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Molecular fossils in the human genome: identification and analysis of the pseudogenes in chromosomes 21 and 22.

We have developed an initial approach for annotating and surveying pseudogenes in the human genome. We search human genomic DNA for regions that are similar to known protein sequences and contain obvious disablements (i.e., mid-sequence stop codons or frameshifts), while ensuring minimal overlap with annotations of known genes. Pseudogenes can be divided into "processed" and "nonprocessed"; the former are reverse transcribed from mRNA (and therefore have no intron structure), whereas the latter presumably arise from genomic duplications. We annotate putative processed pseudogenes based on whether there is a continuous span of homology that is >70% of the length of the closest matching human protein (i.e., with introns removed), or whether there is evidence of polyadenylation. We have applied our approach to chromosomes 21 and 22, the first parts of the human genome completely sequenced, finding 190 new pseudogene annotations beyond the 264 reported by the sequencing centers. In total, on chromosomes 21 and 22, there are 189 processed pseudogenes, 195 nonprocessed pseudogenes, and, additionally, 70 pseudogenic immunoglobulin gene segments. (Detailed assignments are available at http://bioinfo.mbb.yale.edu/genome/pseudogene or http://genecensus.org/pseudogene.) By extrapolation, we predict that there could be up to approximately 20,000 pseudogenes in the whole human genome, with a little more than half of them processed. We have determined the main populations and clusters of pseudogenes on chromosomes 21 and 22. There are notable excesses of pseudogenes relative to genes near the centromeres of both chromosomes, indicating the existence of pseudogenic "hot-spots" in the genome. We have looked at the distribution of InterPro families and Gene Ontology (GO) functional categories in our pseudogenes. Overall, the families in both processed and nonprocessed pseudogene populations occur according to a similar power-law distribution as that found for the occurrence of gene families, with a few big families and many small ones. The processed population is, in particular, enriched in highly expressed ribosomal-protein sequences (approximately 20%), which appear fairly evenly distributed across the chromosomes. We compared processed pseudogenes of different evolutionary ages, observing a high degree of similarity between "ancient" and "modern" subpopulations. This may be attributable to the consistently high expression of ribosomal proteins over evolutionary time. Finally, we find that chromosome 22 pseudogene population is dominated by immunoglobulin segments, which have a greater rate of disablement per amino acid than the other pseudogene populations and are also substantially more diverged.

Chromosome Mapping↗

Morphological irregularities and features of resistance to apoptosis in the dcp-1/pita double mutated egg chambers during Drosophila oogenesis.

In the present study, we demonstrate the most novel characteristic morphological features of Drosophila egg chambers lacking both dcp-1 and pita functions in the germline cells. Dcp-1 is an effector caspase and it has been previously shown to play an important role during Drosophila oogenesis [McCall and Steller, 1998 : Science 279 : 230-234; Laundrie et al., 2003 : Genetics 165 : 1881-1888; Peterson et al., 2003 : Dev Biol 260 : 113-123]. The completion of sequencing and annotation of the Drosophila genome has revealed that the dcp-1 gene is nested within an intron of another distinct gene, called pita, a member of the C2H2 zinc finger protein family that regulates transcriptional initiation. The dcp-1(-/-)/pita(-/-) nurse cells exhibit euchromatic nuclei (delay of apoptosis) during the late stages of oogenesis, as revealed by conventional light and electron microscopy. The phalloidin-FITC staining discloses significant defects in actin cytoskeleton arrangement. The actin bundles fail to organize properly and the distribution of actin filaments in the ring canals is changed compared to the wild type. The oocyte and the chorion structures have been also modified. The oocyte nucleus is out of position and the chorion appears to contain irregular foldings, while the respiratory filaments obtain an altered morphology. The dcp-1(-/-)/pita(-/-) egg chambers do not exhibit the rare events of spontaneously induced apoptosis, observed for the wild type flies, during mid-oogenesis. Interestingly, the mutated egg chambers are protected by staurosporine-induced apoptosis in a percentage of 40%, strongly suggesting the essential role of dcp-1 and/or pita during mid-oogenesis.

Actins↗

Identification of FGF-dependent genes in the Drosophila tracheal system.

