SuperSAGE array: the direct use of 26-base-pair transcript tags in oligonucleotide arrays

Age-related dysfunction of the autophago-lysosomal pathway in human endothelial cells

Senescent cells, which are cells in a post-proliferative state, show an increased number of dysfunctional mitochondria and oxidatively damaged and aggregated proteins. The mitochondrial-lysosomal axis theory of aging proposes that the autophago-lysosomal system is unable to cope with the rising amount of damaged organelles and proteins. We used human umbilical vein endothelial cells (HUVEC) as in vitro model system to determine which part/s of the autophago-lysosomal pathway become deficient by aging. Senescent HUVEC contained a much larger population of autophagosomes and lysosomes compared to young cells. Transcriptome analysis comparing young and old cells demonstrated several age-related changes of autophagy gene expression. One reason for the observed increase of autophagosomes was an impairment of the autophagic flux in senescent cells due to reduced V-ATPase activity required for acidification of the lysosomes and thus functionality of lysosomal hydrolases. The hypothesis that reduced mitochondrial ATP production underlies low V-ATPase activity was supported by addition of exogenous ATP. This procedure rescued the lysosomal acidification and restored the autophagic flux. Thus, we propose impaired lysosomal acidification due to ATP shortage which may result from mitochondrial dysfunction as a mechanism underlying the accumulation of dysfunctional cellular constituents during aging.

The Boechera Genus as a Resource for Apomixis Research

The genera Boechera (A. Löve et D. Löve) and Arabidopsis, the latter containing the model plant Arabidopsis thaliana, belong to the same clade within the Brassicaceae family. Boechera is the only among the more than 370 genera in the Brassicaceae where apomixis is well documented. Apomixis refers to the asexual reproduction through seed, and a better understanding of the underlying mechanisms has great potential for applications in agriculture. The Boechera genus currently includes 110 species (of which 38 are reported to be triploid and thus apomictic), which are distributed mostly in the North America. The apomictic lineages of Boechera occur at both the diploid and triploid level and show signs of a hybridogenic origin, resulting in a modification of their chromosome structure, as reflected by alloploidy, aneuploidy, substitutions of homeologous chromosomes, and the presence of aberrant chromosomes. In this review, we discuss the advantages of the Boechera genus to study apomixis, consider its modes of reproduction as well as the inheritance and possible mechanisms controlling apomixis. We also consider population genetic aspects and a possible role of hybridization at the origin of apomixis in Boechera. The molecular tools available to study Boechera, such as transformation techniques, laser capture microdissection, analysis of transcriptomes etc. are also discussed. We survey available genome assemblies of Boechera spp. and point out the challenges to assemble the highly heterozygous genomes of apomictic species. Due to these challenges, we argue for the application of an alternative reference-free method for the comparative analysis of such genomes, provide an overview of genomic sequencing data in the genus Boechera suitable for such analysis, and provide examples of its application.

SuperSAGE as an analytical tool for host and viral gene expression

SuperSAGE is a tag-based transcript profiling method, which allows to analyze the expression of thousands of genes at a time. In SuperSAGE, 26 bp tags are extracted from cDNA using the type III restriction enzyme, EcoP15I. In SuperSAGE, the amount of transcripts was represented by tag counts. Taking advantage of uniqueness of the 26 bp tags, host and virus transcripts can be monitored in virus-infected cells. Combining next generation sequencing technology, we established High-throughput SuperSAGE (Ht-SuperSAGE), which allows the analysis of multiple samples with reduced time and cost. In this chapter, we present the protocol of Ht-SuperSAGE involving a recently available benchtop type next generation sequencer.

