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Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons.

Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based on more complex expression signatures found in existing functional classes. Previously, support vector machines (SVMs) and other machine-learning methods have been applied to a limited number of functional classes for this purpose. Here we present, for the first time, the comprehensive application of supervised neural networks (SNNs) for functional annotation. Our study is novel in that we report systematic results for ~100 classes in the Munich Information Center for Protein Sequences (MIPS) functional catalog. We found that only ~10% of these are learnable (based on the rate of false negatives). A closer analysis reveals that false positives (and negatives) in a machine-learning context are not necessarily "false" in a biological sense. We show that the high degree of interconnections among functional classes confounds the signatures that ought to be learned for a unique class. We term this the "Borges effect" and introduce two new numerical indices for its quantification. Our analysis indicates that classification systems with a lower Borges effect are better suitable for machine learning. Furthermore, we introduce a learning procedure for combining false positives with the original class. We show that in a few iterations this process converges to a gene set that is learnable with considerably low rates of false positives and negatives and contains genes that are biologically related to the original class, allowing for a coarse reconstruction of the interactions between associated biological pathways. We exemplify this methodology using the well-studied tricarboxylic acid cycle.

Algorithms↗

FunShift: a database of function shift analysis on protein subfamilies.

Members of a protein family normally have a general biochemical function in common, but frequently one or more subgroups have evolved a slightly different function, such as different substrate specificity. It is important to detect such function shifts for a more accurate functional annotation. The FunShift database described here is a compilation of function shift analysis performed between subfamilies in protein families. It consists of two main components: (i) subfamilies derived from protein domain families and (ii) pairwise subfamily comparisons analyzed for function shift. The present release, FunShift 12, was derived from Pfam 12 and consists of 151,934 subfamilies derived from 7300 families. We carried out function shift analysis by two complementary methods on families with up to 500 members. From a total of 179,210 subfamily pairs, 62,384 were predicted to be functionally shifted in 2881 families. Each subfamily pair is provided with a markup of probable functional specificity-determining sites. Tools for searching and exploring the data are provided to make this database a valuable resource for protein function annotation. Knowledge of these functionally important sites will be useful for experimental biologists performing functional mutation studies. FunShift is available at http://FunShift.cgb.ki.se.

Databases, Protein↗

Columba: an integrated database of proteins, structures, and annotations.

BACKGROUND: Structural and functional research often requires the computation of sets of protein structures based on certain properties of the proteins, such as sequence features, fold classification, or functional annotation. Compiling such sets using current web resources is tedious because the necessary data are spread over many different databases. To facilitate this task, we have created COLUMBA, an integrated database of annotations of protein structures. DESCRIPTION: COLUMBA currently integrates twelve different databases, including PDB, KEGG, Swiss-Prot, CATH, SCOP, the Gene Ontology, and ENZYME. The database can be searched using either keyword search or data source-specific web forms. Users can thus quickly select and download PDB entries that, for instance, participate in a particular pathway, are classified as containing a certain CATH architecture, are annotated as having a certain molecular function in the Gene Ontology, and whose structures have a resolution under a defined threshold. The results of queries are provided in both machine-readable extensible markup language and human-readable format. The structures themselves can be viewed interactively on the web. CONCLUSION: The COLUMBA database facilitates the creation of protein structure data sets for many structure-based studies. It allows to combine queries on a number of structure-related databases not covered by other projects at present. Thus, information on both many and few protein structures can be used efficiently. The web interface for COLUMBA is available at http://www.columba-db.de.

Base Sequence↗

Rare variant contribution to the heritability of coronary artery disease.

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Humans↗

Physiological genomics of Escherichia coli protein families.

The well-researched Escherichia coli genome offers the opportunity to explore the value of using protein families within a single organism to enrich functional annotation procedures and to study mechanisms of protein evolution. Having identified multimodular proteins resulting from gene fusion, and treated each module as a separate protein, nonoverlapping sequence-similar families in E. coli could be assembled. Of 3,902 proteins of length 100 residues or more, 2,415 clustered into 609 protein families. The relatedness of function among members of each family was dissected in detail. Data on paralogous protein families provides valuable information in attributing putative function to unknown genes, supplementing existing function annotation. Enzymes, transporters, and regulators represent the three major types of proteins in E. coli. They are shown to have distinctive patterns in gene duplication and divergence and gene fusion, suggesting that details of protein evolution have been different for genes in these categories. Data for the complete list of paralogous protein families and updated functional annotation for E. coli K-12 are accessible in GenProtEC (http://genprotec.mbl.edu).

