A frameshift error detection algorithm for DNA sequencing projects

An approach for searching insertions in bacterial genes leading to the phase shift of triplet periodicity

The concept of the phase shift of triplet periodicity (TP) was used for searching potential DNA insertions in genes from 17 bacterial genomes. A mathematical algorithm for detection of these insertions has been developed. This approach can detect potential insertions and deletions with lengths that are not multiples of three bases, especially insertions of relatively large DNA fragments (>100 bases). New similarity measure between triplet matrixes was employed to improve the sensitivity for detecting the TP phase shift. Sequences of 17,220 bacterial genes with each consisting of more than 1,200 bases were analyzed, and the presence of a TP phase shift has been shown in ~16% of analysed genes (2,809 genes), which is about 4 times more than that detected in our previous work. We propose that shifts of the TP phase may indicate the shifts of reading frame in genes after insertions of the DNA fragments with lengths that are not multiples of three bases. A relationship between the phase shifts of TP and the frame shifts in genes is discussed.

Comparative proteogenomics: combining mass spectrometry and comparative genomics to analyze multiple genomes

Recent proliferation of low-cost DNA sequencing techniques will soon lead to an explosive growth in the number of sequenced genomes and will turn manual annotations into a luxury. Mass spectrometry recently emerged as a valuable technique for proteogenomic annotations that improves on the state-of-the-art in predicting genes and other features. However, previous proteogenomic approaches were limited to a single genome and did not take advantage of analyzing mass spectrometry data from multiple genomes at once. We show that such a comparative proteogenomics approach (like comparative genomics) allows one to address the problems that remained beyond the reach of the traditional "single proteome" approach in mass spectrometry. In particular, we show how comparative proteogenomics addresses the notoriously difficult problem of "one-hit-wonders" in proteomics, improves on the existing gene prediction tools in genomics, and allows identification of rare post-translational modifications. We therefore argue that complementing DNA sequencing projects by comparative proteogenomics projects can be a viable approach to improve both genomic and proteomic annotations.

ANGLE: a sequencing errors resistant program for predicting protein coding regions in unfinished cDNA

In the process of making full-length cDNA, predicting protein coding regions helps both in the preliminary analysis of genes and in any succeeding process. However, unfinished cDNA contains artifacts including many sequencing errors, which hinder the correct evaluation of coding sequences. Especially, predictions of short sequences are difficult because they provide little information for evaluating coding potential. In this paper, we describe ANGLE, a new program for predicting coding sequences in low quality cDNA. To achieve error-tolerant prediction, ANGLE uses a machine-learning approach, which makes better expression of coding sequence maximizing the use of limited information from input sequences. Our method utilizes not only codon usage, but also protein structure information which is difficult to be used for stochastic model-based algorithms, and optimizes limited information from a short segment when deciding coding potential, with the result that predictive accuracy does not depend on the length of an input sequence. The performance of ANGLE is compared with ESTSCAN on four dataset each of them having a different error rate (one frame-shift error or one substitution error per 200-500 nucleotides) and on one dataset which has no error. ANGLE outperforms ESTSCAN by 9.26% in average Matthews's correlation coefficient on short sequence dataset (< 1000 bases). On long sequence dataset, ANGLE achieves comparable performance.

Predicting genes expressed via -1 and +1 frameshifts

Computational identification of ribosomal frameshift sites in genomic sequences is difficult due to their diverse nature, yet it provides useful information for understanding the underlying mechanisms and discovering new genes. We have developed an algorithm that searches entire genomic or mRNA sequences for frameshifting sites, and implements the algorithm as a web-based program called FSFinder (Frameshift Signal Finder). The current version of FSFinder is capable of finding -1 frameshift sites on heptamer sequences X XXY YYZ, and +1 frameshift sites for two genes: protein chain release factor B (prfB) and ornithine decarboxylase antizyme (oaz). We tested FSFinder on approximately 190 genomic and partial DNA sequences from a number of organisms and found that it predicted frameshift sites efficiently and with greater sensitivity and specificity than existing approaches. It has improved sensitivity because it considers many known components of a frameshifting cassette and searches these components on both + and - strands, and its specificity is increased because it focuses on overlapping regions of open reading frames and prioritizes candidate frameshift sites. FSFinder is useful for discovering unknown genes that utilize alternative decoding, as well as for analyzing frameshift sites. It is freely accessible at http://wilab.inha.ac.kr/FSFinder/.

Use and misuse of correspondence analysis in codon usage studies

Correspondence analysis has frequently been used for codon usage studies but this method is often misused. Because amino acid composition exerts constraints on codon usage, it is common to use tables containing relative codon frequencies (or ratios of frequencies) instead of simple codon counts to get rid of these amino acid biases. The problem is that some important properties of correspondence analysis, such as rows weighting, are lost in the process. Moreover, the use of relative measures sometimes introduces other biases and often diminishes the quantity of information to analyse, occasionally resulting in interpretation errors. For instance, in the case of an organism such as Borrelia burgdorferi, the use of relative measures led to the conclusion that there was no translational selection, while analyses based on codon counts show that there is a possibility of a selective effect at that level. In this paper, we expose these problems and we propose alternative strategies to correspondence analysis for studying codon usage biases when amino acid composition effects must be removed.

