G-InforBIO: integrated system for microbial genomics

Background  

Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs.     

The Genome Sequence DataBase: towards an integrated functional genomics resource.

During 1998 the primary focus of the Genome Sequence DataBase (GSDB; http://www.ncgr.org/gsdb ) located at the National Center for Genome Resources (NCGR) has been to improve data quality, improve data collections, and provide new methods and tools to access and analyze data. Data quality has been improved by extensive curation of certain data fields necessary for maintaining data collections and for using certain tools. Data quality has also been increased by improvements to the suite of programs that import data from the International Nucleotide Sequence Database Collaboration (IC). The Sequence Tag Alignment and Consensus Knowledgebase (STACK), a database of human expressed gene sequences developed by the South African National Bioinformatics Institute (SANBI), became available within the last year, allowing public access to this valuable resource of expressed sequences. Data access was improved by the addition of the Sequence Viewer, a platform-independent graphical viewer for GSDB sequence data. This tool has also been integrated with other searching and data retrieval tools. A BLAST homology search service was also made available, allowing researchers to search all of the data, including the unique data, that are available from GSDB. These improvements are designed to make GSDB more accessible to users, extend the rich searching capability already present in GSDB, and to facilitate the transition to an integrated system containing many different types of biological data.     

Identification of biomarkers for bull fertility using functional genomics

Prediction of bull fertility is critical for the sustainability of both dairy and beef cattle production. Even though bulls produce ample amounts of sperm with normal parameters, some bulls may still suffer from subpar fertility. This causes major economic losses in the cattle industry because using artificial insemination, semen from one single bull can be used to inseminate hundreds of thousands of cows. Although there are several traditional methods to estimate bull fertility, such methods are not sufficient to explain and accurately predict the subfertility of individual bulls. Since fertility is a complex trait influenced by a number of factors including genetics, epigenetics, and environment, there is an urgent need for a comprehensive methodological approach to clarify uncertainty in male subfertility. The present review focuses on molecular and functional signatures of bull sperm associated with fertility. Potential roles of functional genomics (proteome, small noncoding RNAs, lipidome, metabolome) on determining male fertility and its potential as a fertility biomarker are discussed. This review provides a better understanding of the molecular signatures of viable and fertile sperm cells and their potential to be used as fertility biomarkers. This information will help uncover the underlying reasons for idiopathic subfertility.     

Rice TOGO Browser: A platform to retrieve integrated information on rice functional and applied genomics

The Rice TOGO Browser is an online public resource designed to facilitate integration and visualization of mapping data of bacterial artificial chromosome (BAC)/P1-derived artificial chromosome (PAC) clones, genes, restriction fragment length polymorphism (RFLP)/simple sequence repeat (SSR) markers and phenotype data represented as quantitative trait loci (QTLs) onto the genome sequence, and to provide a platform for more efficient utilization of genome information from the point of view of applied genomics as well as functional genomics. Three search options, namely keyword search, region search and trait search, generate various types of data in a user-friendly interface with three distinct viewers, a chromosome viewer, an integrated map viewer and a sequence viewer, thereby providing the opportunity to view the position of genes and/or QTLs at the chromosomal level and to retrieve any sequence information in a user-defined genome region. Furthermore, the gene list, marker list and genome sequence in a specified region delineated by RFLP/SSR markers and any sequences designed as primers can be viewed and downloaded to support forward genetics approaches. An additional feature of this database is the graphical viewer for BLAST search to reveal information not only for regions with significant sequence similarity but also for regions adjacent to those with similarity but with no hits between sequences. An easy to use and intuitive user interface can help a wide range of users in retrieving integrated mapping information including agronomically important traits on the rice genome sequence. The database can be accessed at http://agri-trait.dna.affrc.go.jp/.     

An integrated database of the ascidian, Ciona intestinalis: towards functional genomics

An integrated genome database is essential for future studies of functional genomics. In this study, we update cDNA and genomic resources of the ascidian, Ciona intestinalis, and provide an integrated database of the genomic and cDNA data by extending a database published previously. The updated resources include over 190,000 ESTs (672,396 in total together with the previous ESTs) and over 1,000 full-insert sequences (6,773 in total). In addition, results of mapping information of the determined scaffolds onto chromosomes, ESTs from a full-length enriched cDNA library for indication of precise 5'-ends of genes, and comparisons of SNPs and indels among different individuals are integrated into this database, all of these results being reported recently. These advances continue to increase the utility of Ciona intestinalis as a model organism whilst the integrated database will be useful for researchers in comparative and evolutionary genomics.     

