Gene Re-annotation in Genome of the Extremophile Pyrobaculum Aerophilum by Using Bioinformatics Methods

Abstract

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/     

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.     

Improving gene annotation of complete viral genomes

Gene annotation in viruses often relies upon similarity search methods. These methods possess high specificity but some genes may be missed, either those unique to a particular genome or those highly divergent from known homologs. To identify potentially missing viral genes we have analyzed all complete viral genomes currently available in GenBank with a specialized and augmented version of the gene finding program GeneMarkS. In particular, by implementing genome-specific self-training protocols we have better adjusted the GeneMarkS statistical models to sequences of viral genomes. Hundreds of new genes were identified, some in well studied viral genomes. For example, a new gene predicted in the genome of the Epstein–Barr virus was shown to encode a protein similar to α-herpesvirus minor tegument protein UL14 with heat shock functions. Convincing evidence of this similarity was obtained after only 12 PSI-BLAST iterations. In another example, several iterations of PSI-BLAST were required to demonstrate that a gene predicted in the genome of Alcelaphine herpesvirus 1 encodes a BALF1-like protein which is thought to be involved in apoptosis regulation and, potentially, carcinogenesis. New predictions were used to refine annotations of viral genomes in the RefSeq collection curated by the National Center for Biotechnology Information. Importantly, even in those cases where no sequence similarities were detected, GeneMarkS significantly reduced the number of primary targets for experimental characterization by identifying the most probable candidate genes. The new genome annotations were stored in VIOLIN, an interactive database which provides access to similarity search tools for up-to-date analysis of predicted viral proteins.     

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。     

Complete genomic sequence of bacteriophage B3, a Mu-like phage of Pseudomonas aeruginosa

Bacteriophage B3 is a transposable phage of Pseudomonas aeruginosa. In this report, we present the complete DNA sequence and annotation of the B3 genome. DNA sequence analysis revealed that the B3 genome is 38,439 bp long with a G+C content of 63.3%. The genome contains 59 proposed open reading frames (ORFs) organized into at least three operons. Of these ORFs, the predicted proteins from 41 ORFs (68%) display significant similarity to other phage or bacterial proteins. Many of the predicted B3 proteins are homologous to those encoded by the early genes and head genes of Mu and Mu-like prophages found in sequenced bacterial genomes. Only two of the predicted B3 tail proteins are homologous to other well-characterized phage tail proteins; however, several Mu-like prophages and transposable phage D3112 encode approximately 10 highly similar proteins in their predicted tail gene regions. Comparison of the B3 genomic organization with that of Mu revealed evidence of multiple genetic rearrangements, the most notable being the inversion of the proposed B3 immunity/early gene region, the loss of Mu-like tail genes, and an extreme leftward shift of the B3 DNA modification gene cluster. These differences illustrate and support the widely held view that tailed phages are genetic mosaics arising by the exchange of functional modules within a diverse genetic pool.     

A computational study of Shewanella oneidensis MR-1: structural prediction and functional inference of hypothetical proteins

The genomes of many organisms have been sequenced in the last 5 years. Typically about 30% of predicted genes from a newly sequenced genome cannot be given functional assignments using sequence comparison methods. In these situations three-dimensional structural predictions combined with a suite of computational tools can suggest possible functions for these hypothetical proteins. Suggesting functions may allow better interpretation of experimental data (e.g., microarray data and mass spectroscopy data) and help experimentalists design new experiments. In this paper, we focus on three hypothetical proteins of Shewanella oneidensis MR-1 that are potentially related to iron transport/metabolism based on microarray experiments. The threading program PROSPECT was used for protein structural predictions and functional annotation, in conjunction with literature search and other computational tools. Computational tools were used to perform transmembrane domain predictions, coiled coil predictions, signal peptide predictions, sub-cellular localization predictions, motif prediction, and operon structure evaluations. Combined computational results from all tools were used to predict roles for the hypothetical proteins. This method, which uses a suite of computational tools that are freely available to academic users, can be used to annotate hypothetical proteins in general.     

Identification of protein-coding genes in the genome of Vibrio cholerae with more than 98% accuracy using occurrence frequencies of single nucleotides.

The published sequence of the Vibrio cholerae genome indicates that, in addition to the genes that encode proteins of known and unknown function, there are 1577 ORFs identified as conserved hypothetical or hypothetical gene candidates. Because the annotation is not 100% accurate, it is not known which of the 1577 ORFs are true protein-coding genes. In this paper, an algorithm based on the Z curve method, with sensitivity, specificity and accuracy greater than 98%, is used to solve this problem. Twenty-fold cross-validation tests show that the accuracy of the algorithm is 98.8%. A detailed discussion of the mechanism of the algorithm is also presented. It was found that 172 of the 1577 ORFs are unlikely to be protein-coding genes. The number of protein-coding genes in the V. cholerae genome was re-estimated and found to be approximately 3716. This result should be of use in microarray analysis of gene expression in the genome, because the cost of preparing chips may be somewhat decreased. A computer program was written to calculate a coding score called VCZ for gene identification in the genome. Coding/noncoding is simply determined by VCZ > 0/VCZ < 0. The program is freely available on request for academic use.     