Molecular characterization of the CRa gene conferring clubroot resistance in Brassica rapa

Clubroot disease is one of the major diseases affecting Brassicaceae crops, and a number of these crops grown commercially, such as Chinese cabbage (Brassica rapa L. ssp. pekinensis), are known to be highly susceptible to clubroot disease. To provide protection from this disease, plant breeders have introduced genes for resistance to clubroot from the European turnip into susceptible lines. The CRa gene confers specific resistance to the clubroot pathogen Plasmodiophora brassicae isolate M85. Fine mapping of the CRa locus using synteny to the Arabidopsis thaliana genome and partial genome sequences of B. rapa revealed a candidate gene encoding a TIR-NBS-LRR protein. Several structural differences in this candidate gene were found between susceptible and resistant lines, and CRa expression was observed only in the resistant line. Four mutant lines lacking clubroot resistance were obtained by the UV irradiation of pollen from a resistant line, and all of these mutant lines carried independent mutations in the candidate TIR-NBS-LRR gene. This genetic and molecular evidence strongly suggests that the identified gene is CRa. This is the first report on the molecular characterization of a clubroot Resistance gene in Brassicaceae and of the disease resistance gene in B. rapa.

New insights in the sugarcane transcriptome responding to drought stress as revealed by superSAGE

In the scope of the present work, four SuperSAGE libraries have been generated, using bulked root tissues from four drought-tolerant accessions as compared with four bulked sensitive genotypes, aiming to generate a panel of differentially expressed stress-responsive genes. Both groups were submitted to 24 hours of water deficit stress. The SuperSAGE libraries produced 8,787,315 tags (26 bp) that, after exclusion of singlets, allowed the identification of 205,975 unitags. Most relevant BlastN matches comprised 567,420 tags, regarding 75,404 unitags with 164,860 different ESTs. To optimize the annotation efficiency, the Gene Ontology (GO) categorization was carried out for 186,191 ESTs (BlastN against Uniprot-SwissProt), permitting the categorization of 118,208 ESTs (63.5%). In an attempt to elect a group of the best tags to be validated by RTqPCR, the GO categorization of the tag-related ESTs allowed the in silico identification of 213 upregulated unitags responding basically to abiotic stresses, from which 145 presented no hits after BlastN analysis, probably concerning new genes still uncovered in previous studies. The present report analyzes the sugarcane transcriptome under drought stress, using a combination of high-throughput transcriptome profiling by SuperSAGE with the Solexa sequencing technology, allowing the identification of potential target genes during the stress response.

The salt-responsive transcriptome of chickpea roots and nodules via deepSuperSAGE

BACKGROUND

The combination of high-throughput transcript profiling and next-generation sequencing technologies is a prerequisite for genome-wide comprehensive transcriptome analysis. Our recent innovation of deepSuperSAGE is based on an advanced SuperSAGE protocol and its combination with massively parallel pyrosequencing on Roche's 454 sequencing platform. As a demonstration of the power of this combination, we have chosen the salt stress transcriptomes of roots and nodules of the third most important legume crop chickpea (Cicer arietinum L.). While our report is more technology-oriented, it nevertheless addresses a major world-wide problem for crops generally: high salinity. Together with low temperatures and water stress, high salinity is responsible for crop losses of millions of tons of various legume (and other) crops. Continuously deteriorating environmental conditions will combine with salinity stress to further compromise crop yields. As a good example for such stress-exposed crop plants, we started to characterize salt stress responses of chickpeas on the transcriptome level.

RESULTS

We used deepSuperSAGE to detect early global transcriptome changes in salt-stressed chickpea. The salt stress responses of 86,919 transcripts representing 17,918 unique 26 bp deepSuperSAGE tags (UniTags) from roots of the salt-tolerant variety INRAT-93 two hours after treatment with 25 mM NaCl were characterized. Additionally, the expression of 57,281 transcripts representing 13,115 UniTags was monitored in nodules of the same plants. From a total of 144,200 analyzed 26 bp tags in roots and nodules together, 21,401 unique transcripts were identified. Of these, only 363 and 106 specific transcripts, respectively, were commonly up- or down-regulated (>3.0-fold) under salt stress in both organs, witnessing a differential organ-specific response to stress.Profiting from recent pioneer works on massive cDNA sequencing in chickpea, more than 9,400 UniTags were able to be linked to UniProt entries. Additionally, gene ontology (GO) categories over-representation analysis enabled to filter out enriched biological processes among the differentially expressed UniTags. Subsequently, the gathered information was further cross-checked with stress-related pathways. From several filtered pathways, here we focus exemplarily on transcripts associated with the generation and scavenging of reactive oxygen species (ROS), as well as on transcripts involved in Na+ homeostasis. Although both processes are already very well characterized in other plants, the information generated in the present work is of high value. Information on expression profiles and sequence similarity for several hundreds of transcripts of potential interest is now available.

