Serial Analysis Of Gene Expression Libraries Research Articles

Serial Analysis of Gene Expression (SAGE): 13 Years of Application in Research

A number of molecular methods of gene expression analysis can approach genomic level. Among those, Serial Analysis of Gene Expression (SAGE) stands out. Unlike many other techniques, SAGE allows both qualitative and quantitative analysis of previously unknown transcripts. Over the course of the last 13 years, SAGE has became a recognized tool of large-scale gene expression profiling, being used extensively in human, animal, yeast and plant studies of various nature. A number of important adaptations was introduced both to the protocol of SAGE library construction and to the analytical algorithm employed. Moreover, some variations of the original protocol (MAGE, SADE, microSAGE, miniSAGE, longSAGE, superSAGE, deepSAGE, etc.) were derived to improve the utility of SAGE in certain conditions. Current review aims comparing the benefits and drawbacks of the techniques for high-throughput gene expression analysis (including SAGE) in a realistic, balanced manner. Issues related to modifications to the original protocol and further development of the SAGE are discussed.

SAGE Application in the Study of Diabetes

Type 2 diabetes is a multifactorial disease that is caused by the disruption of inter-organ networks. These disruptions lead to absolute and/or relative deficiencies in the actions of insulin due to either a genetic disposition or environmental factors. Specifically, the liver plays a central role in energy homeostasis and is a major source of bioactive secretory proteins that contribute to the pathophysiology of diabetes and subsequent complications. Therefore, comprehensive gene expression analyses of critical tissues, including the liver, are important steps for understanding the molecular signature of type 2 diabetes. Serial analysis of gene expression (SAGE) techniques have made it possible to compare tag levels among independent libraries and to identify previously unrecognized genes with novel functions that may be important in the development of diseases. Here, we review possible applications of SAGE to the study of diabetes from the following perspectives: (1) to understand and quantify normal gene expression profiles in the liver with respect to both a single gene and gene ontology of cellular components; (2) to identify biological pathways or co-regulated gene sets associated with the pathophysiology of diabetes to gain a more comprehensive understanding of genetic and environmental alterations; and (3) to identify novel functional hepatic genes that may regulate the pathophysiology of diabetes by comparing independent SAGE libraries in combination with DNA chip analyses. Such SAGE-based approaches may lead to the identification of novel therapeutic targets for the treatment of type 2 diabetes and its complications.

Comparison of the expression profiles of promastigotes and axenic amastigotes in Leishmania donovani using serial analysis of gene expression

In this study, we examined the transcriptome of Leishmania donovani promastigotes and axenic amastigotes to identify differentially regulated mRNAs utilizing the serial analysis of gene expression (SAGE). The axenic culture of amastigotes was initiated from stationary phase promastigotes. Transformation from promastigote to amastigote occurred when cultures in Medium 199 (pH 5.5), supplemented with 20% (v/v) fetal bovine serum, were transferred from 26 degrees C to 37 degrees C. A total of 20,299 and 20,132 tags were generated from promastigote and amastigote libraries, respectively. The containing unique genes identified in these two SAGE libraries were 8,615 and 7,835, respectively. Characteristics of the expressed genes' frequency distribution were remarkably similar in both libraries: the most abundant tags (frequency>or=20), whose levels were equal to or >1.3% of the identified tags, constituted >23% of the total sequenced tags. Correspondingly, 75.72% or 71.65% of the genes accounted for those tags present at low abundance (frequency=1) contributed only 32.13% or 27.89% of the total tags. A total of 968 genes (11.2% of the total genes in promastigotes and 12.4% in amastigotes) were recorded to have statistically different transcript levels between promastigotes and axenic amastigotes. Of the 968 distinct total genes, there are 326 promastigote-enriched transcripts and 642 amastigote-enriched mRNAs.