Intrinsic and extrinsic approaches for detecting genes in a bacterial genome.

The unannotated regions of the Escherichia coli genome DNA sequence from the EcoSeq6 database, totaling 1,278 'intergenic' sequences of the combined length of 359,279 basepairs, were analyzed using computer-assisted methods with the aim of identifying putative unknown genes. The proposed strategy for finding new genes includes two key elements: i) prediction of expressed open reading frames (ORFs) using the GeneMark method based on Markov chain models for coding and non-coding regions of Escherichia coli DNA, and ii) search for protein sequence similarities using programs based on the BLAST algorithm and programs for motif identification. A total of 354 putative expressed ORFs were predicted by GeneMark. Using the BLASTX and TBLASTN programs, it was shown that 208 ORFs located in the unannotated regions of the E. coli chromosome are significantly similar to other protein sequences. Identification of 182 ORFs as probable genes was supported by GeneMark and BLAST, comprising 51.4% of the GeneMark 'hits' and 87.5% of the BLAST 'hits'. 73 putative new genes, comprising 20.6% of the GeneMark predictions, belong to ancient conserved protein families that include both eubacterial and eukaryotic members. This value is close to the overall proportion of highly conserved sequences among eubacterial proteins, indicating that the majority of the putative expressed ORFs that are predicted by GeneMark, but have no significant BLAST hits, nevertheless are likely to be real genes. The majority of the putative genes identified by BLAST search have been described since the release of the EcoSeq6 database, but about 70 genes have not been detected so far. Among these new identifications are genes encoding proteins with a variety of predicted functions including dehydrogenases, kinases, several other metabolic enzymes, ATPases, rRNA methyltransferases, membrane proteins, and different types of regulatory proteins.     

Novel family of carbohydrate-binding modules revealed by the genome sequence of Spirochaeta thermophila DSM 6192

Spirochaeta thermophila is a thermophilic, free-living, and cellulolytic anaerobe. The genome sequence data for this organism have revealed a high density of genes encoding enzymes from more than 30 glycoside hydrolase (GH) families and a noncellulosomal enzyme system for (hemi)cellulose degradation. Functional screening of a fosmid library whose inserts were mapped on the S. thermophila genome sequence allowed the functional annotation of numerous GH open reading frames (ORFs). Seven different GH ORFs from the S. thermophila DSM 6192 genome, all putative β-glycanase ORFs according to sequence similarity analysis, contained a highly conserved novel GH-associated module of unknown function at their C terminus. Four of these GH enzymes were experimentally verified as xylanase, β-glucanase, β-glucanase/carboxymethylcellulase (CMCase), and CMCase. Binding experiments performed with the recombinantly expressed and purified GH-associated module showed that it represents a new carbohydrate-binding module (CBM) that binds to microcrystalline cellulose and is highly specific for this substrate. In the course of this work, the new CBM type was only detected in Spirochaeta, but recently we found sequences with detectable similarity to the module in the draft genomes of Cytophaga fermentans and Mahella australiensis, both of which are phylogenetically very distant from S. thermophila and noncellulolytic, yet inhabit similar environments. This suggests a possibly broad distribution of the module in nature.     

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.     

Comparative genomic analysis of hyperthermophilic archaeal Fuselloviridae viruses

The complete genome sequences of two Sulfolobus spindle-shaped viruses (SSVs) from acidic hot springs in Kamchatka (Russia) and Yellowstone National Park (United States) have been determined. These nonlytic temperate viruses were isolated from hyperthermophilic Sulfolobus hosts, and both viruses share the spindle-shaped morphology characteristic of the Fuselloviridae family. These two genomes, in combination with the previously determined SSV1 genome from Japan and the SSV2 genome from Iceland, have allowed us to carry out a phylogenetic comparison of these geographically distributed hyperthermal viruses. Each virus contains a circular double-stranded DNA genome of approximately 15 kbp with approximately 34 open reading frames (ORFs). These Fusellovirus ORFs show little or no similarity to genes in the public databases. In contrast, 18 ORFs are common to all four isolates and may represent the minimal gene set defining this viral group. In general, ORFs on one half of the genome are colinear and highly conserved, while ORFs on the other half are not. One shared ORF among all four genomes is an integrase of the tyrosine recombinase family. All four viral genomes integrate into their host tRNA genes. The specific tRNA gene used for integration varies, and one genome integrates into multiple loci. Several unique ORFs are found in the genome of each isolate.     