Current methods of gene prediction, their strengths and weaknesses

While the genomes of many organisms have been sequenced over the last few years, transforming such raw sequence data into knowledge remains a hard task. A great number of prediction programs have been developed that try to address one part of this problem, which consists of locating the genes along a genome. This paper reviews the existing approaches to predicting genes in eukaryotic genomes and underlines their intrinsic advantages and limitations. The main mathematical models and computational algorithms adopted are also briefly described and the resulting software classified according to both the method and the type of evidence used. Finally, the several difficulties and pitfalls encountered by the programs are detailed, showing that improvements are needed and that new directions must be considered.

Detecting and analyzing DNA sequencing errors: toward a higher quality of the Bacillus subtilis genome sequence

During the determination of a DNA sequence, the introduction of artifactual frameshifts and/or in-frame stop codons in putative genes can lead to misprediction of gene products. Detection of such errors with a method based on protein similarity matching is only possible when related sequences are available in databases. Here, we present a method to detect frameshift errors in DNA sequences that is based on the intrinsic properties of the coding sequences. It combines the results of two analyses, the search for translational initiation/termination sites and the prediction of coding regions. This method was used to screen the complete Bacillus subtilis genome sequence and the regions flanking putative errors were resequenced for verification. This procedure allowed us to correct the sequence and to analyze in detail the nature of the errors. Interestingly, in several cases in-frame termination codons or frameshifts were not sequencing errors but confirmed to be present in the chromosome, indicating that the genes are either nonfunctional (pseudogenes) or subject to regulatory processes such as programmed translational frameshifts. The method can be used for checking the quality of the sequences produced by any prokaryotic genome sequencing project.

Protein-coding region discovery in organisms underrepresented in databases

The prediction of coding sequences has received a lot of attention during the last decade. We can distinguish two kinds of methods, those that rely on training with sets of example and counter-example sequences, and those that exploit the intrinsic properties of the DNA sequences to be analyzed. The former are generally more powerful but their domains of application are limited by the availability of a training set. The latter avoid this drawback but can only be applied to sequences that are long enough to allow computation of the statistics. Here, we present a method that fills the gap between the two approaches. A learning step is applied using a set of sequences that are assumed to contain coding and non-coding regions, but with the boundaries of these regions unknown. A test step then uses the discriminant function obtained during the learning to predict coding regions in sequences from the same organism. The learning relies upon a correspondence analysis and prediction is presented on a graphical display. The method has been evaluated on a sample of yeast sequences, and the analysis of a set of expressed sequence tags from the Eucalyptus globulus-Pisolithus tinctorius ectomycorrhiza illustrates the relevance of the approach in its biological context.

Inventory, assembly and analysis of Bacillus subtilis ABC transport systems

We have undertaken the inventory and assembly of the ATP binding cassette (ABC) transporter systems in the complete genome of Bacillus subtilis. We combined the identification of the three protein partners that compose an ABC transporter (nucleotide-binding domain, NBD; membrane spanning domain, MSD; and solute-binding protein, SBP) with constraints on the genetic organization. This strategy allowed the identification of 86 NBDs in 78 proteins, 103 MSD proteins and 37 SBPs. The analysis of transcriptional units allows the reconstruction of 59 ABC transporters, which include at least one NBD and one MSD. A particular class of five dimeric ATPases was not associated to MSD partners and is assumed to be involved either in macrolide resistance or regulation of translation elongation. In addition, we have detected five genes encoding ATPases without any gene coding for MSD protein in their neighborhood and 11 operons that encode only the membrane and solute-binding proteins. On the bases of similarities, three ATP-binding proteins are proposed to energize ten incomplete systems, suggesting that one ATPase may be recruited by more than one transporter. Finally, we estimate that the B. subtilis genome encodes for at least 78 ABC transporters that have been split in 38 importers and 40 extruders. The ABC systems have been further classified into 11 sub-families according to the tree obtained from the NBDs and the clustering of the MSDs and the SBPs. Comparisons with Escherichia coli show that the extruders are over-represented in B. subtilis, corresponding to an expansion of the sub-families of antibiotic and drug resistance systems.

The complete genome sequence of the gram-positive bacterium Bacillus subtilis

Bacillus subtilis is the best-characterized member of the Gram-positive bacteria. Its genome of 4,214,810 base pairs comprises 4,100 protein-coding genes. Of these protein-coding genes, 53% are represented once, while a quarter of the genome corresponds to several gene families that have been greatly expanded by gene duplication, the largest family containing 77 putative ATP-binding transport proteins. In addition, a large proportion of the genetic capacity is devoted to the utilization of a variety of carbon sources, including many plant-derived molecules. The identification of five signal peptidase genes, as well as several genes for components of the secretion apparatus, is important given the capacity of Bacillus strains to secrete large amounts of industrially important enzymes. Many of the genes are involved in the synthesis of secondary metabolites, including antibiotics, that are more typically associated with Streptomyces species. The genome contains at least ten prophages or remnants of prophages, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.