Identification of genes required for neural-specific glycosylation using functional genomics

Glycosylation plays crucial regulatory roles in various biological processes such as development, immunity, and neural functions. For example, α1,3-fucosylation, the addition of a fucose moiety abundant in Drosophila neural cells, is essential for neural development, function, and behavior. However, it remains largely unknown how neural-specific α1,3-fucosylation is regulated. In the present study, we searched for genes involved in the glycosylation of a neural-specific protein using a Drosophila RNAi library. We obtained 109 genes affecting glycosylation that clustered into nine functional groups. Among them, members of the RNA regulation group were enriched by a secondary screen that identified genes specifically regulating α1,3-fucosylation. Further analyses revealed that an RNA-binding protein, second mitotic wave missing (Swm), upregulates expression of the neural-specific glycosyltransferase FucTA and facilitates its mRNA export from the nucleus. This first large-scale genetic screen for glycosylation-related genes has revealed novel regulation of fucTA mRNA in neural cells.     

From population genetics to population genomics of forest trees: integrated population genomics approach

Early works by Altukhov and his associates on pine and spruce laid the foundation for Russian population genetic studies on tree species with the use of molecular genetic markers. In recent years, these species have become especially popular as nontraditional eukaryotic models for population and evolutionary genomic research. Tree species with large, cross-pollinating native populations, high genetic and phenotypic variation, growing in diverse environments and affected by environmental changes during hundreds of years of their individual development, are an ideal model for studying the molecular genetic basis of adaptation. The great advance in this field is due to the rapid development of population genomics in the last few years. In the broad sense, population genomics is a novel, fast-developing discipline, combining traditional population genetic approaches with the genomic level of analysis. Thousands of genes with known function and sometimes known genomic localization can be simultaneously studied in many individuals. This opens new prospects for obtaining statistical estimates for a great number of genes and segregating elements. Mating system, gene exchange, reproductive population size, population disequilibrium, interaction among populations, and many other traditional problems of population genetics can be now studied using data on variation in many genes. Moreover, population genomic analysis allows one to distinguish factors that affect individual genes, alleles, or nucleotides (such as, for example, natural selection) from factors affecting the entire genome (e.g., demography). This paper presents a brief review of traditional methods of studying genetic variation in forest tree species and introduces a new, integrated population genomics approach. The main stages of the latter are : (1) selection of genes, which are tentatively involved in variation of adaptive traits, by means of a detailed examination of the regulation and the expression of individual genes and genotypes, with subsequent determination of their complete allelic composition by direct nucleotide sequencing; (2) examination of the phenotypic effects of individual alleles by, e.g., association mapping; and (3) determining the frequencies of the selected alleles in natural population for identification of the adaptive variation pattern in the heterogeneous environment. Through decoding the phenotypic effects of individual alleles and identification of adaptive variation patterns at the population level, population genomics in the future will serve as a very helpful, efficient, and economical tool, essential for developing a correct strategy for conserving and increasing forests and other commercially valuable plant and animal species.     

MOsDB: an integrated information resource for rice genomics

The MIPS Rice (Oryza sativa) database (MOsDB; http://mips.gsf.de/proj/rice) provides a comprehensive data collection dedicated to the genome information of rice. Rice (O. sativa L.) is one of the most important food crops for over half the world's population and serves as a major model system in cereal genome research. MOsDB integrates data from two publicly available rice genomic sequences, O. sativa L. ssp. indica and O. sativa L. ssp. japonica. Besides regularly updated rice genome sequence information, MOsDB provides an integrated resource for associated analysis data, e.g. internal and external annotation information as well as a complex characterization of all annotated rice genes. The MOsDB web interface supports various search options and allows browsing the database content. MOsDB is continuously expanding to include an increasing range of data type and the growing amount of information on the rice genome.     

Genome-wide mutant collections: toolboxes for functional genomics

The sequencing of entire genomes has led to the identification of many genes. A future challenge will be to determine the function of all of the genes of an organism. One of the best ways to ascertain function is to disrupt genes and determine the phenotype of the resulting organism. Novel large-scale approaches for generating gene disruptions and analyzing the resulting phenotype are underway in the budding yeast Saccharomyces cerevisiae and other organisms including flies, Mycoplasma, worms, plants and mice. These approaches and mutant collections will be extremely valuable to the scientific community and will dramatically alter the manner in which science is performed in the future.     

