PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 12213207

Transcriptome analysis of monocytic leukemia cell differentiation.

David Piquemal·Thérèse Commes·Laurent Manchon·Mireille Lejeune·Conchita Ferraz·Denis Pugnère·Jacques Demaille·Jean-Marc Elalouf·Jacques Marti
View original source ↗Export metadata ↓

Abstract

The human leukemia cell line U937 is a well-established model for studying monocytic cell differentiation. We used a modified protocol (SADE) of serial analysis of gene expression (SAGE) and developed a SADE linker-anchored PCR assay to investigate the pattern of expression of known genes and to identify new transcripts in proliferating cells and during cell growth arrest and differentiation. We implemented new informatic tools to compare expression profiles before and after exposure of cells to differentiation inducers. From the analysis of 47,388 tags, we identified 13,806 distinct transcripts, 265 of which showed significant variations (P<0.01). Among 1219 well-identified genes, major changes concerned transcription and translation components, cytoskeleton, and macrophage-specific genes. Nearly half of the tags, some of them expressed at high levels, matched partially characterized genes or ESTs, or revealed yet-unknown transcripts, providing a wealth of new candidate genes that may reveal novel aspects of terminal monocytic differentiation.

Explore related subjects

Cell DifferentiationCytoskeletonGene Expression ProfilingGene Expression Regulation, NeoplasticGene LibraryHumansLeukemia, MyeloidTranscription, GeneticU937 CellsJournal ArticleResearch Support, Non-U.S. Gov't

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

David Piquemal, Thérèse Commes, Laurent Manchon, Mireille Lejeune, Conchita Ferraz, Denis Pugnère, Jacques Demaille, Jean-Marc Elalouf, Jacques Marti. 2002. Transcriptome analysis of monocytic leukemia cell differentiation.. https://doi.org/10.1006/geno.2002.6836

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

FIERCE: reconstructing dynamic trajectories from the differentiation potency of single cells.

MOTIVATION: Since the introduction of single-cell RNA sequencing (scRNA-seq), numerous computational approaches have been developed to reconstruct dynamic cellular processes from static transcriptional profiles. These methods order cells along continuous trajectories by assessing their similarity in the gene-expression space. However, they rely on several assumptions, such as prior knowledge of the structure and directionality of the expected genealogy. These assumptions can limit their application to complex cellular systems with poorly understood developmental paths. RESULTS: To address this challenge, we introduce FIERCE (Framework for InfERence of the veloCity of Entropy), a novel computational pipeline designed to predict the changes in the differentiation potency of single cells during dynamic processes. Through a fully unsupervised approach, FIERCE enables the inference of cell lineages directly on the differentiation landscape of the biological system, thus eliminating the need for prior specification of developmental parameters. We demonstrate the efficacy of FIERCE by reconstructing three well-known mouse differentiation systems and by quantifying its accuracy on simulated data. AVAILABILITY AND IMPLEMENTATION: The FIERCE R package is available on GitHub at https://github.com/bicciatolab/FIERCE.

Cell Differentiation↗
PubMed2025

mRNA turnover dynamics are affected by cell differentiation and loss of the cytosine methyltransferase Nsun2.

Nsun2 catalyzes 5-methylcytosine (m5C) formation in several types of RNA, including messenger RNAs (mRNAs), transfer RNAs, and other non-coding RNAs. In mRNA, m5C was reported to influence transcript stability. However, it is unclear if it has stabilizing or destabilizing effects. To address the role of Nsun2 in mRNA stability, we characterized the landscape of mRNA turnover dynamics during embryonic stem cell (ESC) differentiation in wild-type and Nsun2-mutant cells. By using an RNA labeling approach combined with thiouridine-to-cytidine-sequencing (TUC-seq), we demonstrate that mRNA synthesis and stability undergo extensive changes during normal cellular differentiation. Remarkably, a large proportion of these changes did not result in altered mRNA abundance, providing evidence for robust transcript buffering during ESC differentiation. Importantly, also the loss of Nsun2 affected mRNA turnover dynamics but not the steady-state levels of transcripts. Furthermore, our data indicate that the effect of Nsun2 on mRNA turnover was not mediated by m5C deposition in mRNA, which is corroborated by catalysis-independent effects of Nsun2 on translation in early ESC differentiation. In conclusion, this study demonstrates that differentiation as well as loss of Nsun2 can induce changes in mRNA turnover dynamics that are independent of mRNA methylation but consistent with a buffering mechanism to maintain constant RNA levels.

Cell Differentiation↗
PubMed2025

Glucose modulates IRF6 transcription factor dimerization to enable epidermal differentiation.

Non-energetic roles for glucose are largely unclear, as is the interplay between transcription factors (TFs) and ubiquitous biomolecules. Metabolomic analyses uncovered elevation of intracellular glucose during differentiation of diverse cell types. Human and mouse tissue engineered with glucose sensors detected a glucose gradient that peaked in the outermost differentiated layers of the epidermis. Free glucose accumulation was essential for epidermal differentiation and required the SGLT1 glucose transporter. Glucose affinity chromatography uncovered glucose binding to diverse regulatory proteins, including the IRF6 TF. Direct glucose binding enabled IRF6 dimerization, DNA binding, genomic localization, and induction of IRF6 target genes, including essential pro-differentiation TFs GRHL1, GRHL3, HOPX, and PRDM1. These data identify a role for glucose as a gradient morphogen that modulates protein multimerization in cellular differentiation.

Cell Differentiation↗