GenColors: accelerated comparative analysis and annotation of prokaryotic genomes at various stages of completeness

SUMMARY: GenColors is a new web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes, considering information on related genomes and making extensive use of genome comparison. It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. The genome comparison tools determine, for example, best-bidirectional hits, gene conservation, syntenies and gene core sets. Swiss-Prot/TrEMBL hits allow annotations in an effective manner. To further support the annotation base-specific quality data can also be displayed if available. With GenColors dedicated genome browsers containing a group of related genomes can be easily set up and maintained. It has been efficiently used for Borrelia garinii and is currently applied to various ongoing genome projects. AVAILABILITY: Detailed information on GenColors is available at http://gencolors.imb-jena.de. Online usage of GenColors-based genome browsers is the preferred application mode. The system is also available upon request for local installation.     

<Emphasis Type="Italic">Ab initio</Emphasis> gene identification: Prokaryote genome annotation with GeneScan and GLIMMER

We compare the annotation of three complete genomes using theab initio methods of gene identification GeneScan and GLIMMER. The annotation given in GenBank, the standard against which these are compared, has been made using GeneMark. We find a number of novel genes which are predicted by both methods used here, as well as a number of genes that are predicted by GeneMark, but are not identified by either of the nonconsensus methods that we have used. The three organisms studied here are all prokaryotic species with fairly compact genomes. The Fourier measure forms the basis for an efficient non-consensus method for gene prediction, and the algorithm GeneScan exploits this measure. We have bench-marked this program as well as GLIMMER using 3 complete prokaryotic genomes. An effort has also been made to study the limitations of these techniques for complete genome analysis. GeneScan and GLIMMER are of comparable accuracy insofar as gene-identification is concerned, with sensitivities and specificities typically greater than 0.9. The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a significant number of cases, similar results are provided by the two techniques. This suggests that there could be some as-yet unidentified additional genes in these three genomes, and also that some of the putative identifications made hitherto might require re-evaluation. All these cases are discussed in detail.     

Proteomic Detection of Non-Annotated Protein-Coding Genes in Pseudomonas fluorescens Pf0-1

Genome sequences are annotated by computational prediction of coding sequences, followed by similarity searches such as BLAST, which provide a layer of possible functional information. While the existence of processes such as alternative splicing complicates matters for eukaryote genomes, the view of bacterial genomes as a linear series of closely spaced genes leads to the assumption that computational annotations that predict such arrangements completely describe the coding capacity of bacterial genomes. We undertook a proteomic study to identify proteins expressed by Pseudomonas fluorescens Pf0-1 from genes that were not predicted during the genome annotation. Mapping peptides to the Pf0-1 genome sequence identified sixteen non-annotated protein-coding regions, of which nine were antisense to predicted genes, six were intergenic, and one read in the same direction as an annotated gene but in a different frame. The expression of all but one of the newly discovered genes was verified by RT-PCR. Few clues as to the function of the new genes were gleaned from informatic analyses, but potential orthologs in other Pseudomonas genomes were identified for eight of the new genes. The 16 newly identified genes improve the quality of the Pf0-1 genome annotation, and the detection of antisense protein-coding genes indicates the under-appreciated complexity of bacterial genome organization.     

Assembly and comparison of two closely related Brassica napus genomes

As an increasing number of plant genome sequences become available, it is clear that gene content varies between individuals, and the challenge arises to predict the gene content of a species. However, genome comparison is often confounded by variation in assembly and annotation. Differentiating between true gene absence and variation in assembly or annotation is essential for the accurate identification of conserved and variable genes in a species. Here, we present the de novo assembly of the B. napus cultivar Tapidor and comparison with an improved assembly of the Brassica napus cultivar Darmor‐bzh. Both cultivars were annotated using the same method to allow comparison of gene content. We identified genes unique to each cultivar and differentiate these from artefacts due to variation in the assembly and annotation. We demonstrate that using a common annotation pipeline can result in different gene predictions, even for closely related cultivars, and repeat regions which collapse during assembly impact whole genome comparison. After accounting for differences in assembly and annotation, we demonstrate that the genome of Darmor‐bzh contains a greater number of genes than the genome of Tapidor. Our results are the first step towards comparison of the true differences between B. napus genomes and highlight the potential sources of error in future production of a B. napus pangenome.     

ISsaga is an ensemble of web-based methods for high throughput identification and semi-automatic annotation of insertion sequences in prokaryotic genomes

Insertion sequences (ISs) play a key role in prokaryotic genome evolution but are seldom well annotated. We describe a web application pipeline, ISsaga (), that provides computational tools and methods for high-quality IS annotation. It uses established ISfinder annotation standards and permits rapid processing of single or multiple prokaryote genomes. ISsaga provides general prediction and annotation tools, information on genome context of individual ISs and a graphical overview of IS distribution around the genome of interest.     