The embryonic development of the tracheal system of the fruit fly Drosophila provides a paradigm for genetic studies of branching morphogenesis. Efforts of many laboratories have identified Branchless (Bnl, a fibroblast growth factor homologue) and Breathless (Btl, the receptor homologue) as crucial factors at many stages of tracheal system development. The downstream targets of the Bnl/Btl signalling cascade, however, remain mostly unknown. Misexpression of the bnl gene results in specific tracheal phenotypes that lead to larval death. We characterised the transcriptional profiles of targeted over-expression of bnl in the embryonic trachea and of loss-of-function bnl(P1) mutant embryos. Gene expression data was mapped to high-throughput in situ hybridisation based ImaGO-annotation. Thus, we identified and confirmed by quantitative PCR 13 Bnl-dependent genes that are expressed in cells within and outside of the tracheal system.

Amino Acid Sequence↗

Extension of CyanoBase. CyanoMutants: repository of mutant information on Synechocystis sp. strain PCC6803.

CyanoBase provides internet access to the complete genomic information of the cyanobacterium Synechocystis sp. strain PCC6803. CyanoBase contains annotations to each protein-coding gene, deduced from the entire nucleotide sequence of the genome, gene classification lists, keywords and similarity search engines. The present paper describes a recent extension of CyanoBase, named CyanoMutants. CyanoMutants is a repository database of mutant information on PCC6803. Each entry contains a dataset which describes a gene identifier, mutant information, and an address for correspondence. Two closely-linked databases, CyanoBase and CyanoMutants, connect information obtained from computational analysis to experimental analysis resulting in the clarification of the functions of hypothetical genes of the cyanobacterial genome. CyanoMutants can be accessed at http://www.kazusa.or. jp/cyano/mutants/

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↗

Phylogenomic identification of five new human homologs of the DNA repair enzyme AlkB.

BACKGROUND: Combination of biochemical and bioinformatic analyses led to the discovery of oxidative demethylation - a novel DNA repair mechanism catalyzed by the Escherichia coli AlkB protein and its two human homologs, hABH2 and hABH3. This discovery was based on the prediction made by Aravind and Koonin that AlkB is a member of the 2OG-Fe2+ oxygenase superfamily. RESULTS: In this article, we report identification and sequence analysis of five human members of the (2OG-Fe2+) oxygenase superfamily designated here as hABH4 through hABH8. These experimentally uncharacterized and poorly annotated genes were not associated with the AlkB family in any database, but are predicted here to be phylogenetically and functionally related to the AlkB family (and specifically to the lineage that groups together hABH2 and hABH3) rather than to any other oxygenase family. Our analysis reveals the history of ABH gene duplications in the evolution of vertebrate genomes. CONCLUSIONS: We hypothesize that hABH 4-8 could either be back-up enzymes for hABH1-3 or may code for novel DNA or RNA repair activities. For example, enzymes that can dealkylate N3-methylpurines or N7-methylpurines in DNA have not been described. Our analysis will guide experimental confirmation of these novel human putative DNA repair enzymes.

Amino Acid Sequence↗

Formin homology 2 domains occur in multiple contexts in angiosperms.

BACKGROUND: Involvement of conservative molecular modules and cellular mechanisms in the widely diversified processes of eukaryotic cell morphogenesis leads to the intriguing question: how do similar proteins contribute to dissimilar morphogenetic outputs. Formins (FH2 proteins) play a central part in the control of actin organization and dynamics, providing a good example of evolutionarily versatile use of a conserved protein domain in the context of a variety of lineage-specific structural and signalling interactions. RESULTS: In order to identify possible plant-specific sequence features within the FH2 protein family, we performed a detailed analysis of angiosperm formin-related sequences available in public databases, with particular focus on the complete Arabidopsis genome and the nearly finished rice genome sequence. This has led to revision of the current annotation of half of the 22 Arabidopsis formin-related genes. Comparative analysis of the two plant genomes revealed a good conservation of the previously described two subfamilies of plant formins (Class I and Class II), as well as several subfamilies within them that appear to predate the separation of monocot and dicot plants. Moreover, a number of plant Class II formins share an additional conserved domain, related to the protein phosphatase/tensin/auxilin fold. However, considerable inter-species variability sets limits to generalization of any functional conclusions reached on a single species such as Arabidopsis. CONCLUSIONS: The plant-specific domain context of the conserved FH2 domain, as well as plant-specific features of the domain itself, may reflect distinct functional requirements in plant cells. The variability of formin structures found in plants far exceeds that known from both fungi and metazoans, suggesting a possible contribution of FH2 proteins in the evolution of the plant type of multicellularity.

