Understanding SAGE data

Transcriptome sequence analysis and mining of SSRs in Jhar Ber (Ziziphus nummularia (Burm.f.) Wight & Arn) under drought stress

Ziziphus nummularia (Burm.f.) Wight & Arn., a perennial shrub that thrives in the arid regions, is naturally tolerant to drought. However, there are limited studies on the genomics of drought tolerance in Ziziphus sp. In this study, RNA-sequencing of one month old seedlings treated with PEG 6000 was performed using Roche GS-FLX454 Titanium pyrosequencing. A total of 367,176 raw sequence reads were generated, and upon adapter trimming and quality filtration 351,872 reads were assembled de novo into 32,739 unigenes. Further characterization of the unigenes indicated that 73.25% had significant hits in the protein database. Kyoto encyclopedia of genes and genomes database (KEGG) identified 113 metabolic pathways from the obtained unigenes. A large number of drought-responsive genes were obtained and among them differential gene expression of 16 highly induced genes was validated by qRT-PCR analysis. To develop genic-markers, 3,425 simple sequence repeats (SSRs) were identified in 2,813 unigene sequences. The data generated shall serve as an important reservoir for the identification and characterization of drought stress responsive genes for development of drought tolerant crops.

Ragweed (Ambrosia artemisiifolia) pollen allergenicity: SuperSAGE transcriptomic analysis upon elevated CO2 and drought stress

BACKGROUND

Pollen of common ragweed (Ambrosia artemisiifolia) is a main cause of allergic diseases in Northern America. The weed has recently become spreading as a neophyte in Europe, while climate change may also affect the growth of the plant and additionally may also influence pollen allergenicity. To gain better insight in the molecular mechanisms in the development of ragweed pollen and its allergenic proteins under global change scenarios, we generated SuperSAGE libraries to identify differentially expressed transcripts.

RESULTS

Ragweed plants were grown in a greenhouse under 380 ppm CO2 and under elevated level of CO2 (700 ppm). In addition, drought experiments under both CO2 concentrations were performed. The pollen viability was not altered under elevated CO2, whereas drought stress decreased its viability. Increased levels of individual flavonoid metabolites were found under elevated CO2 and/or drought. Total RNA was isolated from ragweed pollen, exposed to the four mentioned scenarios and four SuperSAGE libraries were constructed. The library dataset included 236,942 unique sequences, showing overlapping as well as clear differently expressed sequence tags (ESTs). The analysis targeted ESTs known in Ambrosia, as well as in pollen of other plants. Among the identified ESTs, those encoding allergenic ragweed proteins (Amb a) increased under elevated CO2 and drought stress. In addition, ESTs encoding allergenic proteins in other plants were also identified.

CONCLUSIONS

The analysis of changes in the transcriptome of ragweed pollen upon CO2 and drought stress using SuperSAGE indicates that under global change scenarios the pollen transcriptome was altered, and impacts the allergenic potential of ragweed pollen.

The analytical landscape of static and temporal dynamics in transcriptome data

Interpreting gene expression profiles often involves statistical analysis of large numbers of differentially expressed genes, isoforms, and alternative splicing events at either static or dynamic spectrums. Reduced sequencing costs have made feasible dense time-series analysis of gene expression using RNA-seq; however, statistical methods in the context of temporal RNA-seq data are poorly developed. Here we will review current methods for identifying temporal changes in gene expression using RNA-seq, which are limited to static pairwise comparisons of time points and which fail to account for temporal dependencies in gene expression patterns. We also review recently developed very few number of temporal dynamic RNA-seq specific methods. Application and development of RNA-specific temporal dynamic methods have been continuously under the development, yet, it is still in infancy. We fully cover microarray specific temporal methods and transcriptome studies in initial digital technology (e.g., SAGE) between traditional microarray and new RNA-seq.

Modeling the next generation sequencing sample processing pipeline for the purposes of classification

BACKGROUND

A key goal of systems biology and translational genomics is to utilize high-throughput measurements of cellular states to develop expression-based classifiers for discriminating among different phenotypes. Recent developments of Next Generation Sequencing (NGS) technologies can facilitate classifier design by providing expression measurements for tens of thousands of genes simultaneously via the abundance of their mRNA transcripts. Because NGS technologies result in a nonlinear transformation of the actual expression distributions, their application can result in data that are less discriminative than would be the actual expression levels themselves, were they directly observable.

RESULTS

Using state-of-the-art distributional modeling for the NGS processing pipeline, this paper studies how that pipeline, via the resulting nonlinear transformation, affects classification and feature selection. The effects of different factors are considered and NGS-based classification is compared to SAGE-based classification and classification directly on the raw expression data, which is represented by a very high-dimensional model previously developed for gene expression. As expected, the nonlinear transformation resulting from NGS processing diminishes classification accuracy; however, owing to a larger number of reads, NGS-based classification outperforms SAGE-based classification.

CONCLUSIONS

Having high numbers of reads can mitigate the degradation in classification performance resulting from the effects of NGS technologies. Hence, when performing a RNA-Seq analysis, using the highest possible coverage of the genome is recommended for the purposes of classification.

Identification of differential expression genes associated with host selection and adaptation between two sibling insect species by transcriptional profile analysis

Background

Cotton bollworm (Helicoverpa armigera) and oriental tobacco budworm (Helicoverpa assulta) are noctuid sibling species. Under artificial manipulation, they can mate and produce fertile offspring. As serious agricultural insect pests, cotton bollworms are euryphagous insects, but oriental tobacco budworms are oligophagous insects. To identify the differentially expressed genes that affect host recognition and host adaptation between the two species, we constructed digital gene expression tag profiles for four developmental stages of the two species. High-throughput sequencing results indicated that we have got more than 23 million 17nt clean tags from both species, respectively. The number of unique clean tags was nearly same in both species (approximately 357,000).