CONCLUSIONS

This report demonstrates, that the combination of the high-throughput transcriptome profiling technology SuperSAGE with one of the next-generation sequencing platforms allows deep insights into the first molecular reactions of a plant exposed to salinity. Cross validation with recent reports enriched the information about the salt stress dynamics of more than 9,000 chickpea ESTs, and enlarged their pool of alternative transcripts isoforms. As an example for the high resolution of the employed technology that we coin deepSuperSAGE, we demonstrate that ROS-scavenging and -generating pathways undergo strong global transcriptome changes in chickpea roots and nodules already 2 hours after onset of moderate salt stress (25 mM NaCl). Additionally, a set of more than 15 candidate transcripts are proposed to be potential components of the salt overly sensitive (SOS) pathway in chickpea. Newly identified transcript isoforms are potential targets for breeding novel cultivars with high salinity tolerance. We demonstrate that these targets can be integrated into breeding schemes by micro-arrays and RT-PCR assays downstream of the generation of 26 bp tags by SuperSAGE.

Gene Expression Profiling via Multigene Concatemers

We established a novel method, Gene Expression Profiling via Multigene Concatemers (MgC-GEP), to study multigene expression patterns simultaneously. This method consists of the following steps: (1) cDNA was obtained using specific reverse primers containing an adaptor. (2) During the initial 1-3 cycles of polymerase chain reaction (PCR), the products containing universal adaptors with digestion sites at both termini were amplified using specific forward and reverse primers containing the adaptors. (3) In the subsequent 4-28 cycles, the universal adaptors were used as primers to yield products. (4) The products were digested and ligated to produce concatemers. (5) The concatemers were cloned into the vector and sequenced. Then, the occurrence of each gene tag was determined. To validate MgC-GEP, we analyzed 20 genes in Saccharomyces cerevisiae induced by weak acid using MgC-GEP combined with real-time reverse transcription (RT)-PCR. Compared with the results of real-time RT-PCR and the previous reports of microarray analysis, MgC-GEP can precisely determine the transcript levels of multigenes simultaneously. Importantly, MgC-GEP is a cost effective strategy that can be widely used in most laboratories without specific equipment. MgC-GEP is a potentially powerful tool for multigene expression profiling, particularly for moderate-throughput analysis.

The role of gene expression in ecological speciation

Ecological speciation is the process by which barriers to gene flow between populations evolve due to adaptive divergence via natural selection. A relatively unexplored area in ecological speciation is the role of gene expression. Gene expression may be associated with ecologically important phenotypes not evident from morphology and play a role during colonization of new environments. Here we review two potential roles of gene expression in ecological speciation: (1) its indirect role in facilitating population persistence and (2) its direct role in contributing to genetically based reproductive isolation. We find indirect evidence that gene expression facilitates population persistence, but direct tests are lacking. We also find clear examples of gene expression having effects on phenotypic traits and adaptive genetic divergence, but links to the evolution of reproductive isolation itself remain indirect. Gene expression during adaptive divergence seems to often involve complex genetic architectures controlled by gene networks, regulatory regions, and “eQTL hotspots.” Nonetheless, we review how approaches for isolating the functional mutations contributing to adaptive divergence are proving to be successful. The study of gene expression has promise for increasing our understanding ecological speciation, particularly when integrative approaches are applied.

