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PubMed2006

Composition-based statistics and translated nucleotide searches: improving the TBLASTN module of BLAST.

BACKGROUND: TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server. RESULTS: We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy. CONCLUSION: TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms.

Algorithms↗

PubMed2006

Performance assessment of promoter predictions on ENCODE regions in the EGASP experiment.

BACKGROUND: This study analyzes the predictions of a number of promoter predictors on the ENCODE regions of the human genome as part of the ENCODE Genome Annotation Assessment Project (EGASP). The systems analyzed operate on various principles and we assessed the effectiveness of different conceptual strategies used to correlate produced promoter predictions with the manually annotated 5' gene ends. RESULTS: The predictions were assessed relative to the manual HAVANA annotation of the 5' gene ends. These 5' gene ends were used as the estimated reference transcription start sites. With the maximum allowed distance for predictions of 1,000 nucleotides from the reference transcription start sites, the sensitivity of predictors was in the range 32% to 56%, while the positive predictive value was in the range 79% to 93%. The average distance mismatch of predictions from the reference transcription start sites was in the range 259 to 305 nucleotides. At the same time, using transcription start site estimates from DBTSS and H-Invitational databases as promoter predictions, we obtained a sensitivity of 58%, a positive predictive value of 92%, and an average distance from the annotated transcription start sites of 117 nucleotides. In this experiment, the best performing promoter predictors were those that combined promoter prediction with gene prediction. The main reason for this is the reduced promoter search space that resulted in smaller numbers of false positive predictions. CONCLUSION: The main finding, now supported by comprehensive data, is that the accuracy of human promoter predictors for high-throughput annotation purposes can be significantly improved if promoter prediction is combined with gene prediction. Based on the lessons learned in this experiment, we propose a framework for the preparation of the next similar promoter prediction assessment.

Computational Biology↗

PubMed2006

Mass spectrometric genomic data mining: Novel insights into bioenergetic pathways in Chlamydomonas reinhardtii.

A new high-throughput computational strategy was established that improves genomic data mining from MS experiments. The MS/MS data were analyzed by the SEQUEST search algorithm and a combination of de novo amino acid sequencing in conjunction with an error-tolerant database search tool, operating on a 256 processor computer cluster. The error-tolerant search tool, previously established as GenomicPeptideFinder (GPF), enables detection of intron-split and/or alternatively spliced peptides from MS/MS data when deduced from genomic DNA. Isolated thylakoid membranes from the eukaryotic green alga Chlamydomonas reinhardtii were separated by 1-D SDS gel electrophoresis, protein bands were excised from the gel, digested in-gel with trypsin and analyzed by coupling nano-flow LC with MS/MS. The concerted action of SEQUEST and GPF allowed identification of 2622 distinct peptides. In total 448 peptides were identified by GPF analysis alone, including 98 intron-split peptides, resulting in the identification of novel proteins, improved annotation of gene models, and evidence of alternative splicing.

Algorithms↗

PubMed2004

HGVbase: a curated resource describing human DNA variation and phenotype relationships.

The Human Genome Variation Database (HGVbase; http://hgvbase.cgb.ki.se) has provided a curated summary of human DNA variation for more than 5 years, thus facilitating research into DNA sequence variation and human phenotypes. The database has undergone many changes and improvements to accommodate increasing volumes and new types of data. The focus of HGVbase has recently shifted towards information on haplotypes and phenotypes, relationships between phenotypes and DNA variation, and collaborative efforts to provide a global resource for genome-phenome data. Open sharing and precise phenotype definitions are necessary to advance the current understanding of common diseases that are typified by complex aetiologies, small genetic effect sizes and multiple confounding factors that obscure positive study results. Association data will increasingly be collected as part of this new project thrust. This report describes the evolving features of HGVbase, and covers in detail the technological choices we have made to enable efficient storage and data mining of increasingly large and complex data sets.

Computational Biology↗

PubMed2001

Identification of 96 single nucleotide polymorphisms in eight genes involved in iron metabolism: efficiency of bioinformatic extraction compared with a systematic sequencing approach.

