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Analyze the changes in gene expression profiles during the process of Panax ginseng seed dormancy release, and screen for differential genes, providing a basis for analyzing the mechanism of P. ginseng seed dormancy release. Comparative transcriptome analysis was conducted by using RNA-Seq sequencing technology in P. ginseng seeds stored at different low temperature. A total of 80.97 Gb of Raw reads and 80.19 Gb of Clean reads were obtained from the transcriptome. Principal component analysis and correlation analysis showed that there were significant differences in gene expression patterns at different developmental stages. Upset results showed that 46 248 unigenes were co-expressed in four stages, and 414, 445, 400 and 389 unigenes were specifically expressed in 0, 8,14 and 28 days, respectively. Gene Ontology functional annotation showed that the differentially expressed genes were mainly involved in nsaturated fatty acid biosynthetic process, nuclear body and oxidoreductase activity. Encyclopedia of Genes and Genomes metabolic pathway showed that differentially expressed genes were mainly involved in peroxisome, mitogen-activated protein kinase signaling pathway-plant, plant hormone signal transduction, ribosome, biosynthesis of unsaturated fatty acid, circadian rhythm-plant and other metabolic pathways. In the process of P. ginseng seed dormancy release, multiple biological processes, such as unsaturated fatty acid biosynthesis and plant hormone signal transduction, are required to coordinate regulation, which constitutes a complex dormancy release regulation network. Transcriptome analysis and differential gene screening of P. ginseng seeds at different sand storage time laid a foundation for the analysis of P. ginseng seed dormancy release mechanism and molecular breeding.
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Lu Dangshen is the geoherb in Shanxi Province. The content of Codonopsis pilosula polysaccharides (CPP) in Lu Dangshen is more than that in other Codonopsis Radix from other regions. Glycosyltransferase is the key enzyme for the synthesis of bioactive components, such as CPP and tangshenoside I. Based on the transcriptome data of C. pilosula [Codonopsis pilosula (Franch.) Nannf.] from different producing areas, this study carried out functional annotation of GO and KEGG, conservative domain analysis, phylogenetic tree analysis and expression pattern analysis of glycosyltransferase genes in C. pilosula to provides a theoretical basis for exploring the mechanism of genuineness formation in Lu Dangshen. In this study, 98 glycosyltransferase genes were screened and identified, which belonged to GT family 1, GT family 2, GT family 90 and other families. By GO functional annotation, it was found that most of the glycosyltransferase genes had catalytic activity. Analysis of KEGG functional annotation showed that C. pilosula glycosyltransferase was mainly involved in glycan organism and terpenoid and polyketone metabolism. Among them, conserved domain of 42 glycosyltransferase genes in GT family 1 was [X]-W-[2X]-Q-[3X]-[LH]-[5X]-[FLTHCGWNS]-[2X]-E-[4X]-[GVP]-[4X]-P-[4X]-Q-[2X]-[NAK]. Phylogenetic tree analysis based on the glycosyltransferase sequence in Arabidopsis thaliana showed that C. pilosula glycosyltransferases were mainly located in Arabidopsis thaliana UGT73, 72 and 85 branches. Gene expression pattern analysis showed that expression of CpUGT73AH2 was higher in Lu Dangshen than that in Baitiaodang and could respond to drought and low temperature stress. In conclusion, a glycosyltransferase gene CpUGT73AH2, which is involved in the metabolism of terpenoids and polyketides and can respond to environmental stress, was screened from the C. pilosula glycosyltransferase family 1, which was used to further study the role of C. pilosula glycosyltransferase in Lu Dangshen. It laid a theoretical foundation for further study on the role of C. pilosula glycosyltransferase in the formation of Lu Dangshen.