Ecological genetics and genomics of plant defenses: Evidence and approaches

Herbivores exert significant selection on plants, and plants have evolved a variety of constitutive and inducible defenses to resist and tolerate herbivory. Assessing the genetic mechanisms that influence defenses against herbivores will deepen our understanding of the evolution of essential phenotypic traits.Ecogenomics is a powerful interdisciplinary approach that can address fundamental questions about the ecology and evolutionary biology of species, such as: which evolutionary forces maintain variation within a population? and What is the genetic architecture of adaptation? This field seeks to identify gene regions that influence ecologically-important traits, assess the fitness consequences under natural conditions of alleles at key quantitative trait loci (QTLs), and test how the abiotic and biotic environment affects gene expression.Here, we review ecogenomics techniques and emphasize how this framework can address long-standing and emerging questions relating to anti-herbivore defenses in plants. For example, ecogenomics tools can be used to investigate: inducible vs. constitutive defenses; tradeoffs between resistance and tolerance; adaptation to the local herbivore community; selection on alleles that confer resistance and tolerance in natural populations; and whether different genes are activated in response to specialist vs. generalist herbivores and to different types of damage.Ecogenomic studies can be conducted with model species, such as Arabidopsis, or their relatives, in which case myriad molecular tools are already available. Burgeoning sequence data will also facilitate ecogenomic studies of non-model species. Throughout this paper, we highlight approaches that are particularly suitable for ecological studies of non-model organisms, discuss the benefits and disadvantages of specific techniques, and review bioinformatic tools for analyzing data.We focus on established and promising techniques, such as QTL mapping with pedigreed populations, genome wide association studies, transcription profiling strategies, population genomics, and transgenic methodologies. Many of these techniques are complementary and can be used jointly to investigate the genetic architecture of defense traits and selection on alleles in nature.

Apomictic and sexual ovules of Boechera display heterochronic global gene expression patterns

We have compared the transcriptomic profiles of microdissected live ovules at four developmental stages between a diploid sexual and diploid apomictic Boechera. We sequenced >2 million SuperSAGE tags and identified (1) heterochronic tags (n = 595) that demonstrated significantly different patterns of expression between sexual and apomictic ovules across all developmental stages, (2) stage-specific tags (n = 577) that were found in a single developmental stage and differentially expressed between the sexual and apomictic ovules, and (3) sex-specific (n = 237) and apomixis-specific (n = 1106) tags that were found in all four developmental stages but in only one reproductive mode. Most heterochronic and stage-specific tags were significantly downregulated during early apomictic ovule development, and 110 were associated with reproduction. By contrast, most late stage-specific tags were upregulated in the apomictic ovules, likely the result of increased gene copy number in apomictic (hexaploid) versus sexual (triploid) endosperm or of parthenogenesis. Finally, we show that apomixis-specific gene expression is characterized by a significant overrepresentation of transcription factor activity. We hypothesize that apomeiosis is associated with global downregulation at the megaspore mother cell stage. As the diploid apomict analyzed here is an ancient hybrid, these data are consistent with the postulated link between hybridization and asexuality and provide a hypothesis for multiple evolutionary origins of apomixis in the genus Boechera.

Decreased expression of Drp1 and Fis1 mediates mitochondrial elongation in senescent cells and enhances resistance to oxidative stress through PINK1

Mitochondria display different morphologies, depending on cell type and physiological situation. In many senescent cell types, an extensive elongation of mitochondria occurs, implying that the increase of mitochondrial length in senescence could have a functional role. To test this hypothesis, human endothelial cells (HUVECs) were aged in vitro. Young HUVECs had tubular mitochondria, whereas senescent cells were characterized by long interconnected mitochondria. The change in mitochondrial morphology was caused by downregulation of the expression of Fis1 and Drp1, two proteins regulating mitochondrial fission. Targeted photodamage of mitochondria induced the formation of reactive oxygen species (ROS), which triggered mitochondrial fragmentation and loss of membrane potential in young cells, whereas senescent cells proved to be resistant. Alterations of the Fis1 and Drp1 expression levels also influenced the expression of the putative serine-threonine kinase PINK1, which is associated with the PARK6 variant of Parkinson's disease. Downregulation of PINK1 or overexpression of a PINK1 mutant (G309D) increased the sensitivity against ROS in young cells. These results indicate that there is a Drp1- and Fis1-induced, and PINK1-mediated protection mechanism in senescent cells, which, when compromised, could contribute to the age-related progression of Parkinson's disease and arteriosclerosis.

