Different evolutionary patterns among intronless genes in maize genome

Intronless genes, as a characteristic feature of prokaryotes, are an important resource for the study of the evolution of gene architecture in eukaryotes. In the study, 14,623 (36.87%) intronless genes in maize were identified and the percentage is greater than that of other monocots and algae. The number of maize intronless genes on each chromosome has a significant linear correlation with the number of total genes on the chromosome and the length of the chromosomes. Intronless genes in maize play important roles in translation and energy metabolism. Evolutionary analysis revealed that 2601 intronless genes conserved among the three domains of life and 2323 intronless genes that had no homology with genes of other species. These two sets of intronless genes were distinct in genetic features, physical locations and function. These results provided a useful source to understand the evolutionary patterns of related genes and genomes and some intronless genes are good candidates for subsequent functional analyses specifically.     

Genome-wide analysis of intronless genes in rice and <Emphasis Type="Italic">Arabidopsis</Emphasis>

Intronless genes, a characteristic feature of prokaryotes, constitute a significant portion of the eukaryotic genomes. Our analysis revealed the presence of 11,109 (19.9%) and 5,846 (21.7%) intronless genes in rice and Arabidopsis genomes, respectively, belonging to different cellular role and gene ontology categories. The distribution and conservation of rice and Arabidopsis intronless genes among different taxonomic groups have been analyzed. A total of 301 and 296 intronless genes from rice and Arabidopsis, respectively, are conserved among organisms representing the three major domains of life, i.e., archaea, bacteria, and eukaryotes. These evolutionarily conserved proteins are predicted to be involved in housekeeping cellular functions. Interestingly, among the 68% of rice and 77% of Arabidopsis intronless genes present only in eukaryotic genomes, approximately 51% and 57% genes have orthologs only in plants, and thus may represent the plant-specific genes. Furthermore, 831 and 144 intronless genes of rice and Arabidopsis, respectively, referred to as ORFans, do not exhibit homology to any of the genes in the database and may perform species-specific functions. These data can serve as a resource for further comparative, evolutionary, and functional analysis of intronless genes in plants and other organisms. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Analysis of gene ontology features in microarray data using the Proteome BioKnowledge Library

Microarray technology has resulted in an explosion of complex, valuable data. Integrating data analysis tools with a comprehensive underlying database would allow efficient identification of common properties among differentially regulated genes. In this study we sought to compare the utility of various databases in microarray analysis. The Proteome BioKnowledge Library (BKL), a manually curated, proteome-wide compilation of the scientific literature, was used to generate a list of Gene Ontology (GO) Biological Process (BP) terms enriched among proteins involved in cardiovascular disease. Analysis of DNA microarray data generated in a study of rat vascular smooth muscle cell responses revealed significant enrichment in a number of GO BPs that were also enriched among cardiovascular disease-related proteins. Using annotation from LocusLink and chip annotation from the Gene Expression Omnibus yielded fewer enriched cardiovascular disease-associated GO BP terms. Data sets of orthologous genes from mouse and human were generated using the BKL Retriever. Analysis of these sets focusing on BKL Disease annotation, revealed a significant association of these genes with cardiovascular disease. These results and the extensive presence of experimental evidence for BKL GO and Disease features, underscore the benefits of using this database for microarray analysis.     

Genew: the Human Gene Nomenclature Database

Genew, the Human Gene Nomenclature Database, is the only resource that provides data for all human genes which have approved symbols. It is managed by the HUGO Gene Nomenclature Committee (HGNC) as a confidential database, containing over 16 000 records, 80% of which are represented on the Web by searchable text files. The data in Genew are highly curated by HGNC editors and gene records can be searched on the Web by symbol or name to directly retrieve information on gene symbol, gene name, cytogenetic location, OMIM number and PubMed ID. Data are integrated with other human gene databases, e.g. GDB, LocusLink and SWISS-PROT, and approved gene symbols are carefully co-ordinated with the Mouse Genome Database (MGD). Approved gene symbols are available for querying and browsing at http://www.gene.ucl.ac.uk/cgi-bin/nomenclature/searchgenes.pl.     

Analysing the yeast complexome—the Complex Portal rising to the challenge

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.     