Results

According to the gene annotation results, we identified 83 and 68 olfaction related transcripts from H. armigera and H. assulta, respectively. At the same time, 1137 and 1138 transcripts of digestion enzymes were identified from the two species. Among the olfaction related transcripts, more odorant binding protein and G protein-coupled receptor were identified in H. armigera than in H. assulta. Among the digestion enzymes, there are more detoxification enzyme, e.g. P450, carboxypeptidase and ATPase in H. assulta than in H. armigera. These differences partially explain that because of the narrow host plant range of H. assulta, more detoxification enzymes would help them increase the food detoxification and utilization efficiency.

Conclusions

This study supplied some differentially expressed genes affecting host selection and adaptation between the two sibling species. These genes will be useful information for studying on the evolution of host plant selection. It also provides some important target genes for insect species-specific control by RNAi technology.

Insights into the roles of local translation from the axonal transcriptome

Much of our knowledge on the roles of intra-axonal translation derives from the characterization of a small number of individual mRNAs that were found to be localized in axons. However, two recent studies, using large-scale approaches to provide a more comprehensive characterization of the axonal transcriptome, have led to the discovery of thousands of axonal mRNAs. The apparent abundance of mRNAs in axons raises the possibility that local translation has many more functions than previously thought. Here, we review the recent studies that have profiled axonal mRNAs and discuss how the identification of axonal transcripts might point to unappreciated roles for local translation in axons.

Time series expression analyses using RNA-seq: a statistical approach

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

Increased frequency of single base substitutions in a population of transcripts expressed in cancer cells

Background

Single Base Substitutions (SBS) that alter transcripts expressed in cancer originate from somatic mutations. However, recent studies report SBS in transcripts that are not supported by the genomic DNA of tumor cells.

Methods

We used sequence based whole genome expression profiling, namely Long-SAGE (L-SAGE) and Tag-seq (a combination of L-SAGE and deep sequencing), and computational methods to identify transcripts with greater SBS frequencies in cancer. Millions of tags produced by 40 healthy and 47 cancer L-SAGE experiments were compared to 1,959 Reference Tags (RT), i.e. tags matching the human genome exactly once. Similarly, tens of millions of tags produced by 7 healthy and 8 cancer Tag-seq experiments were compared to 8,572 RT. For each transcript, SBS frequencies in healthy and cancer cells were statistically tested for equality.

Results

In the L-SAGE and Tag-seq experiments, 372 and 4,289 transcripts respectively, showed greater SBS frequencies in cancer. Increased SBS frequencies could not be attributed to known Single Nucleotide Polymorphisms (SNP), catalogued somatic mutations or RNA-editing enzymes. Hypothesizing that Single Tags (ST), i.e. tags sequenced only once, were indicators of SBS, we observed that ST proportions were heterogeneously distributed across Embryonic Stem Cells (ESC), healthy differentiated and cancer cells. ESC had the lowest ST proportions, whereas cancer cells had the greatest. Finally, in a series of experiments carried out on a single patient at 1 healthy and 3 consecutive tumor stages, we could show that SBS frequencies increased during cancer progression.

Conclusion

If the mechanisms generating the base substitutions could be known, increased SBS frequency in transcripts would be a new useful biomarker of cancer. With the reduction of sequencing cost, sequence based whole genome expression profiling could be used to characterize increased SBS frequency in patient’s tumor and aid diagnostic.

Duplicate gene enrichment and expression pattern diversification in multicellularity

The enrichment of duplicate genes, and therefore paralogs (proteins coded by duplicate genes), in multicellular versus unicellular organisms enhances genomic functional innovation. This study quantitatively examined relationships among paralog enrichment, expression pattern diversification and multicellularity, aiming to better understand genomic basis of multicellularity. Paralog abundance in specific cells was compared with those in unicellular proteomes and the whole proteomes of multicellular organisms. The budding yeast, Saccharomyces cerevisiae and the nematode, Caenorhabditis elegans, for which the gene sets expressed in specific cells are available, were used as uni and multicellular models, respectively. Paralog count (K) distributions [P_(k)] follow a power-law relationship [P_(k) ∝ k^−α] in the whole proteomes of both species and in specific C. elegans cells. The value of the constant α can be used as a gauge of paralog abundance; the higher the value, the lower the paralog abundance. The α-value is indeed lower in the whole proteome of C. elegans (1.74) than in S. cerevisiae (2.34), quantifying the enrichment of paralogs in multicellular species. We also found that the power-law relationship applies to the proteomes of specific C. elegans cells. Strikingly, values of α in specific cells are higher and comparable to that in S. cerevisiae. Thus, paralog abundance in specific cells is lower and comparable to that in unicellular species. Furthermore, how much the expression level of a gene fluctuates across different C. elegans cells correlates positively with its paralog count, which is further confirmed by human gene-expression patterns across different tissues. Taken together, these results quantitatively and mechanistically establish enrichment of paralogs with diversifying expression patterns as genomic and evolutionary basis of multicellularity.

De novo sequencing and characterization of Picrorhiza kurrooa transcriptome at two temperatures showed major transcriptome adjustments

BACKGROUND

Picrorhiza kurrooa Royle ex Benth. is an endangered plant species of medicinal importance. The medicinal property is attributed to monoterpenoids picroside I and II, which are modulated by temperature. The transcriptome information of this species is limited with the availability of few hundreds of expressed sequence tags (ESTs) in the public databases. In order to gain insight into temperature mediated molecular changes, high throughput de novo transcriptome sequencing and analyses were carried out at 15 °C and 25 °C, the temperatures known to modulate picrosides content.