Actins↗

DNASTAR's Lasergene sequence analysis software.

Lasergene's eight modules provide tools that enable users to accomplish each step of sequence analysis, from trimming and assembly of sequence data, to gene discovery, annotation, gene product analysis, sequence similarity searches, sequence alignment, phylogenetic analysis, oligonucleotide primer design, cloning strategies, and publication of the results. The Lasergene software suite provides the functions and customization tools needed so that users can perform analyses the software writers never imagined.

Base Sequence↗

Pathway proteomics: global and focused approaches.

Biological pathways represent the relationships (reactions and interactions) between biological molecules in the context of normal cellular functions and disease mechanisms. Understanding the roles of proteins and signaling pathways expressed within disease, and their link to drug discovery and drug development are central in today's target-driven pharmaceutical processes. This article gives an overview of proteomics strategies, including global expression analysis as well as focused approaches using multidimensional separation by both gel- and liquid-phase techniques linked to mass spectrometry, as applied to two of the pathways involved in inflammatory diseases. In primary human cell studies, our group has annotated and identified thousands of proteins using both electrospray ionization and matrix-assisted laser desorption ionization (MALDI)-sequencing technology. Annotations made from gel images and chromatography fractionation, interfaced to high-end mass spectrometry sequence and structure identity, are cornerstones in cutting-edge protein expression profiling. Regarding phosphorylation mechanisms of kinases, the quantitative stoichiometry can be determined using affinity probe isolations. Another strategy involves micro-preparative sample processing, which has been used to analyze single-target phosphoproteins and their relative phospho-stoichiometry.

Electrophoresis, Gel, Two-Dimensional↗

The predicted impact of coding single nucleotide polymorphisms database.

Nonsynonymous single nucleotide polymorphisms (nsSNP) have the potential to affect the structure or function of expressed proteins and are, therefore, likely to represent modifiers of inherited susceptibility. We have classified and catalogued the predicted functionality of nsSNPs in genes relevant to the biology of cancer to facilitate sequence-based association studies. Candidate genes were identified using targeted search terms and pathways to interrogate the Gene Ontology Consortium database, Kyoto Encyclopedia of Genes and Genomes database, Iobion's Interaction Explorer PathwayAssist Program, National Center for Biotechnology Information Entrez Gene database, and CancerGene database. A total of 9,537 validated nsSNPs located within annotated genes were retrieved from National Center for Biotechnology Information dbSNP Build 123. Filtering this list and linking it to 7,080 candidate genes yielded 3,666 validated nsSNPs with minor allele frequencies > or =0.01 in Caucasian populations. The functional effect of nsSNPs in genes with a single mRNA transcript was predicted using three computational tools-Grantham matrix, Polymorphism Phenotyping, and Sorting Intolerant from Tolerant algorithms. The resultant pool of 3,009 fully annotated nsSNPs is accessible from the Predicted Impact of Coding SNPs database at http://www.icr.ac.uk/cancgen/molgen/MolPopGen_PICS_database.htm. Predicted Impact of Coding SNPs is an ongoing project that will continue to curate and release data on the putative functionality of coding SNPs.

Algorithms↗

ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes.