Solving the Problem: Genome Annotation Standards before the Data Deluge

The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries.     

Small membrane proteins found by comparative genomics and ribosome binding site models

The correct annotation of genes encoding the smallest proteins is one of the biggest challenges of genome annotation, and perhaps more importantly, few annotated short open reading frames have been confirmed to correspond to synthesized proteins. We used sequence conservation and ribosome binding site models to predict genes encoding small proteins, defined as having 16–50 amino acids, in the intergenic regions of the Escherichia coli genome. We tested expression of these predicted as well as previously annotated genes by integrating the sequential peptide affinity tag directly upstream of the stop codon on the chromosome and assaying for synthesis using immunoblot assays. This approach confirmed that 20 previously annotated and 18 newly discovered proteins of 16–50 amino acids are synthesized. We summarize the properties of these small proteins; remarkably more than half of the proteins are predicted to be single‐transmembrane proteins, nine of which we show co‐fractionate with cell membranes.     

Poxvirus orthologous clusters: toward defining the minimum essential poxvirus genome

Increasingly complex bioinformatic analysis is necessitated by the plethora of sequence information currently available. A total of 21 poxvirus genomes have now been completely sequenced and annotated, and many more genomes will be available in the next few years. First, we describe the creation of a database of continuously corrected and updated genome sequences and an easy-to-use and extremely powerful suite of software tools for the analysis of genomes, genes, and proteins. These tools are available free to all researchers and, in most cases, alleviate the need for using multiple Internet sites for analysis. Further, we describe the use of these programs to identify conserved families of genes (poxvirus orthologous clusters) and have named the software suite POCs, which is available at www.poxvirus.org. Using POCs, we have identified a set of 49 absolutely conserved gene families-those which are conserved between the highly diverged families of insect-infecting entomopoxviruses and vertebrate-infecting chordopoxviruses. An additional set of 41 gene families conserved in chordopoxviruses was also identified. Thus, 90 genes are completely conserved in chordopoxviruses and comprise the minimum essential genome, and these will make excellent drug, antibody, vaccine, and detection targets. Finally, we describe the use of these tools to identify necessary annotation and sequencing updates in poxvirus genomes. For example, using POCs, we identified 19 genes that were widely conserved in poxviruses but missing from the vaccinia virus strain Tian Tan 1998 GenBank file. We have reannotated and resequenced fragments of this genome and verified that these genes are conserved in Tian Tan. The results for poxvirus genes and genomes are discussed in light of evolutionary processes.     

原核基因翻译起始位点预测的新方法

翻译起始位点（TIS,即基因5’端）的精确定位是原核生物基因预测的一个关键问题,而基因组GC含量和翻译起始机制的多样性是影响当前TIS预测水平的重要因素．结合基因组结构的复杂信息（包括GC含量、TIS邻近序列及上游调控信号、序列编码潜能、操纵子结构等）,发展刻画翻译起始机制的数学统计模型,据此设计TIS预测的新算法MED．StartPlus．并将MED．StartPlus与同类方法RBSfinder、GS．Finder、MED-Start、TiCo和Hon-yaku等进行系统地比较和评价．测试针对两种数据集进行：当前14个已知的TIS被确认的基因数据集,以及300个物种中功能已知的基因数据集．测试结果表明,MED-StartPlus的预测精度在总体上超过同类方法．尤其是对高GC含量基因组以及具有复杂翻译起始机制的基因组,MED-StartPlus具有明显的优势．     

A semi-quantitative, synteny-based method to improve functional predictions for hypothetical and poorly annotated bacterial and archaeal genes

During microbial evolution, genome rearrangement increases with increasing sequence divergence. If the relationship between synteny and sequence divergence can be modeled, gene clusters in genomes of distantly related organisms exhibiting anomalous synteny can be identified and used to infer functional conservation. We applied the phylogenetic pairwise comparison method to establish and model a strong correlation between synteny and sequence divergence in all 634 available Archaeal and Bacterial genomes from the NCBI database and four newly assembled genomes of uncultivated Archaea from an acid mine drainage (AMD) community. In parallel, we established and modeled the trend between synteny and functional relatedness in the 118 genomes available in the STRING database. By combining these models, we developed a gene functional annotation method that weights evolutionary distance to estimate the probability of functional associations of syntenous proteins between genome pairs. The method was applied to the hypothetical proteins and poorly annotated genes in newly assembled acid mine drainage Archaeal genomes to add or improve gene annotations. This is the first method to assign possible functions to poorly annotated genes through quantification of the probability of gene functional relationships based on synteny at a significant evolutionary distance, and has the potential for broad application.     

