Large-scale prokaryotic gene prediction and comparison to genome annotation

MOTIVATION: Prokaryotic genomes are sequenced and annotated at an increasing rate. The methods of annotation vary between sequencing groups. It makes genome comparison difficult and may lead to propagation of errors when questionable assignments are adapted from one genome to another. Genome comparison either on a large or small scale would be facilitated by using a single standard for annotation, which incorporates a transparency of why an open reading frame (ORF) is considered to be a gene. RESULTS: A total of 143 prokaryotic genomes were scored with an updated version of the prokaryotic genefinder EasyGene. Comparison of the GenBank and RefSeq annotations with the EasyGene predictions reveals that in some genomes up to approximately 60% of the genes may have been annotated with a wrong start codon, especially in the GC-rich genomes. The fractional difference between annotated and predicted confirms that too many short genes are annotated in numerous organisms. Furthermore, genes might be missing in the annotation of some of the genomes. We predict 41 of 143 genomes to be over-annotated by >5%, meaning that too many ORFs are annotated as genes. We also predict that 12 of 143 genomes are under-annotated. These results are based on the difference between the number of annotated genes not found by EasyGene and the number of predicted genes that are not annotated in GenBank. We argue that the average performance of our standardized and fully automated method is slightly better than the annotation.     

EasyGene – a prokaryotic gene finder that ranks ORFs by statistical significance

Background  

Contrary to other areas of sequence analysis, a measure of statistical significance of a putative gene has not been devised to help in discriminating real genes from the masses of random Open Reading Frames (ORFs) in prokaryotic genomes. Therefore, many genomes have too many short ORFs annotated as genes.     

利用蛋白质序列模式识别改善谷氨酸棒杆菌基因组注释

即使细菌基因组的基因结构较为简单,但在注释过程中也可能出现基因遗漏的现象。当潜在基因在高质量数据库中没有显著同源序列时,基于知识库的基因预测方法就会遇到困难。本文希望通过系统扫描基因组所有可能ORF的蛋白质序列模式来搜索遗漏基因。为验证该方法的可行性,作者系统分析了重要的工业发酵微生物谷氨酸棒杆菌的基因组,发现了25个候选疑似基因。它们具有显著的蛋白质序列模式,但在Swiss-Prot中元显著同源序列,并且在GenBank中仍未注释。深入分析发现,25个候选疑似基因中19个为可能基因,3个为可能假基因,3个为疑似基因序列。这些结果说明本文的分析方法可以有效地用于无显著同源序列基因的搜索。     

Peptides encoded by short ORFs control development and define a new eukaryotic gene family

Despite recent advances in developmental biology, and the sequencing and annotation of genomes, key questions regarding the organisation of cells into embryos remain. One possibility is that uncharacterised genes having nonstandard coding arrangements and functions could provide some of the answers. Here we present the characterisation of tarsal-less (tal), a new type of noncanonical gene that had been previously classified as a putative noncoding RNA. We show that tal controls gene expression and tissue folding in Drosophila, thus acting as a link between patterning and morphogenesis. tal function is mediated by several 33-nucleotide-long open reading frames (ORFs), which are translated into 11-amino-acid-long peptides. These are the shortest functional ORFs described to date, and therefore tal defines two novel paradigms in eukaryotic coding genes: the existence of short, unprocessed peptides with key biological functions, and their arrangement in polycistronic messengers. Our discovery of tal-related short ORFs in other species defines an ancient and noncanonical gene family in metazoans that represents a new class of eukaryotic genes. Our results open a new avenue for the annotation and functional analysis of genes and sequenced genomes, in which thousands of short ORFs are still uncharacterised.     

