Genome Information System Research Articles

Implementation of Privacy and Security for a Genomic Information System Based on Standards.

Genomic information is a very sensitive type of digital information as it not only applies to a person, but also to close relatives. Therefore, privacy provision is key to protecting genomic information from unauthorized access. It is worth noting that most of the current genomic information formats do not provide specific mechanisms by which to secure the stored information. In order to solve, among other things, the privacy provision issue, we proposed the GIPAMS (Genomic Information Protection And Management System) modular architecture, which is based on the use of standards such as ISO/IEC 23092 and a few GA4GH (Global Alliance for Genomics and Health) initiatives. Some of the GIPAMS modules have already been implemented, mainly based on ISO/IEC 23092 features, and we are conducting work on the complete version of the architecture, and other standards are also considered. One of the objectives of GIPAMS is to enable the management of different formats of genomic information in a unique and interoperable way, providing privacy and security for formats that do not currently support them.

Implementation of Privacy and Security for a Genomic Information System.

Genomic information is key for the implementation of real personalized medicine. Nevertheless, access to this kind of information must be controlled because of its high privacy and security requirements. Several genomic information formats exist, although we have started from MPEG-G as it includes metadata and protection mechanisms since its inception and provides a hierarchical structure to organize the information contained. The proposed GIPAMS modular architecture provides a secure and controlled access to genomic information, which may help on improving personalized medicine as described in this paper.

RepetDB: a unified resource for transposable element references

BackgroundThanks to their ability to move around and replicate within genomes, transposable elements (TEs) are perhaps the most important contributors to genome plasticity and evolution. Their detection and annotation are considered essential in any genome sequencing project. The number of fully sequenced genomes is rapidly increasing with improvements in high-throughput sequencing technologies. A fully automated de novo annotation process for TEs is therefore required to cope with the deluge of sequence data.However, all automated procedures are error-prone, and an automated procedure for TE identification and classification would be no exception. It is therefore crucial to provide not only the TE reference sequences, but also evidence justifying their classification, at the scale of the whole genome. A few TE databases already exist, but none provides evidence to justify TE classification. Moreover, biological information about the sequences remains globally poor.ResultsWe present here the RepetDB database developed in the framework of GnpIS, a genetic and genomic information system. RepetDB is designed to store and retrieve detected, classified and annotated TEs in a standardized manner. RepetDB is an implementation with extensions of InterMine, an open-source data warehouse framework used here to store, search, browse, analyze and compare all the data recorded for each TE reference sequence. InterMine can display diverse information for each sequence and allows simple to very complex queries. Finally, TE data are displayed via a worldwide data discovery portal. RepetDB is accessible at urgi.versailles.inra.fr/repetdb.ConclusionsRepetDB is designed to be a TE knowledge base populated with full de novo TE annotations of complete (or near-complete) genome sequences. Indeed, the description and classification of TEs facilitates the exploration of specific TE families, superfamilies or orders across a large range of species. It also makes possible cross-species searches and comparisons of TE family content between genomes.

An integrated clinical and genomic information system for cancer precision medicine

BackgroundIncreasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient’s genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly.ResultsHere, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data.ConclusionsOur CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.

The Global Economy towards 2050: A Paradigm Shift

The contextualization of this paper is to review the changing world order on global resources and sociocultural shifts that would augur a global economy which would grow twice its size by 2050. It is now estimated that population data would be stripped. India’s economy is rivalling that of China and the US, while Fusion power is nearing commercial availability, “Energy Islands” shall remain widespread along with Deep ocean mining. The transformation in technology means virtual telepathy is dominating personal communications, while Biorepository and genomic information systems are transforming healthcare. So, would Claytronics revolutionize consumer products along with breakthroughs in carbon nanotube production? With a global population expected to reach 9 billion, Orbital Solar Power is commercially feasible. Robots shall become a common feature of homes and workplace. With the emergence of AI, personnel costs have shifted from operations, maintenance and training, to design and development. Machines can perform repairs in-flight (including the use of self-healing nanotechnology composites) while routine ground maintenance requires little or no human labor, being done mostly by robots. New tactics and information can simply be programmed into the aircraft, or they can learn from others in the swarm.