Single nucleotide polymorphisms (SNPs) can significantly contribute to the characterization of the genes predisposing to iron overloads or deficiencies. We report an SNP survey of coding and non-coding regions of eight genes involved in iron metabolism, by two successive methods. First, we made use of the public domain sequence data, by using assembled expressed sequence tags, non-redundant sequences, and SNP database screening. We extracted 77 potential SNPs of which only 31 could be further validated by sequencing DNA from 44 unrelated multi-ethnic individuals. Our results indicate that a bioinformatic approach may be effective only in those cases where candidate SNPs are extracted from two different data sources or in cases of experimentally confirmed SNPs. Second, additional systematic sequencing of DNA from 24 unrelated Breton subjects increased the number of SNPs over a total length of 86 kb to 96. The average distance between the SNPs and minor allele frequencies were higher than reported by others authors; this discrepancy may reflect the nature of the genes studied and the ethnic homogeneity of our test population.

Cation Transport Proteins↗

PubMed2005

High frequency of alternative first exons in erythroid genes suggests a critical role in regulating gene function.

The human genome uses alternative pre-mRNA splicing as an important mechanism to encode a complex proteome from a relatively small number of genes. An unknown number of these genes also possess multiple transcriptional promoters and alternative first exons that contribute another layer of complexity to gene expression mechanisms. Using a collection of more than 100 erythroid-expressed genes as a test group, we used genome browser tools and genetic databases to assess the frequency of alternative first exons in the genome. Remarkably, 35% of these erythroid genes show evidence of alternative first exons. The majority of the candidate first exons are situated upstream of the coding exons, whereas a few are located internally within the gene. Computational analyses predict transcriptional promoters closely associated with many of the candidate first exons, supporting their authenticity. Importantly, the frequent presence of consensus translation initiation sites among the alternative first exons suggests that many proteins have alternative N-terminal structures whose expression can be coupled to promoter choice. These findings indicate that alternative promoters and first exons are more widespread in the human genome than previously appreciated and that they may play a major role in regulating expression of selected protein isoforms in a tissue-specific manner.

Alternative Splicing↗

PubMed2005

[Phylogenetic analysis for H3A1 strain of all human influenza A virus].

OBJECTIVE: Influenza A virus remains an important pathogen which threatens humans. With the help of latest developed bioinformatics tools, all available human Influenza A virus H3A1 strains were explored to deeply understanding its evolution and variation rules. METHODS: All data of H3A1 sequence in NCBI Genbank and Influenza sequence database were downloaded and aligned in ClustalX with two step cluster method used to split the data and Bayesian phylogenetic tree analysis method applied to precisely construct phylogenetic tree for each clusters. RESULTS: Tree topology indicated that H3 strains evolved along a single evolution trunk and tree pattern and model parameter showed obvious variety tendency with time period. However, no geographic distribution features were found for key variation strains and big branch in trees. CONCLUSION: The evolution of human H3 strains were mainly driven by the interaction of human immune barriers and antigenic drift of virus. Since the influenza subtype had already been spread in human population, south China should not be considered as the originated areas of new strains, hence it should be treated as equally as other places in the world.

Antigens↗

PubMed2000

Enhanced genome annotation using structural profiles in the program 3D-PSSM.

A method (three-dimensional position-specific scoring matrix, 3D-PSSM) to recognise remote protein sequence homologues is described. The method combines the power of multiple sequence profiles with knowledge of protein structure to provide enhanced recognition and thus functional assignment of newly sequenced genomes. The method uses structural alignments of homologous proteins of similar three-dimensional structure in the structural classification of proteins (SCOP) database to obtain a structural equivalence of residues. These equivalences are used to extend multiply aligned sequences obtained by standard sequence searches. The resulting large superfamily-based multiple alignment is converted into a PSSM. Combined with secondary structure matching and solvation potentials, 3D-PSSM can recognise structural and functional relationships beyond state-of-the-art sequence methods. In a cross-validated benchmark on 136 homologous relationships unambiguously undetectable by position-specific iterated basic local alignment search tool (PSI-Blast), 3D-PSSM can confidently assign 18 %. The method was applied to the remaining unassigned regions of the Mycoplasma genitalium genome and an additional 13 regions were assigned with 95 % confidence. 3D-PSSM is available to the community as a web server: http://www.bmm.icnet.uk/servers/3dpssm

Algorithms↗

PubMed2004

LIP index for peptide classification using MS/MS and SEQUEST search via logistic regression.