Reannotation of hypothetical ORFs in plant pathogen Erwinia carotovora subsp. atroseptica SCRI1043

Over-annotation of hypothetical ORFs is a common phenomenon in bacterial genomes, which necessitates confirming the coding reliability of hypothetical ORFs and then predicting their functions. The important plant pathogen Erwinia carotovora subsp. atroseptica SCRI1043 (Eca1043) is a typical case because more than a quarter of its annotated ORFs are hypothetical. Our analysis focuses on annotation of Eca1043 hypothetical ORFs, and comprises two efforts: (a) based on the Z-curve method, 49 originally annotated hypothetical ORFs are recognized as noncoding, this is further supported by principal components analysis and other evidence; and (b) using sequence-alignment tools and some functional resources, more than a half of the hypothetical genes were assigned functions. The potential functions of 427 hypothetical genes are summarized according to the cluster of orthologous groups functional category. Moreover, 114 and 86 hypothetical genes are recognized as putative 'membrane proteins' and 'exported proteins', respectively. Reannotation of Eca1043 hypothetical ORFs will benefit research into the lifestyle, metabolism and pathogenicity of the important plant pathogen. Also, our study proffers a model for the reannotation of hypothetical ORFs in microbial genomes.     

Estimation of the number of authentic orphan genes in bacterial genomes.

Genome annotation produces a considerable number of putative proteins lacking sequence similarity to known proteins. These are referred to as "orphans." The proportion of orphan genes varies among genomes, and is independent of genome size. In the present study, we show that the proportion of orphan genes roughly correlates with the isolation index of organisms (IIO), an indicator introduced in the present study, which represents the degree of isolation of a given genome as measured by sequence similarity. However, there are outlier genomes with respect to the linear correlation, consisting of those genomes that may contain excess amounts of orphan genes. Comparisons of genome sequences among closely related strains revealed that some of the annotated genes are not conserved, suggesting that they are ORFs occurring by chance. Exclusion of these non-conserved ORFs within closely related genomes improved the correlation between the proportion of orphan genes and the IIO values. Assuming that the correlation holds in general, this relationship was used to estimate the number of "authentic" orphan genes in a genome. Using this definition of authentic orphan genes, the anomalies arising from over-assignments, e.g., the percentages of structural annotations, were corrected for 16 genomes, including those of five archaea.     

Mass spectrometry-based prokaryote gene annotation

MS combined with database searching has become the preferred method for identifying proteins present in cell or tissue samples. The technique enables us to execute large-scale proteome analyses of species whose genomes have already been sequenced. Searching mass spectrometric data against protein databases composed of annotated genes has been widely conducted. However, there are some issues with this technique; wrong annotations in protein databases cause deterioration in the accuracy of protein identification, and only proteins that have already been annotated can be identified. We propose a new framework that can detect correct ORFs by integrating an MS/MS proteomic data mapping and a knowledge-based system regarding the translation initiation sites. This technique can provide correction of predicted coding sequences, together with the possibility of identifying novel genes. We have developed a computational system; it should first conduct the probabilistic peptide-matching against all possible translational frames using MS/MS data, then search for discriminative DNA patterns around the detected peptides, and lastly integrate the facts using empirical knowledge stored in knowledge bases to obtain correct ORFs. We used photosynthetic bacteria Synechocystis sp. PCC6803 as a sample prokaryote, resulting in the finding of 14 N-terminus annotation errors and several new candidate genes.     

Recognizing the pseudogenes in bacterial genomes

Pseudogenes are now known to be a regular feature of bacterial genomes and are found in particularly high numbers within the genomes of recently emerged bacterial pathogens. As most pseudogenes are recognized by sequence alignments, we use newly available genomic sequences to identify the pseudogenes in 11 genomes from 4 bacterial genera, each of which contains at least 1 human pathogen. The numbers of pseudogenes range from 27 in Staphylococcus aureus MW2 to 337 in Yersinia pestis CO92 (e.g. 1–8% of the annotated genes in the genome). Most pseudogenes are formed by small frameshifting indels, but because stop codons are A + T-rich, the two low-G + C Gram-positive taxa (Streptococcus and Staphylococcus) have relatively high fractions of pseudogenes generated by nonsense mutations when compared with more G + C-rich genomes. Over half of the pseudogenes are produced from genes whose original functions were annotated as ‘hypothetical’ or ‘unknown’; however, several broadly distributed genes involved in nucleotide processing, repair or replication have become pseudogenes in one of the sequenced Vibrio vulnificus genomes. Although many of our comparisons involved closely related strains with broadly overlapping gene inventories, each genome contains a largely unique set of pseudogenes, suggesting that pseudogenes are formed and eliminated relatively rapidly from most bacterial genomes.     

