Developments in FINDbase worldwide database for clinically relevant genomic variation allele frequencies

Documentation of clinically relevant genomic biomarker allele frequencies in the next-generation FINDbase worldwide database

FINDbase (http://www.findbase.org) is a comprehensive data resource recording the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants underlying genetic disorders as well as pharmacogenomic biomarkers that can guide drug treatment. Here, we report significant new developments and technological advancements in the database architecture, leading to a completely revamped database structure, querying interface, accompanied with substantial extensions of data content and curation. In particular, the FINDbase upgrade further improves the user experience by introducing responsive features that support a wide variety of mobile and stationary devices, while enhancing computational runtime due to the use of a modern Javascript framework such as ReactJS. Data collection is significantly enriched, with the data records being divided in a Public and Private version, the latter being accessed on the basis of data contribution, according to the microattribution approach, while the front end was redesigned to support the new functionalities and querying tools. The abovementioned updates further enhance the impact of FINDbase, improve the overall user experience, facilitate further data sharing by microattribution, and strengthen the role of FINDbase as a key resource for personalized medicine applications and personalized public health.

HEROD: a human ethnic and regional specific omics database

Motivation

Genetic and gene expression variations within and between populations and across geographical regions have substantial effects on the biological phenotypes, diseases, and therapeutic response. The development of precision medicines can be facilitated by the OMICS studies of the patients of specific ethnicity and geographic region. However, there is an inadequate facility for broadly and conveniently accessing the ethnic and regional specific OMICS data.

Results

Here, we introduced a new free database, HEROD, a human ethnic and regional specific OMICS database. Its first version contains the gene expression data of 53 070 patients of 169 diseases in seven ethnic populations from 193 cities/regions in 49 nations curated from the Gene Expression Omnibus (GEO), the ArrayExpress Archive of Functional Genomics Data (ArrayExpress), the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Geographic region information of curated patients was mainly manually extracted from referenced publications of each original study. These data can be accessed and downloaded via keyword search, World map search, and menu-bar search of disease name, the international classification of disease code, geographical region, location of sample collection, ethnic population, gender, age, sample source organ, patient type (patient or healthy), sample type (disease or normal tissue) and assay type on the web interface.

Availability and implementation

The HEROD database is freely accessible at http://bidd2.nus.edu.sg/herod/index.php. The database and web interface are implemented in MySQL, PHP and HTML with all major browsers supported.

Contact

phacyz@nus.edu.sg.

The 24th annual Nucleic Acids Research database issue: a look back and upcoming changes

This year's Database Issue of Nucleic Acids Research contains 152 papers that include descriptions of 54 new databases and update papers on 98 databases, of which 16 have not been previously featured in NAR As always, these databases cover a broad range of molecular biology subjects, including genome structure, gene expression and its regulation, proteins, protein domains, and protein-protein interactions. Following the recent trend, an increasing number of new and established databases deal with the issues of human health, from cancer-causing mutations to drugs and drug targets. In accordance with this trend, three recently compiled databases that have been selected by NAR reviewers and editors as 'breakthrough' contributions, denovo-db, the Monarch Initiative, and Open Targets, cover human de novo gene variants, disease-related phenotypes in model organisms, and a bioinformatics platform for therapeutic target identification and validation, respectively. We expect these databases to attract the attention of numerous researchers working in various areas of genetics and genomics. Looking back at the past 12 years, we present here the 'golden set' of databases that have consistently served as authoritative, comprehensive, and convenient data resources widely used by the entire community and offer some lessons on what makes a successful database. The Database Issue is freely available online at the https://academic.oup.com/nar web site. An updated version of the NAR Molecular Biology Database Collection is available at http://www.oxfordjournals.org/nar/database/a/.

