽  
Vol 134 (24) ◽  
pp. 2195-2208 ◽  
Author(s):  
Daniel Sasca ◽  
Haiyang Yun ◽  
George Giotopoulos ◽  
Jakub Szybinski ◽  
Theo Evan ◽  
...  

Cohesin mutations are common in myeloid malignancy. Sasca et al elucidate the potential role of cohesin loss in myelodysplastic syndrome and acute myeloid leukemia (MDS/AML). They demonstrate that cohesin binding is critical for erythroid-specific gene expression and that reduction in cohesin impairs terminal erythroid maturation and promotes myeloid malignancy.


2020 ◽  
Vol 48 (6) ◽  
pp. 2880-2896 ◽  
Author(s):  
Jun Li ◽  
Ting Zhang ◽  
Aarthi Ramakrishnan ◽  
Bernd Fritzsch ◽  
Jinshu Xu ◽  
...  

Abstract The transcription factor Six1 is essential for induction of sensory cell fate and formation of auditory sensory epithelium, but how it activates gene expression programs to generate distinct cell-types remains unknown. Here, we perform genome-wide characterization of Six1 binding at different stages of auditory sensory epithelium development and find that Six1-binding to cis-regulatory elements changes dramatically at cell-state transitions. Intriguingly, Six1 pre-occupies enhancers of cell-type-specific regulators and effectors before their expression. We demonstrate in-vivo cell-type-specific activity of Six1-bound novel enhancers of Pbx1, Fgf8, Dusp6, Vangl2, the hair-cell master regulator Atoh1 and a cascade of Atoh1’s downstream factors, including Pou4f3 and Gfi1. A subset of Six1-bound sites carry consensus-sequences for its downstream factors, including Atoh1, Gfi1, Pou4f3, Gata3 and Pbx1, all of which physically interact with Six1. Motif analysis identifies RFX/X-box as one of the most significantly enriched motifs in Six1-bound sites, and we demonstrate that Six1-RFX proteins cooperatively regulate gene expression through binding to SIX:RFX-motifs. Six1 targets a wide range of hair-bundle regulators and late Six1 deletion disrupts hair-bundle polarity. This study provides a mechanistic understanding of how Six1 cooperates with distinct cofactors in feedforward loops to control lineage-specific gene expression programs during progressive differentiation of the auditory sensory epithelium.


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