Simultaneous gene expression profiling in human macrophages infected with Leishmania major parasites using SAGE

BackgroundLeishmania (L) are intracellular protozoan parasites that are able to survive and replicate within the harsh and potentially hostile phagolysosomal environment of mammalian mononuclear phagocytes. A complex interplay then takes place between the macrophage (MΦ) striving to eliminate the pathogen and the parasite struggling for its own survival.To investigate this host-parasite conflict at the transcriptional level, in the context of monocyte-derived human MΦs (MDM) infection by L. major metacyclic promastigotes, the quantitative technique of serial analysis of gene expression (SAGE) was used.ResultsAfter extracting mRNA from resting human MΦs, Leishmania-infected human MΦs and L. major parasites, three SAGE libraries were constructed and sequenced generating up to 28,173; 57,514 and 33,906 tags respectively (corresponding to 12,946; 23,442 and 9,530 unique tags). Using computational data analysis and direct comparison to 357,888 publicly available experimental human tags, the parasite and the host cell transcriptomes were then simultaneously characterized from the mixed cellular extract, confidently discriminating host from parasite transcripts. This procedure led us to reliably assign 3,814 tags to MΦs' and 3,666 tags to L. major parasites transcripts. We focused on these, showing significant changes in their expression that are likely to be relevant to the pathogenesis of parasite infection: (i) human MΦs genes, belonging to key immune response proteins (e.g., IFNγ pathway, S100 and chemokine families) and (ii) a group of Leishmania genes showing a preferential expression at the parasite's intra-cellular developing stage.ConclusionDual SAGE transcriptome analysis provided a useful, powerful and accurate approach to discriminating genes of human or parasitic origin in Leishmania-infected human MΦs. The findings presented in this work suggest that the Leishmania parasite modulates key transcripts in human MΦs that may be beneficial for its establishment and survival. Furthermore, these results provide an overview of gene expression at two developmental stages of the parasite, namely metacyclic promastigotes and intracellular amastigotes and indicate a broad difference between their transcriptomic profiles. Finally, our reported set of expressed genes will be useful in future rounds of data mining and gene annotation.

Serial Analysis of Gene Expression Identifies Connective Tissue Growth Factor Expression as a Prognostic Biomarker in Gallbladder Cancer

Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

Increase in proto-oncogene mRNA transcript levels in bovine lymphoid cells infected with a cytopathic type 2 bovine viral diarrhea virus

Infection of susceptible animals with bovine viral diarrhea viruses (BVDV) can result in an array of disease symptoms that are dependent in part on the strain of infecting virus and the physiological status of the host. BVDV are lymphotrophic and exist as two biotypes. Cytopathic BVDV kill cells outright while noncytopathic strains can readily establish persistent infections. The molecular mechanisms behind these different affects are unknown. To gain a better understanding of the mechanisms of disease, serial analysis of gene expression (SAGE), a powerful method for global gene expression analysis, was employed to examine gene expression changes in BVDV-infected BL3 cells, a bovine B-cell lymphosarcoma cell line. SAGE libraries were constructed from mRNA derived from BL3 cells that were noninfected or infected with the cytopathic BVDV2 strain 296c. Annotation of the SAGE data showed the expression of many genes that are characteristic of B cells and integral to their function. Comparison of the SAGE databases also revealed a number of genes that were differentially expressed. Of particular interest was the increased numbers of transcripts encoding proto-oncogenes (c-fos, c-jun, junB, junD) in 296c-infected cells, all of which are constituents of the AP-1 transcriptional activation complex. Real-time RT-PCR confirmed these results and indicated that the actual increases were larger than that predicted by SAGE. In contrast, there was no corresponding increase in protein levels, but instead a significant decrease of c-jun and junB protein levels in the infected BL3 cells was observed. Rather than an increase in transcription of these genes, it appeared that these proto-oncogenes transcripts accumulated in the BVDV2-infected cells.

