Annotation of orthologous genes in Tunnus thynnus and T.albacore species

Albacore and Atlantic Bluefin tuna are two pelagic fish. Atlantic Bluefin tuna is included in the IUCN red list of threatened species and albacore is considered to be near threatened, so conservation plans are needed. However, no genomic resources are available for any of them. In this study, to better understand their transcriptome we functionally annotated orthologous genes. In all, 159 SNPs distributed in 120 contigs of the muscle transcriptome were analyzed. Genes were predicted for 98 contigs (81.2%) using the bioinformatics tool BLAST. In addition, another bioinformatics tool, BLAST2GO was used in order to achieve GO terms for the genes, in which 41 sequences were given a biological process, and 39 sequences were given a molecular process. The most repeated biological process was metabolism and it is important that no cellular process was given in any of the sequences. The most abundant molecular process was binding and very few catalytic activity processes were given. From the initial 159 SNPs, 40 were aligned with a sequence in the database after BLAST2GO was run, and were polymorphic in Atlantic Bluefin tuna and monomorphic in albacore. From these 40 SNPs, 24 were located in an open reading frame of which four were non-synonymous and 20 were synonymous and 16 were not located in a known open reading frame,. This study provides information for better understanding the ecology and evolution of these species and this is important in order to establish a proper conservation plan and an appropriate management.

Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca)

A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

Learning based automatic face annotation for arbitrary poses and expressions from frontal images only

Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based approach for the automatic annotation of visually deformable objects from a single annotated frontal image is presented and demonstrated on the example of automatically annotating face images that can be used for building AAMs for fitting and tracking. This approach employs the idea of initially learning the correspondences between landmarks in a frontal image and a set of training images with a face in arbitrary poses. Using this learner, virtual images of unseen faces at any arbitrary pose for which the learner was trained can be reconstructed by predicting the new landmark locations and warping the texture from the frontal image. View-based AAMs are then built from the virtual images and used for automatically annotating unseen images, including images of different facial expressions, at any random pose within the maximum range spanned by the virtually reconstructed images. The approach is experimentally validated by automatically annotating face images from three different databases. © 2009 IEEE.

Expressed sequence tags from the zhikong scallop (Chlamys farreri): Discovery and annotation of host-defense genes

A high-quality cDNA library was constructed from whole body tissues of the zhikong scallop, Chlamys farreri, challenged by Listonella anguillarum. A total of 5720 clones were sequenced, yielding 5123 expressed sequence tags (ESTs). Among the 3326 unique genes identified, 2289 (69%) genes had no significant (E-value < 1e-5) matches to known sequences in public databases and 194 (6%) matched proteins of unknown functions. The remaining 843 (25%) genes that exhibited homology with genes of known functions, showed broad involvement in metabolic processes (31%), cell structure and motility (20%), gene and protein expression (12%), cell signaling and cell communication (8%), cell division (4%), and notably, 25% of those genes were related to immune function. They included stress response genes, complement-like genes, proteinase and proteinase inhibitors, immune recognition receptors and immune effectors. The EST collection obtained in this study provides a useful resource for gene discovery and especially for the identification of host-defense genes and systems in scallops and other molluscs. (C) 2009 Elsevier Ltd. All rights reserved.

Discovery of immune related factors in Fenneropenaeus chinensis by annotation of ESTs

A total of 10446 expressed sequence tags (ESTs) are obtained by a large-scale sequencing of a cDNA library from cephalothorax of adult Fenneropenaeus chinensis. An EST analysis platform was built up based on local computers and bioinformatic techniques were used to annotate these ESTs in order to promptly find possible functional genes, especially for immune related factors. About 4% of the ESTs show similarity to the coding sequences of such factors, including lectin, serine protease, serpin, lysozyme, etc. These ESTs provide a partial profile of the immune system in F. chinensis and useful information for further study on these genes.

Discovery of genes involved in defense/immunity functions in a haemocytes cDNA library from Fenneropenaeus chinensis by ESTs annotation

Crustacean haemocytes play important roles in the host immune response including recognition, phagocytosis, melanization, cytotoxicity and inter-cellular signal communication. Expressed sequence tags (ESTs) analysis is proved to be an efficient approach not only for gene discovery, but also for gene expression profiles performance. In order to further understand the innate immune system and defense mechanisms of Chinese shrimp at molecular level, complementary DNA library is constructed from the haemocyte tissue of Fenneropenaeus chinensis. A total of 2371 cDNA clones are successfully sequenced and the average sequence length is 460 bp. About 50% are identified as orthologs of known genes from other organisms by BLASTx and BLASTn program. By sequences comparability and analysis, 34 important genes including 177 ESTs are identified that may be involved in defense or immune functions in shrimp based on the known knowledge. These genes are categorized into five categories according to their putative functions in shrimp immune system: 13 genes are different types of antimicrobial peptides (AMP, penaeidin, antilipopolysaccharide factor, etc.), and their proportion is about 3 8%; 11 genes belong to prophenoloxidase system (prophenoloxidase, serine proteinase, serine proteinase inhibitor, etc.), and their proportion is about 32%; five genes have high homology with clotting protein (lectin, transglutaminase, etc), and their proportion is about 15%; three genes may be involved in inter-cell signal communication (peroxinectin, integrin), and their proportion is about 9%; two genes have been identified to be chaperone proteins (Hsc70, thioredoxin peroxidase), and their proportion is about 6%. These EST sequences enrich our understanding of the immune genes of F chinensis and will help farther experimental research into immune factors and improve our knowledge of the immune mechanisms of shrimp. (c) 2007 Elsevier B.V. All rights reserved.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Phenex: ontological annotation of phenotypic diversity.

BACKGROUND: Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and character-by-taxon matrices. CONCLUSIONS/SIGNIFICANCE: Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology.

Character-angle based video annotation

A video annotation system includes clips organization, feature description and pattern determination. This paper aims to present a system for basketball zone-defence detection. Particularly, a character-angle based descriptor for feature description is proposed. The well-performed experimental results in basketball zone-defence detection demonstrate that it is robust for both simulations and real-life cases, with less sensitivity to the distribution caused by local translation of subprime defenders. Such a framework can be easily applied to other team-work sports.