RESULTS

Using paired-end (PE) Illumina sequencing technology, a total of 20,593,412 and 44,229,272 PE reads were obtained after quality filtering for 15 °C and 25 °C, respectively. Available (e.g., De-Bruijn/Eulerian graph) and in-house developed bioinformatics tools were used for assembly and annotation of transcriptome. A total of 74,336 assembled transcript sequences were obtained, with an average coverage of 76.6 and average length of 439.5. Guanine-cytosine (GC) content was observed to be 44.6%, while the transcriptome exhibited abundance of trinucleotide simple sequence repeat (SSR; 45.63%) markers.Large scale expression profiling through "read per exon kilobase per million (RPKM)", showed changes in several biological processes and metabolic pathways including cytochrome P450s (CYPs), UDP-glycosyltransferases (UGTs) and those associated with picrosides biosynthesis. RPKM data were validated by reverse transcriptase-polymerase chain reaction using a set of 19 genes, wherein 11 genes behaved in accordance with the two expression methods.

CONCLUSIONS

Study generated transcriptome of P. kurrooa at two different temperatures. Large scale expression profiling through RPKM showed major transcriptome changes in response to temperature reflecting alterations in major biological processes and metabolic pathways, and provided insight of GC content and SSR markers. Analysis also identified putative CYPs and UGTs that could help in discovering the hitherto unknown genes associated with picrosides biosynthesis.

Characterization of transcriptome dynamics during watermelon fruit development: sequencing, assembly, annotation and gene expression profiles

Background

Cultivated watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] is an important agriculture crop world-wide. The fruit of watermelon undergoes distinct stages of development with dramatic changes in its size, color, sweetness, texture and aroma. In order to better understand the genetic and molecular basis of these changes and significantly expand the watermelon transcript catalog, we have selected four critical stages of watermelon fruit development and used Roche/454 next-generation sequencing technology to generate a large expressed sequence tag (EST) dataset and a comprehensive transcriptome profile for watermelon fruit flesh tissues.

Results

We performed half Roche/454 GS-FLX run for each of the four watermelon fruit developmental stages (immature white, white-pink flesh, red flesh and over-ripe) and obtained 577,023 high quality ESTs with an average length of 302.8 bp. De novo assembly of these ESTs together with 11,786 watermelon ESTs collected from GenBank produced 75,068 unigenes with a total length of approximately 31.8 Mb. Overall 54.9% of the unigenes showed significant similarities to known sequences in GenBank non-redundant (nr) protein database and around two-thirds of them matched proteins of cucumber, the most closely-related species with a sequenced genome. The unigenes were further assigned with gene ontology (GO) terms and mapped to biochemical pathways. More than 5,000 SSRs were identified from the EST collection. Furthermore we carried out digital gene expression analysis of these ESTs and identified 3,023 genes that were differentially expressed during watermelon fruit development and ripening, which provided novel insights into watermelon fruit biology and a comprehensive resource of candidate genes for future functional analysis. We then generated profiles of several interesting metabolites that are important to fruit quality including pigmentation and sweetness. Integrative analysis of metabolite and digital gene expression profiles helped elucidating molecular mechanisms governing these important quality-related traits during watermelon fruit development.

Conclusion

We have generated a large collection of watermelon ESTs, which represents a significant expansion of the current transcript catalog of watermelon and a valuable resource for future studies on the genomics of watermelon and other closely-related species. Digital expression analysis of this EST collection allowed us to identify a large set of genes that were differentially expressed during watermelon fruit development and ripening, which provide a rich source of candidates for future functional analysis and represent a valuable increase in our knowledge base of watermelon fruit biology.

Influence of host gene transcription level and orientation on HIV-1 latency in a primary-cell model

Human immunodeficiency virus type 1 (HIV-1) establishes a latent reservoir in resting memory CD4(+) T cells. This latent reservoir is a major barrier to the eradication of HIV-1 in infected individuals and is not affected by highly active antiretroviral therapy (HAART). Reactivation of latent HIV-1 is a possible strategy for elimination of this reservoir. The mechanisms with which latency is maintained are unclear. In the analysis of the regulation of HIV-1 gene expression, it is important to consider the nature of HIV-1 integration sites. In this study, we analyzed the integration and transcription of latent HIV-1 in a primary CD4(+) T cell model of latency. The majority of integration sites in latently infected cells were in introns of transcription units. Serial analysis of gene expression (SAGE) demonstrated that more than 90% of those host genes harboring a latent integrated provirus were transcriptionally active, mostly at high levels. For latently infected cells, we observed a modest preference for integration in the same transcriptional orientation as the host gene (63.8% versus 36.2%). In contrast, this orientation preference was not observed in acutely infected or persistently infected cells. These results suggest that transcriptional interference may be one of the important factors in the establishment and maintenance of HIV-1 latency. Our findings suggest that disrupting the negative control of HIV-1 transcription by upstream host promoters could facilitate the reactivation of latent HIV-1 in some resting CD4(+) T cells.

Nutrient-regulated transcriptional responses in the brown tide-forming alga Aureococcus anophagefferens

Long-SAGE (serial analysis of gene expression) was used to profile the transcriptome of the brown tide-forming alga, Aureococcus anophagefferens, under nutrient replete (control), and nitrogen (N) and phosphorus (P) deficiency to understand how this organism responds at the transcriptional level to varying nutrient conditions. This approach has aided A. anophagefferens genome annotation efforts and identified a suite of genes upregulated by N and P deficiency, some of which have known roles in nutrient metabolism. Genes upregulated under N deficiency include an ammonium transporter, an acetamidase/formamidase and two peptidases. This suggests an ability to utilize reduced N compounds and dissolved organic nitrogen, supporting the hypothesized importance of these N sources in A. anophagefferens bloom formation. There are also a broad suite of P-regulated genes, including an alkaline phosphatase, and two 5'-nucleotidases, suggesting A. anophagefferens may use dissolved organic phosphorus under low phosphate conditions. These N- and P-regulated genes may be important targets for exploring nutrient controls on bloom formation in field populations.