Identification of dysregulated genes in lymphocytes from children with Down syndrome

The molecular mechanisms by which trisomy of human chromosome 21 disrupts normal development are not well understood. Global transcriptome studies attempting to analyze the consequences of trisomy in Down syndrome (DS) tissues have reported conflicting results, which have led to the suggestion that the analysis of specific tissues or cell types may be more productive. In the present study, we set out to analyze global changes of gene expression in lymphocytes from children with trisomy 21 by means of the serial analysis of gene expression (SAGE) methodology. Two SAGE libraries were constructed using pooled RNA of normal and Down syndrome children. Comparison between DS and normal profiles revealed that most of the transcripts were expressed at similar levels and functional classes of abundant genes were equally represented. Among the 242 significantly differentially expressed SAGE tags, several transcripts downregulated in DS code for proteins involved in T-cell and B-cell receptor signaling (e.g., PI3Kdelta, RGS2, LY6E, FOS, TAGAP, CD46). The SAGE data and interindividual variability were validated by real-time quantitative PCR. Our results indicate that trisomy 21 induces a modest dysregulation of disomic genes that may be related to the immunological perturbations seen in DS.

Differential SAGE analysis in Arabidopsis uncovers increased transcriptome complexity in response to low temperature

BackgroundAbiotic stress, including low temperature, limits the productivity and geographical distribution of plants, which has led to significant interest in understanding the complex processes that allow plants to adapt to such stresses. The wide range of physiological, biochemical and molecular changes that occur in plants exposed to low temperature require a robust global approach to studying the response. We have employed Serial Analysis of Gene Expression (SAGE) to uncover changes in the transcriptome of Arabidopsis thaliana over a time course of low temperature stress.ResultsFive SAGE libraries were generated from A. thaliana leaf tissue collected at time points ranging from 30 minutes to one week of low temperature treatment (4°C). Over 240,000 high quality SAGE tags, corresponding to 16,629 annotated genes, provided a comprehensive survey of changes in the transcriptome in response to low temperature, from perception of the stress to acquisition of freezing tolerance. Interpretation of these data was facilitated by representing the SAGE data by gene identifier, allowing more robust statistical analysis, cross-platform comparisons and the identification of genes sharing common expression profiles. Simultaneous statistical calculations across all five libraries identified 920 low temperature responsive genes, only 24% of which overlapped with previous global expression analysis performed using microarrays, although similar functional categories were affected. Clustering of the differentially regulated genes facilitated the identification of novel loci correlated with the development of freezing tolerance. Analysis of their promoter sequences revealed subsets of genes that were independent of CBF and ABA regulation and could provide a mechanism for elucidating complementary signalling pathways. The SAGE data emphasised the complexity of the plant response, with alternate pre-mRNA processing events increasing at low temperatures and antisense transcription being repressed.ConclusionAlternate transcript processing appears to play an important role in enhancing the plasticity of the stress induced transcriptome. Novel genes and cis-acting sequences have been identified as compelling targets to allow manipulation of the plant's ability to protect against low temperature stress. The analyses performed provide a contextual framework for the interpretation of quantitative sequence tag based transcriptome analysis which will prevail with the application of next generation sequencing technology.

Interrogating global gene expression in rat neuronal cultures using SAGE

The normal function of the mammalian brain is regulated by complex networks of interactions between cells and molecules, which are to a considerable extent dependent on mechanisms of transcriptional regulation. Disruption of such interactions by neurotoxic stimuli may lead to severe forms of dementia and to other neuropsychiatric disorders. Therefore, critical insight into mechanisms of neuronal dysfunction may be obtained by examining global patterns of gene expression in mammalian models of neurotoxicity. In this regard, the combined use of rat neuronal cultures and serial analysis of gene expression (SAGE) can be viewed as a general platform to enable the search for molecular targets involved in neurotoxic processes. Here, we discuss potential advantages of this approach, highlighting the need for generation of robust SAGE libraries from rat neuronal cultures. The availability and current limitations of bioinformatics tools for SAGE data derived from rat samples is also discussed.

