Planning the human variome project: the Spain report

Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data

The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic methods in recent years. In this paper, machine learning methods are used to analyze metagenomic sequencing data of acne, i.e., all kinds of lipids in the face skin. Firstly, lipids data of the diseased skin (DS) samples and the healthy skin (HS) samples of acne patients and the normal control (NC) samples of healthy person are, respectively, analyzed by using principal component analysis (PCA) and kernel principal component analysis (KPCA). Then, the lipids which have main influence on each kind of sample are obtained. In addition, a multiset canonical correlation analysis (MCCA) is utilized to get lipids which can differentiate the face skins of the above three samples. The experimental results show the machine learning methods can effectively analyze metagenomic sequencing data of acne. According to the results, lipids which only influence one of the three samples or the lipids which simultaneously have different degree of influence on these three samples can be used as indicators to judge skin statuses.

Brazil's Craniofacial Project: Different approaches on orofacial clefts and 22q11.2 deletion syndrome

This article reports the present situation of Brazilian health care in genetics for Orofacial Cleft (OFC) and 22q11.2 Deletions Syndrome (22q11.2 DS) based on research conducted by Brazil's Craniofacial Project (BCFP). Established in 2003, BCFP is a voluntary and cooperative network aiming to investigate the health care of people with these diseases and other craniofacial anomalies. The initiatives and research results are presented in four sections: (a) a comprehensive report of the Brazilian public health system in craniofacial genetics; (b) multicentric studies developed on OFC and 22q11.2 DS; (c) education strategies focused on addressing these conditions for both population and health-care professionals; and (d) the nosology through the Brazilian Database on Craniofacial Anomalies (BDCA). Since 2006, BDCA uses a standardized method with detailed clinical data collection, which allows for conducting studies on nosology, genotype-phenotype correlations, and natural history; data can also contribute to public policies. Currently, the BDCA stores data on 1,724 individuals, including 1,351 (78.36%) who were primarily admitted due to OFC and 373 (21.63%) with clinical suspicion of 22q11.2 DS. Chromosomal abnormalities/genomic imbalances were represented by 92/213 (43.19%) individuals with syndromic OFC, including 43 with 22q11.2 DS, which indicates the need for chromosomal microarray analysis in this group. The nosologic diversity reinforces that monitoring clinical is the best strategy for etiological investigation. BCFP's methodology has introduced the possibility of increasing scientific knowledge and genetic diagnosis of OFC and 22q11.2 DS to in turn improve health care and policies for this group of diseases.

Genomic Medicine Without Borders: Which Strategies Should Developing Countries Employ to Invest in Precision Medicine? A New "Fast-Second Winner" Strategy

Genomic medicine has greatly matured in terms of its technical capabilities, but the diffusion of genomic innovations worldwide faces significant barriers beyond mere access to technology. New global development strategies are sorely needed for biotechnologies such as genomics and their applications toward precision medicine without borders. Moreover, diffusion of genomic medicine globally cannot adhere to a "one-size-fits-all-countries" development strategy, in the same way that drug treatments should be customized. This begs a timely, difficult but crucial question: How should developing countries, and the resource-limited regions of developed countries, invest in genomic medicine? Although a full-scale investment in infrastructure from discovery to the translational implementation of genomic science is ideal, this may not always be feasible in all countries at all times. A simple "transplantation of genomics" from developed to developing countries is unlikely to be feasible. Nor should developing countries be seen as simple recipients and beneficiaries of genomic medicine developed elsewhere because important advances in genomic medicine have materialized in developing countries as well. There are several noteworthy examples of genomic medicine success stories involving resource-limited settings that are contextualized and described in this global genomic medicine innovation analysis. In addition, we outline here a new long-term development strategy for global genomic medicine in a way that recognizes the individual country's pressing public health priorities and disease burdens. We term this approach the "Fast-Second Winner" model of innovation that supports innovation commencing not only "upstream" of discovery science but also "mid-stream," building on emerging highly promising biomarker and diagnostic candidates from the global science discovery pipeline, based on the unique needs of each country. A mid-stream entry into innovation can enhance collective learning from other innovators' mistakes upstream in discovery science and boost the probability of success for translation and implementation when resources are limited. This à la carte model of global innovation and development strategy offers multiple entry points into the global genomics innovation ecosystem for developing countries, whether or not extensive and expensive discovery infrastructures are already in place. Ultimately, broadening our thinking beyond the linear model of innovation will help us to enable the vision and practice of genomics without borders in both developed and resource-limited settings.