How to deal with Haplotype data: An Extension to the Conceptual Schema of the Human Genome

The goal of this work is to describe the advantages of the application of Conceptual Modeling (CM) in complex domains, such as genomics. Nowadays, the study and comprehension of the human genome is a major challenge due to its high level of complexity. The constant evolution in the genomic domain contributes to the generation of ever larger amounts of new data, which means that if we do not manage it correctly data quality could be compromised (i.e., problems related with heterogeneity and inconsistent data). In this paper, we propose the use of a Conceptual Schema of the Human Genome (CSHG), designed to understand and improve our ontological commitment to the domain and also extend (enrich) this schema with the integration of a novel concept: Haplotypes. Our focus is on improving the understanding of the relationship between genotype and phenotype, since new findings show that this question is more complex than was originally thought. Here we present the first steps in our data management approach with haplotypes (variations, frequencies and populations) and discuss the database evolution to support this data. Each new version in our conceptual schema (CS) introduces changes to the underlying database structure that has essential and practical implications for better understanding and managing the relevant information. A solution based on conceptual models gives a clear definition of the domain with direct implications in the medical field (Precision Medicine), in which Genomic Information Systems (GeIS) play a very important role.

Temporal and spatial rearrangements of a repetitive element array on C57BL/6J mouse genome

Repetitive elements (REs) make up the vast majority of the mammalian genomes. We identified species-specific genomic libraries of RE arrays. The non-random configurations of RE arrays suggest their functions. We tested whether RE arrays undergo age- and tissue/cell-specific rearrangements. An RE array of C57BL/6J mice, containing tandem repeats of a mosaic of transposable REs, was selected to examine rearrangements in different ages and tissues. There were marked changes in the array configuration in the genomes of the skin and brain in all mice of six weeks and older, whereas the heart and liver had alterations at 29weeks. The temporal variations were confirmed by identifying putative rearrangement junctions. Temporal and spatial rearrangements of certain RE arrays may contribute to the acquired characteristics of the genome information system.

The coffee genome hub: a resource for coffee genomes.

The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager.

The Roche Cancer Genome Database (RCGDB)

Sequence variations are being studied for a better understanding of the mechanism and development of cancer as a mutation-driven disease. The systematic sequencing of genes in tumors and technological advances in high-throughput techniques combined with efficient data acquisition methods have resulted in an explosion of available cancer genome-related data. Despite the technological progress and increase of data, improvements in the application area, for example, drug target discovery, have failed to keep pace with increased research and development spending. One reason for this discrepancy is the ever increasing number of databases and the absence of a unified access to the mutation data. Currently, researchers typically have to browse several, often highly specialized databases to obtain the required information. A more complete understanding of relations and dependencies between mutations and cancer, however, requires the availability of an efficient integrative cancer genome information system. To facilitate this, we developed the Roche Cancer Genome Database (RCGDB), a freely available biological information system integrating different kinds of mutation data. The database is the first comprehensive integration of disparate cancer genome data like single nucleotide variants, single nucleotide polymorphisms, and chromosomal aberrations (CGH and FISH). RCGDB is freely accessible via a Google-like Web interface at http://rcgdb.bioinf.uni-sb.de/MutomeWeb/.

Ensembl 2009

The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases, and other information for chordate, selected model organism and disease vector genomes. As of release 51 (November 2008), Ensembl fully supports 45 species, and three additional species have preliminary support. New species in the past year include orangutan and six additional low coverage mammalian genomes. Major additions and improvements to Ensembl since our previous report include a major redesign of our website; generation of multiple genome alignments and ancestral sequences using the new Enredo-Pecan-Ortheus pipeline and development of our software infrastructure, particularly to support the Ensembl Genomes project (http://www.ensemblgenomes.org/).

Ensembl 2008.

The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases and other information for chordate and selected model organism and disease vector genomes. As of release 47 (October 2007), Ensembl fully supports 35 species, with preliminary support for six additional species. New species in the past year include platypus and horse. Major additions and improvements to Ensembl since our previous report include extensive support for functional genomics data in the form of a specialized functional genomics database, genome-wide maps of protein–DNA interactions and the Ensembl regulatory build; support for customization of the Ensembl web interface through the addition of user accounts and user groups; and increased support for genome resequencing. We have also introduced new comparative genomics-based data mining options and report on the continued development of our software infrastructure.

P-Adic Modelling of the Genome and the Genetic Code

The present paper is devoted to foundations of p-adic modelling in genomics. Considering nucleotides, codons, DNA and RNA sequences, amino acids, and proteins as information systems, we have formulated the corresponding p-adic formalisms for their investigations. Each of these systems has its characteristic prime number used for construction of the related information space. Relevance of this approach is illustrated by some examples. In particular, it is shown that degeneration of the genetic code is a p-adic phenomenon. We have also put forward a hypothesis on evolution of the genetic code assuming that primitive code was based on single nucleotides and chronologically first four amino acids. This formalism of p-adic genomic information systems can be implemented in computer programs and applied to various concrete cases.

PigGIS: Pig Genomic Informatics System

Pig Genomic Information System (PigGIS) is a web-based depository of pig (Sus scrofa) genomic learning mainly engineered for biomedical research to locate pig genes from their human homologs and position single nucleotide polymorphisms (SNPs) in different pig populations. It utilizes a variety of sequence data, including whole genome shotgun (WGS) reads and expressed sequence tags (ESTs), and achieves a successful mapping solution to the low-coverage genome problem. With the data presently available, we have identified a total of 15 700 pig consensus sequences covering 18.5 Mb of the homologous human exons. We have also recovered 18 700 SNPs and 20 800 unique 60mer oligonucleotide probes for future pig genome analyses. PigGIS can be freely accessed via the web at and .

EuGenes: a eukaryote genome information system.

euGenes is a genome information system and database that provides a common summary of eukaryote genes and genomes, at http://iubio.bio.indiana.edu/eugenes/. Seven popular genomes are included: human, mouse, fruitfly, Caenorhabditis elegans worm, Saccharomyces yeast, Arabidopsis mustard weed and zebrafish, with more planned. This information, automatically extracted and updated from several source databases, offers features not readily available through other genome databases to bioscientists looking for gene relationships across organisms. The database describes 150 000 known, predicted and orphan genes, using consistent gene names along with their homologies and associations with a standard vocabulary of molecular functions, cell locations and biological processes. Usable whole-genome maps including features, chromosome locations and molecular data integration are available, as are options to retrieve sequences from these genomes. Search and retrieval methods for these data are easy to use and efficient, allowing one to ask combined questions of sequence features, protein functions and other gene attributes, and fetch results in reports, computable tabular outputs or bulk database forms. These summarized data are useful for integration in other projects, such as gene expression databases. euGenes provides an extensible, flexible genome information system for many organisms.

DNA Data Bank of Japan at work on genome sequence data.

We at the DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) have recently begun receiving, processing and releasing EST and genome sequence data submitted by various Japanese genome projects. The data include those for human, Arabidopsis thaliana, rice, nematode, Synechocystis sp. and Escherichia coli. Since the quantity of data is very large, we organized teams to conduct preliminary discussions with project teams about data submission and handling for release to the public. We also developed a mass submission tool to cope with a large quantity of data. In addition, to provide genome data on WWW, we developed a genome information system using Java. This system (http://mol.genes.nig.ac.jp/ecoli/) can in theory be used for any genome sequence data. These activities will facilitate processing of large quantities of EST and genome data.