Pharmacogenomics education and research at the Department of Pharmacy, University of Patras, Greece

The Pharmacogenomics and Personalized Medicine group belongs to the Laboratory of Molecular Biology and Immunology, Department of Pharmacy and is active since 2009 mainly in the field of pharmacogenomics and personalized medicine. Herein, we describe the research interests, collaborations and accomplishments of the Pharmacogenomics and Personalized Medicine group together with the teaching activities of the group that greatly enhance the pharmacogenomics knowledge of graduate/postgraduate students and healthcare professionals.

Expanded national database collection and data coverage in the FINDbase worldwide database for clinically relevant genomic variation allele frequencies

FINDbase (http://www.findbase.org) is a comprehensive data repository that records the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants leading mostly to monogenic disorders and pharmacogenomics biomarkers. The database also records the incidence of rare genetic diseases in various populations, all in well-distinct data modules. Here, we report extensive data content updates in all data modules, with direct implications to clinical pharmacogenomics. Also, we report significant new developments in FINDbase, namely (i) the release of a new version of the ETHNOS software that catalyzes development curation of national/ethnic genetic databases, (ii) the migration of all FINDbase data content into 90 distinct national/ethnic mutation databases, all built around Microsoft's PivotViewer (http://www.getpivot.com) software (iii) new data visualization tools and (iv) the interrelation of FINDbase with DruGeVar database with direct implications in clinical pharmacogenomics. The abovementioned updates further enhance the impact of FINDbase, as a key resource for Genomic Medicine applications.

A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

ePGA: A Web-Based Information System for Translational Pharmacogenomics

One of the challenges that arise from the advent of personal genomics services is to efficiently couple individual data with state of the art Pharmacogenomics (PGx) knowledge. Existing services are limited to either providing static views of PGx variants or applying a simplistic match between individual genotypes and existing PGx variants. Moreover, there is a considerable amount of haplotype variation associated with drug metabolism that is currently insufficiently addressed. Here, we present a web-based electronic Pharmacogenomics Assistant (ePGA; http://www.epga.gr/) that provides personalized genotype-to-phenotype translation, linked to state of the art clinical guidelines. ePGA's translation service matches individual genotype-profiles with PGx gene haplotypes and infers the corresponding diplotype and phenotype profiles, accompanied with summary statistics. Additional features include i) the ability to customize translation based on subsets of variants of clinical interest, and ii) to update the knowledge base with novel PGx findings. We demonstrate ePGA's functionality on genetic variation data from the 1000 Genomes Project.

A pan-cancer analysis of prognostic genes

Numerous studies have identified prognostic genes in individual cancers, but a thorough pan-cancer analysis has not been performed. In addition, previous studies have mostly used microarray data instead of RNA-SEQ, and have not published comprehensive lists of associations with survival. Using recently available RNA-SEQ and clinical data from The Cancer Genome Atlas for 6,495 patients, we have investigated every annotated and expressed gene’s association with survival across 16 cancer types. The most statistically significant harmful and protective genes were not shared across cancers, but were enriched in distinct gene sets which were shared across certain groups of cancers. These groups of cancers were independently recapitulated by both unsupervised clustering of Cox coefficients (a measure of association with survival) for individual genes, and for gene programs. This analysis has revealed unappreciated commonalities among cancers which may provide insights into cancer pathogenesis and rationales for co-opting treatments between cancers.

Fetal Anemia and Hydrops Fetalis Associated with Homozygous Hb Constant Spring (HBA2: c.427T > C)

Hb Constant Spring (Hb CS, HBA2: c.427T > C) is a common nondeletional α-thalassemia (α-thal) that results from a nucleotide substitution at the termination codon of the α2-globin gene. Homozygosity for Hb CS (α(CS)α/α(CS)α) is relatively rare, and generally characterized with mild hemolytic anemia, jaundice, and splenomegaly. In this report we present a fetus with cardiomegaly, pericardial effusion, enlarged placenta and increased middle cerebral artery-peak systolic velocity (MCA-PSV) at 24 weeks' gestation. Fetal blood sampling revealed the severe anemia [hemoglobin (Hb) level being 4.8 g/dL] and Hb H (β4) disease-like hematological findings with Hb Bart's (γ4) level of 17.9%. DNA sequencing of the α-globin genes found that both partners were Hb CS carriers and the fetus was an Hb CS homozygote. Therefore, this was a rare case of homozygous Hb CS which demonstrated an unusual and serious anemia and hydrops fetalis in utero.