Carrier Proteins↗

Learnability-based further prediction of gene functions in Gene Ontology.

Currently the functional annotations of many genes are not specific enough, limiting their further application in biology and medicine. It is necessary to push the gene functional annotations deeper in Gene Ontology (GO), or to predict further annotated genes with more specific GO terms. A framework of learnability-based further prediction of gene functions in GO is proposed in this paper. Local classifiers are constructed in local classification spaces rooted at qualified parent nodes in GO, and their classification performances are evaluated with the averaged Tanimoto index (ATI). Classification spaces with higher ATIs are selected out, and genes annotated only to the parent classes are predicted to child classes. Through learnability-based further predicting, the functional annotations of annotated genes are made more specific. Experiments on the fibroblast serum response dataset reported further functional predictions for several human genes and also gave interesting clues to the varied learnability between classes of different GO ontologies, different levels, and different numbers of child classes.

Computational Biology↗

Genomic-scale comparison of sequence- and structure-based methods of function prediction: does structure provide additional insight?

A function annotation method using the sequence-to-structure-to-function paradigm is applied to the identification of all disulfide oxidoreductases in the Saccharomyces cerevisiae genome. The method identifies 27 sequences as potential disulfide oxidoreductases. All previously known thioredoxins, glutaredoxins, and disulfide isomerases are correctly identified. Three of the 27 predictions are probable false-positives. Three novel predictions, which subsequently have been experimentally validated, are presented. Two additional novel predictions suggest a disulfide oxidoreductase regulatory mechanism for two subunits (OST3 and OST6) of the yeast oligosaccharyltransferase complex. Based on homology, this prediction can be extended to a potential tumor suppressor gene, N33, in humans, whose biochemical function was not previously known. Attempts to obtain a folded, active N33 construct to test the prediction were unsuccessful. The results show that structure prediction coupled with biochemically relevant structural motifs is a powerful method for the function annotation of genome sequences and can provide more detailed, robust predictions than function prediction methods that rely on sequence comparison alone.

Algorithms↗

A hitchhiker's guide to expressed sequence tag (EST) analysis.

Expressed sequence tag (EST) sequencing projects are underway for numerous organisms, generating millions of short, single-pass nucleotide sequence reads, accumulating in EST databases. Extensive computational strategies have been developed to organize and analyse both small- and large-scale EST data for gene discovery, transcript and single nucleotide polymorphism analysis as well as functional annotation of putative gene products. We provide an overview of the significance of ESTs in the genomic era, their properties and the applications of ESTs. Methods adopted for each step of EST analysis by various research groups have been compared. Challenges that lie ahead in organizing and analysing the ever increasing EST data have also been identified. The most appropriate software tools for EST pre-processing, clustering and assembly, database matching and functional annotation have been compiled (available online from http://biolinfo.org/EST). We propose a road map for EST analysis to accelerate the effective analyses of EST data sets. An investigation of EST analysis platforms reveals that they all terminate prior to downstream functional annotation including gene ontologies, motif/pattern analysis and pathway mapping.

Animals↗

Search for Bacillus anthracis potential vaccine candidates by a functional genomic-serologic screen.

