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J Tamames

Publications and source records attributed to J Tamames.

13 recordsLinked to original sources

Prediction of human protein function from post-translational modifications and localization features.

We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects such as the length, isoelectric point and composition of the polypeptide chain.

Computational Biology↗

Evolution of gene order conservation in prokaryotes.

BACKGROUND: As more complete genomes are sequenced, conservation of gene order between different organisms is emerging as an informative property of the genomes. Conservation of gene order has been used for predicting function and functional interactions of proteins, as well as for studying the evolutionary relationships between genomes. The reasons for the maintenance of gene order are still not well understood, as the organization of the prokaryote genome into operons and lateral gene transfer cannot possibly account for all the instances of conservation found. Comprehensive studies of gene order are one way of elucidating the nature of these maintaining forces. RESULTS: Gene order is extensively conserved between closely related species, but rapidly becomes less conserved among more distantly related organisms, probably in a cooperative fashion. This trend could be universal in prokaryotic genomes, as archaeal genomes are likely to behave similarly to bacterial genomes. Gene order conservation could therefore be used as a valid phylogenetic measure to study relationships between species. Even between very distant species, remnants of gene order conservation exist in the form of highly conserved clusters of genes. This suggests the existence of selective processes that maintain the organization of these regions. Because the clusters often span more than one operon, common regulation probably cannot be invoked as the cause of the maintenance of gene order. CONCLUSIONS: Gene order conservation is a genomic measure that can be useful for studying relationships between prokaryotes and the evolutionary forces shaping their genomes. Gene organization is extensively conserved in some genomic regions, and further studies are needed to elucidate the reason for this conservation.

Conserved Sequence↗

Bringing gene order into bacterial shape.

A different arrangement of a cluster of genes involved in division and cell-wall synthesis separates bacilli from other bacteria in a phylogenetic analysis. We conclude that the relationships between these genes are not random and might reflect significant events in the evolution of the coupling between growth and division in bacteria.

Bacteria↗

Functional classes in the three domains of life.

The evolutionary divergence among the three major domains of life can now be addressed through the first set of complete genomes from representative species. These model species from the three domains of life, Haemophilus influenzae for Bacteria, Saccharomyces cerevisiae for Eukarya, and Methanococcus jannaschii for Archaea, provide the basis for a universal functional classification and analysis. We have chosen 13 functional classes and three superclasses (ENERGY, COMMUNICATION and INFORMATION) as global descriptors of protein function. Compositional comparison of the three complete genomes reveals that functional classes are ubiquitous yet diverse in the three domains of life. Proteins related with ENERGY processes are generally represented in all three domains, while those related with COMMUNICATION represent the most distinctive functional feature of each single domain. Finally, functions related with INFORMATION processing (translation, transcription, and replication) show a complex behaviour. In Archaea, proteins in this superclass are related with proteins in either Eukarya or Bacteria, as recognized previously. The distribution of functional classes in the three domains accurately reflects the principal characteristics of cellular life forms.

Archaeal Proteins↗

Automated genome sequence analysis and annotation.

MOTIVATION: Large-scale genome projects generate a rapidly increasing number of sequences, most of them biochemically uncharacterized. Research in bioinformatics contributes to the development of methods for the computational characterization of these sequences. However, the installation and application of these methods require experience and are time consuming. RESULTS: We present here an automatic system for preliminary functional annotation of protein sequences that has been applied to the analysis of sets of sequences from complete genomes, both to refine overall performance and to make new discoveries comparable to those made by human experts. The GeneQuiz system includes a Web-based browser that allows examination of the evidence leading to an automatic annotation and offers additional information, views of the results, and links to biological databases that complement the automatic analysis. System structure and operating principles concerning the use of multiple sequence databases, underlying sequence analysis tools, lexical analyses of database annotations and decision criteria for functional assignments are detailed. The system makes automatic quality assessments of results based on prior experience with the underlying sequence analysis tools; overall error rates in functional assignment are estimated at 2.5-5% for cases annotated with highest reliability ('clear' cases). Sources of over-interpretation of results are discussed with proposals for improvement. A conservative definition for reporting 'new findings' that takes account of database maturity is presented along with examples of possible kinds of discoveries (new function, family and superfamily) made by the system. System performance in relation to sequence database coverage, database dynamics and database search methods is analysed, demonstrating the inherent advantages of an integrated automatic approach using multiple databases and search methods applied in an objective and repeatable manner. AVAILABILITY: The GeneQuiz system is publicly available for analysis of protein sequences through a Web server at http://www.sander.ebi.ac. uk/gqsrv/submit

Amino Acid Sequence↗

EUCLID: automatic classification of proteins in functional classes by their database annotations.