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Objective: To excavate the terpenoid synthesis and metabolism-related gene function and screen the interaction protein and fingerprint analysis of Antrodia cinnamomea mycelium, a cDNA library from A. cinnamomea mycelia was constructed and the EST sequences were analyzed. Methods: The cDNA library from the A. cinnamomea mycelium was constructed by the Gateway technique. A part of EST sequences about the bioinformatics, functional annotation and EST-SSR were analyzed. Results: The cDNA library of the A. cinnamomea mycelium was constructed successfully. The recombinant rate of the cDNA library was 95%, the titer of the library was 6.1 × 106 cfu/mL, the total cloning number was 1.2 × 107 cfu, the length of cDNA was between 300-2 000 bp with an average length of 1 000 bp. The clones were randomly sequenced and 65 valid ESTs were obtained. After being compared in the Genbank database, 45 ESTs had a definite annotation, and 18 ESTs were unnamed and hypothetical protein. The results with GO functional annotation showed that the ESTs involved the cell composition, transport, catalytic activity, regulation functions and etc. It contained 271 SSRs of all the ESTs in total. The nucleotide repeats in A. cinnamomea were abundant, among which dinucleotide and trinucleotide repeat units were more common accounting for 94.23%. Conclusion: The cDNA library from the A. cinnamomea mycelium and its ESTs related biological information were preliminarily identified, which will provide a theoretical foundation for research the mycelium genomics of A. cinnamomea.
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In order to explore MYB transcription factors related to developmental processes and secondary metabolism in Morinda officinalis, we analyzed MoMYB expression based on transcriptome data from three tissues (root, stem and leaf). We used this analysis to provide a theoretical foundation for regulating the metabolism of M. officinalis. RNA-seq data along with the five databases including PFAM and plantTFDB and others were used to screen and classify MoMYB, including GO functional annotation and classification, subcellular localization, signal peptide prediction, conserved motif discovery, and comparative phylogenetic analysis. RT-qPCR was carried out to detect tissue-specific expression differences of MoMYB genes. According to transcriptome data, 109 MoMYB sequences were identified and divided into four classes, containing 51 sequences related to R2R3-MYB. Subcellular localization analysis indicated that a majority of sequences were located in nucleus. Blast2GO analysis showed that 109 MoMYB sequences were classified into three major functional ontologies including molecular function (112), biological processes (76) and cellular components (239). The R2-MYB conserved motif of 51 R2R3-MYB sequences possessed three significantly conserved tryptophan residues, whereas a phenylalanine replaced the first tryptophan in R3-MYB. The results of multiple sequence alignment and phylogenetic analysis revealed that the R2R3-MYB was distributed in all subgroups, apart from the S10, S19 and S21 subgroups. RT-qPCR indicated that several R2R3-MYB genes were differentially expressed among the three tissues, and this finding was consistent with transcriptome data. The 109 MoMYB sequences were annotated and divided into different classes, which lays the foundation for further study on MYB transcriptional factors in M. officinalis.
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Noncoding RNAs (ncRNAs) are an important part of genes and having an important role in human cellular activities and serious diseases. To predict ncRNAs structure, there are many computational intelligence algorithms (CIAs) that are developed in past studies. However, many studies suggested that there were still many structures that are still unpredictable by researchers. In this paper, CIAs algorithms were comprehensively reviewed to predict ncRNAs structures. The advantages and disadvantages of CIA algorithms are briefly mentioned related to ncRNA genes. Moreover, the latest software tools are also compared and reviewed to identify the structure of ncRNAs for mining deep sequencing data. In this study, conventional machine learning algorithms are mainly focused and future trends are also described to predict ncRNAs structure. This paper concludes that there is a need for improving CIA algorithms by using deep learning architectures in terms of layers and computational complexity to predict ncRNAs structures.
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The limited understanding of functional annotation of non-coding RNAs (ncRNAs) has been largely due to the complex functionalities of ncRNAs. They perform a vital part in the operation of the cell. There are many ncRNAs available such as micro RNAs or long non-coding RNAs that play important functions in the cell. In practice, there is a strong binding of the function of RNAs that must be considered to develop computational intelligent techniques. Comprehensive modeling of the structure of an ncRNA is essential that may provide the first clue towards an understanding of its functions. Many computational techniques have been developed to predict ncRNAs structures but few of them focused on the functions of ncRNA genes. Nevertheless, the accuracy of the functional annotation of ncRNAs is still facing computational challenges and results are not satisfactory. Here, many computational intelligent methods were described in this paper to predict the functional annotation of ncRNAs. The current literature review is suggested that there is still a dire need to develop advanced computational techniques for functional annotating of ncRNA genes in terms of accuracy and computational time.