Systematic Phenomics Analysis Deconvolutes Genes Mutated in Intellectual Disability into Biologically Coherent Modules

Intellectual disability (ID) disorders are genetically and phenotypically extremely heterogeneous. Can this complexity be depicted in a comprehensive way as a means of facilitating the understanding of ID disorders and their underlying biology? We provide a curated database of 746 currently known genes, mutations in which cause ID (ID-associated genes [ID-AGs]), classified according to ID manifestation and associated clinical features. Using this integrated resource, we show that ID-AGs are substantially enriched with co-expression, protein-protein interactions, and specific biological functions. Systematic identification of highly enriched functional themes and phenotypes revealed typical phenotype combinations characterizing process-defined groups of ID disorders, such as chromatin-related disorders and deficiencies in DNA repair. Strikingly, phenotype classification efficiently breaks down ID-AGs into subsets with significantly elevated biological coherence and predictive power. Custom-made functional Drosophila datasets revealed further characteristic phenotypes among ID-AGs and specific clinical classes. Our study and resource provide systematic insights into the molecular and clinical landscape of ID disorders, represent a significant step toward overcoming current limitations in ID research, and prove the utility of systematic human and cross-species phenomics analyses in highly heterogeneous genetic disorders.     

The DrugAge database of aging‐related drugs

Aging is a major worldwide medical challenge. Not surprisingly, identifying drugs and compounds that extend lifespan in model organisms is a growing research area. Here, we present DrugAge ( http://genomics.senescence.info/drugs/ ), a curated database of lifespan‐extending drugs and compounds. At the time of writing, DrugAge contains 1316 entries featuring 418 different compounds from studies across 27 model organisms, including worms, flies, yeast and mice. Data were manually curated from 324 publications. Using drug–gene interaction data, we also performed a functional enrichment analysis of targets of lifespan‐extending drugs. Enriched terms include various functional categories related to glutathione and antioxidant activity, ion transport and metabolic processes. In addition, we found a modest but significant overlap between targets of lifespan‐extending drugs and known aging‐related genes, suggesting that some but not most aging‐related pathways have been targeted pharmacologically in longevity studies. DrugAge is freely available online for the scientific community and will be an important resource for biogerontologists.     

The Princeton Protein Orthology Database (P-POD): a comparative genomics analysis tool for biologists

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools.     

A QTL resource and comparison tool for pigs: PigQTLDB

During the past decade, efforts to map quantitative trait loci (QTL) in pigs have resulted in hundreds of QTL being reported for growth, meat quality, reproduction, disease resistance, and other traits. It is a challenge to locate, interpret, and compare QTL results from different studies. We have developed a pig QTL database (PigQTLdb) that integrates available pig QTL data in the public domain, thus, facilitating the use of this QTL data in future studies. We also developed a pig trait classification system to standardize names of traits and to simplify organization and searching of the trait data. These steps made it possible to compare primary data from diverse sources and methods. We used existing pig map databases and other publicly available data resources (such as PubMed) to avoid redundant developmental work. The PigQTLdb was also designed to include data representing major genes and markers associated with a large effect on economically important traits. To date, over 790 QTL from 73 publications have been curated into the database. Those QTL cover more than 300 different traits. The data have been submitted to the Entrez Gene and the Map Viewer resources at NCBI, where the information about markers was matched to marker records in NCBI’s UniSTS database. Having these data in a public resource like NCBI allows regularly updated automatic matching of markers to public sequence data by e-PCR. The submitted data, and the results of these calculations, are retrievable from NCBI via Entrez Gene, Map Viewer, and UniSTS. Efforts were undertaken to improve the integrated functional genomics resources for pigs.     

An expressed sequence tag database of T-cell-enriched activated chicken splenocytes: sequence analysis of 5251 clones

The cDNA and gene sequences of many mammalian cytokines and their receptors are known. However, corresponding information on avian cytokines is limited due to the lack of cross-species activity at the functional level or strong homology at the molecular level. To improve the efficiency of identifying cytokines and novel chicken genes, a directionally cloned cDNA library from T-cell-enriched activated chicken splenocytes was constructed, and the partial sequence of 5251 clones was obtained. Sequence clustering indicates that 2357 (42%) of the clones are present as a single copy, and 2961 are distinct clones, demonstrating the high level of complexity of this library. Comparisons of the sequence data with known DNA sequences in GenBank indicate that approximately 25% of the clones match known chicken genes, 39% have similarity to known genes in other species, and 11% had no match to any sequence in the database. Several previously uncharacterized chicken cytokines and their receptors were present in our library. This collection provides a useful database for cataloging genes expressed in T cells and a valuable resource for future investigations of gene expression in avian immunology. A chicken EST Web site (http://udgenome. ags.udel. edu/chickest/chick.htm) has been created to provide access to the data, and a set of unique sequences has been deposited with GenBank (Accession Nos. AI979741-AI982511). Our new Web site (http://www. chickest.udel.edu) will be active as of March 3, 2000, and will also provide keyword-searching capabilities for BLASTX and BLASTN hits of all our clones.     

