SuperSAGE combined with PCR walking allows global gene expression profiling of banana (Musa acuminata), a non-model organism

Light dependent protochlorophyllide oxidoreductase: a succinct look

Reducing protochlorophyllide (Pchlide) to chlorophyllide (Chlide) is a major regulatory step in the chlorophyll biosynthesis pathway. This reaction is catalyzed by light-dependent protochlorophyllide oxidoreductase (LPOR) in oxygenic phototrophs, particularly angiosperms. LPOR-NADPH and Pchlide form a ternary complex to be efficiently photo-transformed to synthesize Chlide and, subsequently, chlorophyll during the transition from skotomorphogenesis to photomorphogenesis. Besides lipids, carotenoids and poly-cis xanthophylls influence the formation of the photoactive LPOR complexes and the PLBs. The crystal structure of LPOR reveals evolutionarily conserved cysteine residues implicated in the Pchlide binding and catalysis around the active site. Different isoforms of LPOR viz PORA, PORB, and PORC expressed at different stages of chloroplast development play a photoprotective role by quickly transforming the photosensitive Pchlide to Chlide. Non-photo-transformed Pchlide acts as a photosensitizer to generate singlet oxygen that causes oxidative stress and cell death. Therefore, different isoforms of LPOR have evolved and differentially expressed during plant development to protect plants from photodamage and thus play a pivotal role during photomorphogenesis. This review brings out the salient features of LPOR structure, structure-function relationships, and ultra-fast photo transformation of Pchlide to Chlide by oligomeric and polymeric forms of LPOR.

Genotype-dependent regulation of drought-responsive genes in tolerant and sensitive sugarcane cultivars

Drought is the most damaging among the major abiotic stresses. Transcriptomic studies allow a global overview of expressed genes, providing the basis for molecular markers development. Here, the HT-SuperSAGE technique allowed the evaluation of four drought-tolerant cultivars and four-sensitive cultivars, after 24h of irrigation suppression. We identified 9831 induced unitags from roots of the tolerant cultivars with different regulations by the -sensitive cultivars after the applied stress. These unitags allowed a proposal of 15 genes, whose expressed profiles were validated by RT-qPCR, evaluating each cultivar independently. These genes covered broad metabolic processes: ethylene stress attenuation (ACCD); root growth (β-EXP8); protein degradation [ubiquitination pathway (E2, 20SPβ4); plant proteases (AP, C13)]; oxidative detoxification (TRX); fatty acid synthesis (ACC); amino acid transport (AAT), and carbohydrate metabolism [glycolysis (PFK, TPI, FBA); TCA cycle (LDP, MDH); pentose phosphate pathway (TKT)]. The expressed profiles showed a genotype-dependent regulation of the target genes. Two drought-tolerant cultivars (SP83-2847; CTC6) presented each one, nine of the induced genes. Among the -sensitive cultivars, CTC13 induced only one, while SP90-1636 induced two genes. These genes should help breeders to identify accessions managing drought stress tolerance responses, showing better ethylene stress attenuation, energy allocation, amino acid transport, and protein homeostasis.

The quest for tolerant varieties: the importance of integrating "omics" techniques to phenotyping

The primary objective of crop breeding is to improve yield and/or harvest quality while minimizing inputs. Global climate change and the increase in world population are significant challenges for agriculture and call for further improvements to crops and the development of new tools for research. Significant progress has been made in the molecular and genetic analysis of model plants. However, is science generating false expectations? Are 'omic techniques generating valuable information that can be translated into the field? The exploration of crop biodiversity and the correlation of cellular responses to stress tolerance at the plant level is currently a challenge. This viewpoint reviews concisely the problems one encounters when working on a crop and provides an outline of possible workflows when initiating cellular phenotyping via "-omic" techniques (transcriptomics, proteomics, metabolomics).

Assessment of RNAi-induced silencing in banana (Musa spp.)

BACKGROUND

In plants, RNA- based gene silencing mediated by small RNAs functions at the transcriptional or post-transcriptional level to negatively regulate target genes, repetitive sequences, viral RNAs and/or transposon elements. Post-transcriptional gene silencing (PTGS) or the RNA interference (RNAi) approach has been achieved in a wide range of plant species for inhibiting the expression of target genes by generating double-stranded RNA (dsRNA). However, to our knowledge, successful RNAi-application to knock-down endogenous genes has not been reported in the important staple food crop banana.