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The implications of germline de novo variants (DNVs) in diseases are well documented. Despite extensive research, inconsistencies between studies remain a challenge, and the distribution and genetic characteristics of DNVs need to be precisely evaluated. To address this issue at the whole-genome scale, a large number of DNVs identified from the whole-genome sequencing of 1,902 healthy trios (i.e., parents and progeny) from the Simons Foundation for Autism Research Initiative study and 20 healthy Korean trios were analyzed. These apparently nonpathogenic DNVs were enriched in functional elements of the genome but relatively depleted in regions of common copy number variants, implying their potential function as triggers of evolution even in healthy groups. No strong mutational hotspots were identified. The pathogenicity of the DNVs was not strongly elevated, reflecting the health status of the cohort. The mutational signatures were consistent with previous studies. This study will serve as a reference for future DNV studies.
Subject(s)
Humans , Autistic Disorder , Cohort Studies , Genome , Parents , VirulenceABSTRACT
Life may have begun in an RNA world, which is supported by increasing evidence of the vital role that RNAs perform in biological systems. In the human genome, most genes actually do not encode proteins; they are noncoding RNA genes. The largest class of noncoding genes is known as long noncoding RNAs (lncRNAs), which are transcripts greater in length than 200 nucleotides, but with no protein-coding capacity. While some lncRNAs have been demonstrated to be key regulators of gene expression and 3D genome organization, most lncRNAs are still uncharacterized. We thus propose several data mining and machine learning approaches for the functional annotation of human lncRNAs by leveraging the vast amount of data from genetic and genomic studies. Recent results from our studies and those of other groups indicate that genomic data mining can give insights into lncRNA functions and provide valuable information for experimental studies of candidate lncRNAs associated with human disease.
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Objective The aim of this study was to investigate the expression of miR-455-5p in epithelial ovarian cancer and its effect on the development of epithelial ovarian cancer. Methods The miRNA expression data of normal ovarian epithelial tis-sues and epithelial ovarian cancer tissues GSE83693 were downloaded from the GEO database. Differential expression analysis was used to obtain differential expression data of miRNAs in epithelial ovarian cancer. The expression of miR-455 -5p was analyzed whether there is difference expression between normal ovarian epithelium and epithelial ovary cancer tissues; qRT-PCR was used to verify the differential expression prediction results; bio-informatics software was used to analyze the KEGG pathway enrichment and GO gene function annotation of miR-455-5p target genes,and to explore the disorders of dyregulated miR-455-5p in the devel-opment of epithelial ovarian cancer. Results A total of 101 cases of differentially expressed miRNAs were screened,34 cases were up-regulated and 67 cases were down-regulated. Among them,miR-455-5p was down-regulated significantly(P<0. 01),and the different fulds were -2. 9019. The results of qRT-PCR showed that the expression of miR-455-5p in epithelial ovarian cancer cells(SKOV-3,OVCAR-3 and A2780)was significantly lower than that in normal ovarian epithelial cells(IOSE-80),and the dif-ferential expression was statistically significant(P<0. 05). The results of KEGG pathway enrichment analysis showed that miR-455-5p regulated target genes mainly involved in five pathways,including TGF-β signaling pathway,Hippo signaling pathway,ECM-receptor interaction,transcriptional dysregulation pathway in cancer,and chronic granule cellular leukemia,which were associated with tumors. GO functional annotation analysis showed that the target genes regulated by miR-455-5p in the above pathway was mainly involved in protein phosphorylation,promoted cell proliferation and migration,inhibited apoptosis,promoted epithelial-mesenchymal transition,regulated transcription and regulated cell cycle,etc. ,which associated with tumorigenesis. Conclusion The expression of miR-455-5p is down-regulated in epithelial ovarian cancer. The miR-455-5p target genes are involved in the pathogenesis and function of epithelial ovarian cancer,and are associated with the development of epithelial ovarian cancer.