BACKGROUND: It necessary to use highly accurate and statistics-based systems for viral and phage genome annotations. The GeneMark systems for gene-finding in virus and phage genomes suffer from some basic drawbacks. This paper puts forward an alternative approach for viral and phage gene-finding to improve the quality of annotations, particularly for newly sequenced genomes. RESULTS: The new system ZCURVE_V has been run for 979 viral and 212 phage genomes, respectively, and satisfactory results are obtained. To have a fair comparison with the currently available software of similar function, GeneMark, a total of 30 viral genomes that have not been annotated by GeneMark are selected to be tested. Consequently, the average specificity of both systems is well matched, however the average sensitivity of ZCURVE_V for smaller viral genomes (< 100 kb), which constitute the main parts of viral genomes sequenced so far, is higher than that of GeneMark. Additionally, for the genome of Amsacta moorei entomopoxvirus, probably with the lowest genomic GC content among the sequenced organisms, the accuracy of ZCURVE_V is much better than that of GeneMark, because the later predicts hundreds of false-positive genes. ZCURVE_V is also used to analyze well-studied genomes, such as HIV-1, HBV and SARS-CoV. Accordingly, the performance of ZCURVE_V is generally better than that of GeneMark. Finally, ZCURVE_V may be downloaded and run locally, particularly facilitating its utilization, whereas GeneMark is not downloadable. Based on the above comparison, it is suggested that ZCURVE_V may serve as a preferred gene-finding tool for viral and phage genomes newly sequenced. However, it is also shown that the joint application of both systems, ZCURVE_V and GeneMark, leads to better gene-finding results. The system ZCURVE_V is freely available at: http://tubic.tju.edu.cn/Zcurve_V/. CONCLUSION: ZCURVE_V may serve as a preferred gene-finding tool used for viral and phage genomes, especially for anonymous viral and phage genomes newly sequenced.

Algorithms↗

Endosperm-preferred expression of maize genes as revealed by transcriptome-wide analysis of expressed sequence tags.

The transcriptome-wide endosperm-preferred expression of maize genes was addressed by analyzing a large database of expressed sequence tags (ESTs). We generated 30,531 high quality sequence-reads from the 5'-ends of cDNA libraries from maize endosperm harvested at 10, 15, and 20 days after pollination. A further 196,900 maize sequence-reads retrieved from public databases were added to this endosperm collection to generate MAIZEST, a database with tools for data storage and analysis. MAIZEST contains 227,431 ESTs, one third of which represents developing endosperm and the remaining two-thirds represent transcripts from 49 cDNA libraries constructed from different organs and tissues. Assembling the MAIZEST ESTs generated 29,206 putative transcripts, of which a set of 4032 assembled sequences was composed exclusively of sequences derived from endosperm cDNA libraries. After sequence analysis using overlapping parameters, a sub-set of 2403 assembled sequences was functionally annotated and revealed a wide variety of putative new genes involved in endosperm development and metabolism.

Expressed Sequence Tags↗

Genome-wide expression profiling of a cardiac pressure overload model identifies major metabolic and signaling pathway responses.

Cardiac hypertrophy is a predictor of cardiovascular morbidity and mortality independent of other risk factors. Pressure overload induces the development of left ventricular hypertrophy (LVH) and left atrial enlargement (LAE) in the mammalian heart. To systematically investigate the transcriptional changes, which mediate these processes, we have performed a genome-wide transcriptional profiling of each of the four heart chambers from mice subjected to transverse aortic constriction (TAC). A major new finding of this analysis is that during enlargement the left atrium undergoes radical changes in gene transcription that may play a significant role in pathophysiology. Structural changes in the LA and LV are correlated with significant changes in the transcriptional profile of these chambers, with thousands of differentially expressed known and novel factors. Statistical analysis of the results identified Gene Ontology biological process groups with significant group-wide changes, including angiogenesis, energy pathways, fatty acid oxidation, oxidative phosphorylation, cytoskeletal and matrix reorganization, and G-protein coupled receptor (GPCR) signaling. To facilitate future research, a searchable annotated Internet database has been constructed that allows access to the expression data presented here. Further study of these genes and processes will lead to better understanding of pathways involved in the pathophysiology of the cardiac response to pressure overload.

Animals↗

A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae).

Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic methods such as affinity precipitation to advanced high-throughput techniques such as gene expression microarrays. In the future, more disparate methods will be developed, further increasing the need for integrated computational analysis of data generated by these studies. We address this problem with MAGIC (Multisource Association of Genes by Integration of Clusters), a general framework that uses formal Bayesian reasoning to integrate heterogeneous types of high-throughput biological data (such as large-scale two-hybrid screens and multiple microarray analyses) for accurate gene function prediction. The system formally incorporates expert knowledge about relative accuracies of data sources to combine them within a normative framework. MAGIC provides a belief level with its output that allows the user to vary the stringency of predictions. We applied MAGIC to Saccharomyces cerevisiae genetic and physical interactions, microarray, and transcription factor binding sites data and assessed the biological relevance of gene groupings using Gene Ontology annotations produced by the Saccharomyces Genome Database. We found that by creating functional groupings based on heterogeneous data types, MAGIC improved accuracy of the groupings compared with microarray analysis alone. We describe several of the biological gene groupings identified.

