Reproducibility, bioinformatic analysis and power of the SAGE method to evaluate changes in transcriptome

Measuring reproducibility of virus metagenomics analyses using bootstrap samples from FASTQ-files

MOTIVATION

High-throughput sequencing data can be affected by different technical errors, e.g. from probe preparation or false base calling. As a consequence, reproducibility of experiments can be weakened. In virus metagenomics, technical errors can result in falsely identified viruses in samples from infected hosts. We present a new resampling approach based on bootstrap sampling of sequencing reads from FASTQ-files in order to generate artificial replicates of sequencing runs which can help to judge the robustness of an analysis. In addition, we evaluate a mixture model on the distribution of read counts per virus to identify potentially false positive findings.

RESULTS

The evaluation of our approach on an artificially generated dataset with known viral sequence content shows in general a high reproducibility of uncovering viruses in sequencing data, i.e. the correlation between original and mean bootstrap read count was highly correlated. However, the bootstrap read counts can also indicate reduced or increased evidence for the presence of a virus in the biological sample. We also found that the mixture-model fits well to the read counts, and furthermore, it provides a higher accuracy on the original or on the bootstrap read counts than on the difference between both. The usefulness of our methods is further demonstrated on two freely available real-world datasets from harbor seals.

AVAILABILITY AND IMPLEMENTATION

We provide a Phyton tool, called RESEQ, available from https://github.com/babaksaremi/RESEQ that allows efficient generation of bootstrap reads from an original FASTQ-file.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcriptome Sequencing Approaches to Elucidate Host-Microbe Interactions in Opportunistic Human Fungal Pathogens

Infections caused by opportunistic human fungal pathogens are a source of increasing medical concern, due to their growing incidence, the emergence of novel pathogenic species, and the lack of effective diagnostics tools. Fungal pathogens are phylogenetically diverse, and their virulence mechanisms can differ widely across species. Despite extensive efforts, the molecular bases of virulence in pathogenic fungi and their interactions with the human host remain poorly understood for most species. In this context, next-generation sequencing approaches hold the promise of helping to close this knowledge gap. In particular, high-throughput transcriptome sequencing (RNA-Seq) enables monitoring the transcriptional profile of both host and microbes to elucidate their interactions and discover molecular mechanisms of virulence and host defense. Here, we provide an overview of transcriptome sequencing techniques and approaches, and survey their application in studying the interplay between humans and fungal pathogens. Finally, we discuss novel RNA-Seq approaches in studying host-pathogen interactions and their potential role in advancing the clinical diagnostics of fungal infections.

Transcriptome-wide identification of preferentially expressed genes in the hypothalamus and pituitary gland

To identify preferentially expressed genes in the central endocrine organs of the hypothalamus and pituitary gland, we generated transcriptome-wide mRNA profiles of the hypothalamus, pituitary gland, and parietal cortex in male mice (12-15 weeks old) using serial analysis of gene expression (SAGE). Total counts of SAGE tags for the hypothalamus, pituitary gland, and parietal cortex were 165824, 126688, and 161045 tags, respectively. This represented 59244, 45151, and 55131 distinct tags, respectively. Comparison of these mRNA profiles revealed that 22 mRNA species, including three potential novel transcripts, were preferentially expressed in the hypothalamus. In addition to well-known hypothalamic transcripts, such as hypocretin, several genes involved in hormone function, intracellular transduction, metabolism, protein transport, steroidogenesis, extracellular matrix, and brain disease were identified as preferentially expressed hypothalamic transcripts. In the pituitary gland, 106 mRNA species, including 60 potential novel transcripts, were preferentially expressed. In addition to well-known pituitary genes, such as growth hormone and thyroid stimulating hormone beta, a number of genes classified to function in transport, amino acid metabolism, intracellular transduction, cell adhesion, disulfide bond formation, stress response, transcription, protein synthesis, and turnover, cell differentiation, the cell cycle, and in the cytoskeleton and extracellular matrix were also preferentially expressed. In conclusion, the current study identified not only well-known hypothalamic and pituitary transcripts but also a number of new candidates likely to be involved in endocrine homeostatic systems regulated by the hypothalamus and pituitary gland.

A single dose of dihydrotestosterone induced a myogenic transcriptional program in female intra-abdominal adipose tissue

Sex steroids are key regulators of adipose tissue (AT) mass, determining gender-specific differences in fat distribution and accumulation. With the aim of exploring the relevance and peculiarities of androgen action in female intra-abdominal AT, we used the serial analysis of gene expression (SAGE) method to analyze the AT transcriptome in four groups of female mice: intact, ovariectomized (OVX), OVX plus dihydrotestosterone (DHT) injection at 3h or 24h before sacrifice (DHT3h, DHT24h). An average of 19555 transcript species was examined in retroperitoneal fat. We found a total of 321 transcripts differentially modulated by DHT and OVX, including 125 novel genes. Several genes involved in energy metabolism/ATP production were up-regulated by DHT, whereas important regulators of lipid metabolism were reduced. Transcripts involved in Ca(2+) uptake/release, cell signalling, cell defence and protein expression were differentially modulated by DHT. A surprising number of myogenic genes were up-regulated, including myosin light and heavy polypeptides, troponins, as well as several actin-binding proteins. These results suggest that DHT24h may have induced a myogenic-like transcriptional program in adipocytes. The present study sheds light on the distinctive female transcriptional pattern acutely induced by androgens in intra-abdominal fat, and may add new insights into the global understanding of menopausal endocrinology and its association to intra-abdominal obesity.