Whole transcriptome analysis: what are we still missing?

New technologies such as tag-based sequencing and tiling arrays have provided unique insights into the transcriptional output of cells. Many new RNA classes have been uncovered in the past decade, despite limitations in current technologies. Even as the repertoire of known functional elements of the transcriptome increases and contemporary technologies become mainstream, inadequacies in conventional protocols for library preparation, sequencing and mapping continue to hamper revelation of the entire transcriptome of cells. In this article, we review current protocols and outline their deficiencies. We also provide our view on what we may be overlooking in the transcriptome, despite exhaustive investigations, and indicate future areas of technological development and research.

hSAGEing: an improved SAGE-based software for identification of human tissue-specific or common tumor markers and suppressors

BACKGROUND

SAGE (serial analysis of gene expression) is a powerful method of analyzing gene expression for the entire transcriptome. There are currently many well-developed SAGE tools. However, the cross-comparison of different tissues is seldom addressed, thus limiting the identification of common- and tissue-specific tumor markers.

METHODOLOGY/PRINCIPAL FINDINGS

To improve the SAGE mining methods, we propose a novel function for cross-tissue comparison of SAGE data by combining the mathematical set theory and logic with a unique "multi-pool method" that analyzes multiple pools of pair-wise case controls individually. When all the settings are in "inclusion", the common SAGE tag sequences are mined. When one tissue type is in "inclusion" and the other types of tissues are not in "inclusion", the selected tissue-specific SAGE tag sequences are generated. They are displayed in tags-per-million (TPM) and fold values, as well as visually displayed in four kinds of scales in a color gradient pattern. In the fold visualization display, the top scores of the SAGE tag sequences are provided, along with cluster plots. A user-defined matrix file is designed for cross-tissue comparison by selecting libraries from publically available databases or user-defined libraries.

CONCLUSIONS/SIGNIFICANCE

The hSAGEing tool provides a combination of friendly cross-tissue analysis and an interface for comparing SAGE libraries for the first time. Some up- or down-regulated genes with tissue-specific or common tumor markers and suppressors are identified computationally. The tool is useful and convenient for in silico cancer transcriptomic studies and is freely available at http://bio.kuas.edu.tw/hSAGEing.

Identifying novel genes in C. elegans using SAGE tags

Background

Despite extensive efforts devoted to predicting protein-coding genes in genome sequences, many bona fide genes have not been found and many existing gene models are not accurate in all sequenced eukaryote genomes. This situation is partly explained by the fact that gene prediction programs have been developed based on our incomplete understanding of gene feature information such as splicing and promoter characteristics. Additionally, full-length cDNAs of many genes and their isoforms are hard to obtain due to their low level or rare expression. In order to obtain full-length sequences of all protein-coding genes, alternative approaches are required.

Results

In this project, we have developed a method of reconstructing full-length cDNA sequences based on short expressed sequence tags which is called sequence tag-based amplification of cDNA ends (STACE). Expressed tags are used as anchors for retrieving full-length transcripts in two rounds of PCR amplification. We have demonstrated the application of STACE in reconstructing full-length cDNA sequences using expressed tags mined in an array of serial analysis of gene expression (SAGE) of C. elegans cDNA libraries. We have successfully applied STACE to recover sequence information for 12 genes, for two of which we found isoforms. STACE was used to successfully recover full-length cDNA sequences for seven of these genes.

Conclusions

The STACE method can be used to effectively reconstruct full-length cDNA sequences of genes that are under-represented in cDNA sequencing projects and have been missed by existing gene prediction methods, but their existence has been suggested by short sequence tags such as SAGE tags.

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.

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.

Global gene expression reveals a set of new genes involved in the modification of cells during erythroid differentiation

OBJECTIVES

Erythroid differentiation is a dynamic process in which a pluripotent stem cell undergoes a series of developmental changes that commit it to a specific lineage. These alterations involve changes in gene expression profiles. In this study, gene expression profiles during differentiation of human erythroid cells of a normal blood donor were evaluated using SAGE.

MATERIALS AND METHODS

Global gene expression was evaluated in cells collected immediately before addition of erythropoietin (0 h) and 192 and 336 h after addition of this hormone. Real-time PCR was used to evaluate activation of differentially expressed genes.

RESULTS

The data indicate that global aspects of the transcriptome were similar during differentiation of the majority of the genes and that a relatively small set of genes is probably involved in modification of erythroid cells during differentiation. We have identified 93 differentially expressed genes during erythroid development, and expression of some of these was confirmed by qPCR. Various genes including EYA3, ERH, HES6, TIMELESS and TRIB3 were found to be homologous to those of Drosophila melanogaster and here are described for the first time during erythroid development. An important and unique carboxypeptidase inhibitor described in mammalians, LXN, was also identified.

CONCLUSIONS

The results of this study amplify previously published data and may contribute to comprehension of erythroid differentiation and identification of new target genes involved in some erythroid concerning diseases.