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Life may have begun in an RNA world, which is supported by increasing evidence of the vital role that RNAs perform in biological systems. In the human genome, most genes actually do not encode proteins; they are noncoding RNA genes. The largest class of noncoding genes is known as long noncoding RNAs (lncRNAs), which are transcripts greater in length than 200 nucleotides, but with no protein-coding capacity. While some lncRNAs have been demonstrated to be key regulators of gene expression and 3D genome organization, most lncRNAs are still uncharacterized. We thus propose several data mining and machine learning approaches for the functional annotation of human lncRNAs by leveraging the vast amount of data from genetic and genomic studies. Recent results from our studies and those of other groups indicate that genomic data mining can give insights into lncRNA functions and provide valuable information for experimental studies of candidate lncRNAs associated with human disease.
Subject(s)
Humans , Autism Spectrum Disorder , Genetics , Data Mining , Genomics , Machine Learning , RNA, Long Noncoding , Physiology , Support Vector MachineABSTRACT
Objective@#To investigate the functional classification of differentially expressed genes in manganese-poisoned rats and related metabolic pathways, and to provide a reference for the study of the mechanism of manganese poisoning and gene regulation in the prevention and treatment of manganese poisoning.@*Methods@#Six healthy specific pathogen-free male Sprague-Dawley rats were randomly divided into control group and experimental group according to body weight, with 3 rats in each group. Rats in the experimental group were injected intraperitoneally with MnCl2·4H2O (25 mg/kg) at 0.2 ml/100 g once every 48 h, and the control group was injected with phosphate-buffered saline at the same dose. After one month of exposure, the rats were anesthetized and then sacrificed by cardiac puncture blood collection. The striatum was isolated on ice, and RNA was extracted to establish a DNA data library. Whole genome sequencing was used to identify the differentially expressed genes in the rats with manganese poisoning. Gene Ontology functional enrichment analysis and pathway enrichment analysis were performed to investigate the possible metabolic pathways in which the differentially expressed genes may participate.@*Results@#A total of 18439 genes were detected in the striatum of rats, and 17 differentially expressed genes were screened out. Among them, 10 genes were up-regulated, and 7 genes were down-regulated. According to gene function analysis, 164 functional branches and 26 metabolic pathways with high gene enrichment were screened out. The genes were enriched in synaptic signaling, signal transduction, etc., especially behavioral function. The metabolic pathways with high gene enrichment were endocytosis pathway, PI3K-Akt pathway, and neuroactive ligand-receptor interaction pathway, in which the PI3K-Akt pathway had enrichment of the same differentially expressed gene (29 517) as the FoxO signaling pathway and mTOR signaling pathway, and the neuroactive ligand-receptor interaction pathway had enrichment of the same differentially expressed gene (24 415) as the glutamatergic synaptic pathway.@*Conclusion@#The differentially expressed genes in manganese-poisoned rats may influence the susceptibility to manganese poisoning through the PI3K-Akt pathway, mTOR metabolic pathway, or FoxO metabolic pathway, and may be involved in behavioral changes.
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Background: Idesia polycarpa Maxim. var. vestita Diels, a dioecious plant, is widely used for biodiesel due to the high oil content of its fruits. However, it is hard to distinguish its sex in the seedling stage, which makes breeding and production problematic as only the female tree can produce fruits, and the mechanisms underlying sex determination and differentiation remain unknown due to the lack of available genomic and transcriptomic information. To begin addressing this issue, we performed the transcriptome analysis of its female and male flower. Results: 28,668,977 and 22,227,992 clean reads were obtained from the female and male cDNA libraries, respectively. After quality checks and de novo assembly, a total of 84,213 unigenes with an average length of 1179 bp were generated and 65,972 unigenes (78.34%) could be matched in at least one of the NR, NT, Swiss-Prot, COG, KEGG and GO databases. Functional annotation of the unigenes uncovered diverse biological functions and processes, including reproduction and developmental process, which may play roles in sex determination and differentiation. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed many unigenes annotated as metabolic pathways, biosynthesis of secondary metabolites pathways, plant pathogen interaction, and plant hormone signal transduction. Moreover, 29,953 simple sequence repeats were identified using the microsatellite software. Conclusion: This work provides the first detailed transcriptome analysis of female and male flower of I. polycarpa and lays foundations for future studies on the molecular mechanisms underlying flower bud development of I. polycarpa.