The discovery of novel protein-coding features in mouse genome based on mass spectrometry data

Identifying protein-coding genes in eukaryotic genomes remains a challenge in post-genome era due to the complex gene models. We applied a proteogenomics strategy to detect un-annotated protein-coding regions in mouse genome. High-accuracy tandem mass spectrometry (MS/MS) data from diverse mouse samples were generated by LTQ-Orbitrap mass spectrometer in house. Two searchable diagnostic proteomic datasets were constructed, one with all possible encoding exon junctions, and the other with all putative encoding exons, for the discovery of novel exon splicing events and novel uninterrupted protein-coding regions. Altogether 29,586 unique peptides were identified. Aligning backwards to the mouse genome, the translation of 4471 annotated genes was validated by the known peptides; and 172 genic events were defined in mouse genome by the novel peptides. The approach in the current work can provide substantial evidences for eukaryote genome annotation in encoding genes.     

Complete nucleotide sequence of pGS18, a 62.8-kb plasmid from <Emphasis Type="Italic">Geobacillus stearothermophilus</Emphasis> strain 18

The complete nucleotide sequence (62.8 kb) of pGS18, the largest sequenced plasmid to date from the species Geobacillus stearothermophilus, was determined. Computational analysis of sequence data revealed 65 putative open reading frames (ORFs); 38 were carried on one strand and 27 were carried on the other. These ORFs comprised 84.1% of the pGS18 sequence. Twenty-five ORFs (38.4%) were assigned to putative functions; four ORFs (6.2%) were annotated as pseudogenes. The amino acid sequences obtained from 29 ORFs (44.6%) had the highest similarity to hypothetical proteins of the other microorganisms, and seven (10.8%) had no significant similarity to any genes present in the current open databases. Plasmid replication region, strongly resembling that of the theta-type replicon, and genes encoding three different plasmid maintenance systems were identified, and a putative discontinuous transfer region was localized. In addition, we also found several mobile genetic elements and genes, responsible for DNA repair, distributed along the whole sequence of pGS18. The alignment of pGS18 with two other large indigenous plasmids of the genus Geobacillus highlighted the presence of well-conserved segments and has provided a framework that can be exploited to formulate hypotheses concerning the molecular evolution of these three plasmids.     

Gene decay in archaea

The gene-dense chromosomes of archaea and bacteria were long thought to be devoid of pseudogenes, but with the massive increase in available genome sequences, whole genome comparisons between closely related species have identified mutations that have rendered numerous genes inactive. Comparative analyses of sequenced archaeal genomes revealed numerous pseudogenes, which can constitute up to 8.6% of the annotated coding sequences in some genomes. The largest proportion of pseudogenes is created by gene truncations, followed by frameshift mutations. Within archaeal genomes, large numbers of pseudogenes contain more than one inactivating mutation, suggesting that pseudogenes are deleted from the genome more slowly in archaea than in bacteria. Although archaea seem to retain pseudogenes longer than do bacteria, most archaeal genomes have unique repertoires of pseudogenes.     

Gene recognition based on nucleotide distribution of ORFs in a hyper-thermophilic crenarchaeon, Aeropyrum pernix K1.