Transcriptome sequencing and comparative analysis of cucumber flowers with different sex types

Background

Cucumber, Cucumis sativus L., is an economically and nutritionally important crop of the Cucurbitaceae family and has long served as a primary model system for sex determination studies. Recently, the sequencing of its whole genome has been completed. However, transcriptome information of this species is still scarce, with a total of around 8,000 Expressed Sequence Tag (EST) and mRNA sequences currently available in GenBank. In order to gain more insights into molecular mechanisms of plant sex determination and provide the community a functional genomics resource that will facilitate cucurbit research and breeding, we performed transcriptome sequencing of cucumber flower buds of two near-isogenic lines, WI1983G, a gynoecious plant which bears only pistillate flowers, and WI1983H, a hermaphroditic plant which bears only bisexual flowers.

Result

Using Roche-454 massive parallel pyrosequencing technology, we generated a total of 353,941 high quality EST sequences with an average length of 175bp, among which 188,255 were from gynoecious flowers and 165,686 from hermaphroditic flowers. These EST sequences, together with ~5,600 high quality cucumber EST and mRNA sequences available in GenBank, were clustered and assembled into 81,401 unigenes, of which 28,452 were contigs and 52,949 were singletons. The unigenes and ESTs were further mapped to the cucumber genome and more than 500 alternative splicing events were identified in 443 cucumber genes. The unigenes were further functionally annotated by comparing their sequences to different protein and functional domain databases and assigned with Gene Ontology (GO) terms. A biochemical pathway database containing 343 predicted pathways was also created based on the annotations of the unigenes. Digital expression analysis identified ~200 differentially expressed genes between flowers of WI1983G and WI1983H and provided novel insights into molecular mechanisms of plant sex determination process. Furthermore, a set of SSR motifs and high confidence SNPs between WI1983G and WI1983H were identified from the ESTs, which provided the material basis for future genetic linkage and QTL analysis.

Conclusion

A large set of EST sequences were generated from cucumber flower buds of two different sex types. Differentially expressed genes between these two different sex-type flowers, as well as putative SSR and SNP markers, were identified. These EST sequences provide valuable information to further understand molecular mechanisms of plant sex determination process and forms a rich resource for future functional genomics analysis, marker development and cucumber breeding.

Large-scale transcriptome data reveals transcriptional activity of fission yeast LTR retrotransposons

Background

Retrotransposons are transposable elements that proliferate within eukaryotic genomes through a process involving reverse transcription. The numbers of retrotransposons within genomes and differences between closely related species may yield insight into the evolutionary history of the elements. Less is known about the ongoing dynamics of retrotransposons, as analysis of genome sequences will only reveal insertions of retrotransposons that are fixed - or near fixation - in the population or strain from which genetic material has been extracted for sequencing. One pre-requisite for retrotransposition is transcription of the elements. Given their intrinsic sequence redundancy, transcriptome-level analyses of transposable elements are scarce. We have used recently published transcriptome data from the fission yeast Schizosaccharomyces pombe to assess the ability to detect and describe transcriptional activity from Long Terminal Repeat (LTR) retrotransposons. LTR retrotransposons are normally flanked by two LTR sequences. However, the majority of LTR sequences in S. pombe exist as solitary LTRs, i.e. as single terminal repeat sequences not flanking a retrotransposon. Transcriptional activity was analysed for both full-length LTR retrotransposons and solitary LTRs.

Results

Two independent sets of transcriptome data reveal the presence of full-length, polyadenylated transcripts from LTR retrotransposons in S. pombe during growth phase in rich medium. The redundancy of retrotransposon sequences makes it difficult to assess which elements are transcriptionally active, but data strongly indicates that only a subset of the LTR retrotransposons contribute significantly to the detected transcription. A considerable level of reverse strand transcription is also detected. Equal levels of transcriptional activity are observed from both strands of solitary LTR sequences. Transcriptome data collected during meiosis suggests that transcription of solitary LTRs is correlated with the transcription of nearby protein-coding genes.

Conclusions

Presumably, the host organism negatively regulates proliferation of LTR retrotransposons. The finding of considerable transcriptional activity of retrotransposons suggests that part of this regulation is likely to take place at a post-transcriptional level. Alternatively, the transcriptional activity may signify a hitherto unrecognized activity level of retrotransposon proliferation. Our findings underline the usefulness of transcriptome data in elucidating dynamics in retrotransposon transcription.

An NGF-responsive element targets myo-inositol monophosphatase-1 mRNA to sympathetic neuron axons

mRNA localization is an evolutionary conserved mechanism that underlies the establishment of cellular polarity and specialized cell functions. To identify mRNAs localized in subcellular compartments of developing neurons, we took an original approach that combines compartmentalized cultures of rat sympathetic neurons and sequential analysis of gene expression (SAGE). Unexpectedly, the most abundant transcript in axons was mRNA for myo-inositol monophosphatase-1 (Impa1), a key enzyme that regulates the inositol cycle and the main target of lithium in neurons. A novel localization element within the 3' untranslated region of Impa1 mRNA specifically targeted Impa1 transcript to sympathetic neuron axons and regulated local IMPA1 translation in response to nerve growth factor (NGF). Selective silencing of IMPA1 synthesis in axons decreased nuclear CREB activation and induced axonal degeneration. These results provide insights into mRNA transport in axons and reveal a new NGF-responsive localization element that directs the targeting and local translation of an axonal transcript.

Gene association analysis: a survey of frequent pattern mining from gene expression data

Establishing an association between variables is always of interest in genomic studies. Generation of DNA microarray gene expression data introduces a variety of data analysis issues not encountered in traditional molecular biology or medicine. Frequent pattern mining (FPM) has been applied successfully in business and scientific data for discovering interesting association patterns, and is becoming a promising strategy in microarray gene expression analysis. We review the most relevant FPM strategies, as well as surrounding main issues when devising efficient and practical methods for gene association analysis (GAA). We observed that, so far, scalability achieved by efficient methods does not imply biological soundness of the discovered association patterns, and vice versa. Ideally, GAA should employ a balanced mining model taking into account best practices employed by methods reviewed in this survey. Integrative approaches, in which biological knowledge plays an important role within the mining process, are becoming more reliable.