Concomitant modulation of transcripts related to fiber type determination and energy metabolism in skeletal muscle of female ovariectomized mice by estradiol injection

In postmenopausal women, prevalence of metabolic syndrome (MS) is 40%. Aging is associated with a decline in basal metabolic rate and an alteration in tissue metabolism, leading to MS. Hormonal therapy has been shown to be effective against some of the MS-related features but its effects on sarcopenia and skeletal muscle metabolism remain unclear. We have analyzed the effects of estradiol (E(2)) on global gene expression in skeletal muscle of ovariectomized (OVX) female C57BL6 mice using the serial analysis of gene expression method. Animals were randomly assigned to six groups of each 14 mice: the vehicle group (OVX), and five groups in which E(2) was injected 1h, 3h, 6h, 18 h or 24h prior to sacrifice. E(2) modulated 177 transcripts, including 11 partially characterized transcripts and 52 potentially novel transcripts. Most of the differentially expressed transcripts were up-regulated at E(2)3h and E(2)18 h, while down-regulated transcripts were observed at E(2)6h and E(2)24h, illustrating two cycles of up and down E(2)-responsive genes. Modulated transcripts were involved in skeletal muscle structure/growth, fiber type distribution and energy metabolism. These results suggest that a single physiological dose of E(2) can concomitantly modulate transcripts determining skeletal muscle type and energy metabolism, which may in turn affect sarcopenia and MS.

Regulation of skeletal muscle transcriptome in elderly men after 6 weeks of endurance training at lactate threshold intensity

A compromised muscle function due to aging, sarcopenia and reduced level of physical activity can lead to metabolic complications and chronic diseases. Endurance exercise counters these diseases by inducing beneficial adaptations whose molecular mechanisms remain unclear. We have investigated the transcriptomic changes following mild-intensity endurance training in skeletal muscle of elderly men. Seven healthy subjects followed an exercise program of cycle ergometer training at lactate threshold (LT) level for 60 min/day, five times/week during six weeks. Physiological and transcriptomic changes were analyzed before and after training. LT training decreased percentage body fat and fasting levels of plasma glucose, while increasing high-density lipoprotein cholesterol and lecithin-cholesterol acyltransferase levels. Transcriptomic analysis revealed fast-to-slow fiber type transition, increased amount of mtDNA encoded transcripts and modulation of 12 transcripts notably related to extracellular matrix (ECM), oxidative phosphorylation (OXPHOS), as well as partially characterized and novel transcripts. The training simultaneously induced the expression of genes related to slow fiber type transition, OXPHOS and ECM, which might contribute to the improvement of glucose and lipid metabolisms and whole body aerobic capacity.

Comparative analysis of secreted protein evolution using expressed sequence tags from four poplar leaf rusts (Melampsora spp.)

BACKGROUND

Obligate biotrophs such as rust fungi are believed to establish long-term relationships by modulating plant defenses through a plethora of effector proteins, whose most recognizable feature is the presence of a signal peptide for secretion. Since the phenotypes of these effectors extend to host cells, their genes are expected to be under accelerated evolution stimulated by host-pathogen coevolutionary arms races. Recently, whole genome sequence data has allowed the prediction of secretomes, facilitating the identification of putative effectors.

RESULTS

We generated cDNA libraries from four poplar leaf rust pathogens (Melampsora spp.) and used computational approaches to identify and annotate putative secreted proteins with the aim of uncovering new knowledge about the nature and evolution of the rust secretome. While more than half of the predicted secretome members encoded lineage-specific proteins, similarities with experimentally characterized fungal effectors were also identified. A SAGE analysis indicated a strong stage-specific regulation of transcripts encoding secreted proteins. The average sequence identity of putative secreted proteins to their closest orthologs in the wheat stem rust Puccinia graminis f. sp. tritici was dramatically reduced compared with non-secreted ones. A comparative genomics approach based on homologous gene groups unravelled positive selection in putative members of the secretome.

CONCLUSION

We uncovered robust evidence that different evolutionary constraints are acting on the rust secretome when compared to the rest of the genome. These results are consistent with the view that these genes are more likely to exhibit an effector activity and be involved in coevolutionary arms races with host factors.

Acute molecular mechanisms responsive to feeding and meal constitution in mesenteric adipose tissue

To identify the acute effects of feeding on mesenteric fat, we have performed a transcriptomic study in the mesenteric adipose tissue after low-fat (LF) and high-fat (HF) meal ingestion. After fasting, one group of mice was killed and the others were fed ad libitum with HF or LF meal, and killed 3 h after the ingestion. Serial analysis of gene expression (SAGE) was performed, generating approximately 150,000 tags/sample. The results were confirmed using quantitative real-time PCR (qRT-PCR). Transcripts involved in lipid biosynthesis were upregulated only by LF meal, whereas intracellular lipid catabolism was repressed by feeding. Apoptotic genes were downregulated, whereas antiapoptosis and proteolysis were upregulated by feeding. The expression levels of genes coding for adiponectin and ribosomal proteins were decreased by HF meal, as well as transcripts involved in mRNA processing, cytoskeleton, and extracellular matrix. Several other fat-responsive genes were identified, including diverse uncharacterized transcripts. These results revealed that mesenteric adipose tissue transcriptome was responsive to food intake and was affected differently according to meal constitution. The identification of uncharacterized transcripts regulated by LF and HF meals is a first step toward further understanding the early mechanisms of diet-induced obesity as well as discovering new therapeutic targets for obesity-related diseases.

Feeding regulates the expression of pancreatic genes in gastric mucosa

The ineffective short-term control of feeding behavior compromises energy homeostasis and can lead to obesity. The gastrointestinal tract secretes several regulatory peptides. However, little is known about the stomach peptide contribution to the acute regulation of intake. In an attempt to identify new gastric signals, the serial analysis of gene expression (SAGE) method was used for the transcription profiling of stomach mucosa in 7 groups of mice: fasting and sacrificed 30 minutes, 1 hour, 3 hours after a low-fat (LF) or high-fat (HF) ad libitum meal. In total, 35 genes were differentially modulated by LF and HF meals compared to fasting, including 15 mRNAs coding for digestive enzymes/secretory proteins, and 10 novel transcripts. Although the basic expression profile did not undergo substantial variations, both LF and HF meals influenced the transcription. This study represents the first global analysis of stomach transcriptome as induced by different nutritional stimuli. Further studies including the characterization of novel genes may help to identify new targets for the therapy and prevention of obesity.

Feeding induced changes in the hypothalamic transcriptome

BACKGROUND

Obesity is a complex multifactorial disorder which needs a comprehensive approach for prevention and treatment. We investigated the modifications in the hypothalamic gene expression induced by high-fat (HF) and low-fat (LF) meal ingestion in mice, in order to identify the signals rapidly mediating the hypothalamic control on energy intake.