Identification of Genes with Prognostic and Therapeutic Relevance in Multiple Myeloma Using Serial Analysis of Gene Expression Technique.

Serial analysis of gene expression (SAGE) allows a comprehensive profiling of gene expression within a given tissue and also an assessment of transcript abundance.Objectives: We generated SAGE libraries from normal and neoplastic plasma cells with the aim of identifying genes differentially expressed in MM that could be useful as new potential diagnostic, prognostic markers or therapeutic targets.Material and methods: Normal plasma cells were obtained from palatine tonsils of 20 children who underwent tonsillectomy. MM SAGE library was obtained from bone marrow plasma cells of two IgGk newly diagnosed MM patients. Purified normal and neoplastic plasma cells were isolated after magnetic sorting of CD-138-positive cells.Results: We obtained 29,918 SAGE tags from normal and 10,340 tags from tumor libraries. Computer-generated genomic analysis identified 50 overexpressed genes in MM library. After comparison of unique tags expression levels, we selected 12 overexpressed (at least 10 times) genes in the MM library (ZFHX1B, XBP1, PIM2, LGALS1, RANBP2, P53CSV, DDX5, LSM5, JUND, MAPKAPK2, SP140 and NTN1) for further investigation. Expression of 10 out of 12 genes was validated by quantitative real-time PCR in purified plasma cells of 31 MM patients and three controls. XBP1, RANBP2, P53CSV, DDX5, MAPKAPK2 were overexpressed in at least 50% of MM cases. Comparative analyses of relative expression (2-D D CT) of the 10 genes in 31 MM cases and 3 controls showed statistically significant difference between cases and controls for all genes but PIM2 and ZHFX1B, confirming the SAGE data. Also, we could identify that RANBP2 and ZHFX1B have prognostic impact in MM OS (p = 0.040 and p = 0.0502, respectively). Multivariate analysis confirmed RANBP2 expression as a good independent prognostic marker.Conclusions: SAGE technique allowed the identification of genes differentially expressed in normal and neoplastic plasma cells. These genes may have important role in tumorigenesis or may be possible therapeutic targets for MM control, particularly P53CSV and MAPKAPK2, or prognostic impact, as RANBP2.

Comparison between the Gene Expression Profile of Human Müller Cells and Two Spontaneous Müller Cell Lines

Müller cells are the principal glial cells in the retina. They play important functions in this tissue. Alterations in Müller cell behavior were observed in the retinal tissue of patients with proliferative diabetic retinopathy. The purpose of this study was to determine the gene expression profile of normal human Müller cells (NHMCs) and to compare it with that of two spontaneously generated human Müller cell lines (HMCLs) from type 1 and type 2 diabetic donors by using serial analysis of gene expression (SAGE). Approximatively 50,000 tags were sequenced for each SAGE library. Identification of the transcripts was obtained by matching the 15-bp tags with the UniGene and GenBank databases. Classification of the genes was based on the updated information of the genome directory found at the National Center for Biotechnology Information (NCBI) Web site. SAGE was used to characterize the entire transcriptome of human Müller cells and to compare these data with those from Müller cell lines generated from type 1 and type 2 diabetic donors. The transcriptome of NHMCs and HMCLs demonstrated that "metabolism" and "protein synthesis" are the two main categories of genes expressed by human Müller cells. Only 106 genes are differentially expressed between NHMCs and HMCLs. The SAGE libraries reported in this article provide the gene expression profile of NHMCs and HMLCs. It thus represents a valuable source of information regarding the function of Müller cells as well as their role in the development of diabetic retinopathy.