Applications of new sequencing technologies for transcriptome analysis

Transcriptome analysis has been a key area of biological inquiry for decades. Over the years, research in the field has progressed from candidate gene-based detection of RNAs using Northern blotting to high-throughput expression profiling driven by the advent of microarrays. Next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution.

Detection of low-abundant novel transcripts in mouse hematopoietic stem cells

Gene expression profiles of hematopoietic stem cells (HSCs) provide clues for understanding molecular mechanisms of HSC behavior, including self-renewal and differentiation. We took advantage of serial analysis of gene expression (SAGE) to identify medium- and low-abundant transcripts expressed in HSCs/hematopoietic progenitor cells (HPCs). Among a total of 31,380 unique transcripts, 17,326 (55%) correspond to known genes and, 14,054 (45%) are low-copy transcripts that have no matches to currently known genes. Among the former class, 3,899 (23%) were alternatively spliced transcripts and 3,754 (22%) represent anti-sense transcripts from known genes. Mapping of the SAGE tags to the mouse genome showed that differences in gene expression exist among chromosomes. In addition, comparison of the HSCs/HPCs SAGE data to that of myeloid progenitor cells revealed that massive genetic reprogramming occurs in hematopoietic cell differentiation. Our results demonstrate a previously unrecognized complexity of gene expression in HSCs/HPCs, and indicate the need for further efforts to fully identify and characterize the transcripts expressed in this cell type.

An integrated strategy to study muscle development and myofilament structure in Caenorhabditis elegans

A crucial step in the development of muscle cells in all metazoan animals is the assembly and anchorage of the sarcomere, the essential repeat unit responsible for muscle contraction. In Caenorhabditis elegans, many of the critical proteins involved in this process have been uncovered through mutational screens focusing on uncoordinated movement and embryonic arrest phenotypes. We propose that additional sarcomeric proteins exist for which there is a less severe, or entirely different, mutant phenotype produced in their absence. We have used Serial Analysis of Gene Expression (SAGE) to generate a comprehensive profile of late embryonic muscle gene expression. We generated two replicate long SAGE libraries for sorted embryonic muscle cells, identifying 7,974 protein-coding genes. A refined list of 3,577 genes expressed in muscle cells was compiled from the overlap between our SAGE data and available microarray data. Using the genes in our refined list, we have performed two separate RNA interference (RNAi) screens to identify novel genes that play a role in sarcomere assembly and/or maintenance in either embryonic or adult muscle. To identify muscle defects in embryos, we screened specifically for the Pat embryonic arrest phenotype. To visualize muscle defects in adult animals, we fed dsRNA to worms producing a GFP-tagged myosin protein, thus allowing us to analyze their myofilament organization under gene knockdown conditions using fluorescence microscopy. By eliminating or severely reducing the expression of 3,300 genes using RNAi, we identified 122 genes necessary for proper myofilament organization, 108 of which are genes without a previously characterized role in muscle. Many of the genes affecting sarcomere integrity have human homologs for which little or nothing is known.

Muscular diseases affect many people worldwide. While we have learned much about the sarcomere, the basic building block of muscle cells, there are still numerous questions that remain to be answered. We must learn more about proteins expressed in muscle and how they interact so that better treatments for myopathies can be developed. The nematode Caenorhabditis elegans is a valuable model organism for the study of muscle due to similarities between worm body wall muscle and vertebrate muscle, along with its semi-transparent cuticle that allows for visualization of muscle structures in live animals. We have used transcriptional profiling methods to identify the majority of genes that are expressed in the embryonic body wall muscle cells of C. elegans. To gain insight into possible functions performed by these genes and their corresponding proteins, we examined animals and muscle cells for abnormalities after the targeted inactivation of about 3,300 genes. We identified 122 genes necessary for proper myofilament organization, 108 of which had no previously characterized role in muscle. This approach proved to be a rapid and sensitive means to identify genes that affect muscle differentiation and sarcomere assembly.

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.

Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes

The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.

Proteins are the active players that execute the genetic program of a cell, and their levels and interactions are precisely controlled. Routinely monitoring thousands of proteins is difficult, as they can be present at vastly different abundances, come with various sizes, shapes, and charge, and have a more complex alphabet of twenty “letters,” in contrast to the four letters of the genome itself. Here, we used mass spectrometry to extensively characterize the proteins of a popular model organism, the nematode Caenorhabditis elegans. Together with previous data from the fruit fly Drosophila melanogaster, this allows us to compare the protein levels of two animals on a global scale. Surprisingly, we find that individual protein abundance is highly conserved between the two species. So, although worms and flies look very different, they need similar amounts of each conserved, orthologous protein. Because many C. elegans and D. melanogaster proteins also have counterparts in humans, our results suggest that similar rules may apply to our own proteins.

A quantitative comparison of two animal proteomes shows a striking correlation of protein abundance levels, a better correlation than transcript levels. Are the latter more variable during evolution?

Identification of genes expressed in the hermaphrodite germ line of C. elegans using SAGE

BACKGROUND

Germ cells must progress through elaborate developmental stages from an undifferentiated germ cell to a fully differentiated gamete. Some of these stages include exiting mitosis and entering meiosis, progressing through the various stages of meiotic prophase, adopting either a male (sperm) or female (oocyte) fate, and completing meiosis. Additionally, many of the factors needed to drive embryogenesis are synthesized in the germ line. To increase our understanding of the genes that might be necessary for the formation and function of the germ line, we have constructed a SAGE library from hand dissected C. elegans hermaphrodite gonads.