Bacillus anthracis proteins that possess antigenic properties and are able to evoke an immune response were identified by a reductive genomic-serologic screen of a set of in silico-preselected open reading frames (ORFs). The screen included in vitro expression of the selected ORFs by coupled transcription and translation of linear PCR-generated DNA fragments, followed by immunoprecipitation with antisera from B. anthracis-infected animals. Of the 197 selected ORFs, 161 were chromosomal and 36 were on plasmids pXO1 and pXO2, and 138 of the 197 ORFs had putative functional annotations (known ORFs) and 59 had no assigned functions (unknown ORFs). A total of 129 of the known ORFs (93%) could be expressed, whereas only 38 (64%) of the unknown ORFs were successfully expressed. All 167 expressed polypeptides were subjected to immunoprecipitation with the anti-B. anthracis antisera, which revealed 52 seroreactive immunogens, only 1 of which was encoded by an unknown ORF. The high percentage of seroreactive ORFs among the functionally annotated ORFs (37%; 51/129) attests to the predictive value of the bioinformatic strategy used for vaccine candidate selection. Furthermore, the experimental findings suggest that surface-anchored proteins and adhesins or transporters, such as cell wall hydrolases, proteins involved in iron acquisition, and amino acid and oligopeptide transporters, have great potential to be immunogenic. Most of the seroreactive ORFs that were tested as DNA vaccines indeed appeared to induce a humoral response in mice. We list more than 30 novel B. anthracis immunoreactive virulence-related proteins which could be useful in diagnosis, pathogenesis studies, and future anthrax vaccine development.

Animals↗

TEAM: a tool for the integration of expression, and linkage and association maps.

The identification of genes primarily responsible for complex genetic disorders is a daunting task. Despite the assignment of many susceptibility loci, there has only been limited success in identifying disease genes based solely on positional information from genome-wide screens. The incorporation of several complementary strategies in a single integrated approach should facilitate and further enhance the efficacy of this search for genes. To permit the integration of linkage, association and expression data, together with functional annotations, we have developed a Java-based software tool: TEAM (tool for the integration of expression, and linkage and association maps). TEAM includes a genome viewer, capable of overlaying karyobands, genes, markers, linkage graphs, association data, gene expression levels and functional annotations in one composite view. Data management, analysis and filtering functionality was implemented and extended with links to the Ensembl, Unigene and Gene Ontology databases to facilitate gene annotation. Filtering functionality can help prevent the exclusion of poorly annotated, but differentially expressed, genes that reside in candidate regions that show linkage or association. Here we demonstrate the program's functionality in our study on coeliac disease (OMIM 212750), a multifactorial gluten-sensitive enteropathy. We performed a combined data analysis of a genome-wide linkage screen in 82 Dutch families with affected siblings and the microarray expression profiles of 18,110 cDNAs in 22 intestinal biopsies.

Celiac Disease↗

Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families.

MOTIVATION: Annotation of the biological function of different protein sequences is a time-consuming process currently performed by human experts. Genome analysis tools encounter great difficulty in performing this task. Database curators, developers of genome analysis tools and biologists in general could benefit from access to tools able to suggest functional annotations and facilitate access to functional information. APPROACH: We present here the first prototype of a system for the automatic annotation of protein function. The system is triggered by collections of s related to a given protein, and it is able to extract biological information directly from scientific literature, i.e. MEDLINE abstracts. Relevant keywords are selected by their relative accumulation in comparison with a domain-specific background distribution. Simultaneously, the most representative sentences and MEDLINE abstracts are selected and presented to the end-user. Evolutionary information is considered as a predominant characteristic in the domain of protein function. Our system consequently extracts domain-specific information from the analysis of a set of protein families. RESULTS: The system has been tested with different protein families, of which three examples are discussed in detail here: 'ataxia-telangiectasia associated protein', 'ran GTPase' and 'carbonic anhydrase'. We found generally good correlation between the amount of information provided to the system and the quality of the annotations. Finally, the current limitations and future developments of the system are discussed. AVAILABILITY: The current system can be considered as a prototype system. As such, it can be accessed as a server at http://columba.ebi.ac. uk:8765/andrade/abx. The system accepts text related to the protein or proteins to be evaluated (optimally, the result of a MEDLINE search by keyword) and the results are returned in the form of Web pages for keywords, sentences and s. SUPPLEMENTARY INFORMATION: Web pages containing full information on the examples mentioned in the text are available at: http://www.cnb.uam.es/ approximately cnbprot/keywords/ CONTACT: valencia@cnb.uam.es

Abstracting and Indexing↗

The institute for genomic research Osa1 rice genome annotation database.