β-Thalassemia Haplotypes in Romania in the Context of Genetic Mixing in the Mediterranean Area

The purpose of this meta-study was to investigate β-thalassemia (β-thal) mutations and their chromosomal background in order to highlight the origin and spread of thalassemia alleles in the European and Mediterranean areas. Screening of more than 100 new Romanian β-thal alleles was also conducted. The results suggest an ancient introduction of mutations at codon 39 (C > T) (HBB: c.118C > T) and IVS-I-6 (T > C) (HBB: c.92 + 6T > C) in Romania. A comparative study was performed based on restriction fragment length polymorphism (RFLP) haplotypes associated with β-thal mutations in Romania and in Mediterranean countries. Each common β-thal allele from different populations exhibits a high degree of haplotype similarity, a sign of a clear unicentric origin for the IVS-I-110 (G > A) (HBB: c.93-21G > A), IVS-I-6, IVS-II-745 (C > G) (HBB: c.316-106C > G) and codon 39 mutations (the 17a [+ - - - - + +], 13c [ - + + - - - +], 17c [ + - - - - - +] and 14a [- + + - + + + ] ancestral RFLP background, respectively), followed by recurrent recombination events. This study also showed that geographic distances played a major role in shaping the spread of the predominant β-thal alleles, whereas no genetic boundaries were detected between broad groups of populations living in the Middle East, Europe and North Africa. The analyses revealed some discrepancies concerning Morocco and Serbia, which suggest some peculiar genetic flows. Marked variations in β(A) were observed between Southeast Asia and the Mediterranean, whereas a relative genetic homogeneity was found around the Mediterranean Basin. This homogeneity is undoubtedly the result of the high level of specific historic human migrations that occurred in this area.

Calling genotypes from public RNA-sequencing data enables identification of genetic variants that affect gene-expression levels

Background

RNA-sequencing (RNA-seq) is a powerful technique for the identification of genetic variants that affect gene-expression levels, either through expression quantitative trait locus (eQTL) mapping or through allele-specific expression (ASE) analysis. Given increasing numbers of RNA-seq samples in the public domain, we here studied to what extent eQTLs and ASE effects can be identified when using public RNA-seq data while deriving the genotypes from the RNA-sequencing reads themselves.

Methods

We downloaded the raw reads for all available human RNA-seq datasets. Using these reads we performed gene expression quantification. All samples were jointly normalized and subjected to a strict quality control. We also derived genotypes using the RNA-seq reads and used imputation to infer non-coding variants. This allowed us to perform eQTL mapping and ASE analyses jointly on all samples that passed quality control. Our results were validated using samples for which DNA-seq genotypes were available.

Results

4,978 public human RNA-seq runs, representing many different tissues and cell-types, passed quality control. Even though these data originated from many different laboratories, samples reflecting the same cell type clustered together, suggesting that technical biases due to different sequencing protocols are limited. In a joint analysis on the 1,262 samples with high quality genotypes, we identified cis-eQTLs effects for 8,034 unique genes (at a false discovery rate ≤0.05). eQTL mapping on individual tissues revealed that a limited number of samples already suffice to identify tissue-specific eQTLs for known disease-associated genetic variants. Additionally, we observed strong ASE effects for 34 rare pathogenic variants, corroborating previously observed effects on the corresponding protein levels.

Conclusions

By deriving and imputing genotypes from RNA-seq data, it is possible to identify both eQTLs and ASE effects. Given the exponential growth of the number of publicly available RNA-seq samples, we expect this approach will become especially relevant for studying the effects of tissue-specific and rare pathogenic genetic variants to aid clinical interpretation of exome and genome sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0152-4) contains supplementary material, which is available to authorized users.