RESULTS

We found that 4699 genes, roughly 21% of all known C. elegans genes, are expressed in the adult hermaphrodite germ line. Ribosomal genes are highly expressed in the germ line; roughly four fold above their expression levels in the soma. We further found that 1063 of the germline-expressed genes have enriched expression in the germ line as compared to the soma. A comparison of these 1063 germline-enriched genes with a similar list of genes prepared using microarrays revealed an overlap of 460 genes, mutually reinforcing the two lists. Additionally, we identified 603 germline-enriched genes, supported by in situ expression data, which were not previously identified. We also found >4 fold enrichment for RNA binding proteins in the germ line as compared to the soma.

CONCLUSION

Using multiple technological platforms provides a more complete picture of global gene expression patterns. Genes involved in RNA metabolism are expressed at a significantly higher level in the germ line than the soma, suggesting a stronger reliance on RNA metabolism for control of the expression of genes in the germ line. Additionally, the number and expression level of germ line expressed genes on the X chromosome is lower than expected based on a random distribution.

Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics. Thus, to carry out these studies Transcriptomics, Proteomics and Metabolomics approaches are employed together with an adequate integration of the information that they provide. In this article, an overview of the current methodologies and a thorough revision of the advances in analytical technologies and their possibilities for future developments and applications in the field of Nutrigenomics is provided.

Identification of novel transcripts with differential dorso-ventral expression in Xenopus gastrula using serial analysis of gene expression

Comparison of dorsal and ventral transcriptomes of Xenopus tropicalis gastrulae using serial analysis of gene expression provides at least 86 novel differentially expressed transcripts.

Background

Recent evidence from global studies of gene expression indicates that transcriptomes are more complex than expected. Xenopus has been typically used as a model organism to study early embryonic development, particularly dorso-ventral patterning. In order to identify novel transcripts involved in dorso-ventral patterning, we compared dorsal and ventral transcriptomes of Xenopus tropicalis at the gastrula stage using serial analysis of gene expression (SAGE).

Results

Of the experimental tags, 54.5% were confidently mapped to transcripts and 125 showed a significant difference in their frequency of occurrence between dorsal and ventral libraries. We selected 20 differentially expressed tags and assigned them to specific transcripts using bioinformatics and reverse SAGE. Five mapped to transcripts with known dorso-ventral expression and the frequency of appearance for these tags in each library is in agreement with the expression described by other methods. The other 15 tags mapped to transcripts with no previously described asymmetric expression along the dorso-ventral axis. The differential expression of ten of these novel transcripts was validated by in situ hybridization and/or RT-PCR. We can estimate that this SAGE experiment provides a list of at least 86 novel transcripts with differential expression along the dorso-ventral axis. Interestingly, the expression of some novel transcripts was independent of β-catenin.

Conclusions

Our SAGE analysis provides a list of novel transcripts with differential expression in the dorso-ventral axis and a large number of orphan tags that can be used to identify novel transcripts and to improve the current annotation of the X. tropicalis genome.

Serial analysis of gene expression reveals differential expression between endometriosis and normal endometrium. Possible roles for AXL and SHC1 in the pathogenesis of endometriosis

BACKGROUND

Endometriosis is a clinical condition that affects up to 10% of the women of reproductive age. Endometriosis is characterized by the presence of endometrial tissues outside the uterine cavity and can lead to chronic pelvic pain, infertility and, in some cases, to ovarian cancer.

METHODS

In order to better understand the pathogenesis of endometriosis, we have used Serial Analysis of Gene Expression (SAGE) to identify genes differentially in this disease by studying three endometriotic tissues and a normal endometrium sample. Promising candidates (AXL, SHC1, ACTN4, PI3KCA, p-AKT, p-mTOR, and p-ERK) were independently validated by immunohistochemistry in additional normal and endometriotic tissues.

RESULTS

We identified several genes differentially expressed between endometriosis and normal endometrium. IGF2, ACTN4, AXL, and SHC1 were among the most upregulated genes. Comparison of the endometriosis gene expression profiles with the gene expression patterns observed in normal human tissues allowed the identification of endometriosis-specific genes, which included several members of the MMP family (MMP1,2,3,10,11,14). Immunohistochemical analysis of several candidates confirmed the SAGE findings, and suggested the involvement of the PI3K-Akt and MAPK signaling pathways in endometriosis.

CONCLUSION

In human endometriosis, the PI3K-Akt and MAPK signaling pathways may be activated via overexpression of AXL and SHC1, respectively. These genes, as well as others identified as differentially expressed in this study, may be useful for the development of novel strategies for the detection and/or therapy of endometriosis.

Applications of next-generation sequencing technologies in functional genomics

A new generation of sequencing technologies, from Illumina/Solexa, ABI/SOLiD, 454/Roche, and Helicos, has provided unprecedented opportunities for high-throughput functional genomic research. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted resequencing, discovery of transcription factor binding sites, and noncoding RNA expression profiling. This review discusses applications of next-generation sequencing technologies in functional genomics research and highlights the transforming potential these technologies offer.

Interrogating global gene expression in rat neuronal cultures using SAGE

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

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.