Comparative and functional genomics of Rhodococcus opacus PD630 for biofuels development

The Actinomycetales bacteria Rhodococcus opacus PD630 and Rhodococcus jostii RHA1 bioconvert a diverse range of organic substrates through lipid biosynthesis into large quantities of energy-rich triacylglycerols (TAGs). To describe the genetic basis of the Rhodococcus oleaginous metabolism, we sequenced and performed comparative analysis of the 9.27 Mb R. opacus PD630 genome. Metabolic-reconstruction assigned 2017 enzymatic reactions to the 8632 R. opacus PD630 genes we identified. Of these, 261 genes were implicated in the R. opacus PD630 TAGs cycle by metabolic reconstruction and gene family analysis. Rhodococcus synthesizes uncommon straight-chain odd-carbon fatty acids in high abundance and stores them as TAGs. We have identified these to be pentadecanoic, heptadecanoic, and cis-heptadecenoic acids. To identify bioconversion pathways, we screened R. opacus PD630, R. jostii RHA1, Ralstonia eutropha H16, and C. glutamicum 13032 for growth on 190 compounds. The results of the catabolic screen, phylogenetic analysis of the TAGs cycle enzymes, and metabolic product characterizations were integrated into a working model of prokaryotic oleaginy.     

An integrated functional genomics screening program reveals a role for BMP-9 in glucose homeostasis

A coordinated functional genomics program was implemented to identify secreted polypeptides with therapeutic applications in the treatment of diabetes. Secreted factors were predicted from a diverse expressed-sequence tags (EST) database, representing >1,000 cDNA libraries, using a combination of bioinformatic algorithms. Subsequently, approximately 8,000 human proteins were screened in high-throughput cell-based assays designed to monitor key physiological transitions known to be centrally involved in the physiology of type 2 diabetes. Bone morphogenetic protein-9 (BMP-9) gave a positive response in two independent assays: reducing phosphoenolpyruvate carboxykinase (PEPCK) expression in hepatocytes and activating Akt kinase in differentiated myotubes. Purified recombinant BMP-9 potently inhibited hepatic glucose production and activated expression of key enzymes of lipid metabolism. In freely fed diabetic mice, a single subcutaneous injection of BMP-9 reduced glycemia to near-normal levels, with maximal reduction observed 30 hours after treatment. BMP-9 represents the first hepatic factor shown to regulate blood glucose concentration. Using a combination of bioinformatic and high-throughput functional analyses, we have identified a factor that may be exploited for the treatment of diabetes.     

Maize biology: From functional genomics to breeding application

<正>Maize(Zea mays L.)is one of the most important crops globally for food,feed,and fuel.Maize grain production has increased more than eight-fold in the past century to a current annual global production of one billion tons(http://faostat.fao.org/).By 2050,it will require 70%more food than todayfs consummation since the population size will increase to9 billions.It is estimated that maize will contribute more than half of the increased demand for cereals in the future.Thus,there is a tremendous innovation stream for maize breeders to utilize in their attempts to substantially increase maize productivity in an environmentally sensitive way(FAO 2009).     

Pseudomonas for biocontrol of phytopathogens: from functional genomics to commercial exploitation

Pseudomonas spp. that can colonise the roots of crop plants and produce antifungal metabolites represent a real alternative to the application of chemical fungicides. Presently, much research is aimed at understanding, at the molecular level, the mechanisms that enable Pseudomonas strains to act as efficient biological control agents. This approach is facilitating the development of novel strains with modified traits for enhanced biocontrol efficacy. However, without solving some inherent problems associated with the effective delivery of microbial inoculants to seeds and without knowledge on the biosafety aspects of novel biocontrol agents, the commercial potential of Pseudomonas spp. for plant disease control will not be realised.     

FlyMine: an integrated database for Drosophila and Anopheles genomics

FlyMine is a data warehouse that addresses one of the important challenges of modern biology: how to integrate and make use of the diversity and volume of current biological data. Its main focus is genomic and proteomics data for Drosophila and other insects. It provides web access to integrated data at a number of different levels, from simple browsing to construction of complex queries, which can be executed on either single items or lists.