The 2694 ORFs originally annotated as potential genes in the genome of Aeropyrum pernix can be categorized into three clusters (A, B, C), according to their nucleotide composition at three codon positions. Coding potential was found to be responsible for the phenomenon of three clusters in a 9-dimensional space derived from the nucleotide composition of ORFs: ORFs assigned to cluster A are coding ones, while those assigned to clusters B and C are non-coding ORFs. A "codingness" index called the AZ score is defined based on a clustering method used to recognize protein-coding genes in the A. pernix genome. The criterion for a coding or non-coding ORF is based on the AZ score. ORFs with AZ > 0 or AZ < 0 are coding or non-coding, respectively. Consequently, 620 out of 632 ORFs with putative functions based on the original annotation are contained in cluster A, which have positive AZ scores. In addition, all 29 ORFs encoding putative or conserved proteins newly added in RefSeq annotation also have positive AZ scores. Accordingly, the number of re-recognized protein-coding genes in the A. pernix genome is 1610, which is significantly less than 2694 in the original annotation and also much less than 1841 in the RefSeq annotation curated by NCBI staff. Annotation information of re-recognized genes and their AZ scores are available at: http://tubic.tju.edu.cn/Aper/.     

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.     

Gene re-annotation in genome of the extremophile Pyrobaculum aerophilum by using bioinformatics methods

In this paper, we re-annotated the genome of Pyrobaculum aerophilum str. IM2, particularly for hypothetical ORFs. The annotation process includes three parts. Firstly and most importantly, 23 new genes, which were missed in the original annotation, are found by combining similarity search and the ab initio gene finding approaches. Among these new genes, five have significant similarities with function-known genes and the rest have significant similarities with hypothetical ORFs contained in other genomes. Secondly, the coding potentials of the 1645 hypothetical ORFs are re-predicted by using 33 Z curve variables combined with Fisher linear discrimination method. With the accuracy being 99.68%, 25 originally annotated hypothetical ORFs are recognized as non-coding by our method. Thirdly, 80 hypothetical ORFs are assigned with potential functions by using similarity search with BLAST program. Re-annotation of the genome will benefit related researches on this hyperthermophilic crenarchaeon. Also, the re-annotation procedure could be taken as a reference for other archaeal genomes. Details of the revised annotation are freely available at http://cobi.uestc.edu.cn/resource/paero/     

Comparative Analysis of Functional Metagenomic Annotation and the Mappability of Short Reads

To assess the functional capacities of microbial communities, including those inhabiting the human body, shotgun metagenomic reads are often aligned to a database of known genes. Such homology-based annotation practices critically rely on the assumption that short reads can map to orthologous genes of similar function. This assumption, however, and the various factors that impact short read annotation, have not been systematically evaluated. To address this challenge, we generated an extremely large database of simulated reads (totaling 15.9 Gb), spanning over 500,000 microbial genes and 170 curated genomes and including, for many genomes, every possible read of a given length. We annotated each read using common metagenomic protocols, fully characterizing the effect of read length, sequencing error, phylogeny, database coverage, and mapping parameters. We additionally rigorously quantified gene-, genome-, and protocol-specific annotation biases. Overall, our findings provide a first comprehensive evaluation of the capabilities and limitations of functional metagenomic annotation, providing crucial goal-specific best-practice guidelines to inform future metagenomic research.     

A systematic investigation identifies a significant number of probable pseudogenes in the Escherichia coli genome

Pseudogenes are open reading frames (ORFs) encoding dysfunctional proteins with high homology to known protein-coding genes. Although pseudogenes were reported to exist in the genomes of many eukaryotes and bacteria, no systematic search for pseudogenes in the Escherichia coli genome has been carried out. Genome comparisons of E. coli strains K-12 and O157 revealed that many protein-coding sequences have prematurely terminated orthologs encoding unstable proteins. To systematically screen for pseudogenes, we selected ORFs generated by premature termination of the orthologous protein-coding genes and subsequently excluded those possibly arising from sequence errors. Lastly we eliminated those with close homologs in this and other species, as these shortened ORFs may actually have functions. The process produced 95 and 101 pseudogene candidates in K-12 and O157, respectively. The assigned three-dimensional structures suggest that most of the encoded proteins cannot fold properly and thus are dysfunctional, indicating that they are probably pseudogenes. Therefore, the existence of a significant number of probable pseudogenes in E. coli is predicted, awaiting experimental verification. Most of them were found to be genes with paralogs or horizontally transferred genes or both. We suggest that pseudogenes constitute a small fraction of the genomes of free-living bacteria in general, reflecting the faster elimination than production of pseudogenes.     

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.