SAGETTARIUS: a program to reduce the number of tags mapped to multiple transcripts and to plan SAGE sequencing stages

SAGE (Serial Analysis of Gene Expression) experiments generate short nucleotide sequences called ‘tags’ which are assumed to map unambiguously to their original transcripts (1 tag to 1 transcript mapping). Nevertheless, many tags are generated that do not map to any transcript or map to multiple transcripts. Current bioinformatics resources, such as SAGEmap and TAGmapper, have focused on reducing the number of unmapped tags. Here, we describe SAGETTARIUS, a new high-throughput program that performs successive precise Nla3 and Sau3A tag to transcript mapping, based on specifically designed Virtual Tag (VT) libraries. First, SAGETTARIUS decreases the number of tags mapped to multiple transcripts. Among the various mapping resources compared, SAGETTARIUS performed the best in this respect by decreasing up to 11% the number of multiply mapped tags. Second, SAGETTARIUS allows the establishment of a guideline for SAGE experiment sequencing efforts through efficient mapping of the CRT (Cytoplasmic Ribosomal protein Transcripts)-specific tags. Using all publicly available human and mouse Nla3 SAGE experiments, we show that sequencing 100 000 tags is sufficient to map almost all CRT-specific tags and that four sequencing stages can be identified when carrying out a human or mouse SAGE project. SAGETTARIUS is web interfaced and freely accessible to academic users.

Differential gene expression in an elite hybrid rice cultivar (Oryza sativa, L) and its parental lines based on SAGE data

BACKGROUND

It was proposed that differentially-expressed genes, aside from genetic variations affecting protein processing and functioning, between hybrid and its parents provide essential candidates for studying heterosis or hybrid vigor. Based our serial analysis of gene expression (SAGE) data from an elite Chinese super-hybrid rice (LYP9) and its parental cultivars (93-11 and PA64s) in three major tissue types (leaves, roots and panicles) at different developmental stages, we analyzed the transcriptome and looked for candidate genes related to rice heterosis.

RESULTS

By using an improved strategy of tag-to-gene mapping and two recently annotated genome assemblies (93-11 and PA64s), we identified 10,268 additional high-quality tags, reaching a grand total of 20,595 together with our previous result. We further detected 8.5% and 5.9% physically-mapped genes that are differentially-expressed among the triad (in at least one of the three stages) with P-values less than 0.05 and 0.01, respectively. These genes distributed in 12 major gene expression patterns; among them, 406 up-regulated and 469 down-regulated genes (P < 0.05) were observed. Functional annotations on the identified genes highlighted the conclusion that up-regulated genes (some of them are known enzymes) in hybrid are mostly related to enhancing carbon assimilation in leaves and roots. In addition, we detected a group of up-regulated genes related to male sterility and 442 down-regulated genes related to signal transduction and protein processing, which may be responsible for rice heterosis.

CONCLUSION

We improved tag-to-gene mapping strategy by combining information from transcript sequences and rice genome annotation, and obtained a more comprehensive view on genes that related to rice heterosis. The candidates for heterosis-related genes among different genotypes provided new avenue for exploring the molecular mechanism underlying heterosis.

Moderated statistical tests for assessing differences in tag abundance

MOTIVATION

Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small.

RESULTS

We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. Not only is our strategy applicable even with the smallest number of libraries, but it also proves to be more powerful than previous strategies when more libraries are available. The methodology is equally applicable to other counting technologies, such as proteomic spectral counts.

AVAILABILITY

An R package can be accessed from http://bioinf.wehi.edu.au/resources/

Technology insight: microarrays--research and clinical applications

For microarrays, the transition from research to clinical and diagnostic applications is well underway. Microarrays use a range of specific probes that are immobilized in known locations on a support matrix; this technique can measure levels of specific DNA, RNA and proteins, as well as carbohydrates and lipids. It is anticipated that analysis of these levels will lead to identification of biomarkers for the diagnosis, treatment and prognosis of a wide range of diseases. So far, this type of analysis has been particularly useful in clinical oncology, but the technology is being actively and successfully explored for diseases such as diabetes, endocrine tumors and endocrine modulators of tumors. There are now many commercial sources of microarrays, which have robust quality-control procedures in place. Progress will be enhanced when biomarkers can be established, statistical approaches can be refined and when we better understand the interactions of genes and of particular gene loci in disease progression.

miRAS: a data processing system for miRNA expression profiling study

Background

The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.

Results

With miRAS, miRNAs and possible miRNA candidates contained in the submitted sequencing data were obtained together with their expression profile. The functions of known and predicted miRNAs were then analyzed by miRNA target prediction followed by target gene annotations. Finally, to extract the biological significance of the miRNAs in the samples, further annotations of the known miRNA and target genes were performed by collecting the public expression datasets of miRNA and target genes in normal and cancer tissues.

Conclusion

We introduce a web-based analysis platform called miRNA Analysis System (miRAS), for processing and analyzing of the sequence data obtained from the total RNA clone method. The system was built on generalizing the study of a liver cancer cell line total RNA sequencing project. miRAS is freely available on the web.

Ovarian gene expression in the absence of FIGLA, an oocyte-specific transcription factor

Background

Ovarian folliculogenesis in mammals is a complex process involving interactions between germ and somatic cells. Carefully orchestrated expression of transcription factors, cell adhesion molecules and growth factors are required for success. We have identified a germ-cell specific, basic helix-loop-helix transcription factor, FIGLA (Factor In the GermLine, Alpha) and demonstrated its involvement in two independent developmental processes: formation of the primordial follicle and coordinate expression of zona pellucida genes.

Results

Taking advantage of Figla null mouse lines, we have used a combined approach of microarray and Serial Analysis of Gene Expression (SAGE) to identify potential downstream target genes. Using high stringent cutoffs, we find that FIGLA functions as a key regulatory molecule in coordinating expression of the NALP family of genes, genes of known oocyte-specific expression and a set of functionally un-annotated genes. FIGLA also inhibits expression of male germ cell specific genes that might otherwise disrupt normal oogenesis.

Conclusion

These data implicate FIGLA as a central regulator of oocyte-specific genes that play roles in folliculogenesis, fertilization and early development.