Back-translation for discovering distant protein homologies

Frameshift mutations in protein-coding DNA sequences produce a drastic change in the resulting protein sequence, which prevents classic protein alignment methods from revealing the proteins' common origin. Moreover, when a large number of substitutions are additionally involved in the divergence, the homology detection becomes difficult even at the DNA level. To cope with this situation, we propose a novel method to infer distant homology relations of two proteins, that accounts for frameshift and point mutations that may have affected the coding sequences. We design a dynamic programming alignment algorithm over memory-efficient graph representations of the complete set of putative DNA sequences of each protein, with the goal of determining the two putative DNA sequences which have the best scoring alignment under a powerful scoring system designed to reflect the most probable evolutionary process. This allows us to uncover evolutionary information that is not captured by traditional alignment methods, which is confirmed by biologically significant examples.Comment: The 9th International Workshop in Algorithms in Bioinformatics (WABI), Philadelphia : \'Etats-Unis d'Am\'erique (2009

MACSE: Multiple Alignment of Coding SEquences Accounting for Frameshifts and Stop Codons

Until now the most efficient solution to align nucleotide sequences containing open reading frames was to use indirect procedures that align amino acid translation before reporting the inferred gap positions at the codon level. There are two important pitfalls with this approach. Firstly, any premature stop codon impedes using such a strategy. Secondly, each sequence is translated with the same reading frame from beginning to end, so that the presence of a single additional nucleotide leads to both aberrant translation and alignment

Modélisation et comparaison de la structure de gènes

La bio-informatique est un domaine de recherche multi-disciplinaire, à la croisée de différents domaines : biologie, médecine, mathématiques, statistiques, chimie, physique et informatique. Elle a pour but de concevoir et d’appliquer des modèles et outils statistiques et computationnels visant l’avancement des connaissances en biologie et dans les sciences connexes. Dans ce contexte, la compréhension du fonctionnement et de l’évolution des gènes fait l’objet de nombreuses études en bio-informatique. Ces études sont majoritairement fondées sur la comparaison des gènes et en particulier sur l’alignement de séquences génomiques. Cependant, dans leurs calculs d’alignement de séquences génomiques, les méthodes existantes se basent uniquement sur la similarité des séquences et ne tiennent pas compte de la structure des gènes. L’alignement prenant en compte la structure des séquences offre l’opportunité d’en améliorer la précision ainsi que les résultats des méthodes développées à partir de ces alignements. C’est dans cette hypothèse que s’inscrit l’objectif de cette thèse de doctorat : proposer des modèles tenant compte de la structure des gènes lors de l’alignement des séquences de familles de gènes. Ainsi, par cette thèse, nous avons contribué à accroître les connaissances scientifiques en développant des modèles d’alignement de séquences biologiques intégrant des informations sur la structure de codage et d’épissage des séquences. Nous avons proposé un algorithme et une nouvelle fonction du score pour l’alignement de séquences codantes d’ADN (CDS) en tenant compte de la longueur des décalages du cadre de traduction. Nous avons aussi proposé un algorithme pour aligner des paires de séquences d’une famille de gènes en considérant leurs structures d’épissage. Nous avons également développé un algorithme pour assembler des alignements épissés par paire en alignements multiples de séquences. Enfin, nous avons développé un outil pour la visualisation d’alignements épissés multiples de famille de gènes. Dans cette thèse, nous avons souligné l’importance et démontré l’utilité de tenir compte de la structure des séquences en entrée lors du calcul de leur alignement

Multiple sequence alignments of partially coding nucleic acid sequences

BACKGROUND: High quality sequence alignments of RNA and DNA sequences are an important prerequisite for the comparative analysis of genomic sequence data. Nucleic acid sequences, however, exhibit a much larger sequence heterogeneity compared to their encoded protein sequences due to the redundancy of the genetic code. It is desirable, therefore, to make use of the amino acid sequence when aligning coding nucleic acid sequences. In many cases, however, only a part of the sequence of interest is translated. On the other hand, overlapping reading frames may encode multiple alternative proteins, possibly with intermittent non-coding parts. Examples are, in particular, RNA virus genomes. RESULTS: The standard scoring scheme for nucleic acid alignments can be extended to incorporate simultaneously information on translation products in one or more reading frames. Here we present a multiple alignment tool, codaln, that implements a combined nucleic acid plus amino acid scoring model for pairwise and progressive multiple alignments that allows arbitrary weighting for almost all scoring parameters. Resource requirements of codaln are comparable with those of standard tools such as ClustalW. CONCLUSION: We demonstrate the applicability of codaln to various biologically relevant types of sequences (bacteriophage Levivirus and Vertebrate Hox clusters) and show that the combination of nucleic acid and amino acid sequence information leads to improved alignments. These, in turn, increase the performance of analysis tools that depend strictly on good input alignments such as methods for detecting conserved RNA secondary structure elements

