Global transcription analysis of immature avian erythrocytic progenitors: from self-renewal to differentiation

Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process

In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.

A single-cell transcriptomics analysis offers a new dynamical view of the differentiation process, involving an increase in between-cell variability prior to commitment.

The differentiation process has classically been seen as a stereotyped program leading from one progenitor toward a functional cell. This vision was based upon cell population-based analyses averaged over millions of cells. However, new methods have recently emerged that allow interrogation of the molecular content at the single-cell level, challenging this view with a new model suggesting that cell-to-cell gene expression stochasticity could play a key role in differentiation. We took advantage of a physiologically relevant avian cellular model to analyze the expression level of 92 genes in individual cells collected at several time-points during differentiation. We first observed that the process analyzed at the single-cell level is very different and much less well ordered than the population-based average view. Furthermore, we showed that cell-to-cell variability in gene expression peaks transiently before strongly decreasing. This rise in variability precedes two key events: an irreversible commitment to differentiation, followed by a significant increase in cell size variability. Altogether, our results support the idea that differentiation is not a “simple” series of well-ordered molecular events executed identically by all cells in a population but likely results from dynamical behavior of the underlying molecular network.

Cholesterol synthesis-related enzyme oxidosqualene cyclase is required to maintain self-renewal in primary erythroid progenitors

OBJECTIVES

Molecular mechanisms controlling cell fate decision making in self-renewing cells are poorly understood. A previous transcriptomic study, carried out in primary avian erythroid progenitor cells (T2ECs), revealed that the gene encoding oxidosqualene cyclase (OSC/LSS), an enzyme involved in cholesterol biosynthesis, is significantly up-regulated in self-renewing cells. The aim of the present work is to understand whether this up-regulation is required for self-renewal maintenance and what are the mechanisms involved.

MATERIALS AND METHODS

To investigate OSC function, we studied effects of its enzymatic activity inhibition using Ro48-8071, a specific OSC inhibitor. In addition, we completed this pharmacological approach by RNAi-mediated OSC/LSS knockdown. The study of OSC inhibition was carried out on both self-renewing and differentiating cells to observe any state-dependent effect.

RESULTS

  Our data show that OSC acts both by protecting self-renewing T2EC cells from apoptosis and by blocking their differentiation program, as OSC inhibition is sufficient to trigger spontaneous commitment of self-renewing cells towards an early differentiation state. This is self-renewal specific, as OSC inhibition has no effect on erythroid progenitors that have already differentiated.

CONCLUSIONS

Taken together, our results suggest that OSC/LSS expression and activity are required to maintain cell self-renewal and may be involved in the self-renewal versus differentiation/apoptosis decision making, by keeping cells in a self-renewal state.

Cloning and functional characterization of chicken stem cell antigen 2

Stem cell antigen 2 (SCA2) is a Ly6 family member whose function is largely unknown. To characterize biological properties and tissue distribution of chicken SCA2, SCA2 was expressed in E. coli, purified, and a polyclonal antibody developed. Utilizing the polyclonal antibody, SCA2 is a 13 kDa cell surface protein anchored by a glycosyl-phosphatidylinositol (GPI) moiety. SCA2 is expressed in connective tissues of thymus and bursa based on immunohistochemistry, immunoprecipitation, and western blots. In bursal follicles, SCA2 is specifically expressed on the cortical-medullary epithelial cells (CMEC) surrounded by MHC class II presenting cells. Expression profiles of bursal cells induced by contact with SCA2-expressing cells shows down-regulation of numerous genes including CD79B, B cell linker (BLNK), spleen tyrosine kinase (SYK), and gamma 2-phospholipase C (PLCG2) that are involved in the B cell receptor (BCR) and immune response signaling pathways. These results suggest chicken SCA2 plays a role in regulating B lymphocytes.

A combination of transposable elements and magnetic cell sorting provides a very efficient transgenesis system for chicken primary erythroid progenitors

Background

Stable transgenesis is an undeniable key to understanding any genetic system. Retrovirus-based insertional strategies, which feature several technical challenges when they are used, are often limited to one particular species, and even sometimes to a particular cell type as the infection depends on certain cellular receptors. A universal-like system, which would allow both stable transgene expression independent of the cell type and an efficient sorting of transfected cells, is required when handling cellular models that are incompatible with retroviral strategies.

Results

We report here on the combination of a stable insertional transgenesis technique, based on the Tol2 transposon system together with the magnetic cell sorting (MACS) technique, which allows specific selection of cells carrying the transgene in an efficient, reliable and rapid way.

Conclusion

This new Tol2/MACS system leads to stable expression in a culture of primary chicken erythroid cells highly enriched in cells expressing the transgene of interest. This system could be used in a wide variety of vertebrate species.

Stem cell antigen 2: a new gene involved in the self-renewal of erythroid progenitors

OBJECTIVES

Stem cell antigen 2 (SCA2), also known as TSA1 and LY6E, is a glycosylphosphatidylinositol-anchored molecule that belongs to the Ly-6 family and whose function remains largely unknown. We have previously shown that SCA2 is overexpressed in self-renewing avian erythroid progenitors (T2ECs) as opposed to differentiating T2ECs. The aim of this study was to define the role of SCA2 in the switch between self-renewal and differentiation of erythroid progenitors.