Bias correction and Bayesian analysis of aggregate counts in SAGE libraries

Background

Tag-based techniques, such as SAGE, are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation process may allow for multiple tags to be generated from a given mRNA transcript. The probability of forming a tag varies with its relative location. As a result, the observed tag counts represent a biased sample of the actual transcript pool. In SAGE this bias can be avoided by ignoring all but the 3' most tag but will discard a large fraction of the observed data. Taking this bias into account should allow more of the available data to be used leading to increased statistical power.

Results

Three new hierarchical models, which directly embed a model for the variation in tag formation probability, are proposed and their associated Bayesian inference algorithms are developed. These models may be applied to libraries at both the tag and aggregate level. Simulation experiments and analysis of real data are used to contrast the accuracy of the various methods. The consequences of tag formation bias are discussed in the context of testing differential expression. A description is given as to how these algorithms can be applied in that context.

Conclusions

Several Bayesian inference algorithms that account for tag formation effects are compared with the DPB algorithm providing clear evidence of superior performance. The accuracy of inferences when using a particular non-informative prior is found to depend on the expression level of a given gene. The multivariate nature of the approach easily allows both univariate and joint tests of differential expression. Calculations demonstrate the potential for false positive and negative findings due to variation in tag formation probabilities across samples when testing for differential expression.

Molecular signatures of apomictic and sexual ovules in the Boechera holboellii complex

Apomixis, a natural form of asexual seed production in plants, has evolved independently in various taxa, and represents an important potential technology for agriculture. The switch to apomixis is based on de-regulation of developmental pathways originally leading to sexual seed formation. Hybridization and polyploidy, both typical characteristics of asexual plants and animals, are mechanisms that could trigger de-regulation. Here we show that up-regulation of alleles in apomeiotic ovules is mediated by genomic duplication, heterochrony and the residual effects of ancient hybridization in diploid apomicts of the Boechera holboellii complex. Using SuperSAGE, we have identified over 4000 differentially expressed mRNA tags between micro-dissected ovules from two diploid sexual (Boechera stricta and B. holboellii) and two diploid apomictic (Boechera divaricarpa) accessions. Pairwise sequence comparisons between tags enabled identification of allelic variants of the same loci. Up-regulated candidate apomeiosis alleles consistently have more than three related alleles, thus demonstrating transcription from duplicated loci. A further 543 alleles were heterochronically expressed between sexual and apomeiotic ovules at developmental stages 2-II to 2-IV. Intriguingly, 69 B. holboellii specific alleles were preferentially up-regulated in apomeiotic ovules, thus showing a remnant'parent of origin' effect stemming from the Pleistocene origin of the hybrid B. divaricarpa from taxa related to B. holboellii and B. stricta. These data implicate polyploid gene dosage in the expression of asexual seed formation, and support hypotheses of de-regulation of the sexual pathway. The observed 'parent of origin' effect suggests that the genomic memory of hybridization has somehow been maintained after hundreds, if not thousands, of asexual generations.

Unravelling the interaction of human cytomegalovirus with dendritic cells by using SuperSAGE