Optimal DNA-protein alignments with application to large-scale genome analysis

DNA-protein alignment algorithms can be used to discover coding sequences in a genomic sequence, if the corresponding protein derivatives are known. They can also be used to identify potential coding sequences of a newly sequenced genome by using proteins from related species. Previously known algorithms for computing DNA-protein alignments have one or more of the following drawbacks: not taking into account all aspects in problem formulation, providing optimal solutions that are run-time/memory expensive, and sacrificing optimality to achieve practical implementation. In this thesis, we present a comprehensive formulation of the DNA-protein alignment problem including indels, substitutions, frameshift errors, and intronic insertions between and within codons. We then provide an algorithm to compute an optimal alignment in O(mn) time using only four dynamic programming tables of size (m+1)x(n+1), where m and n are the lengths of the DNA and protein sequences, respectively. We developed a Protein and DNA Alignment program (PanDA) that implements the proposed solution. Experimental results indicate that our algorithm provides alignments that accurately reproduce GenBank annotation in nearly all cases when tested on gene and protein sequences from the same organism. We also present experimental evidence that our algorithm produces high-quality alignments and exon-intron predictions when aligning DNA sequences with proteins corresponding to orthologous genes from other species. We also present a parallel software that can be used to annotate, validate, and improve the quality of an assembly of a genome in a large scale. Spliced alignments between DNA sequences of the assembly and protein sequences from other organisms are done to achieve the same. Experimental results indicate that our software can produce putative annotations, while detecting candidate contigs to improve quality of an assembly

Cross-species protein sequence and gene structure prediction with fine-tuned Webscipio 2.0 and Scipio

<p>Abstract</p> <p>Background</p> <p>Obtaining transcripts of homologs of closely related organisms and retrieving the reconstructed exon-intron patterns of the genes is a very important process during the analysis of the evolution of a protein family and the comparative analysis of the exon-intron structure of a certain gene from different species. Due to the ever-increasing speed of genome sequencing, the gap to genome annotation is growing. Thus, tools for the correct prediction and reconstruction of genes in related organisms become more and more important. The tool Scipio, which can also be used via the graphical interface WebScipio, performs significant hit processing of the output of the Blat program to account for sequencing errors, missing sequence, and fragmented genome assemblies. However, Scipio has so far been limited to high sequence similarity and unable to reconstruct short exons.</p> <p>Results</p> <p>Scipio and WebScipio have fundamentally been extended to better reconstruct very short exons and intron splice sites and to be better suited for cross-species gene structure predictions. The Needleman-Wunsch algorithm has been implemented for the search for short parts of the query sequence that were not recognized by Blat. Those regions might either be short exons, divergent sequence at intron splice sites, or very divergent exons. We have shown the benefit and use of new parameters with several protein examples from completely different protein families in searches against species from several kingdoms of the eukaryotes. The performance of the new Scipio version has been tested in comparison with several similar tools.</p> <p>Conclusions</p> <p>With the new version of Scipio very short exons, terminal and internal, of even just one amino acid can correctly be reconstructed. Scipio is also able to correctly predict almost all genes in cross-species searches even if the ancestors of the species separated more than 100 Myr ago and if the protein sequence identity is below 80%. For our test cases Scipio outperforms all other software tested. WebScipio has been restructured and provides easy access to the genome assemblies of about 640 eukaryotic species. Scipio and WebScipio are freely accessible at <url>http://www.webscipio.org</url>.</p

Pseudo–Messenger RNA: Phantoms of the Transcriptome

The mammalian transcriptome harbours shadowy entities that resist classification and analysis. In analogy with pseudogenes, we define pseudo–messenger RNA to be RNA molecules that resemble protein-coding mRNA, but cannot encode full-length proteins owing to disruptions of the reading frame. Using a rigorous computational pipeline, which rules out sequencing errors, we identify 10,679 pseudo–messenger RNAs (approximately half of which are transposon-associated) among the 102,801 FANTOM3 mouse cDNAs: just over 10% of the FANTOM3 transcriptome. These comprise not only transcribed pseudogenes, but also disrupted splice variants of otherwise protein-coding genes. Some may encode truncated proteins, only a minority of which appear subject to nonsense-mediated decay. The presence of an excess of transcripts whose only disruptions are opal stop codons suggests that there are more selenoproteins than currently estimated. We also describe compensatory frameshifts, where a segment of the gene has changed frame but remains translatable. In summary, we survey a large class of non-standard but potentially functional transcripts that are likely to encode genetic information and effect biological processes in novel ways. Many of these transcripts do not correspond cleanly to any identifiable object in the genome, implying fundamental limits to the goal of annotating all functional elements at the genome sequence level