METHODS

After fasting, 1 group of mice was sacrificed and the others were fed ad libitum with HF or LF diet, and sacrificed 3 h after the beginning of the meal. The hypothalamus was sampled and the serial analysis of gene expression method was performed.

RESULTS

Approximately 254,588 tags, which correspond to 65,548 tag species were isolated from the 3 groups. The data showed twelve transcripts regulated by food intake. Among these, 2 transcripts have mitochondrial functions (MtCo1, Ppid), 3 are involved in protein transport and regulation (Ube2q2, Mup1, Sec13), 1 in cellular pH control (Slc4a3) and another 1 has a role in the epigenetic control of gene expression (Setd3). In addition, 5 potentially novel transcripts were differentially modulated.

CONCLUSION

We identified genes that may regulate hypothalamic circuits governing the early response to food intake. 3 genes were specifically modulated by high-fat intake.

Atlas of dihydrotestosterone actions on the transcriptome of prostate in vivo

BACKGROUND

Using serial analysis of gene expression (SAGE), we studied the transcriptomic changes in vivo by dihydrotestosterone (DHT) treatment in mice to better understand androgen effects in the prostate.

METHODS

Approximately 872,000 SAGE tags were isolated from intact and castrated (GDX) mice with and without DHT injection.

RESULTS

GDX significantly altered 431 transcripts, including 110 transcripts restored by DHT, and 146 potentially new transcripts. Totally, 187 transcripts were significantly affected by DHT treatment, of which 124 were induced and 63 were repressed. Interestingly and consistent with the prostate's secretory role, DHT up-regulated the expression of many genes involved in various steps of protein metabolism such as synthesis, folding, and secretion. GDX modulated the expression of genes which induce cell apoptosis and inhibit cell proliferation through polyamine biosynthesis, retinoid X receptor actions as well as several signaling pathways and some related factors. These results clarify DHT effects on prostate transcriptome in the areas of protein metabolism, cell proliferation and apoptosis. In addition, we detected gene expression changes in metabolic pathways, cytoskeleton, immunity and endoplasmic reticulum stress. Furthermore, knockdown of S-adenosylmethionine decarboxylase 1 in LNCaP cells confirmed the importance of androgen-regulated genes (ARGs) in prostate cancer cell growth.

CONCLUSION

Our data support the idea that ARGs are essential for the normal development of the prostate and can also be responsible for the pathogenesis of the prostate cancer.

Regulation of gene expression by estrogen in mammary gland of wild type and estrogen receptor alpha knockout mice

Using serial analysis of gene expression, we examined the effects of estrogen (E2) replacement in gonadectomized wild type (WT) and E2 receptor alpha knockout (ERalphaKO) mice on global gene expression in mammary gland. In WT mice, a total of 429,302 tags were sequenced, representing the expression level of 99,854 tag species. A total of ten transcripts were found to be modulated by E2, such as sorting nexin 5 and two no match tags. In the ERalphaKO mice, a total of 459,439 tags were sequenced, representing the expression level of 120,149 tag species. Interestingly, the same three transcripts were inversely regulated by E2 in ERalphaKO mice. In total, 78 transcripts were upregulated by E2, while 29 transcripts were downregulated. In contrast to WT mice, the majority of transcripts related to immunity were repressed in ERalphaKO mice. Moreover, induction of transcripts involved in cell differentiation, Ca2+ response, cytoskeleton, protein biosynthesis and secretion, glycolysis, and oxidative phosphorylation were seen only in ERalphaKO mice. The current study will provide useful information to understand the cellular mechanisms of E(2)-mediated gene regulation in tissues in vivo for the development of novel drugs targeting specific ER action in pathological conditions.

Regulation of pituitary gene expression by adrenalectomy

Excessive secretion of adrenal hormones, such as glucocorticoid and mineralocorticoid, leads to metabolic syndrome, including insulin resistance, obesity, and hypertension. These metabolic abnormalities are ameliorated by adrenalectomy (ADX). To identify pituitary mediators for ADX-induced physiological alterations, such as weight loss and hypotension, we investigated the effect of ADX on the pituitary transcriptome using serial analysis of gene expression (SAGE). SAGE method is based on isolation of short sequence tags, which usually correspond to unique mRNA species. The SAGE libraries were constructed from pituitary gland of intact (n = 51) and ADX (n = 12) mice. Thirty-one transcripts were differentially expressed between intact and ADX. Three transcripts encoding for proopiomelanocortin and three other transcripts involved in regulation of hormone secretion (neuromedin B, proprotein convertase subtilisin/kexin type 2, and IA-2) were induced by ADX. In addition, ADX increased the expression levels of genes encoding for cation extracellular matrix (matrix gamma-carboxyglutamate protein) and transport (solute carrier family 22 member 17). Conversely, ADX downregulated two transcripts involved in mitochondrial oxidative phosphorylation (nicotinamide adenine dinucleotide (NADH) dehydrogenase 3 and cytochrome c oxidase 3). Moreover, ADX significantly modulated the expression levels of one gene with uncharacterized function and 20 novel transcripts. This study reveals alterations of pituitary gene expressions that may be associated with ADX-induced physiological changes including weight loss.

High-fat meal-induced changes in the duodenum mucosa transcriptome

In order to identify the potential peripheral signals of appetite and satiety from duodenum, we have performed a transcriptomic study in the mucosa after high-fat (HF) and low-fat (LF) meal ingestion. After fasting, one group of mice was killed and the others were fed ad libitum with HF or LF diet, and killed 30 min, 1 h, and 3 h after the beginning of the meal. The duodenum mucosa was sampled, and the serial analysis of gene expression (SAGE) method was performed. The mRNA regulations were confirmed by real-time PCR. Energy, protein, and fat intakes were higher in the HF than in the LF group. Gene expression profile revealed 118 characterized or partially characterized differentially expressed transcripts. The HF meal delayed the expressions of peptidases compared to the LF groups. Most of mRNAs related to fat absorption, including apolipoprotein A-IV (Apoa4), were decreased in HF1h group, whereas plasma triglyceride (TG) levels were comparable between HF and LF groups. Noteworthy, these downregulations were concomitant to a break in fat intake 1 h after HF meal. At the same time, the HF meal induced transcripts related to cell growth and organization, whereas transcripts involved in cell defense were repressed. Moreover, we have identified fat-responsive transcripts. This study has characterized the molecular responses of duodenum mucosa after HF or LF meal ingestion. Characterization of novel fat-specific candidates whose relations with feeding behavior have never been reported may contribute to the development of new therapeutic targets for appetite and satiety controls.