Subject(s)
Reproduction/genetics , Salicaceae/genetics , Transcriptome , Sequence Analysis, RNA , Genes, Plant , Microsatellite Repeats , Salicaceae/growth & development , Databases, Genetic , High-Throughput Nucleotide Sequencing , Molecular Sequence AnnotationABSTRACT
Ligusticum chuanxiong is a well-known traditional Chinese medicine plant. The study on its molecular markers development and germplasm resources is very important. In this study, we obtained 24 422 unigenes by assembling transcriptome sequencing reads of L. chuanxiong root. EST-SSR was detected and 4 073 SSR loci were identified. EST-SSR distribution and characteristic analysis results showed that the mono-nucleotide repeats were the main repeat types, accounting for 41.0%. In addition, the sequences containing SSR were functionally annotated in Gene Ontology (GO) and KEGG pathway and were assigned to 49 GO categories, 242 KEGG pathways, among them 2 201 sequences were annotated against Nr database. By validating 235 EST-SSRs,74 primer pairs were ultimately proved to have high quality amplification. Subsequently, genetic diversity analysis, UPGMA cluster analysis, PCoA analysis and population structure analysis of 34 L. chuanxiong germplasm resources were carried out with 74 primer pairs. In both UPGMA tree and PCoA results, L. chuanxiong resources were clustered into two groups, which are believed to be partial related to their geographical distribution. In this study, EST-SSRs in L. chuanxiong was firstly identified, and newly developed molecular markers would contribute significantly to further genetic diversity study, the purity detection, gene mapping, and molecular breeding.
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OBJECTIVE: To proteins in toad venom. To investigate the by proteomic approach. METHODS: The total proteins from the ear-side gland of toad were digested by trypsin, and the peptides were further analyzed by the NanoLC-linear trap quadropole (LTQ)-Orbitrap Velos Pro.. The raw data acquired by mass spectrometer were imported into MaxQuant software for the identification of peptides and proteins. The proteins were categorized based on gene ontology annotation in biological process, cellular component and molecular function. RESULTS: A total of 407 protein groups and 880 peptides were identified. There were 76 pathways associated with the identified proteins in toad venom, including the 5-HT receptor mediated signaling pathway, beta adrenergic receptor signaling pathway, blood coagulation, cadherin signaling pathway, cholesterol biosynthesis, etc.. CONCLUSION: This study lays the foundation for further exploration of the proteins in toad venom and their functions.
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BACKGROUND: The aim of this study was to explore epilepsy-related mechanism so as to figure out the possible targets for epilepsy treatment. METHODS: The gene expression profile dataset GES32534 was downloaded from Gene Expression Omnibus database. We identified the differentially expressed genes (DEGs) by Affy package. Then the DEGs were used to perform gene ontology (GO) and pathway enrichment analyses. Furthermore, a protein-protein interaction (PPI) network was constructed with the DEGs followed by co-expression modules construction and analysis. RESULTS: Total 420 DEGs were screened out, including 214 up-regulated and 206 down-regulated genes. Functional enrichment analysis revealed that down-regulated genes were mainly involved in the process of immunity regulation and biological repairing process while up-regulated genes were closely related to transporter activity. PPI network analysis showed the top ten genes with high degrees were all down-regulated, among which FN1 had the highest degree. The up-regulated and down-regulated DEGs in the PPI network generated two obvious sub-co-expression modules, respectively. In up-co-expression module, SCN3B (sodium channel, voltage gated, type III beta subunit) was enriched in GO:0006814 ~ sodium ion transport. In down-co-expression module, C1QB (complement C1s), CIS (complement component 1, S subcomponent) and CFI (complement factor I) were enriched in GO:0006955 ~ immune response. CONCLUSION: The immune response and complement system play a major role in the pathogenesis of epilepsy. Additionally, C1QB, C1S, CFI, SCN3B and FN1 may be potential therapeutic targets for epilepsy.