Transcriptome annotation using tandem SAGE tags

Analysis of several million expressed gene signatures (tags) revealed an increasing number of different sequences, largely exceeding that of annotated genes in mammalian genomes. Serial analysis of gene expression (SAGE) can reveal new Poly(A) RNAs transcribed from previously unrecognized chromosomal regions. However, conventional SAGE tags are too short to identify unambiguously unique sites in large genomes. Here, we design a novel strategy with tags anchored on two different restrictions sites of cDNAs. New transcripts are then tentatively defined by the two SAGE tags in tandem and by the spanning sequence read on the genome between these tagged sites. Having developed a new algorithm to locate these tag-delimited genomic sequences (TDGS), we first validated its capacity to recognize known genes and its ability to reveal new transcripts with two SAGE libraries built in parallel from a single RNA sample. Our algorithm proves fast enough to experiment this strategy at a large scale. We then collected and processed the complete sets of human SAGE tags to predict yet unknown transcripts. A cross-validation with tiling arrays data shows that 47% of these TDGS overlap transcriptional active regions. Our method provides a new and complementary approach for complex transcriptome annotation.

Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model

BackgroundSerial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Binomial or Poisson distribution. However, tag counts observed across multiple libraries (for example, one or more groups of biological replicates) have additional variance that cannot be accommodated by this assumption alone. Several models have been proposed to account for this effect, all of which utilize a continuous prior distribution to explain the excess variance. Here, a Poisson mixture model, which assumes excess variability arises from sampling a mixture of distinct components, is proposed and the merits of this model are discussed and evaluated.ResultsThe goodness of fit of the Poisson mixture model on 15 sets of biological SAGE replicates is compared to the previously proposed hierarchical gamma-Poisson (negative binomial) model, and a substantial improvement is seen. In further support of the mixture model, there is observed: 1) an increase in the number of mixture components needed to fit the expression of tags representing more than one transcript; and 2) a tendency for components to cluster libraries into the same groups. A confidence score is presented that can identify tags that are differentially expressed between groups of SAGE libraries. Several examples where this test outperforms those previously proposed are highlighted.ConclusionThe Poisson mixture model performs well as a) a method to represent SAGE data from biological replicates, and b) a basis to assign significance when testing for differential expression between multiple groups of replicates. Code for the R statistical software package is included to assist investigators in applying this model to their own data.

The gene expression patterns of peripheral blood mononuclear cells in patients with systemic lupus erythematosus

This study examined the gene expression patterns of peripheral blood mononuclear cells (PBMCs) in patients with systemic lupus erythematosus (SLE) by using serial analysis of gene expression (SAGE) technology. Following the construction of serial analysis of gene expression (SAGE) library of PBMCs collected from 3 cases of familial SLE patients, a large scale of tag sequencing was performed. The data extracted from sequencing files was analyzed with SAGE 2000 V 4.5 software. The top 30 expressed genes of SLE patients were uploaded to http://david.niaid.nih.gov/david/ease.htm and the functional classification of genes was obtained. The differences among those expressed gene were analyzed by Chi-square tests. The results showed that a total of 1286 unique SAGE tags were identified from 1814 individual SAGE tags. Among the 1286 unique tags, 86.8% had single copy, and only 0.2% tags had more than 20 copies. And 68.4% of the tags matched known expressed sequences, 41.1% of which matched more than one known expressed sequence. About 31.6% of the tags had no match and could represent potentially novel genes. Approximately one third of the top 30 genes were ribosomal protein, and the rest were genes related to metabolism or with unknown functions. Eight tags were found to express differentially in SAGE library of SLE patients. This study draws a profile of gene expression patterns of PBMCs in patients with SLE. Comparison of SAGE database from PBMCs between normal individuals and SLE patients will help us to better understand the pathogenesis of SLE.