Identification of functional open reading frames in chloroplast genomes

We have used a rapid computer dot-matrix comparison method to identify all DNA regions which have been evolutionarily conserved between the completely sequenced chloroplast genomes of tobacco and a liverwort. Analysis of these regions reveals 74 homologous open reading frames (ORFs) which have been conserved as to length and amino acid sequence; these ORFs also have an excess of nucleotide substitutions at silent sites of codons. Since the nonfunctional parts of these genomes have become saturated with mutations and show no sequence similarity whatsoever, the homologous ORFs are almost certainly functional. A further four pairs of ORFs show homology limited to only a short part of their putative gene products. Amino acid sequence identities range between 50 and 99%; some chloroplast proteins are seen to be among the most slowly evolving of all known proteins. A search of the nucleotide and amino acid sequence databanks has revealed several previously unidentified genes in chloroplast sequences from other species, but no new homologies to prokaryotic genes.     

A "polyORFomic" analysis of prokaryote genomes using disabled-homology filtering reveals conserved but undiscovered short ORFs

Prokaryote gene annotation is complicated by large numbers of short open reading frames (ORFs) that arise naturally from genetic code design. Historically, many hypothetical ORFs have been annotated as genes in microbes, usually with an arbitrary length threshold (e.g. greater than 100 codons). Given the use of such thresholds, what is the extent of genuine undiscovered short genes in the current sampling of prokaryote genomes? To assess rigorously the potential under-annotation of short ORFs with homology, we exhaustively compared the polyORFome--all possible ORFs in 64 prokaryotes (53 bacteria and 11 archaea) plus budding yeast--to itself and to all known proteins. The novelty of our analysis is that, firstly, sequence comparisons to/between both annotated and un-annotated ORFs are considered, and secondly a two-step disabled-homology filter is applied to set aside putative pseudogenes and spurious ORFs. We find that un-annotated homologous short ORFs (uhORFs) correspond to a small but non-negligible fraction of the annotated prokaryote proteomes (0.5-3.8%, depending on selection criteria). Moreover, the disabled-homology filter indicates that about a third of uhORFs correspond to putative pseudogenes or spurious ORFs. Our analysis shows that the use of annotation length thresholds is unnecessary, as there are manageable numbers of short ORF homologies conserved (without disablements) across microbial genomes. Data on uhORFs are available from http://pseudogene.org/polyo     

Whole genome searching with shotgun proteomic data: applications for genome annotation

High-throughput genome sequencing continues to accelerate the rate at which complete genomes are available for biological research. Many of these new genome sequences have little or no genome annotation currently available and hence rely upon computational predictions of protein coding genes. Evidence of translation from proteomic techniques could facilitate experimental validation of protein coding genes, but the techniques for whole genome searching with MS/MS data have not been adequately developed to date. Here we describe GENQUEST, a novel method using peptide isoelectric focusing and accurate mass to greatly reduce the peptide search space, making fast, accurate, and sensitive whole human genome searching possible on common desktop computers. In an initial experiment, almost all exonic peptides identified in a protein database search were identified when searching genomic sequence. Many peptides identified exclusively in the genome searches were incorrectly identified or could not be experimentally validated, highlighting the importance of orthogonal validation. Experimentally validated peptides exclusive to the genomic searches can be used to reannotate protein coding genes. GENQUEST represents an experimental tool that can be used by the proteomics community at large for validating computational approaches to genome annotation.     

Gene recognition from questionable ORFs in bacterial and archaeal genomes

The ORFs of microbial genomes in annotation files are usually classified into two groups: the first corresponds to known genes; whereas the second includes 'putative', 'probable', 'conserved hypothetical', 'hypothetical', 'unknown' and 'predicted' ORFs etc. Since the annotation is not 100% accurate, it is essential to confirm which ORF of the latter group is coding and which is not. Starting from known genes in the former, this paper describes an improved Z curve method to recognize genes in the latter. Ten-fold cross-validation tests show that the average accuracy of the algorithm is greater than 99% for recognizing the known genes in 57 bacterial and archaeal genomes. The method is then applied to recognize genes of the latter group. The likely non-coding ORFs in each of the 57 bacterial or archaeal genomes studied here are recognized and listed at the website http://tubic.tju.edu.cn/ZCURVE_C_html/noncoding.html. The working mechanism of the algorithm has been discussed in details. A computer program, called ZCURVE_C, was written to calculate a coding score called Z-curve score for ORFs in the above 57 bacterial and archaeal genomes. Coding/non-coding is simply determined by the criterion of Z-curve score > 0/ Z-curve score < 0. A website has been set up to provide the service to calculate the Z-curve score. A user may submit the DNA sequence of an ORF to the server at http://tubic.tju.edu.cn/ZCURVE_C/Default.cgi, and the Z-curve score of the ORF is calculated and returned to the user immediately.     

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.