RESULTS

Using embryogenic cell suspension (ECS) transformed with ß-glucuronidase (GUS) as a model system, we assessed silencing of gusAINT using three intron-spliced hairpin RNA (ihpRNA) constructs containing gusAINT sequences of 299-nt, 26-nt and 19-nt, respectively. Their silencing potential was analysed in 2 different experimental set-ups. In the first, Agrobacterium-mediated co-transformation of banana ECS with a gusAINT containing vector and an ihpRNA construct resulted in a significantly reduced GUS enzyme activity 6-8 days after co-cultivation with either the 299-nt and 19-nt ihpRNA vectors. In the second approach, these ihpRNA constructs were transferred to stable GUS-expressing ECS and their silencing potential was evaluated in the regenerated in vitro plants. In comparison to control plants, transgenic plants transformed with the 299-nt gusAINT targeting sequence showed a 4.5 fold down-regulated gusA mRNA expression level, while GUS enzyme activity was reduced by 9 fold. Histochemical staining of plant tissues confirmed these findings. Northern blotting used to detect the expression of siRNA in the 299-nt ihpRNA vector transgenic in vitro plants revealed a negative relationship between siRNA expression and GUS enzyme activity. In contrast, no reduction in GUS activity or GUS mRNA expression occurred in the regenerated lines transformed with either of the two gusAINT oligo target sequences (26-nt and 19-nt).

CONCLUSIONS

RNAi-induced silencing was achieved in banana, both at transient and stable level, resulting in significant reduction of gene expression and enzyme activity. The success of silencing was dependent on the targeted region of the target gene. The successful generation of transgenic ECS for second transformation with (an)other construct(s) can be of value for functional genomics research in banana.

Selection and validation of reference genes for quantitative RT-PCR expression studies of the non-model crop Musa

Gene expression analysis by reverse transcriptase real-time or quantitative polymerase chain reaction (RT-qPCR) is becoming widely used for non-model plant species. Given the high sensitivity of this method, normalization using multiple housekeeping or reference genes is critical, and careful selection of these reference genes is one of the most important steps to obtain reliable results. In this study, reference genes commonly used for other plant species were investigated to identify genes displaying highly uniform expression patterns in different varieties, tissues, developmental stages, fungal infection, and osmotic stress conditions for the non-model crop Musa (banana and plantains). The expression stability of six candidate reference genes was tested on six different sample sets, and the results were analyzed using the publicly available algorithms geNorm and NormFinder. Our results show that variety, plant material, primer set, and gene identity can all influence the robustness and outcome of RT-qPCR analysis. In the case of Musa, a combination of three reference genes (EF1, TUB and ACT) can be used for normalization of gene expression data from greenhouse leaf samples. In the case of shoot meristem cultures, numerous combinations can be used because the investigated reference genes exhibited limited variability. In contrast, variability in expression of the reference genes was much larger among leaf samples from plants grown in vitro, for which the best combination of reference genes (L2 and ACT genes) is still suboptimal. Overall, our data confirm that the stability of candidate reference genes should be thoroughly investigated for each experimental condition under investigation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-012-9711-1) contains supplementary material, which is available to authorized users.

In silico identification of known osmotic stress responsive genes from Arabidopsis in soybean and Medicago

Plants experience various environmental stresses, but tolerance to these adverse conditions is a very complex phenomenon. The present research aimed to evaluate a set of genes involved in osmotic response, comparing soybean and medicago with the well-described Arabidopsis thaliana model plant. Based on 103 Arabidopsis proteins from 27 categories of osmotic stress response, comparative analyses against Genosoja and Medicago truncatula databases allowed the identification of 1,088 soybean and 1,210 Medicago sequences. The analysis showed a high number of sequences and high diversity, comprising genes from all categories in both organisms. Genes with unknown function were among the most representative, followed by transcription factors, ion transport proteins, water channel, plant defense, protein degradation, cellular structure, organization & biogenesis and senescence. An analysis of sequences with unknown function allowed the annotation of 174 soybean and 217 Medicago sequences, most of them concerning transcription factors. However, for about 30% of the sequences no function could be attributed using in silico procedures. The establishment of a gene set involved in osmotic stress responses in soybean and barrel medic will help to better understand the survival mechanisms for this type of stress condition in legumes.

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.