This study addresses the issue of peptide identification resulting from tandem mass spectrometry proteomics analysis followed by database search. This work shows that the Logistic Identification of Peptides (LIP) Index achieves high sensitivity and specificity for peptide classification relative to a manually verified "gold" standard and also accurately estimates the probability of a correct peptide match. The LIP Index is a weighted average of SEQUEST output variables based on logistic regression models and is a transparent, easy to use, inclusive, extendable, and statistically sound approach to classify correct peptide identifications. Modifications, such as normalizing cross-correlations (Xcorr) for peptide length, adjusting for charge state, and the number of tryptic termini, significantly improve the fit the logistic regression models, as well as increase sensitivity and specificity. The LIP Index also incorporates earlier developed statistical models on spectral quality assessment and peptide identification, which further improves sensitivity and specificity.

Algorithms↗

PubMed2002

Dictionary-driven protein annotation.

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

Algorithms↗

PubMed2003

PCAS--a precomputed proteome annotation database resource.

BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. RESULTS: We report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome.PCAS is available at http://pak.cbi.pku.edu.cn/proteome/gca.php CONCLUSION: PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified.

Algorithms↗

PubMed2005

eXPRESSION: an in silico tool to predict patterns of gene expression.

In embryological studies, expression pattern analyses are of special importance since genes that have temporally and spatially restricted expression are not only essential as lineage markers but are often causative in formation of specific fates. Further, where a molecule is expressed can be quite revealing in regard to its endogenous function. We present a gene discovery tool, termed eXPRESSION, that utilizes the public EST databases to identify genes matching desired transcriptional profiles. We first tested and validated the ability of eXPRESSION to discover tissue-specific genes in the adult mouse; empirically as well as with DNA microarrays and RT-PCRs. These studies showed that eXPRESSION predictions could identify genes that are specifically expressed in adult mouse tissues. Next, we developed a novel search strategy to find genes that are expressed in specific regions or tissues of the developing mouse embryo. With these tools, we identified several novel genes that exhibited a neural-specific or neural-enriched expression pattern during murine development. The data show that eXPRESSION is widely applicable and may be used to identify both adult and embryonic tissue- or organ-specific genes with minimal cost and effort.

Algorithms↗

PubMed2004

The SUPERFAMILY database in 2004: additions and improvements.

The SUPERFAMILY database provides structural assignments to protein sequences and a framework for analysis of the results. At the core of the database is a library of profile Hidden Markov Models that represent all proteins of known structure. The library is based on the SCOP classification of proteins: each model corresponds to a SCOP domain and aims to represent an entire superfamily. We have applied the library to predicted proteins from all completely sequenced genomes (currently 154), the Swiss-Prot and TrEMBL databases and other sequence collections. Close to 60% of all proteins have at least one match, and one half of all residues are covered by assignments. All models and full results are available for download and online browsing at http://supfam.org. Users can study the distribution of their superfamily of interest across all completely sequenced genomes, investigate with which other superfamilies it combines and retrieve proteins in which it occurs. Alternatively, concentrating on a particular genome as a whole, it is possible first, to find out its superfamily composition, and secondly, to compare it with that of other genomes to detect superfamilies that are over- or under-represented. In addition, the webserver provides the following standard services: sequence search; keyword search for genomes, superfamilies and sequence identifiers; and multiple alignment of genomic, PDB and custom sequences.

Animals↗

PubMed2005

Inference and analysis of haplotypes from combined genotyping studies deposited in dbSNP.

In the attempt to understand human variation and the genetic basis of complex disease, a tremendous number of single nucleotide polymorphisms (SNPs) have been discovered and deposited into NCBI's dbSNP public database. More than 2.7 million SNPs in the database have genotype information. This data provides an invaluable resource for understanding the structure of human variation and the design of genetic association studies. The genotypes deposited to dbSNP are unphased, and thus, the haplotype information is unknown. We applied the phasing method HAP to obtain the haplotype information, block partitions, and tag SNPs for all publicly available genotype data and deposited this information into the dbSNP database. We also deposited the orthologous chimpanzee reference sequence for each predicted haplotype block computed using the UCSC BLASTZ alignments of human and chimpanzee. Using dbSNP, researchers can now easily perform analyses using multiple genotype data sets from the same genomic regions. Dense and sparse genotype data sets from the same region were combined to show that the number of common haplotypes is significantly underestimated in whole genome data sets, while the predicted haplotypes over the common SNPs are consistent between studies. To validate the accuracy of the predictions, we bench-marked HAP's running time and phasing accuracy against PHASE. Although HAP is slightly less accurate than PHASE, HAP is over 1000 times faster than PHASE, making it suitable for application to the entire set of genotypes in dbSNP.

Animals↗

PubMed2006

Rank information: a structure-independent measure of evolutionary trace quality that improves identification of protein functional sites.