Transcriptional oncogenomic hot spots in Barrett's adenocarcinomas: Serial analysis of gene expression

Serial analysis of gene expression (SAGE) provides quantitative and comprehensive expression profiling in a given cell population. In our efforts to define gene expression alterations in Barrett's‐related adenocarcinomas (BA), we produced eight SAGE libraries and obtained a total of 457,894 expressed tags with 32,035 (6.9%) accounting for singleton tags. The tumor samples produced an average of 71,804 tags per library, whereas normal samples produced an average of 42,669 tags per library. Our libraries contained 67,200 unique tags representing 16,040 known gene symbols. Five hundred and sixty‐eight unique tags were differentially expressed between BAs and normal tissue samples (at least twofold; P ≤ 0.05), 395 of these matched to known genes. Interestingly, the distribution of altered genes was not uniform across the human genome. Overexpressed genes tended to cluster in well‐defined hot spots located in certain chromosomes. For example, chromosome 19 had 26 overexpressed genes, of which 18 mapped to 19q13. Using the gene ontology approach for functional classification of genes, we identified several groups that are relevant to carcinogenesis. We validated the SAGE results of five representative genes (ANPEP, ECGF1, PP1201, EIF5A1, and GKN1) using quantitative real‐time reverse‐transcription PCR on 31 BA samples and 26 normal samples. In addition, we performed an immunohistochemistry analysis for ANPEP, which demonstrated overexpression of ANPEP in 6/7 (86%) Barrett's dysplasias and 35/65 (54%) BAs. ANPEP is a secreted protein that may have diagnostic and/or prognostic significance for Barrett's progression. The use of genomic approaches in this study provided useful information about the molecular pathobiology of BAs. © 2007 Wiley‐Liss, Inc.

A quantitative view of the transcriptome of Schistosoma mansoni adult-worms using SAGE

BackgroundFive species of the genus Schistosoma, a parasitic trematode flatworm, are causative agents of Schistosomiasis, a disease that is endemic in a large number of developing countries, affecting millions of patients around the world. By using SAGE (Serial Analysis of Gene Expression) we describe here the first large-scale quantitative analysis of the Schistosoma mansoni transcriptome, one of the most epidemiologically relevant species of this genus.ResultsAfter extracting mRNA from pooled male and female adult-worms, a SAGE library was constructed and sequenced, generating 68,238 tags that covered more than 6,000 genes expressed in this developmental stage. An analysis of the ordered tag-list shows the genes of F10 eggshell protein, pol-polyprotein, HSP86, 14-3-3 and a transcript yet to be identified to be the five top most abundant genes in pooled adult worms. Whereas only 8% of the 100 most abundant tags found in adult worms of S. mansoni could not be assigned to transcripts of this parasite, 46.9% of the total ditags could not be mapped, demonstrating that the 3 sequence of most of the rarest transcripts are still to be identified. Mapping of our SAGE tags to S. mansoni genes suggested the occurrence of alternative-polyadenylation in at least 13 gene transcripts. Most of these events seem to shorten the 3 UTR of the mRNAs, which may have consequences over their stability and regulation.ConclusionSAGE revealed the frequency of expression of the majority of the S. mansoni genes. Transcriptome data suggests that alternative polyadenylation is likely to be used in the control of mRNA stability in this organism. When transcriptome was compared with the proteomic data available, we observed a correlation of about 50%, suggesting that both transcriptional and post-transcriptional regulation are important for determining protein abundance in S. mansoni. The generation of SAGE tags from other life-cycle stages should contribute to reveal the dynamics of gene expression in this important parasite.

Serial analysis of gene expression (SAGE) in rat liver regeneration

We have applied serial analysis of gene expression for studying the molecular mechanism of the rat liver regeneration in the model of 70% partial hepatectomy. We generated three SAGE libraries from a normal control liver (NL library: 52,343 tags), from a sham control operated liver (Sham library: 51,028 tags), and from a regenerating liver (PH library: 53,061 tags). By SAGE bioinformatics analysis we identified 40 induced genes and 20 repressed genes during the liver regeneration. We verified temporal expression of such genes by real time PCR during the regeneration process and we characterized 13 induced genes and 3 repressed genes. We found connective tissue growth factor transcript and protein induced very early at 4 h after PH operation before hepatocytes proliferation is triggered. Our study suggests CTGF as a growth factor signaling mediator that could be involved directly in the mechanism of liver regeneration induction.