Human cytomegalovirus (HCMV) is a ubiquitous pathogen with a predilection for dendritic cells (DCs). Latently infected myeloid progenitor cells develop into actively infected DCs with impaired functionality, allowing dissemination and transfer of virus throughout the body. However, the viral genes expressed in DCs and their effect on the cellular transcriptome are currently unknown. We investigated human DCs infected with HCMV by using SuperSAGE, allowing us to analyse the transcriptomes of both host and pathogen simultaneously. A small number of viral transcripts were expressed strongly and rapidly post-infection. However, only two were of the immediate-early class, including one with an unknown function. The viral genes expressed reflected the cellular milieu, with the majority having a known or suspected immune-evasion function. Several viral genes identified lack a known function and may fulfil specialized roles within DCs. The cellular response to infection included a strong interferon response, induction of cytokine and anti-apoptotic genes and alterations in genes involved in antigen presentation. We demonstrated the validity of our approach by showing that novel changes first seen in the transcriptome were reflected in the phenotype of HCMV-infected DCs. Delineation of the transcriptional changes underlying the phenotype of HCMV-infected DCs allows a better understanding of how a herpesvirus infects DCs and pinpoints linkages between phenotype and specific viral genes.

SuperSAGE: the drought stress-responsive transcriptome of chickpea roots

BACKGROUND

Drought is the major constraint to increase yield in chickpea (Cicer arietinum). Improving drought tolerance is therefore of outmost importance for breeding. However, the complexity of the trait allowed only marginal progress. A solution to the current stagnation is expected from innovative molecular tools such as transcriptome analyses providing insight into stress-related gene activity, which combined with molecular markers and expression (e)QTL mapping, may accelerate knowledge-based breeding. SuperSAGE, an improved version of the serial analysis of gene expression (SAGE) technique, generating genome-wide, high-quality transcription profiles from any eukaryote, has been employed in the present study. The method produces 26 bp long fragments (26 bp tags) from defined positions in cDNAs, providing sufficient sequence information to unambiguously characterize the mRNAs. Further, SuperSAGE tags may be immediately used to produce microarrays and probes for real-time-PCR, thereby overcoming the lack of genomic tools in non-model organisms.

RESULTS

We applied SuperSAGE to the analysis of gene expression in chickpea roots in response to drought. To this end, we sequenced 80,238 26 bp tags representing 17,493 unique transcripts (UniTags) from drought-stressed and non-stressed control roots. A total of 7,532 (43%) UniTags were more than 2.7-fold differentially expressed, and 880 (5.0%) were regulated more than 8-fold upon stress. Their large size enabled the unambiguous annotation of 3,858 (22%) UniTags to genes or proteins in public data bases and thus to stress-response processes. We designed a microarray carrying 3,000 of these 26 bp tags. The chip data confirmed 79% of the tag-based results, whereas RT-PCR confirmed the SuperSAGE data in all cases.

CONCLUSION

This study represents the most comprehensive analysis of the drought-response transcriptome of chickpea available to date. It demonstrates that--inter alias--signal transduction, transcription regulation, osmolyte accumulation, and ROS scavenging undergo strong transcriptional remodelling in chickpea roots already 6 h after drought stress. Certain transcript isoforms characterizing these processes are potential targets for breeding for drought tolerance. We demonstrate that these can be easily accessed by micro-arrays and RT-PCR assays readily produced downstream of SuperSAGE. Our study proves that SuperSAGE owns potential for molecular breeding also in non-model crops.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient

Background

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data.

Results

In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns.

Conclusion

This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Functional genomics in a non-model crop: transcriptomics or proteomics?

There is no question that protein- and RNA-based measurements are complementary, but which approach has the highest return in the case of a non-model crop and what is the correlation between mRNA and proteins? We describe and evaluate in detail the advantages and pitfalls of both a proteomics and a transcriptomics approach. The information on the abundance of transcripts was obtained by serial analysis of gene expression (SAGE), while information on the abundance of proteins was obtained via two-dimensional gel electrophoresis.

High throughput ‘omics’ approaches to assess the effects of phytochemicals in human health studies

Human health is affected by many factors. Diet and inherited genes play an important role. Food constituents, including secondary metabolites of fruits and vegetables, may interact directly with DNA via methylation and changes in expression profiles (mRNA, proteins) which results in metabolite content changes. Many studies have shown that food constituents may affect human health and the exact knowledge of genotypes and food constituent interactions with both genes and proteins may delay or prevent the onset of diseases. Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research, namely in the field of genomics and transcriptomics, exist. Studies on epigenetics and RNome significance have been launched. Proteomics and metabolomics need to encompass large numbers of experiments and linked data. Due to the nature of the proteins, as well as due to the properties of various metabolites, experimental approaches require the use of comprehensive high throughput methods and a sufficiency of analysed tissue or body fluids. In this contribution, we describe the basic tools currently used in nutrigenomics studies and indicate the general requirements for future technology methodological routings.