Serial analysis of the vascular endothelial transcriptome under static and shear stress conditions

We have utilized serial analysis of gene expression (SAGE) to analyze the response of human coronary artery endothelial cells (HCAECs) to laminar shear stress (LSS). Primary cultures of HCAECs were exposed to 15 dyn/cm(2) LSS for 24 h in a parallel plate flow chamber and compared with identical same passage cells cultured under static conditions. The expression levels of a number of functional categories of genes were reduced by shear stress including those encoding proteins involved in cell proliferation (CDC10, CDC20, CDC23, CCND1, CCNB1), angiogenesis (ANGPTL4, CTGF, CYR61, ENG, EPAS1, EGFR, LGALS3, PGK1, and SPARC), extracellular matrix and cell-matrix adhesion (EFEMP1, LOXL2, P4HB, FBN1, FN1, ITGA5, ITGAE, ITGAV, ILK, LAMR1) and ATP synthesis (ATP5G3, ATP5J2, ATP5L, ATP5D). We also observed an increase in the LSS-responsive expression of genes encoding stress response proteins, including HMOX1, which is significant since HMOX1 may have anti-inflammatory and vasodilatory vascular effects. The autosomal dominant polycystic kidney disease (ADPKD) genes PKD1 and PKD2 were also elevated by LSS. ADPKD is associated with vascular malfunction, including the impairment of vasoreactive processes. To our knowledge, this is the first SAGE-based analysis of the shear stress-responsive endothelial cell transcriptome. These immortal data provide a resource for further analyses of the molecular mechanisms underlying the biological response to LSS and contribute to the expanding collection of publicly available SAGE data.

How the new tools to analyze the human genome are opening new perspectives: the use of gene expression in investigations of the adrenal cortex

With the promise of state-of-the-art molecular technologies and the tools provided by the human genome project, a number of investigators are trying to identify molecular targets of adrenocortical tumorigenesis. One path in this endeavor was the identification by positional cloning of genes that are mutated in rare adrenocortical tumors. The subject of this article is an update of the results of experiments in the second path that was followed by us and others: that of using genome-wide expression analysis of adrenocortical cells in normal and various disease states. Transcriptomic analysis is a rapidly evolving technology; this article summarizes some data on the adrenal cortex and points out how these new technologies can be used in the identification of important genes and molecular pathways in both normal and diseased adrenal cortex.

Prostate-specific genes and their regulation by dihydrotestosterone

BACKGROUND

Prostate is a well-known androgen-dependent tissue.

METHODS

By sequencing 4,294,186 serial analysis of gene expression (SAGE) tags, we have investigated the transcriptomes of normal mouse prostate, liver, testis, lung, brain, femur, skin, adipose tissue, skeletal muscle, vagina, ovary, mammary gland, and uterus in order to identify the most abundant and tissue-specific transcripts in the prostate, as well as to target the androgen responsive transcripts specifically regulated in the prostate. Small interference RNA (siRNA) in LNCaP cells was applied to validate the roles of prostate-specific/enriched ARGs in the growth of human prostate cancer cells.

RESULTS

The most abundant transcripts were involved in prostatic secretion, energy metabolism and immunity. Previously well-known prostate-specific transcripts, including many transcripts involved in prostatic secretion, polyamine biosynthesis and transport, and immunity were specific/enriched in the prostate. Only 22 transcripts among 114 androgen-regulated genes (ARGs) in the mouse prostate were modulated by dihydrotestosterone (DHT) in two or more tissues. The siRNA results showed that inhibition of HSPA5 and MAT2A gene expression repressed growth of human cancer LNCaP cells.

CONCLUSIONS

The current study globally assessed the transcriptome of the prostate and revealed the most abundant and tissue-specific transcripts which are responsible for the unique functions of this organ. These prostate-specific ARGs might be used as targets to develop safe and effective gene-based therapy for the prevention and treatment of prostate cancer.

Identification of cellular processes that are rapidly modulated in response to tracheal occlusion within mice lungs

Lung development progresses through a process reliant on mechanical cell stretch. However, this process is not well defined at the molecular level. Our goal was to globally analyze the transcriptome of fetal mouse lungs following short periods of tracheal occlusion (TO) to identify cellular processes that are rapidly modulated in response to intraluminal stretch increase. Serial analysis of gene expression (SAGE) was used to examine the global transcriptomic response of mouse prealveolar stage lungs to in vivo TO at 1 and 3 h. SAGE results were extended by histo- and immunochemical examination. Based on the 97 TO-modulated transcripts identified, our results further point out that continuous stretch in developing lungs leads directly to rapid and highly specific phenotypic modifications in a significant proportion of pulmonary cells. We conclude that intraluminal stretch increase during prealveolar stage of lung development induces a critical transition of pulmonary cells phenotype in which there is an increase in alpha-smooth muscle actin (alpha-SMA)-containing cells along with a relative decrease in lipid-containing cells.

SAGE and LongSAGE

Serial analysis of gene expression (SAGE) is a high-throughput method for global gene expression analysis that allows the quantitative and simultaneous analysis of a large number of transcripts. SAGE is a digital method and its sensitivity depends only on the number of tags sequenced. Furthermore, SAGE is a powerful tool for finding novel genes that are expressed under certain conditions or in certain tissues. SAGE has been widely used in fields as diverse as cancer research and the development and study of microorganisms. The SAGE method is a series of routine molecular biology procedure and can, at least in principle, be carried out in any laboratory. However, the number of consecutive steps is quite large and in practice, SAGE has been difficult to carry out on a routine basis.

Duplicate ditag analysis in LongSAGE

The Long serial analysis of gene expression (SAGE) protocol generates ditags from tags with overlapping overhangs, thereby increasing the probability of duplicate ditag formation in LongSAGE. In this chapter, a tool is presented that facilitates the analysis of duplicate ditags in LongSAGE studies to determine whether they should be included or not.

Deep analysis of cellular transcriptomes - LongSAGE versus classic MPSS

BACKGROUND

Deep transcriptome analysis will underpin a large fraction of post-genomic biology. 'Closed' technologies, such as microarray analysis, only detect the set of transcripts chosen for analysis, whereas 'open' e.g. tag-based technologies are capable of identifying all possible transcripts, including those that were previously uncharacterized. Although new technologies are now emerging, at present the major resources for open-type analysis are the many publicly available SAGE (serial analysis of gene expression) and MPSS (massively parallel signature sequencing) libraries. These technologies have never been compared for their utility in the context of deep transcriptome mining.

RESULTS

We used a single LongSAGE library of 503,431 tags and a "classic" MPSS library of 1,744,173 tags, both prepared from the same T cell-derived RNA sample, to compare the ability of each method to probe, at considerable depth, a human cellular transcriptome. We show that even though LongSAGE is more error-prone than MPSS, our LongSAGE library nevertheless generated 6.3-fold more genome-matching (and therefore likely error-free) tags than the MPSS library. An analysis of a set of 8,132 known genes detectable by both methods, and for which there is no ambiguity about tag matching, shows that MPSS detects only half (54%) the number of transcripts identified by SAGE (3,617 versus 1,955). Analysis of two additional MPSS libraries shows that each library samples a different subset of transcripts, and that in combination the three MPSS libraries (4,274,992 tags in total) still only detect 73% of the genes identified in our test set using SAGE. The fraction of transcripts detected by MPSS is likely to be even lower for uncharacterized transcripts, which tend to be more weakly expressed. The source of the loss of complexity in MPSS libraries compared to SAGE is unclear, but its effects become more severe with each sequencing cycle (i.e. as MPSS tag length increases).

CONCLUSION

We show that MPSS libraries are significantly less complex than much smaller SAGE libraries, revealing a serious bias in the generation of MPSS data unlikely to have been circumvented by later technological improvements. Our results emphasize the need for the rigorous testing of new expression profiling technologies.

Polony Multiplex Analysis of Gene Expression (PMAGE) in Mouse Hypertrophic Cardiomyopathy

We describe a sensitive mRNA profiling technology, PMAGE (for "polony multiplex analysis of gene expression"), which detects messenger RNAs (mRNAs) as rare as one transcript per three cells. PMAGE incorporates an improved ligation-based method to sequence 14-nucleotide tags derived from individual mRNA molecules. One sequence tag from each mRNA molecule is amplified onto a separate 1-micrometer bead, denoted as a polymerase colony or polony, and about 5 million polonies are arrayed in a flow cell for parallel sequencing. Using PMAGE, we identified early transcriptional changes that preceded pathological manifestations of hypertrophic cardiomyopathy in mice carrying a disease-causing mutation. PMAGE provided a comprehensive profile of cardiac mRNAs, including low-abundance mRNAs encoding signaling molecules and transcription factors that are likely to participate in disease pathogenesis.

Housekeeping and tissue-specific genes in mouse tissues

BACKGROUND

This study aims to characterize the housekeeping and tissue-specific genes in 15 mouse tissues by using the serial analysis of gene expression (SAGE) strategy which indicates the relative level of expression for each transcript matched to the tag.

RESULTS

Here, we identified constantly expressed housekeeping genes, such as eukaryotic translation elongation factor 2, which is expressed in all tissues without significant difference in expression levels. Moreover, most of these genes were not regulated by experimental conditions such as steroid hormones, adrenalectomy and gonadectomy. In addition, we report previously postulated housekeeping genes such as peptidyl-prolyl cis-trans isomerase A, glyceraldehyde-3-phosphate dehydrogenase and beta-actin, which are expressed in all the tissues, but with significant difference in their expression levels. We have also identified genes uniquely detected in each of the 15 tissues and other tissues from public databases.

CONCLUSION

These identified housekeeping genes could represent appropriate controls for RT-PCR and northern blot when comparing the expression levels of genes in several tissues. The results reveal several tissue-specific genes highly expressed in testis and pituitary gland. Furthermore, the main function of tissue-specific genes expressed in liver, lung and bone is the cell defence, whereas several keratins involved in cell structure function are exclusively detected in skin and vagina. The results from this study can be used for example to target a tissue for agent delivering by using the promoter of tissue-specific genes. Moreover, this study could be used as basis for further researches on physiology and pathology of these tissues.

Transcriptomic characterization of the long-term dihydrotestosterone effects in adipose tissue

OBJECTIVE

To study the long-term transcriptomic effects of dihydrotestosterone (DHT) in adipose tissue. Fat distribution is regulated by sexual hormones. It is still unclear if androgens are promoting or reducing intra-abdominal fat accumulation.

RESEARCH METHODS AND PROCEDURES

Retroperitoneal adipose tissue were isolated from each group of gonadectomized (GDX) C57BL6 male mice treated with vehicle or DHT for 21 days. Serial analysis of gene expression (SAGE) was performed to generate approximately 150,000 SAGE tags from each sample.

RESULTS

Among the numerous genes regulated by DHT, transcripts involved in glycolysis, such as aldolase 1 A isoform and pyruvate kinase muscle as well as lipogenic transcripts, such as malic enzyme supernatant and ELOVL family member 6 elongation of long chain fatty acids were down-regulated by androgen supplementation. In contrast, transcripts involved in lipolysis and fatty acid oxidation, such as carboxylesterase 3, acetyl-coenzyme A acyltransferase 1, 3-ketoacyl-CoA thiolase B and enoyl-coenzyme A hydratase/3-hydroxyacyl coenzyme A dehydrogenase were up-regulated by DHT. Pro-apoptotic transcripts such as cell death-inducing DFFA-like effector c, BCL2/adenovirus E1B 19 kDa-interacting protein 1 NIP3 and -interacting protein 3-like were up-regulated by DHT, whereas transcripts involved in promotion of cell cycle such as cyclin D2 were down-regulated by DHT.

DISCUSSION

These results suggest that chronic androgen treatment may help to improve metabolic profile by regulating various critical pathways involved in adipose tissue physiology. In addition, several genes associated with a healthier metabolic profile, such as adiponectin and CD36 antigen, were up-regulated by 21 days of DHT treatment.

Discarding duplicate ditags in LongSAGE analysis may introduce significant error

BACKGROUND

During 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.

RESULTS

An 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.

CONCLUSION

The 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.

The +4G site in Kozak consensus is not related to the efficiency of translation initiation

The optimal context for translation initiation in mammalian species is GCCRCCaugG (where R = purine and “aug” is the initiation codon), with the -3R and +4G being particularly important. The presence of +4G has been interpreted as necessary for efficient translation initiation. Accumulated experimental and bioinformatic evidence has suggested an alternative explanation based on amino acid constraint on the second codon, i.e., amino acid Ala or Gly are needed as the second amino acid in the nascent peptide for the cleavage of the initiator Met, and the consequent overuse of Ala and Gly codons (GCN and GGN) leads to the +4G consensus. I performed a critical test of these alternative hypotheses on +4G based on 34169 human protein-coding genes and published gene expression data. The result shows that the prevalence of +4G is not related to translation initiation. Among the five G-starting codons, only alanine codons (GCN), and glycine codons (GGN) to a much smaller extent, are overrepresented at the second codon, whereas the other three codons are not overrepresented. While highly expressed genes have more +4G than lowly expressed genes, the difference is caused by GCN and GGN codons at the second codon. These results are inconsistent with +4G being needed for efficient translation initiation, but consistent with the proposal of amino acid constraint hypothesis.

Most expressed transcripts in sexual organs and other tissues

This study characterizes the most highly expressed transcripts of 15 intact tissues in mice by using the serial analysis of gene expression (SAGE) strategy which indicates the relative level of expression for each transcript matched to the tag. We show that the most abundant transcripts in the prostate, testis, and skeletal muscle characterize the main functions of these organs as an exocrine gland of male reproduction, spermatogenesis, and contraction, respectively. In addition, the top nine most abundant transcripts in the testis are tissue-specific genes while the most abundant transcripts in the prostate are also abundantly expressed in the liver. Furthermore, the most abundant transcripts in the ovary, mammary gland, and vagina are related to steroidogenesis, adipocytes, and keratinization, respectively, whereas genes involved in the cell defence are abundantly expressed in the liver, lung, bone, mammary gland, and adipose tissue. These findings suggest that the top 10 transcripts are sufficient to characterize each tissue of the body.

Large-scale production of SAGE libraries from microdissected tissues, flow-sorted cells, and cell lines

We describe the details of a serial analysis of gene expression (SAGE) library construction and analysis platform that has enabled the generation of >298 high-quality SAGE libraries and >30 million SAGE tags primarily from sub-microgram amounts of total RNA purified from samples acquired by microdissection. Several RNA isolation methods were used to handle the diversity of samples processed, and various measures were applied to minimize ditag PCR carryover contamination. Modifications in the SAGE protocol resulted in improved cloning and DNA sequencing efficiencies. Bioinformatic measures to automatically assess DNA sequencing results were implemented to analyze the integrity of ditag structure, linker or cross-species ditag contamination, and yield of high-quality tags per sequence read. Our analysis of singleton tag errors resulted in a method for correcting such errors to statistically determine tag accuracy. From the libraries generated, we produced an essentially complete mapping of reliable 21-base-pair tags to the mouse reference genome sequence for a meta-library of approximately 5 million tags. Our analyses led us to reject the commonly held notion that duplicate ditags are artifacts. Rather than the usual practice of discarding such tags, we conclude that they should be retained to avoid introducing bias into the results and thereby maintain the quantitative nature of the data, which is a major theoretical advantage of SAGE as a tool for global transcriptional profiling.

Understanding SAGE data

Serial analysis of gene expression (SAGE) is a method for identifying and quantifying transcripts from eukaryotic genomes. Since its invention, SAGE has been widely applied to analyzing gene expression in many biological and medical studies. Vast amounts of SAGE data have been collected and more than a thousand SAGE-related studies have been published since the mid-1990s. The principle of SAGE has been developed to address specific issues such as determination of normal gene structure and identification of abnormal genome structural changes. This review focuses on the general features of SAGE data, including the specificity of SAGE tags with respect to their original transcripts, the quantitative nature of SAGE data for differentially expressed genes, the reproducibility, the comparability of SAGE with microarray and the future potential of SAGE. Understanding these basic features should aid the proper interpretation of SAGE data to address biological and medical questions.

No accelerated rate of protein evolution in male-biased Drosophila pseudoobscura genes

Sexually dimorphic traits are often subject to diversifying selection. Genes with a male-biased gene expression also are probably affected by sexual selection and have a high rate of protein evolution. We used SAGE to measure sex-biased gene expression in Drosophila pseudoobscura. Consistent with previous results from D. melanogaster, a larger number of genes were male biased (402 genes) than female biased (138 genes). About 34% of the genes changed the sex-related expression pattern between D. melanogaster and D. pseudoobscura. Combining gene expression with protein divergence between both species, we observed a striking difference in the rate of evolution for genes with a male-biased gene expression in one species only. Contrary to expectations, D. pseudoobscura genes in this category showed no accelerated rate of protein evolution, while D. melanogaster genes did. If sexual selection is driving molecular evolution of male-biased genes, our data imply a radically different selection regime in D. pseudoobscura.