A computer filtering method to drive out tiny genes from the yeast genome

The authors of the first yeast chromosome sequence defined a minimum threshold requirement of 100 codons, above which an open reading frame (ORF) is retained as a putative coding sequence. However, at least 58 yeast genes shorter than 100 codons have an assigned protein function. Therefore, the yeast genome may contain other tiny but functionally important genes that are discarded from analyses by this simple filtering rule. We have established discriminant functions from the in-phase hexamer frequencies of functional genes and of simulated ORFs derived from a stationary Markov chain model. Fifty-two out of the 58 genes were recognized as coding ORFs by our discriminating method. The test was also applied to all the small ORFs (36 to 100 codons) found in the intergenic regions of published chromosomes. It retained 140 new potential tiny coding sequences, among which we identified seven new genes by similarity searches. Our method, used conjointly with similarity searches, can also highlight sequencing errors resulting from the disruption of the coding frame of longer ORFs. This method, by its ability to detect potential coding ORFs, can be a very useful tool for functional analysis.

PairWise and SearchWise: finding the optimal alignment in a simultaneous comparison of a protein profile against all DNA translation frames

DNA translation frames can be disrupted for several reasons, including: (i) errors in sequence determination; (ii) RNA processing, such as intron removal and guide RNA editing; (iii) less commonly, polymerase frameshifting during transcription or ribosomal frameshifting during translation. Frameshifts frequently confound computational activities involving homologous sequences, such as database searches and inferences on structure, function or phylogeny made from multiple alignments. A dynamic alignment algorithm is reported here which compares a protein profile (a residue scoring matrix for one or more aligned sequences) against the three translation frames of a DNA strand, allowing frameshifting. The algorithm has been incorporated into a new package, WiseTools, for comparison of biological sequences. A protein profile can be compared against either a DNA sequence or a protein sequence. The program PairWise may be used interactively for alignment of any two sequence inputs. SearchWise can perform combinations of searches through DNA or protein databases by a protein profile or DNA sequence. Routine application of the programs has revealed a set of database entries with frameshifts caused by errors in sequence determination.

Discrimination between fortuitous and biologically constrained open reading frames in DNA sequences of Saccharomyces cerevisiae

The systematic sequencing of the yeast genome has raised the problem of the biological significance of the open reading frames (ORFs) revealed: it is possible that some of these are fortuitous. To avoid the analysis of such fortuitous ORFs, a minimum length of 100 sense codons was adopted. Nevertheless, the presence of fortuitous ORFs of more than 100 codons cannot be excluded. Thus, in the context of functional analysis, a method for discrimination between fortuitous and biologically active ORFs may be useful. The discrimination method described here is based on multiple criteria: ORF length, codon bias, and both amino-acid and dipeptide composition of the corresponding polypeptide. The thresholds for each criterion are based on the comparison between two learning sets: one drawn from random DNA sequences and the second from known genes. The method was validated by two test sets (one random and one biological) and then applied to the ORFs of chromosomes I, II, III, V, VIII, IX and XI. This method predicts 123 fortuitous ORFs among the 1773 identified on these chromosomes.

A segment-based dynamic programming algorithm for predicting gene structure

An algorithm called segment-based dynamic programming is described for predicting gene structure from a sequence of genomic DNA. The algorithm explores the space of gene structures that satisfy junctional and frame constraints and finds the gene structure that optimizes the sum of junctional and segmental scoring functions. Junctional constraints specify acceptable sites of initiation, termination, and splicing, whereas frame constraints ensure that the total exon length is a multiple of three and that no in-frame stop codons occur within exons or at exon-exon junctions. By computing over segments, segment-based dynamic programming maintains reading frame and phase information for each segment, it can assemble exons in-frame as well as score them in-frame. The algorithm is used to quantify the computational power of constraints. Experimental results show that frame constraints reduce the size of the search space by several orders of magnitude and that cardinality constraints place an asymptotic limit on the size of the search space. The algorithm is also used to compare the accuracy of different methods for assembly and scoring. A scoring scheme based on fifth-order Markov hexamer frequencies is presented and used in three objective functions, corresponding to in-frame, frame-independent, and frame-maximal scoring strategies. Experimental results show that in-frame assembly improves specificity only slightly over frame-independent assembly, whereas in-frame scoring improves specificity substantially over frame-independent and frame-maximal scoring.

WWW-query: an on-line retrieval system for biological sequence banks

We have developed a World Wide Web (WWW) version of the sequence retrieval system Query: WWW-Query. This server allows to query nucleotide sequence banks in the EMBL/GenBank/DDBJ formats and protein sequence banks in the NBRF/PIR format. WWW-Query includes all the features of the on-line sequences browsers already available: possibility to build complex queries, integration of cross-references with different data banks, and access to the functional zones of biological interest. It also provides original services not available elsewhere: introduction of the notion of re-usable sequence lists, integration of dedicated helper applications for visualizing alignments and phylogenetic trees and links with multivariate methods for studying codon usage or for complementing phylogenies.