MATERIALS AND METHODS

We have investigated the cellular processes controlled by SCA2 in T2ECs by RNA interference and overexpression approaches. Moreover, we have used a SAGE Querying and analysis tools developed in our laboratory, to investigate the expression level of SCA2 gene in different human cell types.

RESULTS

We demonstrate the regulation of SCA2 expression by TGF-beta, a growth factor essential for self-renewal of T2ECs. We establish that SCA2 knockdown by RNA interference reduced the proliferation and promoted the differentiation of T2ECs. In contrast, SCA2 overexpression inhibited differentiation of T2ECs only. Furthermore, by using a bioinformatic approach, we found that SCA2 is highly expressed in a variety of human cancer cells. We confirmed this result by quantitative PCR on human colon and kidney tissues.

CONCLUSIONS

Altogether, these findings imply that SCA2 may function in a dose-dependent manner to support the self-renewal state and that its deregulation might contribute to the development of some human cancers.

SQUAT: A web tool to mine human, murine and avian SAGE data

Background

There is an increasing need in transcriptome research for gene expression data and pattern warehouses. It is of importance to integrate in these warehouses both raw transcriptomic data, as well as some properties encoded in these data, like local patterns.

Description

We have developed an application called SQUAT (SAGE Querying and Analysis Tools) which is available at: . This database gives access to both raw SAGE data and patterns mined from these data, for three species (human, mouse and chicken). This database allows to make simple queries like "In which biological situations is my favorite gene expressed?" as well as much more complex queries like: ≪what are the genes that are frequently co-over-expressed with my gene of interest in given biological situations?≫. Connections with external web databases enrich biological interpretations, and enable sophisticated queries. To illustrate the power of SQUAT, we show and analyze the results of three different queries, one of which led to a biological hypothesis that was experimentally validated.

Conclusion

SQUAT is a user-friendly information retrieval platform, which aims at bringing some of the state-of-the-art mining tools to biologists.

A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome

Background

"Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression), LongSAGE and MPSS (Massively Parallel Signature Sequencing) are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered.

Results

In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method.

Conclusion

We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method.

Serial analysis of gene expression

Serial analysis of gene expression (SAGE) is a method used to obtain comprehensive, unbiased and quantitative gene-expression profiles. Its major advantage over arrays is that it does not require a priori knowledge of the genes to be analyzed and reflects absolute mRNA levels. Since the original SAGE protocol was developed in a short-tag (10-bp) format, several modifications have been made to produce longer SAGE tags for more precise gene identification and to decrease the amount of starting material necessary. Several SAGE-like methods have also been developed for the genome-wide analysis of DNA copy-number changes and methylation patterns, chromatin structure and transcription factor targets. In this protocol, we describe the 17-bp longSAGE method for transcriptome profiling optimized for a small amount of starting material. The generation of such libraries can be completed in 7-10 d, whereas sequencing and data analysis require an additional 2-3 wk.

Large-scale analysis by SAGE reveals new mechanisms of v-erbA oncogene action

Background:

The v-erbA oncogene, carried by the Avian Erythroblastosis Virus, derives from the c-erbAα proto-oncogene that encodes the nuclear receptor for triiodothyronine (T3R). v-ErbA transforms erythroid progenitors in vitro by blocking their differentiation, supposedly by interference with T3R and RAR (Retinoic Acid Receptor). However, v-ErbA target genes involved in its transforming activity still remain to be identified.

Results:

By using Serial Analysis of Gene Expression (SAGE), we identified 110 genes deregulated by v-ErbA and potentially implicated in the transformation process. Bioinformatic analysis of promoter sequence and transcriptional assays point out a potential role of c-Myb in the v-ErbA effect. Furthermore, grouping of newly identified target genes by function revealed both expected (chromatin/transcription) and unexpected (protein metabolism) functions potentially deregulated by v-ErbA. We then focused our study on 15 of the new v-ErbA target genes and demonstrated by real time PCR that in majority their expression was activated neither by T3, nor RA, nor during differentiation. This was unexpected based upon the previously known role of v-ErbA.

Conclusion:

This paper suggests the involvement of a wealth of new unanticipated mechanisms of v-ErbA action.

Identitag, a relational database for SAGE tag identification and interspecies comparison of SAGE libraries

Background

Serial Analysis of Gene Expression (SAGE) is a method of large-scale gene expression analysis that has the potential to generate the full list of mRNAs present within a cell population at a given time and their frequency. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has to be improved in the analysis of SAGE libraries. Indeed, the existing web sites providing correspondence between tags and transcripts do not concern all species for which numerous EST and cDNA have already been sequenced.

Results

This is the reason why we designed and implemented a freely available tool called Identitag for tag identification that can be used in any species for which transcript sequences are available. Identitag is based on a relational database structure in order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to precisely define identification parameters. This structure can be seen like three interconnected modules : the first one stores virtual tags extracted from a given list of transcript sequences, the second stores experimental tags observed in SAGE experiments, and the third allows the annotation of the transcript sequences used for virtual tag extraction. It therefore connects an observed tag to a virtual tag and to the sequence it comes from, and then to its functional annotation when available. Databases made from different species can be connected according to orthology relationship thus allowing the comparison of SAGE libraries between species. We successfully used Identitag to identify tags from our chicken SAGE libraries and for chicken to human SAGE tags interspecies comparison. Identitag sources are freely available on web site.

Conclusions

Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology.