Annotation Terms Research Articles

De novo transcriptome assembly of Ipomoea nil using Illumina sequencing for gene discovery and SSR marker identification.

Ipomoea nil is widely used as an ornamental plant due to its abundance of flower color, but the limited transcriptome and genomic data hinder research on it. Using illumina platform, transcriptome profiling of I. nil was performed through high-throughput sequencing, which was proven to be a rapid and cost-effective means to characterize gene content. Our goal is to use the resulting information to facilitate the relevant research on flowering and flower color formation in I. nil. In total, 268 million unique illumina RNA-Seq reads were produced and used in the transcriptome assembly. These reads were assembled into 220,117 contigs, of which 137,307 contigs were annotated using the GO and KEGG database. Based on the result of functional annotations, a total of 89,781 contigs were assigned 455,335 GO term annotations. Meanwhile, 17,418 contigs were identified with pathway annotation and they were functionally assigned to 144 KEGG pathways. Our transcriptome revealed at least 55 contigs as probably flowering-related genes in I. nil, and we also identified 25 contigs that encode key enzymes in the phenylpropanoid biosynthesis pathway. Based on the analysis relating to gene expression profiles, in the phenylpropanoid biosynthesis pathway of I. nil, the repression of lignin biosynthesis might lead to the redirection of the metabolic flux into anthocyanin biosynthesis. This may be the most likely reason that I. nil has high anthocyanins content, especially in its flowers. Additionally, 15,537 simple sequence repeats (SSRs) were detected using the MISA software, and these SSRs will undoubtedly benefit future breeding work. Moreover, the information uncovered in this study will also serve as a valuable resource for understanding the flowering and flower color formation mechanisms in I. nil.

Chronic toxicological effects of β-diketone antibiotics on Zebrafish (Danio rerio) using transcriptome profiling of deep sequencing.

Transcriptome analysis is important for interpreting the functional elements of the genome and revealing the molecular constituents of cells and tissues. Herein, differentially transcribed genes were identified by deep sequencing after zebrafish (Danio rerio) were exposed to β-diketone antibiotics (DKAs); 23,129 and 23,550 mapped genes were detected in control and treatment groups, a total of 3238 genes were differentially expressed between control and treatment groups. Of these genes, 328 genes (213 up- and 115 down-regulation) had significant differential expression (p < 0.05) and an expression ratio (control/treatment) of >2 or <0.5. Additionally, we performed Gene Ontology (GO) category and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and found 266 genes in the treatment group with annotation terms linked to the GO category. A total of 77 differentially expressed transcriptional genes were associated with 132 predicted KEGG metabolic pathways. Serious liver tissue damage was reflected and consistent with the differences in genetic classification and function from the transcriptome analysis. These results enhance our understanding of zebrafish developmental processes under exposure to DKA stress. © 2015 Wiley Periodicals, Inc. Environ Toxicol 31: 1357-1371, 2016.

Retraction note: Reanalysis of the gene expression profile in chronic pancreatitis via bioinformatics methods.

Diagnosis at an early stage of chronic pancreatitis (CP) is challenging. It has been reported that microRNAs (miRNAs) are increasingly found and applied as targets for the diagnosis and treatment of various cancers. However, to the best of our knowledge, few published papers have described the role of miRNAs in the diagnosis of CP. We downloaded gene expression profile data from the Gene Expression Omnibus and identified differentially expressed genes (DEGs) between CP and normal samples of Harlan mice and Jackson Laboratory mice. Common DEGs were filtered out, and the semantic similarities of gene classes were calculated using the GOSemSim software package. The gene class with the highest functional consistency was selected, and then the Lists2Networks web-based system was used to analyse regulatory relationships between miRNAs and gene classes. The functional enrichment of the gene classes was assessed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway annotation terms. A total of 405 common upregulated DEGs and 7 common downregulated DEGs were extracted from the two kinds of mice. Gene cluster D was selected from the common upregulated DEGs because it had the highest semantic similarity. miRNA 124a (miR-124a) was found to have a significant regulatory relationship with cluster D, and DEGs such as CHSY1 and ABCC4 were found to be regulated by miR-124a. The GO term of response to DNA damage stimulus and the pathway of Escherichia coli infection were significantly enriched in cluster D. DNA damage and E. coli infection might play important roles in CP pathogenesis. In addition, miR-124a might be a potential target for the diagnosis and treatment of CP.

RNA-Seq transcriptome analysis of maize inbred carrying nicosulfuron-tolerant and nicosulfuron-susceptible alleles.

Postemergence applications of nicosulfuron can cause great damage to certain maize inbred lines and hybrids. Variation among different responses to nicosulfuron may be attributed to differential rates of herbicide metabolism. We employed RNA-Seq analysis to compare transcriptome responses between nicosulfuron-treated and untreated in both tolerant and susceptible maize plants. A total of 71.8 million paired end Illumina RNA-Seq reads were generated, representing the transcription of around 40,441 unique reads. About 345,171 gene ontology (GO) term assignments were conducted for the annotation in terms of biological process, cellular component and molecular function categories, and 6413 sequences with 108 enzyme commission numbers were assigned to 134 predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways. Digital gene expression profile (DGE) analysis using Solexa sequencing was performed within the susceptible and tolerant maize between the nicosulfuron-treated and untreated conditions, 13 genes were selected as the candidates most likely involved in herbicide metabolism, and quantitative RT-PCR validated the RNA-Seq results for eight genes. This transcriptome data may provide opportunities for the study of sulfonylurea herbicides susceptibility emergence of Zea mays.

De Novo Assembly and Characterization of the Transcriptome and Molecular Discovery in Capsicum Annuum L. R597

Pepper (Capsicum spp.) is one of the most economically and agriculturally important vegetable crops on the globe. However, the genomic resources of Pepper (Capsicum spp.) were scarcity, and only a few nucleotide sequences could be obtained in public databases. In this study, we examined transcriptome in C.annuum R597. More than 66million of high quality reads were generated using Illumina paired-end sequencing technology. Approximately 6 Gbp of data were generated, and de novo assembled into 96, 340 unigenes, with an N50 of 989 bp. The average length of unigenes was 651 bp. Based on sequence similarity search with known protein database, 51, 053 (53.0%) showed significant similarity to know proteins in Nr database, and 33, 766 (35.0%) had BLAST hits in Swiss-Prot database. Among the annotated unigenes, 26, 050 of C.annuum R597 unigenes were assigned to GO term annotation, and 28, 428 were found to have COG classification. In addition, a total of 14, 279 unigenes were assigned to 270 KEGG pathways. Moreover, a total 5, 960 SNPs, 5, 426 SSRs, and 2, 199 InDels were detected as potential molecular markers in pepper. Our study enriches the genomic resources of Pepper (Capsicum spp.) and provides powerful information for future studies. The availability of this ample amount of information about the transcriptome and SSRs, SNPs and InDels in pepper could server as valuable for studies on the agronomic traits and identification of molecular mechanism such plant resistance.

Transcriptome responses to heat stress in hypothalamus of a meat-type chicken.

BackgroundHeat stress has resulted in great losses in poultry production. To address this issue, we systematically analyzed chicken hypothalamus transcriptome responses to thermal stress using a 44 k chicken Agilent microarray,MethodsHypothalamus samples were collected from a control group reared at 25°C, a heat-stress group treated at 34°C for 24 h, and a temperature-recovery group reared at 25°C for 24 h following a heat-stress treatment. We compared the expression profiles between each pair of the three groups using microarray data.ResultsA total of 1,967 probe sets were found to be differentially expressed in the three comparisons with P < 0.05 and a fold change (FC) higher than 1.5, and the genes were mainly involved in self-regulation and compensation required to maintain homeostasis. Consistent expression results were found for 11 selected genes by quantitative real-time PCR. Thirty-eight interesting differential expression genes were found from GO term annotation and those genes were related to meat quality, growth, and crucial enzymes. Using these genes for genetic network analysis, we obtained three genetic networks. Moreover, the transcripts of heat-shock protein, including Hsp 40 and Hsp 90, were significantly altered in response to thermal stress.ConclusionsThis study provides a broader understanding of molecular mechanisms underlying stress response in chickens and discovery of novel genes that are regulated in a specific thermal-stress manner.Electronic supplementary materialThe online version of this article (doi:10.1186/s40104-015-0003-6) contains supplementary material, which is available to authorized users.

PUFA diets alter the microRNA expression profiles in an inflammation rat model

Omega-3 and -6 polyunsaturated fatty acids (PUFAs) can directly or indirectly regulate immune homeostasis via inflammatory pathways, and components of these pathways are crucial targets of microRNAs (miRNAs). However, no study has examined the changes in the miRNA transcriptome during PUFA-regulated inflammatory processes. Here, we established PUFA diet-induced autoimmune-prone (AP) and autoimmune-averse (AA) rat models, and studied their physical characteristics and immune status. Additionally, miRNA expression patterns in the rat models were compared using microarray assays and bioinformatic methods. A total of 54 miRNAs were differentially expressed in common between the AP and the AA rats, and the changes in rno-miR-19b-3p, -146b-5p and -183-5p expression were validated using stem-loop reverse transcription-quantitative polymerase chain reaction. To better understand the mechanisms underlying PUFA-regulated miRNA changes during inflammation, computational algorithms and biological databases were used to identify the target genes of the three validated miRNAs. Furthermore, Gene Ontology (GO) term annotation and KEGG pathway analyses of the miRNA targets further allowed to explore the potential implication of the miRNAs in inflammatory pathways. The predicted PUFA-regulated inflammatory pathways included the Toll-like receptor (TLR), T cell receptor (TCR), NOD-like receptor (NLR), RIG-I-like receptor (RLR), mitogen-activated protein kinase (MAPK) and the transforming growth factor-β (TGF-β) pathway. This study is the first report, to the best of our knowledge, on in vivo comparative profiling of miRNA transcriptomes in PUFA diet-induced inflammatory rat models using a microarray approach. The results provide a useful resource for future investigation of the role of PUFA-regulated miRNAs in immune homeostasis.

ENViz: a Cytoscape App for integrated statistical analysis and visualization of sample-matched data with multiple data types.

Summary: ENViz (Enrichment Analysis and Visualization) is a Cytoscape app that performs joint enrichment analysis of two types of sample matched datasets in the context of systematic annotations. Such datasets may be gene expression or any other high-throughput data collected in the same set of samples. The enrichment analysis is done in the context of pathway information, gene ontology or any custom annotation of the data. The results of the analysis consist of significant associations between profiled elements of one of the datasets to the annotation terms (e.g. miR-19 was associated to the cell-cycle process in breast cancer samples). The results of the enrichment analysis are visualized as an interactive Cytoscape network.Availability and implementation: ENViz is publically available in the Cytoscape App Store (http://apps.cytoscape.org/apps/enviz). For additional information please visit the tool website: http://www.agilent.com/labs/research/compbio/enviz/Contact: israel_steinfeld@agilent.com

RNA-Seq screening of differentially-expressed genes during somatic embryogenesis in Fragaria × ananassa Duch. ‘Benihopp’

SUMMARYSomatic embryogenesis is an important model system for studies on embryo development. In order to gain a better understanding of the molecular mechanisms underlying somatic embryogenesis, RNA-Seq data were generated from non-embryogenic callus, embryogenic callus, somatic embryos, early-germinated somatic embryos, and late-germinated somatic embryos of Fragaria X ananassa Duch. ‘Benihopp’. Totals of 21 x 106–34 x 106 high-quality reads were obtained from the various RNA-seq libraries, with average lengths of 87–94 base pairs. A total of 81% of the reads were mapped to the reference Fragaria vesca genome and 946 differentially-expressed genes were identified, most of which were associated with non-embryonic callus. An analysis of the expression data using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database indicated that the gene ontology (GO) classes with the highest representation were ‘metabolic process’ and ‘metabolism’. In total, 38 transcription factors were identified, including members of the AP2/EREBP and MYB families. Three genes related to hormone signalling pathways were identified: one gene encoding the AUXIN RESISTANT 1 (AUX1) protein and two genes encoding pathogenesis- related 1 (PR1) proteins. During somatic embryogenesis, levels of transcripts corresponding to the AUX1 protein increased, while those corresponding to PR1 decreased. Non-embryogenic callus showed the greatest difference in transcriptome profile compared with the other samples, and the GO annotation term ‘metabolism pathways’ was particularly common in the data associated with strawberry somatic embryogenesis. Based on the RNA-seq data, we speculate that the phytohormones auxin and salicylic acid may play important roles during somatic embryogenesis. Our transcriptome dataset represents a valuable resource for researchers studying somatic embryogenesis and has the potential to provide new insights into the underlying mechanisms of molecular regulation.

レシピ用語の定義とその自動認識のためのタグ付与コーパスの構築

レシピ用語の定義とその自動認識のためのタグ付与コーパスの構築

A computational platform to maintain and migrate manual functional annotations for BioCyc databases.

BackgroundBioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database.ResultsWe have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers.ConclusionsAutomating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-014-0115-1) contains supplementary material, which is available to authorized users.

Aberrantly expressed long noncoding RNAs in human intervertebral disc degeneration: a microarray related study

IntroductionIn addition to the well-known short noncoding RNAs such as microRNAs (miRNAs), increasing evidence suggests that long noncoding RNAs (lncRNAs) act as key regulators in a wide aspect of biologic processes. Dysregulated expression of lncRNAs has been demonstrated being implicated in a variety of human diseases. However, little is known regarding the role of lncRNAs with regards to intervertebral disc degeneration (IDD). In the present study we aimed to determine whether lncRNAs are differentially expressed in IDD.MethodsAn lncRNA-mRNA microarray analysis of human nucleus pulposus (NP) was employed. Bioinformatics prediction was also applied to delineate the functional roles of the differentially expressed lncRNAs. Several lncRNAs and mRNAs were chosen for quantitative real-time PCR (qRT-PCR) validation.ResultsMicroarray data profiling indicated that 116 lncRNAs (67 up and 49 down) and 260 mRNAs were highly differentially expressed with an absolute fold change greater than ten. Moreover, 1,052 lncRNAs and 1,314 mRNAs were differentially expressed in the same direction in at least four of the five degenerative samples with fold change greater than two. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for the differentially expressed mRNAs indicated a number of pathways, such as extracellular matrix (ECM)-receptor interaction. A coding-noncoding gene co-expression (CNC) network was constructed for the ten most significantly changed lncRNAs. Annotation terms of the coexpressed mRNAs were related to several known degenerative alterations, such as chondrocyte differentiation. Moreover, lncRNAs belonging to a particular subgroup were identified. Functional annotation for the corresponding nearby coding genes showed that these lncRNAs were mainly associated with cell migration and phosphorylation. Interestingly, we found that Fas-associated protein factor-1 (FAF1), which potentiates the Fas-mediated apoptosis and its nearby enhancer-like lncRNA RP11-296A18.3, were highly expressed in the degenerative discs. Subsequent qRT-PCR results confirmed the changes.ConclusionsThis is the first study to demonstrate that aberrantly expressed lncRNAs play a role in the development of IDD. Our study noted that up-regulated RP11-296A18.3 highly likely induced the over-expression of FAF1, which eventually promoted the aberrant apoptosis of disc cells. Such findings further broaden the understanding of the etiology of IDD.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-014-0465-5) contains supplementary material, which is available to authorized users.

Flies who cannot take the heat: genome-wide gene expression analysis of temperature-sensitive lethality in an inbred line of Drosophila melanogaster.

Fitness decreases associated with inbreeding depression often become more pronounced in a stressful environment. The functional genomic causes of these inbreeding-by-environment (I×E) interactions, and of inbreeding depression in general, are poorly known. To further our understanding of I×E interactions, we performed a genome-wide gene expression study of a single inbred line that suffers from temperature-sensitive lethality. We confirmed that increased differential expression between the thermosensitive line and the control line occurs at the restrictive temperature. This demonstrates that I×E interactions in survival are reflected in similar I×E interactions at the gene expression level. To make an impression of the cellular response associated with the lethal effect, we analysed all functional annotation terms that were overrepresented among the differentially expressed genes. Some sets of differentially expressed genes function in the general stress response, and these are more likely to also be differentially expressed in other studies of inbreeding, inbreeding depression, immunity and heat stress. Other sets of differentially expressed genes are shared with studies of gene expression in inbred lines, but not studies of the response to extrinsic stress, and represent a general transcriptomic signature of inbreeding. Finally, some sets of genes have an annotation that is not reported in other studies. These we consider to be candidates for the genes harbouring the mutations responsible for the thermosensitive phenotype, as these mutations are expected to be unique to this line. These genes may also serve as candidate QTL in studies of thermal tolerance and heat resistance.

A Classifier System for Determining the Functions of Un-Annotated Proteins Based on Their Semantic Similarities with Gene Ontology Annotation Terms

A Classifier System for Determining the Functions of Un-Annotated Proteins Based on Their Semantic Similarities with Gene Ontology Annotation Terms

An approach to identify SNPs in the gene encoding acetyl-CoA acetyltransferase-2 (ACAT-2) and their proposed role in metabolic processes in pig.

The novel liver protein acetyl-CoA acetyltransferase-2 (ACAT2) is involved in the beta-oxidation and lipid metabolism. Its comprehensive relative expression, in silico non-synonymous single nucleotide polymorphism (nsSNP) analysis, as well as its annotation in terms of metabolic process with another protein from the same family, namely, acetyl-CoA acyltransferase-2 (ACAA2) was performed in Sus scrofa. This investigation was conducted to understand the most important nsSNPs of ACAT2 in terms of their effects on metabolic activities and protein conformation. The two most deleterious mutations at residues 122 (I to V) and 281 (R to H) were found in ACAT2. Validation of expression of genes in the laboratory also supported the idea of differential expression of ACAT2 and ACAA2 conceived through the in silico analysis. Analysis of the relative expression of ACAT2 and ACAA2 in the liver tissue of Jeju native pig showed that the former expressed significantly higher (P<0.05). Overall, the computational prediction supported by wet laboratory analysis suggests that ACAT2 might contribute more to metabolic processes than ACAA2 in swine. Further associations of SNPs in ACAT2 with production traits might guide efforts to improve growth performance in Jeju native pigs.

Using Targeted Chromatin Regulators to Engineer Combinatorial and Spatial Transcriptional Regulation

The transcription of genomic information in eukaryotes is regulated in large part by chromatin. How a diverse array of chromatin regulator (CR) proteins with different functions and genomic localization patterns coordinates chromatin activity to control transcription remains unclear. Here, we take a synthetic biology approach to decipher the complexity of chromatin regulation by studying emergent transcriptional behaviors from engineered combinatorial, spatial, and temporal patterns of individual CRs. We fuse 223 yeast CRs to programmable zinc finger proteins. Site-specific and combinatorial recruitment of CRs to distinct intralocus locations reveals a range of transcriptional logic and behaviors, including synergistic activation, long-range and spatial regulation, and gene expression memory. Comparing these transcriptional behaviors with annotated CR complex and function terms provides design principles for the engineering of transcriptional regulation. This work presents a bottom-up approach to investigating chromatin-mediated transcriptional regulation and introduces chromatin-based components and systems for synthetic biology and cellular engineering.

Transcriptome-based analysis of kidney gene expression changes associated with diabetes in OVE26 mice, in the presence and absence of losartan treatment.

Diabetes is among the most common causes of end-stage renal disease, although its pathophysiology is incompletely understood. We performed next-generation sequencing-based transcriptome analysis of renal gene expression changes in the OVE26 murine model of diabetes (age 15 weeks), relative to non-diabetic control, in the presence and absence of short-term (seven-day) treatment with the angiotensin receptor blocker, losartan (n = 3–6 biological replicates per condition). We detected 1438 statistically significant changes in gene expression across conditions. Of the 638 genes dysregulated in diabetes relative to the non-diabetic state, >70% were downregulation events. Unbiased functional annotation of genes up- and down-regulated by diabetes strongly associated (p<1×10−8) with terms for oxidative stress and for endoplasmic reticulum stress/protein folding. Most of the individual gene products up- or down-regulated with diabetes were unaffected by losartan treatment; however, of the gene products dysregulated in diabetes and influenced by losartan treatment, the vast majority of changes were in the direction of amelioration rather than exacerbation of the diabetic dysregulation. This group of losartan-protected genes associated strongly with annotation terms for endoplasmic reticulum stress, heat shock proteins, and chaperone function, but not oxidative stress; therefore, the losartan-unaffected genes suggest avenues for additional therapeutic opportunity in diabetes. Interestingly, the gene product most highly upregulated by diabetes (>52-fold), encoded by the cationic amino acid transporter Slc7a12, and the gene product most highly downregulated by diabetes (>99%) – encoded by the “pseudogene” Gm6300 – are adjacent in the murine genome, are members of the SLC7 gene family, and are likely paralogous. Therefore, diabetes activates a near-total genetic switch between these two paralogs. Other individual-level changes in gene expression are potentially relevant to diabetic pathophysiology, and novel pathways are suggested. Genes unaffected by diabetes alone but exhibiting increased renal expression with losartan produced a signature consistent with malignant potential.

CategoryCompare, an analytical tool based on feature annotations.

Assessment of high-throughput—omics data initially focuses on relative or raw levels of a particular feature, such as an expression value for a transcript, protein, or metabolite. At a second level, analyses of annotations including known or predicted functions and associations of each individual feature, attempt to distill biological context. Most currently available comparative- and meta-analyses methods are dependent on the availability of identical features across data sets, and concentrate on determining features that are differentially expressed across experiments, some of which may be considered “biomarkers.” The heterogeneity of measurement platforms and inherent variability of biological systems confounds the search for robust biomarkers indicative of a particular condition. In many instances, however, multiple data sets show involvement of common biological processes or signaling pathways, even though individual features are not commonly measured or differentially expressed between them. We developed a methodology, categoryCompare, for cross-platform and cross-sample comparison of high-throughput data at the annotation level. We assessed the utility of the approach using hypothetical data, as well as determining similarities and differences in the set of processes in two instances: (1) denervated skin vs. denervated muscle, and (2) colon from Crohn's disease vs. colon from ulcerative colitis (UC). The hypothetical data showed that in many cases comparing annotations gave superior results to comparing only at the gene level. Improved analytical results depended as well on the number of genes included in the annotation term, the amount of noise in relation to the number of genes expressing in unenriched annotation categories, and the specific method in which samples are combined. In the skin vs. muscle denervation comparison, the tissues demonstrated markedly different responses. The Crohn's vs. UC comparison showed gross similarities in inflammatory response in the two diseases, with particular processes specific to each disease.

Creating a test corpus for term extractors through term annotation

In this paper, we describe a methodology used to create a test corpus for the evaluation of term extractors. This methodology relies on term annotation: terms in a corpus on automotive engineering are selected based on specific criteria pertaining to the terminological setting as well as linguistic and formal properties of terms and term variations. The test corpus accounts for the variety of ways in which terms are realized in running text, and provides a means of automatically evaluating the relevance of term candidate lists produced by term extractors. Due to the XML annotation scheme used, the corpus can be customized, e.g. by filtering out some of the annotated terms based on the type of term or term variation, or frequency. In this paper, we focus on the methodological aspects of this work.

Hierarchical representation of video sequences for annotation

Video annotation is an important issue in video content management systems. Rapid growth of the digital video data has created a need for efficient and reasonable mechanisms that can ease the annotation process. In this paper, we propose a novel hierarchical clustering based system for video annotation. The proposed system generates a top-down hierarchy of the video streams using hierarchical k-means clustering. A tree-based structure is produced by dividing the video recursively into sub-groups, each of which consists of similar content. Based on the visual features, each node of the tree is partitioned into its children using k-means clustering. Each sub-group is then represented by its key frame, which is selected as the closest frame to the centroids of the corresponding cluster, and then can be displayed at the higher level of the hierarchy. The experiments show that very good hierarchical view of the video sequences can be created for annotation in terms of efficiency.