Algorithms↗

Molecular decomposition of complex clinical phenotypes using biologically structured analysis of microarray data.

MOTIVATION: Today, the characterization of clinical phenotypes by gene-expression patterns is widely used in clinical research. If the investigated phenotype is complex from the molecular point of view, new challenges arise and these have not been addressed systematically. For instance, the same clinical phenotype can be caused by various molecular disorders, such that one observes different characteristic expression patterns in different patients. RESULTS: In this paper we describe a novel algorithm called Structured Analysis of Microarrays (StAM), which accounts for molecular heterogeneity of complex clinical phenotypes. Our algorithm goes beyond established methodology in several aspects: in addition to the expression data, it exploits functional annotations from the Gene Ontology database to build biologically focussed classifiers. These are used to uncover potential molecular disease subentities and associate them to biological processes without compromising overall prediction accuracy. AVAILABILITY: Bioconductor compliant R package SUPPLEMENTARY INFORMATION: Complete analyses are available at http://compdiag.molgen.mpg.de/supplements/lottaz05.

Biomarkers, Tumor↗

Orthology between the genomes of Plasmodium falciparum and rodent malaria parasites: possible practical applications.

The work of the consortium that has been formed to complete the entire sequence of the genome of a selected clone of the human malaria parasite, Plasmodium falciparum, is almost finished. Already huge tracts of the genome are available as fully assembled chromosomes or large contigs and the work of initial annotation is in an advanced state. Post-genomic research is in one sense the process of furthering the process of annotation, creating biological atlases and preliminary attempts to make global descriptions of gene transcription and proteome analysis are underway. Comparison between significant amounts of genome data from both closely, and more distantly related organisms, can facilitate the identification of genes themselves, coordinately regulated gene expression groups, gene function and genome organization. Models of malaria can fulfil these functions and in addition provide an experimental system wherein predictions can be tested and basic experimental investigations performed within numerous aspects of disease, pathology, parasite-host and parasite-vector interactions. Comparative genomics in Plasmodium has already been shown to have informative roles in the completion of annotation and the elucidation of gene function. These roles will be illustrated by example and used as the basis for a discussion of the utility of genome information and malaria models in realizing the desired product of Plasmodium genomics, the development of malaria therapies.

Animals↗

POCUS: mining genomic sequence annotation to predict disease genes.

Here we present POCUS (prioritization of candidate genes using statistics), a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease. We show that POCUS can provide high (up to 81-fold) enrichment of real disease genes in the candidate-gene shortlists it produces compared with the original large sets of positional candidates. In contrast to existing methods, POCUS can also suggest counterintuitive candidates.

Autistic Disorder↗

Assessing protein co-evolution in the context of the tree of life assists in the prediction of the interactome.

The identification of the whole set of protein interactions taking place in an organism is one of the main tasks in genomics, proteomics and systems biology. One of the computational techniques used by many investigators for studying and predicting protein interactions is the comparison of evolutionary histories (phylogenetic trees), under the hypothesis that interacting proteins would be subject to a similar evolutionary pressure resulting in a similar topology of the corresponding trees. Here, we present a new approach to predict protein interactions from phylogenetic trees, which incorporates information on the overall evolutionary histories of the species (i.e. the canonical "tree of life") in order to correct by the expected background similarity due to the underlying speciation events. We test the new approach in the largest set of annotated interacting proteins for Escherichia coli. This assessment of co-evolution in the context of the tree of life leads to a highly significant improvement (P(N) by sign test approximately 10E-6) in predicting interaction partners with respect to the previous technique, which does not incorporate information on the overall speciation tree. For half of the proteins we found a real interactor among the 6.4% top scores, compared with the 16.5% by the previous method. We applied the new method to the whole E.coli proteome and propose functions for some hypothetical proteins based on their predicted interactors. The new approach allows us also to detect non-canonical evolutionary events, in particular horizontal gene transfers. We also show that taking into account these non-canonical evolutionary events when assessing the similarity between evolutionary trees improves the performance of the method predicting interactions.

Algorithms↗