Protein functional sites are key targets for drug design and protein engineering, but their large-scale experimental characterization remains difficult. The evolutionary trace (ET) is a computational approach to this problem that has been useful in a variety of case studies, but its proteomic scale application is partially hindered because automated retrieval of input sequences from databases often includes some with errors that degrade functional site identification. To recognize and purge these sequences, this study introduces a novel and structure-free measure of ET quality called rank information (RI). It is shown that RI decreases in response to errors in sequences, alignments, or functional classifications. Conversely, an automated procedure to increase RI by selectively removing sequences improves functional site identification so as to nearly match manually curated traces in kinases and in a test set of 79 diverse proteins. Thus we conclude that RI partially reflects the evolutionary consistency of sequence, structure, and function. In practice, as the size of the proteome continues to grow exponentially, it provides a novel and structure-free measure of ET quality that increases its accuracy for large-scale automated annotation of protein functional sites.

Algorithms↗

PubMed2005

The complement of enzymatic sets in different species.

We present here a comprehensive analysis of the complement of enzymes in a large variety of species. As enzymes are a relatively conserved group there are several classification systems available that are common to all species and link a protein sequence to an enzymatic function. Enzymes are therefore an ideal functional group to study the relationship between sequence expansion, functional divergence and phenotypic changes. By using information retrieved from the well annotated SWISS-PROT database together with sequence information from a variety of fully sequenced genomes and information from the EC functional scheme we have aimed here to estimate the fraction of enzymes in genomes, to determine the extent of their functional redundancy in different domains of life and to identify functional innovations and lineage specific expansions in the metazoa lineage. We found that prokaryote and eukaryote species differ both in the fraction of enzymes in their genomes and in the pattern of expansion of their enzymatic sets. We observe an increase in functional redundancy accompanying an increase in species complexity. A quantitative assessment was performed in order to determine the degree of functional redundancy in different species. Finally, we report a massive expansion in the number of mammalian enzymes involved in signalling and degradation.

Animals↗

PubMed2001

Automated prediction of 15N, 13Calpha, 13Cbeta and 13C' chemical shifts in proteins using a density functional database.

A database of peptide chemical shifts, computed at the density functional level, has been used to develop an algorithm for prediction of 15N and 13C shifts in proteins from their structure; the method is incorporated into a program called SHIFTS (version 4.0). The database was built from the calculated chemical shift patterns of 1335 peptides whose backbone torsion angles are limited to areas of the Ramachandran map around helical and sheet configurations. For each tripeptide in these regions of regular secondary structure (which constitute about 40% of residues in globular proteins) SHIFTS also consults the database for information about sidechain torsion angle effects for the residue of interest and for the preceding residue, and estimates hydrogen bonding effects through an empirical formula that is also based on density functional calculations on peptides. The program optionally searches for alternate side-chain torsion angles that could significantly improve agreement between calculated and observed shifts. The application of the program on 20 proteins shows good consistency with experimental data, with correlation coefficients of 0.92, 0.98, 0.99 and 0.90 and r.m.s. deviations of 1.94, 0.97, 1.05, and 1.08 ppm for 15N, 13Calpha, 13Cbeta and 13C', respectively. Reference shifts fit to protein data are in good agreement with 'random-coil' values derived from experimental measurements on peptides. This prediction algorithm should be helpful in NMR assignment, crystal and solution structure comparison, and structure refinement.

Algorithms↗

PubMed2001

Strain-specific genes of Helicobacter pylori: distribution, function and dynamics.

Whole-genome clustering of the two available genome sequences of Helicobacter pylori strains 26695 and J99 allows the detection of 110 and 52 strain-specific genes, respectively. This set of strain-specific genes was compared with the sets obtained with other computational approaches of direct genome comparison as well as experimental data from microarray analysis. A considerable number of novel function assignments is possible using database-driven sequence annotation, although the function of the majority of the identified genes remains unknown. Using whole-genome clustering, it is also possible to detect species-specific genes by comparing the two H.pylori strains against the genome sequence of Campylobacter jejuni. It is interesting that the majority of strain-specific genes appear to be species specific. Finally, we introduce a novel approach to gene position analysis by employing measures from directional statistics. We show that although the two strains exhibit differences with respect to strain-specific gene distributions, this is due to the extensive genome rearrangements. If these are taken into account, a common pattern for the genome dynamics of the two Helicobacter strains emerges, suggestive of certain spatial constraints that may act as control mechanisms of gene flux.

Amino Acid Sequence↗