Subject(s)
Humans , Epilepsy/genetics , Epilepsy/therapy , Gene Expression Profiling/methods , Transcriptome , Databases, Genetic , Down-Regulation , Gene Ontology , Gene Regulatory Networks , Gene Targeting , Protein Interaction Maps , Up-RegulationABSTRACT
Schistosoma mansoni is one of the three main causative agents of human schistosomiasis, a major health problem with a vast socio-economic impact. Recent advances in the proteomic analysis of schistosomes have revealed that peptidases are the main virulence factors involved in the pathogenesis of this disease. In this context, evolutionary studies can be applied to identify peptidase families that have been expanded in genomes over time in response to different selection pressures. Using a phylogenomic approach, we searched for expanded endopeptidase families in the S. mansoni predicted proteome with the aim of contributing to the knowledge of such enzymes as potential therapeutic targets. We found three endopeptidase families that comprise leishmanolysins (metallopeptidase M8 family), cercarial elastases (serine peptidase S1 family) and cathepsin D proteins (aspartic peptidase A1 family). Our results suggest that the Schistosoma members of these families originated from successive gene duplication events in the parasite lineage after its diversification from other metazoans. Overall, critical residues are conserved among the duplicated genes/proteins. Furthermore, each protein family displays a distinct evolutionary history. Altogether, this work provides an evolutionary view of three S. mansoni peptidase families, which allows for a deeper understanding of the genomic complexity and lineage-specific adaptations potentially related to the parasitic lifestyle.
Subject(s)
Animals , Cathepsin D/genetics , Metalloproteases/genetics , Pancreatic Elastase/genetics , Schistosoma mansoni/enzymology , Biological Evolution , Phylogeny , Proteomics , Schistosoma mansoni/genetics , Schistosoma mansoni/pathogenicityABSTRACT
The biological interpretation of two-dimensional (2D) gel electrophoresis experiments is a key step toward understanding the functions of biological systems. We here present a web-based integrated database, called 2DSpotDB, for the management of proteome data derived from several pathogens. The 2DSpotDB was established as a part of the management of a pathogen proteome project at the Korea National Institute of Health. The goals of the 2DSpotDB implementation are to store and define important pathogen genes, retrieve information obtained by 2D polyacrylamide gel electrophoresis and mass spectrometry, and create an integrated system to provide pathogen proteome information for biological scientists. This database currently contains 14 gels and information on 387 protein spots, among which 329 proteins were identified and annotated.
Subject(s)
Acrylic Resins , Data Mining , Electrophoresis , Electrophoresis, Gel, Two-Dimensional , Electrophoresis, Polyacrylamide Gel , Gels , Korea , Mass Spectrometry , Proteins , ProteomeABSTRACT
The EST Knowledge Integrated System, EKIS (http://ekis.kribb.re.kr), was established as a part of Korea's Ministry of Education, Science and Technology initiative for genome sequencing and application research of the biological model organisms (GEAR) project. The goals of the EKIS are to collect EST information from GEAR projects and make an integrated database to provide transcriptomic and metabolomic information for biological scientists. The EKIS constitutes five independent categories and several retrieval systems in each category for incorporating massive EST data from high-throughput sequencing of 65 different species. Through the EKIS database, scientists can freely access information including BLAST functional annotation as well as Genechip and pathway information for KEGG. By integrating complex data into a framework of existing EST knowledge information, the EKIS provides new insights into specialized metabolic pathway information for an applied industrial material.
Subject(s)
Data Mining , Expressed Sequence Tags , Genome , Metabolic Networks and Pathways , Metabolomics , Models, BiologicalABSTRACT
Serial analysis of gene expression (SAGE) technology produces large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in these gene sets. We present an interactive web-based tool, called Gene Class, which allows functional annotation of SAGE data using the Gene Ontology (GO) database. This tool performs searches in the GO database for each SAGE tag, making associations in the selected GO category for a level selected in the hierarchy. This system provides user-friendly data navigation and visualization for mapping SAGE data onto the gene ontology structure. This tool also provides graphical visualization of the percentage of SAGE tags in each GO category, along with confidence intervals and hypothesis testing.