BEACON: automated tool for Bacterial GEnome Annotation ComparisON

Background

Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs).

Results

The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON’s utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27 %, while the number of genes without any function assignment is reduced.

Conclusions

We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1826-4) contains supplementary material, which is available to authorized users.     

蛋白质基因组学：运用蛋白质组技术注释基因组

随着高通量DNA测序技术的飞速发展,越来越多的物种完成了基因组测序．定位编码基因、确定编码基因结构是基因组注释的基本任务,然而以往的基因组注释方法主要依赖于DNA及RNA序列信息．为了更加精确地解读完成测序的基因组,我们需要整合多种类型的组学数据进行基因组注释．近年来,基于串联质谱技术的蛋白质组学已经发展成熟,实现了对蛋白质组的高覆盖,使得利用串联质谱数据进行基因组注释成为可能．串联质谱数据一方面可以对已注释的基因进行表达验证,另一方面还可以校正原注释基因,进而发现新基因,实现对基因组序列的重新注释．这正是当前进展较快的蛋白质基因组学的研究内容．利用该方法系统地注释已完成测序的基因组已成为解读基因组的一个重要补充．本文综述了蛋白质基因组学的主要研究内容和研究方法,并展望了该研究方向未来的发展．     

Functional annotation of hypothetical proteins - A review

The complete human genome sequences in the public database provide ways to understand the blue print of life. As of June 29, 2006, 27 archaeal, 326 bacterial and 21 eukaryotes is complete genomes are available and the sequencing for 316 bacterial, 24 archaeal, 126 eukaryotic genomes are in progress. The traditional biochemical/molecular experiments can assign accurate functions for genes in these genomes. However, the process is time-consuming and costly. Despite several efforts, only 50-60 % of genes have been annotated in most completely sequenced genomes. Automated genome sequence analysis and annotation may provide ways to understand genomes. Thus, determination of protein function is one of the challenging problems of the post-genome era. This demands bioinformatics to predict functions of un-annotated protein sequences by developing efficient tools. Here, we discuss some of the recent and popular approaches developed in Bioinformatics to predict functions for hypothetical proteins.     

Improving the Caenorhabditis elegans genome annotation using machine learning

For modern biology, precise genome annotations are of prime importance, as they allow the accurate definition of genic regions. We employ state-of-the-art machine learning methods to assay and improve the accuracy of the genome annotation of the nematode Caenorhabditis elegans. The proposed machine learning system is trained to recognize exons and introns on the unspliced mRNA, utilizing recent advances in support vector machines and label sequence learning. In 87% (coding and untranslated regions) and 95% (coding regions only) of all genes tested in several out-of-sample evaluations, our method correctly identified all exons and introns. Notably, only 37% and 50%, respectively, of the presently unconfirmed genes in the C. elegans genome annotation agree with our predictions, thus we hypothesize that a sizable fraction of those genes are not correctly annotated. A retrospective evaluation of the Wormbase WS120 annotation [] of C. elegans reveals that splice form predictions on unconfirmed genes in WS120 are inaccurate in about 18% of the considered cases, while our predictions deviate from the truth only in 10%-13%. We experimentally analyzed 20 controversial genes on which our system and the annotation disagree, confirming the superiority of our predictions. While our method correctly predicted 75% of those cases, the standard annotation was never completely correct. The accuracy of our system is further corroborated by a comparison with two other recently proposed systems that can be used for splice form prediction: SNAP and ExonHunter. We conclude that the genome annotation of C. elegans and other organisms can be greatly enhanced using modern machine learning technology.     

rrndb: the Ribosomal RNA Operon Copy Number Database

The Ribosomal RNA Operon Copy Number Database (rrndb) is an Internet-accessible database containing annotated information on rRNA operon copy number among prokaryotes. Gene redundancy is uncommon in prokaryotic genomes, yet the rRNA genes can vary from one to as many as 15 copies. Despite the widespread use of 16S rRNA gene sequences for identification of prokaryotes, information on the number and sequence of individual rRNA genes in a genome is not readily accessible. In an attempt to understand the evolutionary implications of rRNA operon redundancy, we have created a phylogenetically arranged report on rRNA gene copy number for a diverse collection of prokaryotic microorganisms. Each entry (organism) in the rrndb contains detailed information linked directly to external websites including the Ribosomal Database Project, GenBank, PubMed and several culture collections. Data contained in the rrndb will be valuable to researchers investigating microbial ecology and evolution using 16S rRNA gene sequences. The rrndb web site is directly accessible on the WWW at http://rrndb.cme. msu.edu.