Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research

SUMMARY: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. AVAILABILITY: Blast2GO is freely available via Java Web Start at http://www.blast2go.de. SUPPLEMENTARY MATERIAL: http://www.blast2go.de -> Evaluation.     

Complete reannotation of the Arabidopsis genome: methods, tools, protocols and the final release

Background

Since the initial publication of its complete genome sequence, Arabidopsis thaliana has become more important than ever as a model for plant research. However, the initial genome annotation was submitted by multiple centers using inconsistent methods, making the data difficult to use for many applications.

Results

Over the course of three years, TIGR has completed its effort to standardize the structural and functional annotation of the Arabidopsis genome. Using both manual and automated methods, Arabidopsis gene structures were refined and gene products were renamed and assigned to Gene Ontology categories. We present an overview of the methods employed, tools developed, and protocols followed, summarizing the contents of each data release with special emphasis on our final annotation release (version 5).

Conclusion

Over the entire period, several thousand new genes and pseudogenes were added to the annotation. Approximately one third of the originally annotated gene models were significantly refined yielding improved gene structure annotations, and every protein-coding gene was manually inspected and classified using Gene Ontology terms.     

Genome Sequence of Enterococcus hirae (Streptococcus faecalis) ATCC 9790, a Model Organism for the Study of Ion Transport, Bioenergetics, and Copper Homeostasis

Enterococcus hirae ATCC 9790 is a Gram-positive lactic acid bacterium that has been used in basic research for over 4 decades. Here we report the sequence and annotation of the 2.8-Mb genome of E. hirae and its endemic 29-kb plasmid pTG9790.     

PRESTA: associating promoter sequences with information on gene expression

Background  

Large sets of well-characterized promoter sequences are required to facilitate the understanding of promoter architecture. The major sequence databases are a prospective source of upstream regulatory regions, but suffer from inaccurate annotation. The software tool PRESTA (PRomoter EST Association) presented in this study is designed for efficient recovery of characterized and partially verified promoters from GenBank and EMBL libraries.     

In Silico analysis of the lateral organ junction (LOJ) gene and promoter of Arabidopsis thaliana

A T-DNA based promoter trapped mutant has led to the identification of a novel lateral organ junction specific promoter upstream of the pentatricopeptide repeat (PPR) protein coding gene LOJ in Arabidopsis thaliana by our laboratory. Various in silico based prediction tools are employed to characterize the upstream sequence of the LOJ gene. Out of numerous cis-elements detected in the LOJ promoter a few are considered important based on the expression pattern of the LOJ gene. These elements would provide a basis for designing experiments for more accurate promoter function annotation. A comparative search for conserved elements in the 5'-upstream region of a few genes involved in lateral organ development and meristem related expression reveals a few common relevant regulatory motifs. The coding region of the LOJ gene is intron-less and contains 19 PPR units. Based on in silico analysis, LOJ protein is predicted to be hydrophobic in nature and targeted to mitochondria. A partial 3D model of LOJ protein has been suggested using a homology-based modeling program.     

Unsupervised pattern recognition: an introduction to the whys and wherefores of clustering microarray data

Clustering has become an integral part of microarray data analysis and interpretation. The algorithmic basis of clustering -- the application of unsupervised machine-learning techniques to identify the patterns inherent in a data set -- is well established. This review discusses the biological motivations for and applications of these techniques to integrating gene expression data with other biological information, such as functional annotation, promoter data and proteomic data.     

SEED Servers: High-Performance Access to the SEED Genomes,Annotations, and Metabolic Models

The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Yet, genome annotation, comparison, and modeling remain a major bottleneck to the translation of sequence information into biological knowledge, hence computational analysis tools are continuously being developed for rapid genome annotation and interpretation. Among the earliest, most comprehensive resources for prokaryotic genome analysis, the SEED project, initiated in 2003 as an integration of genomic data and analysis tools, now contains >5,000 complete genomes, a constantly updated set of curated annotations embodied in a large and growing collection of encoded subsystems, a derived set of protein families, and hundreds of genome-scale metabolic models. Until recently, however, maintaining current copies of the SEED code and data at remote locations has been a pressing issue. To allow high-performance remote access to the SEED database, we developed the SEED Servers (http://www.theseed.org/servers): four network-based servers intended to expose the data in the underlying relational database, support basic annotation services, offer programmatic access to the capabilities of the RAST annotation server, and provide access to a growing collection of metabolic models that support flux balance analysis. The SEED servers offer open access to regularly updated data, the ability to annotate prokaryotic genomes, the ability to create metabolic reconstructions and detailed models of metabolism, and access to hundreds of existing metabolic models. This work offers and supports a framework upon which other groups can build independent research efforts. Large integrations of genomic data represent one of the major intellectual resources driving research in biology, and programmatic access to the SEED data will provide significant utility to a broad collection of potential users.     

Community-based gene structure annotation

Uncertainty and inconsistency of gene structure annotation remain limitations on research in the genome era, frustrating both biologists and bioinformaticians, who have to sort out annotation errors for their genes of interest or to generate trustworthy datasets for algorithmic development. It is unrealistic to hope for better software solutions in the near future that would solve all the problems. The issue is all the more urgent with more species being sequenced and analyzed by comparative genomics - erroneous annotations could easily propagate, whereas correct annotations in one species will greatly facilitate annotation of novel genomes. We propose a dynamic, economically feasible solution to the annotation predicament: broad-based, web-technology-enabled community annotation, a prototype of which is now in use for Arabidopsis.     

A novel method for prokaryotic promoter prediction based on DNA stability

Background  

In the post-genomic era, correct gene prediction has become one of the biggest challenges in genome annotation. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. This work presents a novel prokaryotic promoter prediction method based on DNA stability.     

Bioverse: Functional,structural and contextual annotation of proteins and proteomes

Functional annotation is routinely performed for large-scale genomics projects and databases. Researchers working on more specific problems, for instance on an individual pathway or complex, also need to be able to quickly, completely and accurately annotate sequences. The Bioverse sequence annotation server (http://bioverse.compbio.washington.edu) provides a web-based interface to allow users to submit protein sequences to the Bioverse framework. Sequences are functionally and structurally annotated and potential contextual annotations are provided. Researchers can also submit candidate genomes for annotation of all proteins encoded by the genome (proteome).     

金针菇高表达基因的密码子偏好性及特征分析

为探究金针菇的密码子偏好性,挖掘高表达基因的特征信息,以金针菇基因组及转录组数据为材料,分析金针菇的密码子偏好性及其影响因素,并对发育阶段高表达基因进行功能注释和顺式元件分析。分析表明,金针菇高表达基因表现出较强的密码子偏好性,且其偏好密码子多以胞嘧啶(C)结尾,此外在高表达基因中存在6种氨基酸的最优密码子较为保守。在进化过程中,金针菇高表达基因密码子偏好性受到自然选择压力的影响较大。功能注释分类表明,高表达基因多为核糖体通路相关的基因,与蛋白质翻译和生物合成相关。顺式元件分析表明,高表达基因启动子区域大多存在MeJA响应元件、ABA响应元件、光响应元件及MYB转录因子结合元件。研究结果可为提高金针菇异源表达效率和挖掘强启动子提供理论基础和思路。