Gill transcriptome response to changes in environmental calcium in the green spotted puffer fish

Background

Calcium ion is tightly regulated in body fluids and for euryhaline fish, which are exposed to rapid changes in environmental [Ca²⁺], homeostasis is especially challenging. The gill is the main organ of active calcium uptake and therefore plays a crucial role in the maintenance of calcium ion homeostasis. To study the molecular basis of the short-term responses to changing calcium availability, the whole gill transcriptome obtained by Super Serial Analysis of Gene Expression (SuperSAGE) of the euryhaline teleost green spotted puffer fish, Tetraodon nigroviridis, exposed to water with altered [Ca²⁺] was analysed.

Results

Transfer of T. nigroviridis from 10 ppt water salinity containing 2.9 mM Ca²⁺ to high (10 mM Ca²⁺ ) and low (0.01 mM Ca²⁺) calcium water of similar salinity for 2-12 h resulted in 1,339 differentially expressed SuperSAGE tags (26-bp transcript identifiers) in gills. Of these 869 tags (65%) were mapped to T. nigroviridis cDNAs or genomic DNA and 497 (57%) were assigned to known proteins. Thirteen percent of the genes matched multiple tags indicating alternative RNA transcripts. The main enriched gene ontology groups belong to Ca²⁺ signaling/homeostasis but also muscle contraction, cytoskeleton, energy production/homeostasis and tissue remodeling. K-means clustering identified co-expressed transcripts with distinct patterns in response to water [Ca²⁺] and exposure time.

Conclusions

The generated transcript expression patterns provide a framework of novel water calcium-responsive genes in the gill during the initial response after transfer to different [Ca²⁺]. This molecular response entails initial perception of alterations, activation of signaling networks and effectors and suggests active remodeling of cytoskeletal proteins during the initial acclimation process. Genes related to energy production and energy homeostasis are also up-regulated, probably reflecting the increased energetic needs of the acclimation response. This study is the first genome-wide transcriptome analysis of fish gills and is an important resource for future research on the short-term mechanisms involved in the gill acclimation responses to environmental Ca²⁺ changes and osmoregulation.

Heterologous oligonucleotide microarrays for transcriptomics in a non-model species; a proof-of-concept study of drought stress in Musa

BACKGROUND

'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip(R) microarrays to profile the response of the banana (Musa spp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts.

RESULTS

Following cross-hybridisation of Musa gDNA to the Rice GeneChip(R) Genome Array, ~33,700 gene-specific probe-sets had a sufficiently high degree of homology to be retained for transcriptomic analyses. In a proof-of-concept approach, pooled RNA representing a single biological replicate of control and drought stressed leaves of the Musa cultivar 'Cachaco' were hybridised to the Affymetrix Rice Genome Array. A total of 2,910 Musa gene homologues with a >2-fold difference in expression levels were subsequently identified. These drought-responsive transcripts included many functional classes associated with plant biotic and abiotic stress responses, as well as a range of regulatory genes known to be involved in coordinating abiotic stress responses. This latter group included members of the ERF, DREB, MYB, bZIP and bHLH transcription factor families. Fifty-two of these drought-sensitive Musa transcripts were homologous to genes underlying QTLs for drought and cold tolerance in rice, including in 2 instances QTLs associated with a single underlying gene. The list of drought-responsive transcripts also included genes identified in publicly-available comparative transcriptomics experiments.

CONCLUSION

Our results demonstrate that despite the general paucity of nucleotide sequence data in Musa and only distant phylogenetic relations to rice, gDNA probe-based cross-hybridisation to the Rice GeneChip(R) is a highly promising strategy to study complex biological responses and illustrates the potential of such strategies for gene discovery in non-model species.

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.

Analysis of wheat SAGE tags reveals evidence for widespread antisense transcription

Background

Serial Analysis of Gene Expression (SAGE) is a powerful tool for genome-wide transcription studies. Unlike microarrays, it has the ability to detect novel forms of RNA such as alternatively spliced and antisense transcripts, without the need for prior knowledge of their existence. One limitation of using SAGE on an organism with a complex genome and lacking detailed sequence information, such as the hexaploid bread wheat Triticum aestivum, is accurate annotation of the tags generated. Without accurate annotation it is impossible to fully understand the dynamic processes involved in such complex polyploid organisms. Hence we have developed and utilised novel procedures to characterise, in detail, SAGE tags generated from the whole grain transcriptome of hexaploid wheat.