Use of short representative sequences for structural and functional genomic studies

Existing approaches to direct genomic studies are costly and time-consuming. To overcome these problems, a series of tag-based methods utilizing short fragments uniquely representing full-length transcripts/genes from which they originate has been developed. This review summarizes basic principles underlying these methods and their numerous modifications designed for studying transcriptome profiles, searching for unidentified expressed loci, characterization of promoter regions, and high-throughput mapping of various genomic sites, such as hypo- and hypermethylated CpGs, and chromatin-binding and DNase I cleavage sites.

SAGE tag based cDNA microarray analysis during larval to pupal development and isolation of novel cDNAs in Bombyx mori

Many genes act together during the complex process of insect larval and pupal development. 20-hydroxyecdysone interacts with juvenile hormone to control insect growth and development and then activates several transcription factors, i.e., Broad, E74, and E75, and, subsequently, the late target genes. To investigate this phenomenon, we used serial analysis of gene expression (SAGE) tag-based cDNA microarray analysis to monitor the global gene expression profile during larval development and larva-pupa metamorphosis of the silkworm Bombyx mori. Of the 330 clones that were dotted to the chip, 267 were obtained by generating longer cDNA fragments from SAGE tags for gene identification, and the others were obtained from SAGE tag-matched genes or expressed sequence tags from public databases. According to the gene expression profile, the genes were classified into 12 clusters using a self-organizing map analysis. The results were partially confirmed using real-time reverse transcription-polymerase chain reaction. We obtained 22 full-length cDNAs using rapid amplification of 5' cDNA ends, of which eight genes were novel in the silkworm. Our results indicated that use of a cDNA microarray based on SAGE tags is effective for identifying and examining some low-expression genes associated with insect development.

Global identification and characterization of transcriptionally active regions in the rice genome

Genome tiling microarray studies have consistently documented rich transcriptional activity beyond the annotated genes. However, systematic characterization and transcriptional profiling of the putative novel transcripts on the genome scale are still lacking. We report here the identification of 25,352 and 27,744 transcriptionally active regions (TARs) not encoded by annotated exons in the rice (Oryza. sativa) subspecies japonica and indica, respectively. The non-exonic TARs account for approximately two thirds of the total TARs detected by tiling arrays and represent transcripts likely conserved between japonica and indica. Transcription of 21,018 (83%) japonica non-exonic TARs was verified through expression profiling in 10 tissue types using a re-array in which annotated genes and TARs were each represented by five independent probes. Subsequent analyses indicate that about 80% of the japonica TARs that were not assigned to annotated exons can be assigned to various putatively functional or structural elements of the rice genome, including splice variants, uncharacterized portions of incompletely annotated genes, antisense transcripts, duplicated gene fragments, and potential non-coding RNAs. These results provide a systematic characterization of non-exonic transcripts in rice and thus expand the current view of the complexity and dynamics of the rice transcriptome.

Cell type-specific gene expression profiling in plants by using a combination of laser microdissection and high-throughput technologies

Laser microdissection (LM) allows for the isolation of specific cells of interest from heterogeneous tissues under direct microscopic visualization with the assistance of a laser beam. By permitting global analyses of gene expression and metabolites in the selected cells, it is a powerful tool for understanding the biological processes in individual cell types during development or in response to various stimuli. Recently, LM technology has been successfully applied to the separation of individual plant cell types. Here, we provide an overview of applications of LM combined with high-throughput technologies including transcript analyses [microarrays, serial analysis of gene expression (SAGE) and 454-sequencing], proteomic analyses and metabolomic profiling, for cell type-specific gene expression analyses in plants.

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.