We have developed a rice (Oryza sativa) genome annotation database (Osa1) that provides structural and functional annotation for this emerging model species. Using the sequence of O. sativa subsp. japonica cv Nipponbare from the International Rice Genome Sequencing Project, pseudomolecules, or virtual contigs, of the 12 rice chromosomes were constructed. Our most recent release, version 3, represents our third build of the pseudomolecules and is composed of 98% finished sequence. Genes were identified using a series of computational methods developed for Arabidopsis (Arabidopsis thaliana) that were modified for use with the rice genome. In release 3 of our annotation, we identified 57,915 genes, of which 14,196 are related to transposable elements. Of these 43,719 non-transposable element-related genes, 18,545 (42.4%) were annotated with a putative function, 5,777 (13.2%) were annotated as encoding an expressed protein with no known function, and the remaining 19,397 (44.4%) were annotated as encoding a hypothetical protein. Multiple splice forms (5,873) were detected for 2,538 genes, resulting in a total of 61,250 gene models in the rice genome. We incorporated experimental evidence into 18,252 gene models to improve the quality of the structural annotation. A series of functional data types has been annotated for the rice genome that includes alignment with genetic markers, assignment of gene ontologies, identification of flanking sequence tags, alignment with homologs from related species, and syntenic mapping with other cereal species. All structural and functional annotation data are available through interactive search and display windows as well as through download of flat files. To integrate the data with other genome projects, the annotation data are available through a Distributed Annotation System and a Genome Browser. All data can be obtained through the project Web pages at http://rice.tigr.org.

Computational Biology↗

Benchmarking PSI-BLAST in genome annotation.

The recognition of remote protein homologies is a major aspect of the structural and functional annotation of newly determined genomes. Here we benchmark the coverage and error rate of genome annotation using the widely used homology-searching program PSI-BLAST (position-specific iterated basic local alignment search tool). This study evaluates the one-to-many success rate for recognition, as often there are several homologues in the database and only one needs to be identified for annotating the sequence. In contrast, previous benchmarks considered one-to-one recognition in which a single query was required to find a particular target. The benchmark constructs a model genome from the full sequences of the structural classification of protein (SCOP) database and searches against a target library of remote homologous domains (<20 % identity). The structural benchmark provides a reliable list of correct and false homology assignments. PSI-BLAST successfully annotated 40 % of the domains in the model genome that had at least one homologue in the target library. This coverage is more than three times that if one-to-one recognition is evaluated (11 % coverage of domains). Although a structural benchmark was used, the results equally apply to just sequence homology searches. Accordingly, structural and sequence assignments were made to the sequences of Mycoplasma genitalium and Mycobacterium tuberculosis (see http://www.bmm.icnet. uk). The extent of missed assignments and of new superfamilies can be estimated for these genomes for both structural and functional annotations.

Algorithms↗

Beyond exons: Linking noncoding heritability and polygenicity across complex human traits and disorders.

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across 74 functional annotations covering exonic, intronic, and intergenic regions for 34 complex traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons account for a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less-polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of the broader set of functional annotations also reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less-polygenic traits show stronger contributions from promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, shifting from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects.

MiXeR↗

Practical limits of function prediction.

The widening gap between known protein sequences and their functions has led to the practice of assigning a potential function to a protein on the basis of sequence similarity to proteins whose function has been experimentally investigated. We present here a critical view of the theoretical and practical bases for this approach. The results obtained by analyzing a significant number of true sequence similarities, derived directly from structural alignments, point to the complexity of function prediction. Different aspects of protein function, including (i) enzymatic function classification, (ii) functional annotations in the form of key words, (iii) classes of cellular function, and (iv) conservation of binding sites can only be reliably transferred between similar sequences to a modest degree. The reason for this difficulty is a combination of the unavoidable database inaccuracies and the plasticity of protein function. In addition, analysis of the relationship between sequence and functional descriptions defines an empirical limit for pairwise-based functional annotations, namely, the three first digits of the six numbers used as descriptors of protein folds in the FSSP database can be predicted at an average level as low as 7.5% sequence identity, two of the four EC digits at 15% identity, half of the SWISS-PROT key words related to protein function would require 20% identity, and the prediction of half of the residues in the binding site can be made at the 30% sequence identity level.