Human Variome Project Quality Assessment Criteria for Variation Databases

Numerous databases containing information about DNA, RNA, and protein variations are available. Gene-specific variant databases (locus-specific variation databases, LSDBs) are typically curated and maintained for single genes or groups of genes for a certain disease(s). These databases are widely considered as the most reliable information source for a particular gene/protein/disease, but it should also be made clear they may have widely varying contents, infrastructure, and quality. Quality is very important to evaluate because these databases may affect health decision-making, research, and clinical practice. The Human Variome Project (HVP) established a Working Group for Variant Database Quality Assessment. The basic principle was to develop a simple system that nevertheless provides a good overview of the quality of a database. The HVP quality evaluation criteria that resulted are divided into four main components: data quality, technical quality, accessibility, and timeliness. This report elaborates on the developed quality criteria and how implementation of the quality scheme can be achieved. Examples are provided for the current status of the quality items in two different databases, BTKbase, an LSDB, and ClinVar, a central archive of submissions about variants and their clinical significance.

DNA variant databases improve test accuracy and phenotype prediction in Alport syndrome

X-linked Alport syndrome is a form of progressive renal failure caused by pathogenic variants in the COL4A5 gene. More than 700 variants have been described and a further 400 are estimated to be known to individual laboratories but are unpublished. The major genetic testing laboratories for X-linked Alport syndrome worldwide have established a Web-based database for published and unpublished COL4A5 variants ( https://grenada.lumc.nl/LOVD2/COL4A/home.php?select_db=COL4A5 ). This conforms with the recommendations of the Human Variome Project: it uses the Leiden Open Variation Database (LOVD) format, describes variants according to the human reference sequence with standardized nomenclature, indicates likely pathogenicity and associated clinical features, and credits the submitting laboratory. The database includes non-pathogenic and recurrent variants, and is linked to another COL4A5 mutation database and relevant bioinformatics sites. Access is free. Increasing the number of COL4A5 variants in the public domain helps patients, diagnostic laboratories, clinicians, and researchers. The database improves the accuracy and efficiency of genetic testing because its variants are already categorized for pathogenicity. The description of further COL4A5 variants and clinical associations will improve our ability to predict phenotype and our understanding of collagen IV biochemistry. The database for X-linked Alport syndrome represents a model for databases in other inherited renal diseases.

The InSiGHT database: utilizing 100 years of insights into Lynch syndrome

This article provides a historical overview of the online database ( www.insight-group.org/mutations ) maintained by the International Society for Gastrointestinal Hereditary Tumours. The focus is on the mismatch repair genes which are mutated in Lynch Syndrome. APC, MUTYH and other genes are also an important part of the database, but are not covered here. Over time, as the understanding of the genetics of Lynch Syndrome increased, databases were created to centralise and share the variants which were being detected in ever greater numbers. These databases were eventually merged into the InSiGHT database, a comprehensive repository of gene variant and disease phenotype information, serving as a starting point for important endeavours including variant interpretation, research, diagnostics and enhanced global collection. Pivotal to its success has been the collaborative spirit in which it has been developed, its association with the Human Variome Project, the appointment of a full time curator and its governance stemming from the well established organizational structure of InSiGHT.

Mutations in the EXT1 and EXT2 genes in Spanish patients with multiple osteochondromas

Multiple osteochondromas is an autosomal dominant skeletal disorder characterized by the formation of multiple cartilage-capped tumours. Two causal genes have been identified, EXT1 and EXT2, which account for 65% and 30% of cases, respectively. We have undertaken a mutation analysis of the EXT1 and EXT2 genes in 39 unrelated Spanish patients, most of them with moderate phenotype, and looked for genotype-phenotype correlations. We found the mutant allele in 37 patients, 29 in EXT1 and 8 in EXT2. Five of the EXT1 mutations were deletions identified by MLPA. Two cases of mosaicism were documented. We detected a lower number of exostoses in patients with missense mutation versus other kinds of mutations. In conclusion, we found a mutation in EXT1 or in EXT2 in 95% of the Spanish patients. Eighteen of the mutations were novel.

Implementing the brazilian database on orofacial clefts

Background. High-quality clinical and genetic descriptions are crucial to improve knowledge of orofacial clefts and support specific healthcare polices. The objective of this study is to discuss the potential and perspectives of the Brazilian Database on Orofacial Clefts. Methods. From 2008 to 2010, clinical and familial information on 370 subjects was collected by geneticists in eight different services. Data was centrally processed using an international system for case classification and coding. Results. Cleft lip with cleft palate amounted to 198 (53.5%), cleft palate to 99 (26.8%), and cleft lip to 73 (19.7%) cases. Parental consanguinity was present in 5.7% and familial history of cleft was present in 26.3% subjects. Rate of associated major plus minor defects was 48% and syndromic cases amounted to 25% of the samples. Conclusions. Overall results corroborate the literature. Adopted tools are user friendly and could be incorporated into routine patient care. The BDOC exemplifies a network for clinical and genetic research. The data may be useful to develop and improve personalized treatment, family planning, and healthcare policies. This experience should be of interest for geneticists, laboratory-based researchers, and clinicians entrusted with OC worldwide.

Beyond the genomics blueprint: the 4th Human Variome Project Meeting, UNESCO, Paris, 2012

The 4th Biennial Meeting of the Human Variome Project Consortium was held at the headquarters of the United Nations Educational, Scientific and Cultural Organization (UNESCO) in Paris, 11-15 June 2012. The Human Variome Project, a nongovernmental organization and an official partner of UNESCO, enables the routine collection, curation, interpretation, and sharing of information on all human genetic variation. This meeting was attended by more than 180 delegates from 39 countries and continued the theme of addressing issues of implementation in this unique project. The meeting was structured around the four main themes of the Human Variome Project strategic plan, "Project Roadmap 2012-2016": setting normative function, behaving ethically, sharing knowledge, and building capacity. During the meeting, the members held extensive discussions to formulate an action plan in the key areas of the Human Variome Project. The actions agreed on were promulgated at the Project's two Advisory Council and Scientific Advisory Committee postconference meetings.

Genetic databases in pharmacogenomics: the Frequency of Inherited Disorders Database (FINDbase)

Pharmacogenomics studies how the variations of the individuals' genetic makeup are correlated with a person's response to certain drugs in relation to the therapeutic efficiency, clinical outcome, or even survival, and how they affect drug metabolism, transport, or clearance. Yet, since the incidence of these polymorphisms, being either single-point variations or small insertions/deletions, varies among different populations, a systematic collection and documentation of these variations is warranted, in order to facilitate implementation of pharmacogenomics in different populations. Here we review the existing electronic databases related to pharmacogenomics and pay particular attention in the description of the pharmacogenomics module Frequency of Inherited Disorders database (FINDbase), which documents curated allelic frequency data pertaining to 144 pharmacogenomics markers across 14 genes, representing approximately 87,000 individuals from 150 populations and ethnic groups worldwide. Long-term sustainability of these resources aims to contribute to the design, development, and implementation of pharmacogenomics testing towards the application of personalized approaches in medical treatment.

Databases for neurogenetics: introduction, overview, and challenges

The importance for research and clinical utility of mutation databases, as well as the issues and difficulties entailed in their construction, is discussed within the Human Variome Project. While general principles and standards can apply to most human diseases, some specific questions arise when dealing with the nature of genetic neurological disorders. So far, publically accessible mutation databases exist for only about half of the genes causing neurogenetic disorders; and a considerable work is clearly still needed to optimize their content. The current landscape, main challenges, some potential solutions, and future perspectives on genetic databases for disorders of the nervous system are reviewed in this special issue of Human Mutation on neurogenetics.

Personalizing rare disease research: how genomics is revolutionizing the diagnosis and treatment of rare disease

A decade after the complete sequencing of the human genome, combined with recent advances in throughput and sequencing costs, the genetics of rare diseases has entered a new era. There has now been an explosion in the identification and mapping of rare diseases, with over 10,000 exomes having been sequenced to date. This article surveys the progress and development of technologies to understand rare disease; it provides a historical overview of traditional techniques such as karyotyping and homozygosity mapping, reviews current methods of whole-exome and -genome sequencing, and provides a future perspective on upcoming developments such as targeted drugs and gene therapy. This article will discuss the implications of these methods for rare disease research, along with a discussion of the success stories that provide great hope and optimism for patients and scientists alike.

VarioML framework for comprehensive variation data representation and exchange

BACKGROUND

Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement.

RESULTS

The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components.

CONCLUSIONS

VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of Cerebrotendinous xanthomatosis

Background

Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction.

Methods

Due to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies.

Results

A framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption.

Conclusions

This work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms required to query patient datasets at different levels of abstraction. The open world assumption is especially good for describing only partially known phenotype-genotype relationships, in a way that is easily extensible. In future, this type of approach could offer researchers a valuable resource to infer new data from patient data for statistical analysis in translational research. In conclusion, phenotype description formalization and mapping to clinical data are two key elements for interchanging knowledge between basic and clinical research.

Human Variome Project country nodes: documenting genetic information within a country

The Human Variome Project (http://www.humanvariomeproject.org) is an international effort aiming to systematically collect and share information on all human genetic variation. The two main pillars of this effort are gene/disease-specific databases and a network of Human Variome Project Country Nodes. The latter are nationwide efforts to document the genomic variation reported within a specific population. The development and successful operation of the Human Variome Project Country Nodes are of utmost importance to the success of Human Variome Project's aims and goals because they not only allow the genetic burden of disease to be quantified in different countries, but also provide diagnosticians and researchers access to an up-to-date resource that will assist them in their daily clinical practice and biomedical research, respectively. Here, we report the discussions and recommendations that resulted from the inaugural meeting of the International Confederation of Countries Advisory Council, held on 12th December 2011, during the 2011 Human Variome Project Beijing Meeting. We discuss the steps necessary to maximize the impact of the Country Node effort for developing regional and country-specific clinical genetics resources and summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects.

Recommendations for genetic variation data capture in developing countries to ensure a comprehensive worldwide data collection

Developing countries have significantly contributed to the elucidation of the genetic basis of both common and rare disorders, providing an invaluable resource of cases due to large family sizes, consanguinity, and potential founder effects. Moreover, the recognized depth of genomic variation in indigenous African populations, reflecting the ancient origins of humanity on the African continent, and the effect of selection pressures on the genome, will be valuable in understanding the range of both pathological and nonpathological variations. The involvement of these populations in accurately documenting the extant genetic heterogeneity is more than essential. Developing nations are regarded as key contributors to the Human Variome Project (HVP; http://www.humanvariomeproject.org), a major effort to systematically collect mutations that contribute to or cause human disease and create a cyber infrastructure to tie databases together. However, biomedical research has not been the primary focus in these countries even though such activities are likely to produce economic and health benefits for all. Here, we propose several recommendations and guidelines to facilitate participation of developing countries in genetic variation data documentation, ensuring an accurate and comprehensive worldwide data collection. We also summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects. Hum Mutat 31:1–8, 2010. © 2010 Wiley-Liss, Inc.

Difficulties in finding DNA mutations and associated phenotypic data in web resources using simple, uncomplicated search terms, and a suggested solution

DNA mutation data currently reside in many online databases, which differ markedly in the terminology used to describe or define the mutation and also in completeness of content, potentially making it difficult both to locate a mutation of interest and to find sought-after data (eg phenotypic effect). To highlight the current deficiencies in the accessibility of web-based genetic variation information, we examined the ease with which various resources could be interrogated for five model mutations, using a set of simple search terms relating to the change in amino acid or nucleotide. Fifteen databases were investigated for the time and/or number of mouse clicks; clicks required to find the mutations; availability of phenotype data; the procedure for finding information; and site layout. Google and PubMed were also examined. The three locus-specific databases (LSDBs) generally yielded positive outcomes, but the 12 genome-wide databases gave poorer results, with most proving not to be search-able and only three yielding successful outcomes. Google and PubMed searches found some mutations and provided patchy information on phenotype. The results show that many web-based resources are not currently configured for fast and easy access to comprehensive mutation data, with only the isolated LSDBs providing optimal outcomes. Centralising this information within a common repository, coupled with a simple, all-inclusive interrogation process, would improve searching for all gene variation data.

Call for participation in the neurogenetics consortium within the Human Variome Project

The rate of DNA variation discovery has accelerated the need to collate, store and interpret the data in a standardised coherent way and is becoming a critical step in maximising the impact of discovery on the understanding and treatment of human disease. This particularly applies to the field of neurology as neurological function is impaired in many human disorders. Furthermore, the field of neurogenetics has been proven to show remarkably complex genotype-to-phenotype relationships. To facilitate the collection of DNA sequence variation pertaining to neurogenetic disorders, we have initiated the "Neurogenetics Consortium" under the umbrella of the Human Variome Project. The Consortium's founding group consisted of basic researchers, clinicians, informaticians and database creators. This report outlines the strategic aims established at the preliminary meetings of the Neurogenetics Consortium and calls for the involvement of the wider neurogenetic community in enabling the development of this important resource.

How to catch all those mutations--the report of the third Human Variome Project Meeting, UNESCO Paris, May 2010

The third Human Variome Project (HVP) Meeting "Integration and Implementation" was held under UNESCO Patronage in Paris, France, at the UNESCO Headquarters May 10-14, 2010. The major aims of the HVP are the collection, curation, and distribution of all human genetic variation affecting health. The HVP has drawn together disparate groups, by country, gene of interest, and expertise, who are working for the common good with the shared goal of pushing the boundaries of the human variome and collaborating to avoid unnecessary duplication. The meeting addressed the 12 key areas that form the current framework of HVP activities: Ethics; Nomenclature and Standards; Publication, Credit and Incentives; Data Collection from Clinics; Overall Data Integration and Access-Peripheral Systems/Software; Data Collection from Laboratories; Assessment of Pathogenicity; Country Specific Collection; Translation to Healthcare and Personalized Medicine; Data Transfer, Databasing, and Curation; Overall Data Integration and Access-Central Systems; and Funding Mechanisms and Sustainability. In addition, three societies that support the goals and the mission of HVP also held their own Workshops with the view to advance disease-specific variation data collection and utilization: the International Society for Gastrointestinal Hereditary Tumours, the Micronutrient Genomics Project, and the Neurogenetics Consortium.

Locus-specific database domain and data content analysis: evolution and content maturation toward clinical use

Genetic variation databases have become indispensable in many areas of health care. In addition, more and more experts are depositing published and unpublished disease-causing variants of particular genes into locus-specific databases (LSDBs). Some of these databases contain such extensive information that they have become known as knowledge bases. Here, we analyzed 1,188 LSDBs and their content for the presence or absence of 44 content criteria related to database features (general presentation, locus-specific information, database structure) and data content (data collection, summary table of variants, database querying). Our analyses revealed that several elements have helped to advance the field and reduce data heterogeneity, such as the development of specialized database management systems and the creation of data querying tools. We also identified a number of deficiencies, namely, the lack of detailed disease and phenotypic descriptions for each genetic variant and links to relevant patient organizations, which, if addressed, would allow LSDBs to better serve the clinical genetics community. We propose a structure, based on LSDBs and closely related repositories (namely, clinical genetics databases), which would contribute to a federated genetic variation browser and also allow the maintenance of variation data.

Practical guidelines addressing ethical issues pertaining to the curation of human locus-specific variation databases (LSDBs)

More than 1,000 Web-based locus-specific variation databases (LSDBs) are listed on the Website of the Human Genetic Variation Society (HGVS). These individual efforts, which often relate phenotype to genotype, are a valuable source of information for clinicians, patients, and their families, as well as for basic research. The initiators of the Human Variome Project recently recognized that having access to some of the immense resources of unpublished information already present in diagnostic laboratories would provide critical data to help manage genetic disorders. However, there are significant ethical issues involved in sharing these data worldwide. An international working group presents second-generation guidelines addressing ethical issues relating to the curation of human LSDBs that provide information via a Web-based interface. It is intended that these should help current and future curators and may also inform the future decisions of ethics committees and legislators. These guidelines have been reviewed by the Ethics Committee of the Human Genome Organization (HUGO). Hum Mutat 31:–6, 2010. © 2010 Wiley-Liss, Inc.

Development of NIPBL locus-specific database using LOVD: from novel mutations to further genotype-phenotype correlations in Cornelia de Lange Syndrome

The establishment of Locus Specific Databases (LSDB) is a crucial aspect for the Human Genetics field and one of the aims of the Human Variation Project. We report the development of a publicly accessible LSDB for the NIPBL gene (http://www.lovd.nl/NIPBL) implicated in Cornelia de Lange Syndrome (CdLS). This rare disorder is characterized by developmental and growth retardation, typical facial features, limb anomalies, and multiple organ involvement. Mutations in the NIPBL gene, the product of which is involved in control of the cohesion complex, account for over half of the patients currently characterized. The NIPBL LSDB adopted the Leiden Open Variation database (LOVD) software platform, which enables the comprehensive Web-based listing and curation of sequence variations and associated phenotypical information. The NIPBL-LOVD database contains 199 unique mutations reported in 246 patients (last accessed April 2010). Information on phenotypic characteristics included in the database enabled further genotype-phenotype correlations, the most evident being the severe form of CdLS associated with premature termination codons in the NIPBL gene. In addition to the NIPBL LSDB, 50 novel mutations are described in detail, resulting from a collaborative multicenter study.

Carbohydrate metabolic pathway genes associated with quantitative trait loci (QTL) for obesity and type 2 diabetes: identification by data mining

Increasing consumption of refined carbohydrates is now being recognized as a primary contributor to the development of nutritionally related chronic diseases such as obesity and type 2 diabetes mellitus (T2DM). A data mining approach was used to evaluate the role of carbohydrate metabolic pathway genes in the development of obesity and T2DM. Data from public databases were used to map the position of the carbohydrate metabolic pathway genes to known quantitative trait loci (QTL) for obesity and T2DM and for examining the pathway genes for the presence of sequence and structural genetic variants such as single nucleotide polymorphisms (SNPs) and copy number variants (CNS), respectively. The results demonstrated that a majority of the genes of the carbohydrate metabolic pathways are associated with QTL for obesity and many for T2DM. In addition, some key genes of the pathways also encode non-synonymous SNPs that exhibit significant differences in population frequencies. This study emphasizes the significance of the metabolic pathways genes in the development of disease phenotypes, its differential occurrence across populations and between individuals, and a strategy for interpreting an individuals' risk for disease.

Connecting the Human Variome Project to nutrigenomics

Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.

FINDbase: a worldwide database for genetic variation allele frequencies updated

Frequency of INherited Disorders database (FIND base; http://www.findbase.org) records frequencies of causative genetic variations worldwide. Database records include the population and ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related external resources and the genetic variation together with its frequency in that population. In addition to the regular data content updates, we report the following significant advances: (i) the systematic collection and thorough documentation of population/ethnic group-specific pharmacogenomic markers allele frequencies for 144 markers in 14 genes of pharmacogenomic interest from different classes of drug-metabolizing enzymes and transporters, representing 150 populations and ethnic groups worldwide; (ii) the development of new data querying and visualization tools in the expanded FINDbase data collection, built around Microsoft's PivotViewer software (http://www.getpivot.com), based on Microsoft Silverlight technology (http://www.silverlight.net) that facilitates querying of large data sets and visualizing the results; and (iii) the establishment of the first database journal, by affiliating FINDbase with Human Genomics and Proteomics, a new open-access scientific journal, which would serve as a prime example of a non-profit model for sustainable database funding.

The Micronutrient Genomics Project: a community-driven knowledge base for micronutrient research

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it is becoming feasible to assess the activity of single and multiple micronutrients in their complete biological context. Existing research collects fragments of information, which are not stored systematically and are thus not optimally disseminated. The Micronutrient Genomics Project (MGP) was established as a community-driven project to facilitate the development of systematic capture, storage, management, analyses, and dissemination of data and knowledge generated by biological studies focused on micronutrient–genome interactions. Specifically, the MGP creates a public portal and open-source bioinformatics toolbox for all “omics” information and evaluation of micronutrient and health studies. The core of the project focuses on access to, and visualization of, genetic/genomic, transcriptomic, proteomic and metabolomic information related to micronutrients. For each micronutrient, an expert group is or will be established combining the various relevant areas (including genetics, nutrition, biochemistry, and epidemiology). Each expert group will (1) collect all available knowledge, (2) collaborate with bioinformatics teams towards constructing the pathways and biological networks, and (3) publish their findings on a regular basis. The project is coordinated in a transparent manner, regular meetings are organized and dissemination is arranged through tools, a toolbox web portal, a communications website and dedicated publications.

The phenylalanine hydroxylase c.30C>G synonymous variation (p.G10G) creates a common exonic splicing silencer

PKU is caused by mutations in PAH. A c.30C>G synonymous variation in exon 1, previously reported as neutral, was observed in two patients. The variation creates a GGG triplet, which is part of several exonic splicing silencer (ESS) motifs. Because the 5'-splice site of PAH exon 1 is intrinsically weak and therefore could be responsive to a new flanking ESS, we hypothesized that c.30C>G could cause aberrant mRNA splicing. We demonstrate that c.30C>G causes aberrant mRNA splicing in two different reporter minigenes, and that this is abolished if a preexisting flanking GGG triplet is disrupted. GGG triplets are part of the consensus motif bound by splicing-inhibitory hnRNPH proteins and we observed a dramatic increase in hnRNPH binding to c.30C>G PAH RNA. We conclude that c.30C>G creates a hnRNPH-binding ESS, which can disrupt mRNA splicing. A disease-causing mutation in HEXB, which has previously been associated with exon skipping in patients also creates a GGG triplet. We show that the mutant HEXB motif causes exon skipping of a reporter minigene and that this is also influenced by a flanking GGG triplet. We suggest that aberrant splicing caused by creation/abolishment of GGG triplets located together with a preexisting flanking GGG triplet, may be an underreported cause of human disease. It is important to recognize that exonic sequence changes may disrupt mRNA splicing. This is particularly important in PAH, since PKU patients harboring such mutations are unlikely to respond to therapy with 6R-tetrahydrobiopterin (BH(4)), despite the fact that the genetic code indicates otherwise.

Human variation databases

More than 100 000 human genetic variations have been described in various genes that are associated with a wide variety of diseases. Such data provides invaluable information for both clinical medicine and basic science. A number of locus-specific databases have been developed to exploit this huge amount of data. However, the scope, format and content of these databases differ strongly and as no standard for variation databases has yet been adopted, the way data is presented varies enormously. This review aims to give an overview of current resources for human variation data in public and commercial resources.