The metallothionein genes of Mytilus galloprovincialis: genomic organization, tissue expression and evolution

Recently, increasing interest has been directed to the study of metallothioneins (MTs), which are small proteins that are able to bind metal ions. The induction of MT synthesis after exposure to metal or other environmental contaminants in a large number of aquatic invertebrates makes these proteins good biomarkers in water monitoring programs. Within bivalves, the species Mytilus galloprovincialis and Mytilus edulis represent model organisms for these types of studies, as well as for molecular studies regarding the expression and characterization of MT encoding genes. In the present paper, we focused on the genomic characterization, evolutionary, and tissue-expression analyses of the MT-10, MT-10 Intronless, and MT-20 genes in M. galloprovincialis. The comparison of the genomic sequences showed the presence of long nucleotide stretches within the introns of the MT genes that are conserved between M. galloprovincialis and M. edulis. These non-coding conserved sequences may contain regulatory motifs. Real-Time RT-PCR experiments revealed that, at the basal conditions, the MT-10 and MT-10 Intronless genes are expressed at levels considerably higher than the MT-20 gene, mainly in the digestive gland and gill tissue. The strong induction of the MT-20 gene expression detected in a field-collected sample is associated with the up-regulation of both the MT-10 and MT-10 Intronless genes. Evolutionary analysis revealed signals of localized positive selection that, together with the tissue-expression data, support a possible functional diversification between the MTs encoded by the MT-10 and MT-10 Intronless genes.     

Evolutionary rate variation in eukaryotic lineage specific human intronless proteins

The present study examines 783 human-mouse orthologous gene pairs for their pattern of sequence evolution, contrasting mammalia, eukaryota, coelomata, and bilateria specific human intronless genes. Such comparisons may be of use in understanding the general evolution of human genome. Evolutionary rate analyses indicate that mammalia specific human intronless genes are evolving faster as compared to other intronless genes specific to eukaryotic lineage, indicating towards their rapid evolution. The observations indicates that the genes conserved in eukaryota, coelomata, and bilateria, that is, proteins that arose earlier in evolution as compared to mammalia specific genes evolve slowly and are subjected to negative selection. The cause underlying rate variations was also explored. Although mutational bias might slightly fasten the nonsynonymous rates in mammalia specific genes, it is unlikely to be major cause of rate difference between the various categories. Furthermore, rate of divergence of mammalia specific intronless genes has been related to functional classification using the protein family annotation. Protein function was found in some cases to have larger impact on the rate of evolution of genes. Also, the codon usage pattern of mammalia specific intronless genes do not seem to differ much from those of other intronless genes conserved solely in eukaryotic lineage.     

The cytochrome P450 gene superfamily in Drosophila melanogaster: annotation, intron-exon organization and phylogeny

The cytochrome P450 gene superfamily is represented by 90 sequences in the Drosophila melanogaster genome. Of these 90 P450 sequences, 83 code for apparently functional genes whereas seven are apparent pseudogenes. More than half of the genes belong to only two families, CYP4 and CYP6. The CYP6 family is insect specific whereas the CYP4 family includes sequences from vertebrates. There are eight genes coding for mitochondrial P450s as deduced from their homology to CYP12A1 from the house fly. The genetic map of the distribution of D. melanogaster P450 genes shows (a) the absence of P450 genes on the chromosome 4 and Y, (b) more than half of the P450 genes are found on chromosome 2, and (c) the largest cluster contains nine genes. Sequence alignments were used to draw phylogenetic trees and to analyze the intron-exon organization of each functional P450 gene. Only five P450 genes are intronless. We found 57 unique intron positions, of which 23 were phase zero, 19 were phase one and 15 were phase two. There was a relatively good correlation between intron conservation and phylogenetic relationship between members of the P450 subfamilies. Although the function of many P450 proteins from vertebrates, fungi, plants and bacteria is known, only a single P450 from D. melanogaster, CYP6A2, has been functionally characterized. Gene organization appears to be a useful tool in the study of the regulation, the physiological role and the function of these P450s.