Amino Acid Sequence↗

Pathway analysis in metabolic databases via differential metabolic display (DMD).

MOTIVATION: A number of metabolic databases are available electronically, some with features for querying and visualizing metabolic pathways and regulatory networks. We present a unifying, systematic approach based on PETRI nets for storing, displaying, comparing, searching and simulating such nets from a number of different sources. RESULTS: Information from each data source is extracted and compiled into a PETRI net. Such PETRI nets then allow to investigate the (differential) content in metabolic databases, to map and integrate genomic information and functional annotations, to compare sequence and metabolic databases with respect to their functional annotations, and to define, generate and search paths and pathways in nets. We present an algorithm to systematically generate all pathways satisfying additional constraints in such PETRI nets. Finally, based on the set of valid pathways, so-called differential metabolic displays (DMDs) are introduced to exhibit specific differences between biological systems, i.e. different developmental states, disease states, or different organisms, on the level of paths and pathways. DMDs will be useful for target finding and function prediction, especially in the context of the interpretation of expression data.

Algorithms↗

Differential gene expression in abdomens of the malaria vector mosquito, Anopheles gambiae, after sugar feeding, blood feeding and Plasmodium berghei infection.

BACKGROUND: Large scale sequencing of cDNA libraries can provide profiles of genes expressed in an organism under defined biological and environmental circumstances. We have analyzed sequences of 4541 Expressed Sequence Tags (ESTs) from 3 different cDNA libraries created from abdomens from Plasmodium infection-susceptible adult female Anopheles gambiae. These libraries were made from sugar fed (S), rat blood fed (RB), and P. berghei-infected (IRB) mosquitoes at 30 hours after the blood meal, when most parasites would be transforming ookinetes or very early oocysts. RESULTS: The S, RB and IRB libraries contained 1727, 1145 and 1669 high quality ESTs, respectively, averaging 455 nucleotides (nt) in length. They assembled into 1975 consensus sequences--567 contigs and 1408 singletons. Functional annotation was performed to annotate probable molecular functions of the gene products and the biological processes in which they function. Genes represented at high frequency in one or more of the libraries were subjected to digital Northern analysis and results on expression of 5 verified by qRT-PCR. CONCLUSION: 13% of the 1965 ESTs showing identity to the A. gambiae genome sequence represent novel genes. These, together with untranslated regions (UTR) present on many of the ESTs, will inform further genome annotation. We have identified 23 genes encoding products likely to be involved in regulating the cellular oxidative environment and 25 insect immunity genes. We also identified 25 genes as being up or down regulated following blood feeding and/or feeding with P. berghei infected blood relative to their expression levels in sugar fed females.

Abdomen↗

Transcriptome analyses of human genes and applications for proteome analyses.

By utilizing recently developed full-length cDNA technologies, large-scale cDNA sequencing was carried out by several cDNA projects. Now full-length cDNA resources cover the major part of the protein-coding human genes. Comprehensive analyses of the collected full-length cDNA data revealed not only the complete sequences of thousands of novel gene transcripts but also novel alternatively spliced isoforms of hitherto identified genes. However, it was not as easy as expected to deduce their encoded amino acid sequences based solely on the full-length cDNA sequences. It was neither always the case that the longest open reading frame corresponded to the real protein coding region nor that the first ATG was the translation initiator codon. Also, proteome-wide mass-spectrometry analysis has shown that there is an unexpectedly large population of small proteins, encoded by so-called upstream open reading frames, within the cell. Since sound manual annotations by experts were still indispensable to address these problems, an international meeting to make transcriptome-wide functional annotations of cDNAs was held, namely the H-invitational. In this meeting, functional annotations were made both manually and computationally for most of the pre-existing full-length cDNAs collected from world-wide cDNA projects. The achieved integrated information for each of the cDNAs was published as a database. It was also shown that the full-length cDNA data were useful for identifying alternative splicing variants, exact transcriptional start sites of the mRNAs and the adjacent promoter regions. Rapidly accumulating genome data as well as versatile use of the transcriptome information will shortly lay a firm foundation for proteome-level understanding of human gene networks.

Alternative Splicing↗