Results

Examination of 71,930 Long SAGE tags generated from six libraries derived from two wheat genotypes grown under two different conditions suggested that SAGE is a reliable and reproducible technique for use in studying the hexaploid wheat transcriptome. However, our results also showed that in poorly annotated and/or poorly sequenced genomes, such as hexaploid wheat, considerably more information can be extracted from SAGE data by carrying out a systematic analysis of both perfect and "fuzzy" (partially matched) tags. This detailed analysis of the SAGE data shows first that while there is evidence of alternative polyadenylation this appears to occur exclusively within the 3' untranslated regions. Secondly, we found no strong evidence for widespread alternative splicing in the developing wheat grain transcriptome. However, analysis of our SAGE data shows that antisense transcripts are probably widespread within the transcriptome and appear to be derived from numerous locations within the genome. Examination of antisense transcripts showing sequence similarity to the Puroindoline a and Puroindoline b genes suggests that such antisense transcripts might have a role in the regulation of gene expression.

Conclusion

Our results indicate that the detailed analysis of transcriptome data, such as SAGE tags, is essential to understand fully the factors that regulate gene expression and that such analysis of the wheat grain transcriptome reveals that antisense transcripts maybe widespread and hence probably play a significant role in the regulation of gene expression during grain development.

Proteome analysis of non-model plants: a challenging but powerful approach

Biological research has focused in the past on model organisms and most of the functional genomics studies in the field of plant sciences are still performed on model species or species that are characterized to a great extent. However, numerous non-model plants are essential as food, feed, or energy resource. Some features and processes are unique to these plant species or families and cannot be approached via a model plant. The power of all proteomic and transcriptomic methods, that is, high-throughput identification of candidate gene products, tends to be lost in non-model species due to the lack of genomic information or due to the sequence divergence to a related model organism. Nevertheless, a proteomics approach has a great potential to study non-model species. This work reviews non-model plants from a proteomic angle and provides an outline of the problems encountered when initiating the proteome analysis of a non-model organism. The review tackles problems associated with (i) sample preparation, (ii) the analysis and interpretation of a complex data set, (iii) the protein identification via MS, and (iv) data management and integration. We will illustrate the power of 2DE for non-model plants in combination with multivariate data analysis and MS/MS identification and will evaluate possible alternatives.

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.

Serial analysis of gene expression in sugarcane (Saccharum spp.) leaves revealed alternative C4 metabolism and putative antisense transcripts

Sugarcane (Saccharum spp.) is a highly efficient biomass and sugar producing crop. Leaf reactions have been considered as potential rate-limiting step for sucrose accumulation in sugarcane stalks. To characterize the sugarcane leaf transcriptome, field-grown mature leaves from cultivar "SP80-3280" were analyzed using Serial Analysis of Gene Expression (SAGE). From 480 sequenced clones, 9,482 valid tags were extracted, with 5,227 unique sequences, from which 3,659 (70%) matched at least a sugarcane assembled sequence (SAS) with putative function; while 872 tags (16.7%) matched SAS with unknown function; 523 (10%) matched SAS without a putative annotation; and only 173 (3.3%) did not match any sugarcane ESTs. Based on gene ontology (GO), photosystem (PS) I reaction center was identified as the most frequent gene product location, followed by the remaining sites of PS I, PS II and thylakoid complexes. For metabolic processes, photosynthesis light harvesting complexes; carbon fixation; and chlorophyll biosynthesis were the most enriched GO-terms. Considering the alternative photosynthetic C(4) cycles, tag frequencies related to phosphoenolpyruvate carboxykinase (PEPCK) and aspartate aminotransferase compared to those for NADP(+)-malic enzyme (NADP-ME) and NADP-malate dehydrogenase, suggested that PEPCK-type decarboxylation appeared to predominate over NADP-ME in mature leaves, although both may occur, opposite to currently assumed in sugarcane. From the unique tag set, 894 tags (17.1%) were assigned as potentially derived from antisense transcripts, while 73 tags (1.4%) were assigned to more than one SAS, suggesting the occurrence of alternative processing. The occurrence of antisense was validated by quantitative reverse transcription amplification. Sugarcane leaf transcriptome provided new insights for functional studies associated with sucrose synthesis and accumulation.

Reaping the Benefits of SAGE

Serial analysis of gene expression (SAGE) is a powerful technique which yields a digital measure of gene expression through the sequencing of libraries of specific mRNA-derived fragments, namely SAGE tags. This chapter introduces the methods and software tools that are available for researchers to analyze gene expression through SAGE analysis. A detailed examination of SAGE analysis in Arabidopsis thaliana using the publicly available analysis tool, SaskSAGE, is provided. The use of this software allows the user to maximize the information gained from SAGE experiments in a model system with a fully sequenced genome.