GenInfoGuard--a robust and distortion-free watermarking technique for genetic data

Genetic data, in digital format, is used in different biological phenomena such as DNA translation, mRNA transcription and protein synthesis. The accuracy of these biological phenomena depend on genetic codes and all subsequent processes. To computerize the biological procedures, different domain experts are provided with the authorized access of the genetic codes; as a consequence, the ownership protection of such data is inevitable. For this purpose, watermarks serve as the proof of ownership of data. While protecting data, embedded hidden messages (watermarks) influence the genetic data; therefore, the accurate execution of the relevant processes and the overall result becomes questionable. Most of the DNA based watermarking techniques modify the genetic data and are therefore vulnerable to information loss. Distortion-free techniques make sure that no modifications occur during watermarking; however, they are fragile to malicious attacks and therefore cannot be used for ownership protection (particularly, in presence of a threat model). Therefore, there is a need for a technique that must be robust and should also prevent unwanted modifications. In this spirit, a watermarking technique with aforementioned characteristics has been proposed in this paper. The proposed technique makes sure that: (i) the ownership rights are protected by means of a robust watermark; and (ii) the integrity of genetic data is preserved. The proposed technique—GenInfoGuard—ensures its robustness through the “watermark encoding” in permuted values, and exhibits high decoding accuracy against various malicious attacks.

DruGeVar: an online resource triangulating drugs with genes and genomic biomarkers for clinical pharmacogenomics

BACKGROUND/AIMS

Pharmacogenomics aims to rationalize drug use by minimizing drug toxicity and/or by increasing drug efficacy. A large number of genomic markers have been correlated with variable drug responses and severity of adverse drug reactions. Although a number of these drugs bear pharmacogenomic information in their labels--approved by regulatory agencies--and comprehensive drug/gene lists exist online, information related to the respective pharmacogenomic biomarkers is currently missing from such lists.

METHODS

We extracted information from the published literature and online resources and developed DruGeVar (http://drugevar.genomicmedicinealliance.org), an online resource triangulating drugs with genes and pharmacogenomic biomarkers in an effort to build a comprehensive database that could serve clinical pharmacogenomics.

RESULTS AND CONCLUSIONS

A user-friendly data querying and visualization interface allows users to formulate simple and complex queries. Such a database would be readily applicable as a stand-alone resource or a plug-in module for other databases.

Bridging genomics research between developed and developing countries: the Genomic Medicine Alliance

The Genomic Medicine Alliance is a global academic research network that aims to establish and strengthen collaborative ties between the various genomic medicine stakeholders. Its focus lies on the translation of scientific research findings into clinical practice. It brings together experts from disciplines including genome informatics, pharmacogenomics, public health genomics, ethics in genomics and health economics, and it is supervised by a 14-member International Scientific Advisory Committee comprising internationally renowned scientists. The Alliance's official journal, Public Health Genomics, offers members a highly respected publication forum for their original research findings. In the short-to-medium term, the Genomic Medicine Alliance hopes to harmonize research activities between developed and developing countries and to organize educational activities in the field of genomic medicine.

Genomics into Healthcare: the 5th Pan Arab Human Genetics Conference and 2013 Golden Helix Symposium

The joint 5th Pan Arab Human Genetics conference and 2013 Golden Helix Symposium, "Genomics into Healthcare" was coorganized by the Center for Arab Genomic Studies (http://www.cags.org.ae) in collaboration with the Golden Helix Foundation (http://www.goldenhelix.org) in Dubai, United Arab Emirates from 17 to 19 November, 2013. The meeting was attended by over 900 participants, doctors and biomedical students from over 50 countries and was organized into a series of nine themed sessions that covered cancer genomics and epigenetics, genomic and epigenetic studies, genomics of blood and metabolic disorders, cytogenetic diagnosis and molecular profiling, next-generation sequencing, consanguinity and hereditary diseases, clinical genomics, clinical applications of pharmacogenomics, and genomics in public health.