UNLABELLED: A tool is described for the automatic classification of sequences in functional classes using their database annotations. The Euclid system is based on a simple learning procedure from examples provided by human experts. AVAILABILITY: Euclid is freely available for academics at http://www.gredos.cnb.uam.es/EUCLID, with the corresponding dictionaries for the generation of three, eight and 14 functional classes. CONTACT: E-mail: valencia@cnb.uam.es SUPPLEMENTARY INFORMATION: The results of the EUCLID classification of different genomes are available at http://www.sander.ebi.ac. uk/genequiz/. A detailed description of the different applications mentioned in the text is available at http://www.gredos.cnb.uam. es/EUCLID/Full_Paper

Computational Biology↗

Conserved clusters of functionally related genes in two bacterial genomes.

An approach for genome comparison, combining function classification of gene products and sequence comparison, is presented. The genomes of Haemophilus influenzae and Escherichia coli are analyzed, and all genes are classified into nine major functional classes, corresponding to important cellular processes. To study gene order relationships and genome organization in the two bacteria, we performed statistics on neighboring pairs of genes. To estimate the significance of the observations, a statistical model based on binomial distributions has been developed. Significant patterns of gene order are observed within, as well as between, the two bacterial genomes: Functionally related genes tend to be neighbors more often than do unrelated genes. Some of these groups represent well-known operons, but additional gene clusters are identified. These clusters correspond to genomic elements that have been conserved during bacterial evolution. In addition to nearest-neighbor relationships, the method is also useful to study the relative direction of transcription in genomes, which is also highly conserved between homologous gene pairs. This new approach combines the high-level description of molecular function with pair statistics that express genome organization. It is expected to complement traditional methods of sequence analysis in the study of genomic structure, function, and evolution.

Binomial Distribution↗

Genomes with distinct function composition.

The functional composition of organisms can be analysed for the first time with the appearance of complete or sizeable parts of various genomes. We have reduced the problem of protein function classification to a simple scheme with three classes of protein function: energy-, information- and communication-associated proteins. Finer classification schemes can be easily mapped to the above three classes. To deal with the vast amount of information, a system for automatic function classification using database annotations has been developed. The system is able to classify correctly about 80% of the query sequences with annotations. Using this system, we can analyse samples from the genomes of the most represented species in sequence databases and compare their genomic composition. The similarities and differences for different taxonomic groups are strikingly intuitive. Viruses have the highest proportion of proteins involved in the control and expression of genetic information. Bacteria have the highest proportion of their genes dedicated to the production of proteins associated with small molecule transformations and transport. Animals have a very large proportion of proteins associated with intra- and intercellular communication and other regulatory processes. In general, the proportion of communication-related proteins increases during evolution, indicating trends that led to the emergence of the eukaryotic cell and later the transition from unicellular to multicellular organisms.

Animals↗

Computational comparisons of model genomes.

Complete genomes from model organisms provide new challenges for computational molecular biology. Novel questions emerge from the genome data obtained from the functional prediction of thousands of gene products. In this review, we present some approaches to the computational comparison of genomes, based on sequence and text analysis, and comparisons of genome composition and gene order.

Biotechnology↗

Nucleotide sequence and analysis of the centromeric region of yeast chromosome IX.

We have determined the nucleotide sequence of a cosmid (pIX338) containing the centromere region of yeast (Saccharomyces cerevisiae) chromosome IX. The complete nucleotide sequence of 33.8 kb was obtained by using an efficient directed sequencing strategy in combination with automated DNA sequencing on the A.L.F. DNA sequencer. Sequence analysis revealed the presence of 17 open reading frames (ORFs), four of them previously known yeast genes (sly12, pan1, sts1 and prl1), a tRNA gene and the centromere motif. Exhaustive database searches detected sequence homologues of known function for as many as 14 of the 17 ORFs. These include a mammalian tyrosine kinase substrate; the Escherichia coli cell cycle protein MinD; the human inositol polyphosphate-5-phosphatase (gene OCRL) involved in Lowe's syndrome, a developmental disorder; and helicases, for which the new yeast member defines a distinct DEAD/H-box subfamily. A surprisingly large fraction of the ORFs (at least six out of 17) in the centromeric region are apparently involved in RNA or DNA binding.

Adenosine Triphosphatases↗