Genes that may modulate longevity in C. elegans in both dauer larvae and long-lived daf-2 adults

We used Serial Analysis of Gene Expression (SAGE) to compare the global transcription profiles of long-lived mutant daf-2 adults and dauer larvae, aiming to identify aging-related genes based on similarity of expression patterns. Genes that are expressed similarly in both long-lived types potentially define a common life-extending program. Comparison of eight SAGE libraries yielded a set of 120 genes, the expression of which was significantly different in long-lived worms vs. normal adults. The gene annotations indicate a strong link between oxidative stress and life span, further supporting the hypothesis that metabolic activity is a major determinant in longevity. The SAGE data show changes in mRNA levels for electron transport chain components, elevated expression of glyoxylate shunt enzymes and significantly reduced expression for components of the TCA cycle in longer-lived nematodes. We propose a model for enhanced longevity through a cytochrome c oxidase-mediated reduction in reactive oxygen species commonly held to be a major contributor to aging.

Bone Morphogenetic Protein 4 Expressed in Esophagitis Induces a Columnar Phenotype in Esophageal Squamous Cells

Barrett's esophagus (BE) is a metaplastic condition in which normal squamous esophageal epithelium is replaced by columnar epithelium. It is proposed that one of the possible mechanisms is dedifferentiation of squamous epithelium into columnar epithelium. The pathophysiology through which this metaplasia occurs is unknown. A recent study by serial analysis of gene expression showed that bone morphogenetic protein 4 (BMP-4) is uniquely expressed in BE. In this study, the role of the BMP pathway in the metaplastic transformation of normal squamous cells into columnar cells was examined. Tissues from patients with esophagitis and BE and in an esophagitis-BE rat model were examined for the activation of the BMP pathway. Short-term cultures of primary normal squamous esophageal cells were treated with BMP-4, and cell biological changes were examined by Western blot analysis, immunohistochemistry, and microarrays. In both human and rat tissues, the BMP pathway proved to be activated in esophagitis and BE. Upon incubation of squamous cell cultures with BMP-4, the cytokeratin expression pattern showed a shift that was consistent with columnar epithelium. Involvement of the BMP pathway was suggested by up-regulation of Phosphorylated-Smad 1/5/8 (P-Smad 1/5/8) that was effectively blocked by Noggin, a BMP antagonist. Comparison of the gene expression profiles of squamous cells, BMP-4-treated squamous cells, and BE cells showed a significant shift in the profile of the BMP-4-treated squamous cells toward that of the cultured BE cells. These results suggest that the BMP pathway could play a role in the transformation of normal esophageal squamous cells into columnar cells.

Discarding duplicate ditags in LongSAGE analysis may introduce significant error

BackgroundDuring gene expression analysis by Serial Analysis of Gene Expression (SAGE), duplicate ditags are routinely removed from the data analysis, because they are suspected to stem from artifacts during SAGE library construction. As a consequence, naturally occurring duplicate ditags are also removed from the analysis leading to an error of measurement.ResultsAn algorithm was developed to analyze the differential occurrence of SAGE tags in different ditag combinations. Analysis of a pancreatic acinar cell LongSAGE library showed no sign of a general amplification bias that justified the removal of all duplicate ditags. Extending the analysis to 10 additional LongSAGE libraries showed no justification for removal of all duplicate ditags either. On the contrary, while the error introduced in original SAGE by removal of naturally occurring duplicate ditags is insignificant, it leads to an error of up to 3 fold in LongSAGE. However, the algorithm developed for the analysis of duplicate ditags was able to identify individual artifact ditags that originated from rare nucleotide variations of tags and vector contamination.ConclusionThe removal of all duplicate ditags was unfounded for the datasets analyzed and led to large errors. This may also be the case for other LongSAGE datasets already present in databases. Analysis of the ditag population, however, can identify artifact tags that should be removed from analysis or have their tag count adjusted.