Sequence biases in large scale gene expression profiling data

We present the results of a simple, statistical assay that measures the G+C content sensitivity bias of gene expression experiments without the requirement of a duplicate experiment. We analyse five gene expression profiling methods: Affymetrix GeneChip, Long Serial Analysis of Gene Expression (LongSAGE), LongSAGELite, 'Classic' Massively Parallel Signature Sequencing (MPSS) and 'Signature' MPSS. We demonstrate the methods have systematic and random errors leading to a different G+C content sensitivity. The relationship between this experimental error and the G+C content of the probe set or tag that identifies each gene influences whether the gene is detected and, if detected, the level of gene expression measured. LongSAGE has the least bias, while Signature MPSS shows a strong bias to G+C rich tags and Affymetrix data show different bias depending on the data processing method (MAS 5.0, RMA or GC-RMA). The bias in the Affymetrix data primarily impacts genes expressed at lower levels. Despite the larger sampling of the MPSS library, SAGE identifies significantly more genes (60% more RefSeq genes in a single comparison).

Reverse Serial Analysis of Gene Expression (SAGE) Characterization of Orphan SAGE Tags from Human Embryonic Stem Cells Identifies the Presence of Novel Transcripts and Antisense Transcription of Key Pluripotency Genes

Serial analysis of gene expression (SAGE) is a powerful technique for the analysis of gene expression. A significant portion of SAGE tags, designated as orphan tags, however, cannot be reliably assigned to known transcripts. We used an improved reverse SAGE (rSAGE) strategy to convert human embryonic stem cell (hESC)-specific orphan SAGE tags into longer 3' cDNAs. We show that the systematic analysis of these 3' cDNAs permitted the discovery of hESC-specific novel transcripts and cis-natural antisense transcripts (cis-NATs) and improved the assignment of SAGE tags that resulted from splice variants, insertion/deletion, and single-nucleotide polymorphisms. More importantly, this is the first description of cis-NATs for several key pluripotency markers in hESCs and mouse embryonic stem cells, suggesting that the formation of short interfering RNA could be an important regulatory mechanism. A systematic large-scale analysis of the remaining orphan SAGE tags in the hESC SAGE libraries by rSAGE or other 3' cDNA extension strategies should unravel additional novel transcripts and cis-NATs that are specifically expressed in hESCs. Besides contributing to the complete catalog of human transcripts, many of them should prove to be a valuable resource for the elucidation of the molecular pathways involved in the self-renewal and lineage commitment of hESCs.

Identification of novel genes and transcription factors involved in spleen, thymus and immunological development and function

We constructed and analyzed six serial analysis of gene expression (SAGE) libraries to identify genes with previously uncharacterized roles in spleen or thymus development. A total of 625 070 tags were sequenced from the three spleen (embryonic day (E)15.5, E16.5 and adult) and three thymus (E15.5, E18.5 and adult) libraries. These tags corresponded to 83 182 tag types, which mapped unambiguously to 36 133 different genes. Genes over-represented in these libraries, compared to 115 mouse SAGE libraries (www.mouseatlas.org), included genes of known and unknown immunological or developmental relevance. The expression profiles of 11 genes with unknown roles in spleen and thymus development were validated using reverse transcription-qPCR. We further characterized the expression of one of these candidates, RIKEN cDNA 9230105E10 that encodes a murine homolog of Trim5alpha, in numerous adult tissues and immune cell types. In addition, we demonstrate that transcript levels are upregulated in response to TLR stimulation of plasmacytoid dendritic cells and macrophages. This work provides the first evidence of regulated and cell type-specific expression of this gene. In addition, these observations suggest that the SAGE libraries provide an important resource for further investigations into the molecular mechanisms regulating spleen and thymus organogenesis, as well as the development of immunological competence.

Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals

BACKGROUND

The ability of an oocyte to develop into a viable embryo depends on the accumulation of specific maternal information and molecules, such as RNAs and proteins. A serial analysis of gene expression (SAGE) was carried out in parallel with proteomic analysis on fully-grown ovarian follicles from zebrafish (Danio rerio). The data obtained were compared with ovary/follicle/egg molecular phenotypes of other animals, published or available in public sequence databases.

RESULTS

Sequencing of 27,486 SAGE tags identified 11,399 different ones, including 3,329 tags with an occurrence superior to one. Fifty-eight genes were expressed at over 0.15% of the total population and represented 17.34% of the mRNA population identified. The three most expressed transcripts were a rhamnose-binding lectin, beta-actin 2, and a transcribed locus similar to the H2B histone family. Comparison with the large-scale expressed sequence tags sequencing approach revealed highly expressed transcripts that were not previously known to be expressed at high levels in fish ovaries, like the short-sized polarized metallothionein 2 transcript. A higher sensitivity for the detection of transcripts with a characterized maternal genetic contribution was also demonstrated compared to large-scale sequencing of cDNA libraries. Ferritin heavy polypeptide 1, heat shock protein 90-beta, lactate dehydrogenase B4, beta-actin isoforms, tubulin beta 2, ATP synthase subunit 9, together with 40 S ribosomal protein S27a, were common highly-expressed transcripts of vertebrate ovary/unfertilized egg. Comparison of transcriptome and proteome data revealed that transcript levels provide little predictive value with respect to the extent of protein abundance. All the proteins identified by proteomic analysis of fully-grown zebrafish follicles had at least one transcript counterpart, with two exceptions: eosinophil chemotactic cytokine and nothepsin.

CONCLUSION

This study provides a complete sequence data set of maternal mRNA stored in zebrafish germ cells at the end of oogenesis. This catalogue contains highly-expressed transcripts that are part of a vertebrate ovarian expressed gene signature. Comparison of transcriptome and proteome data identified downregulated transcripts or proteins potentially incorporated in the oocyte by endocytosis. The molecular phenotype described provides groundwork for future experimental approaches aimed at identifying functionally important stored maternal transcripts and proteins involved in oogenesis and early stages of embryo development.

SAGE reveals expression of Wnt signalling pathway members during mouse prostate development

To identify genes and pathways not previously implicated in the mesenchymal-epithelial (M/E) interactions that are critical for normal mouse prostate development, we constructed six serial analysis of gene expression (SAGE) libraries. Bioinformatic analyses revealed expression of various members of numerous signalling pathways and the differential expression of several members of the wingless-related MMTV integration site (Wnt) signalling pathway. This pathway has not been previously implicated in prostate development thus expression of selected Wnt pathway members in the developing prostate was confirmed by RT-qPCR. Of particular interest, an antagonist of the Wnt pathway, secreted frizzled related protein 2 (Sfrp2), was highly expressed in the early prostate libraries and down regulated at later developmental stages. The expression levels of four Wnt ligands reported to interact with Sfrp2 were, therefore, examined by RT-qPCR. We found that only Wnt4 transcripts were detectable in the developing prostate. Expression of Sfrp2 was validated using RT-qPCR and localization of Sfrp2 transcripts and protein was carried out using in situ hybridization and immunofluorescence, respectively. These studies provide the first evidence that Wnt pathway members are expressed in the developing prostate. Functional analyses are now required to establish the biological significance of this observation.