Personalisierte Medizin durch individuelle Genome

Die dynamische Entwicklung in der Sequenziertechnologie hat die technischen Kosten sowie die Zeit, die benötigt wird, ein individuelles Genom zu entschlüsseln, so dramatisch reduziert, dass die komplette Sequenzierung persönlicher Genome für Privatpersonen und Gesundheitssysteme finanzierbar wird. Die breite Verfügbarkeit individueller Genome wird die Medizin weiter in Richtung einer informationsbasierten Wissenschaft treiben und die Bedeutung der informationswissenschaftlichen Techniken erhöhen.

Mutation@A Glance: an integrative web application for analysing mutations from human genetic diseases

Although mutation analysis serves as a key part in making a definitive diagnosis about a genetic disease, it still remains a time-consuming step to interpret their biological implications through integration of various lines of archived information about genes in question. To expedite this evaluation step of disease-causing genetic variations, here we developed Mutation@A Glance (http://rapid.rcai.riken.jp/mutation/), a highly integrated web-based analysis tool for analysing human disease mutations; it implements a user-friendly graphical interface to visualize about 40 000 known disease-associated mutations and genetic polymorphisms from more than 2600 protein-coding human disease-causing genes. Mutation@A Glance locates already known genetic variation data individually on the nucleotide and the amino acid sequences and makes it possible to cross-reference them with tertiary and/or quaternary protein structures and various functional features associated with specific amino acid residues in the proteins. We showed that the disease-associated missense mutations had a stronger tendency to reside in positions relevant to the structure/function of proteins than neutral genetic variations. From a practical viewpoint, Mutation@A Glance could certainly function as a ‘one-stop’ analysis platform for newly determined DNA sequences, which enables us to readily identify and evaluate new genetic variations by integrating multiple lines of information about the disease-causing candidate genes.

A primer on metagenomics

Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics.

Ensembl's 10th year

Ensembl (http://www.ensembl.org) integrates genomic information for a comprehensive set of chordate genomes with a particular focus on resources for human, mouse, rat, zebrafish and other high-value sequenced genomes. We provide complete gene annotations for all supported species in addition to specific resources that target genome variation, function and evolution. Ensembl data is accessible in a variety of formats including via our genome browser, API and BioMart. This year marks the tenth anniversary of Ensembl and in that time the project has grown with advances in genome technology. As of release 56 (September 2009), Ensembl supports 51 species including marmoset, pig, zebra finch, lizard, gorilla and wallaby, which were added in the past year. Major additions and improvements to Ensembl since our previous report include the incorporation of the human GRCh37 assembly, enhanced visualisation and data-mining options for the Ensembl regulatory features and continued development of our software infrastructure.

Interindividual variation in epigenomic phenomena in humans

Our knowledge of regulatory mechanisms of gene expression and other chromosomal processes related to DNA methylation and chromatin state is continuing to grow at a rapid pace. Understanding how these epigenomic phenomena vary between individuals will have an impact on understanding their broader role in determining variation in gene expression and biochemical, physiological, and behavioural phenotypes. In this review we survey recent progress in this area, focusing on data available from humans. We highlight the role of obligatory (sequence-dependent) epigenomic variation as an important mechanism for generating interindividual variation that could impact our understanding of the mechanistic basis of complex trait architecture.

A strategy for analyzing gene-nutrient interactions in type 2 diabetes

Type 2 diabetes mellitus (T2DM), like all chronic diseases, results from interactions between multiple genes and multiple environmental factors. Nevertheless, many research studies focus on either nutrition or genetic factors independently of each other. The challenges of analyzing gene-nutrient interactions in T2DM are the (i) genetic heterogeneity in humans, (ii) complexity of environmental factors, particularly dietary chemicals, and (iii) diverse physiologies that produce the same apparent disease. Many of these variables are not accounted for in the design or study of T2DM or, indeed, most chronic diseases, although exceptions are noteworthy. Establishing experimental paradigms to analyze the complexity of these interactions and physiologies is challenging, but possible. This article provides a strategy to extend nutrigenomic experimental strategies to include early environmental influences that may promote adult-onset disease.