Regulation of hypothalamic gene expression by glucocorticoid: implications for energy homeostasis

The present study investigated the hypothalamic gene expressions regulated by glucocorticoids (GC), key hormones in energy homeostasis. Using the serial analysis of gene expression (SAGE) method, we studied the effects of adrenalectomy (ADX) and GC on the transcriptomes of mouse hypothalamus. Approximately 180,000 SAGE tags, which correspond to 50,000 tag species, were isolated from each group of intact or adrenalectomized mice as well as 1, 3, and 24 h after GC injection. ADX upregulated diazepam binding inhibitor gene expression while downregulating vomeronasal 1 receptor D4, genes involved in mitochondrial phosphorylation (cytochrome-c oxidase 1 and NADH dehydrogenase 3), 3beta-hydroxysteroid dehydrogenase-1, and prostaglandin D2 synthase. GC increased the gene expression levels of dehydrogenase/reductase member 3, prostaglandin D2 synthase, solute carrier family 4 member 4, and five cytoskeletal proteins including myosin light chain phosphorylatable fast and troponin C2 fast. On the other hand, GC reduced the mRNA levels of calmodulin 1 and expressed sequence tag similar to calmodulin 2, ATP synthase F0 subunit 6, and solute carrier family 4 member 3. Moreover, 7 uncharacterized and 43 novel transcripts were modulated by ADX and GC. The present study has identified genes that may regulate hypothalamic systems governing energy balance in response to ADX and GC.

Sexually dimorphic gene expression in the hypothalamus, pituitary gland, and cortex

We examined sex differences in the transcriptomes of hypothalamus, pituitary gland, and cortex of male and female mice using serial analysis of gene expression. In total 940,669 tags were sequenced. In hypothalamus, 3 transcripts are differentially expressed by gender, including growth hormone (neuromodulation) and 3beta-hydroxysteroid dehydrogenase-1 (steroidogenesis). In pituitary gland, 43 transcripts are differentially expressed, including RAS guanyl-releasing protein 2 (cell signaling), ornithine transporter (mitochondrial transport), H3 histone family 3B (chromatin structure), heterogeneous nuclear ribonucleoprotein U (chromatin remodeling), NADH dehydrogenase (mitochondrial oxidative phosphorylation), neuronatin (cell differentiation), and ribosomal protein S27a (protein metabolism). EST X (inactive)-specific transcript antisense is expressed at a higher level in the three female organs, whereas growth hormone and NADH dehydrogenase are expressed at higher levels in female cortex. Thus, the current study has characterized key sexual dimorphisms in the transcriptomes of the hypothalamus, pituitary, and cortex.

Characterization of the global profile of genes expressed in cervical epithelium by Serial Analysis of Gene Expression (SAGE)

BACKGROUND

Serial Analysis of Gene Expression (SAGE) is a new technique that allows a detailed and profound quantitative and qualitative knowledge of gene expression profile, without previous knowledge of sequence of analyzed genes. We carried out a modification of SAGE methodology (microSAGE), useful for the analysis of limited quantities of tissue samples, on normal human cervical tissue obtained from a donor without histopathological lesions. Cervical epithelium is constituted mainly by cervical keratinocytes which are the targets of human papilloma virus (HPV), where persistent HPV infection of cervical epithelium is associated with an increase risk for developing cervical carcinomas (CC).

RESULTS

We report here a transcriptome analysis of cervical tissue by SAGE, derived from 30,418 sequenced tags that provide a wealth of information about the gene products involved in normal cervical epithelium physiology, as well as genes not previously found in uterine cervix tissue involved in the process of epidermal differentiation.

CONCLUSION

This first comprehensive and profound analysis of uterine cervix transcriptome, should be useful for the identification of genes involved in normal cervix uterine function, and candidate genes associated with cervical carcinoma.

Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips

Background

Serial Analysis of Gene Expression (SAGE) and microarrays have found awidespread application, but much ambiguity exists regarding the evaluation of these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce the need for duplicate experiments and facilitate a more extensive exchange of data within the research community. This requires a measure for the correspondence of the different gene expression platforms. To date, a number of cross-platform evaluations (including a few studies using SAGE and Affymetrix GeneChips) have been conducted showing a variable, but overall low, concordance. This study evaluates these overall measures and introduces the between-ratio difference as a concordance measure pergene.

Results

In this study, gene expression measurements of Unigene clusters represented by both Affymetrix GeneChips HG-U133A and SAGE were compared using two independent RNA samples. After matching of the data sets the final comparison contains a small data set of 1094 unique Unigene clusters, which is unbiased with respect to expression level. Different overall correlation approaches, like Up/Down classification, contingency tables and correlation coefficients were used to compare both platforms. In addition, we introduce a novel approach to compare two platforms based on the calculation of differences between expression ratios observed in each platform for each individual transcript. This approach results in a concordance measure per gene (with statistical probability value), as opposed to the commonly used overall concordance measures between platforms.

Conclusion

We can conclude that intra-platform correlations are generally good, but that overall agreement between the two platforms is modest. This might be due to the binomially distributed sampling variation in SAGE tag counts, SAGE annotation errors and the intensity variation between probe sets of a single gene in Affymetrix GeneChips. We cannot identify or advice which platform performs better since both have their (dis)-advantages. Therefore it is strongly recommended to perform follow-up studies of interesting genes using additional techniques. The newly introduced between-ratio difference is a filtering-independent measure for between-platform concordance. Moreover, the between-ratio difference per gene can be used to detect transcripts with similar regulation on both platforms.