Impact of the 1000 genomes project on the next wave of pharmacogenomic discovery

Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes

More than 1100 genetic loci have been correlated with drug response outcomes but disproportionately few have been translated into clinical practice. One explanation for the low rate of clinical implementation is that the majority of associated variants may be in linkage disequilibrium (LD) with the causal variants, which are often elusive. This study aims to identify and characterize likely causal variants within well-established pharmacogenomic genes using next-generation sequencing data from the 1000 Genomes Project. We identified 69,319 genetic variations within 160 pharmacogenomic genes, of which 8207 variants are in strong LD (r2>0.8) with known pharmacogenomic variants. Of the latter, eight are coding or structural variants predicted to have high impact, with 19 additional missense variants that are predicted to have moderate impact. In conclusion, we identified putatively functional variants within known pharmacogenomics loci that could account for the association signals and represent the missing causative variants underlying drug response phenotypes.

Characterization of drought stress-responsive root transcriptome of faba bean (Vicia faba L.) using RNA sequencing

Drought and salinity are the major factors that limit the faba bean (Vicia faba L.) production worldwide. The aim of this study is to identify the water stress differentially expressed genes (DEGs) through the root transcriptome analyses of the drought-tolerant Hassawi 2 genotype at vegetative and flowering stages. A total of 624.8 M high-quality Illumina reads were generated and assembled into 198,155 all-unigenes with a mean length of 738 bp and an N50 length of 1347 bp. Among all-unigenes, 78,262 were assigned to non-redundant (Nr), 66,254 to nucleotide (Nt), 54,034 to KEGG, and 43,913 to gene ontology (GO) annotations. A total of 36,834 and 35,510 unigenes were differentially expressed at the vegetative and flowering stages of Hassawi 2 under drought stress, respectively. The majority of unigenes were down-regulated at both developmental stages. However, the number of genes up-regulated (15,366) at the flowering stage exceeded the number of those up-regulated (14,097) at the vegetative stage, and the number of genes down-regulated (20,144) at the flowering stage was smaller than the number of those down-regulated (22,737) at the vegetative stage. The drought stress-responsive differentially expressed unigenes coded for various regulatory proteins, including protein kinases and phosphatases, transcription factors and plant hormones and functional proteins including enzymes for osmoprotectant, detoxification and transporters were differentially expressed, most of which were largely up-regulated. Moreover, a substantial proportion of the DEGs identified in this study were novel, most exhibited a significant change in their expression levels under water stress, making them an unexploited resource that might control specific responses to drought stress in the faba bean. Finally, qRT-PCR results were found almost consistent with the results of next-generation sequencing. Our data will help in understanding the drought tolerance mechanisms in plants and will provide resources for functional genomics.

A 1000 Arab genome project to study the Emirati population

Discoveries from the human genome, HapMap, and 1000 genome projects have collectively contributed toward the creation of a catalog of human genetic variations that has improved our understanding of human diversity. Despite the collegial nature of many of these genome study consortiums, which has led to the cataloging of genetic variations of different ethnic groups from around the world, genome data on the Arab population remains overwhelmingly underrepresented. The National Arab Genome project in the United Arab Emirates (UAE) aims to address this deficiency by using Next Generation Sequencing (NGS) technology to provide data to improve our understanding of the Arab genome and catalog variants that are unique to the Arab population of the UAE. The project was conceived to shed light on the similarities and differences between the Arab genome and those of the other ethnic groups.

Using Galaxy for Proteomics

The area of informatics for mass spectrometry (MS)-based proteomics data has steadily grown over the last two decades. Numerous, effective software programs now exist for various aspects of proteomic informatics. However, many researchers still have difficulties in using these software. These difficulties arise from problems with running and integrating disparate software programs, scalability issues when dealing with large data volumes, and lack of ability to share and reproduce workflows comprised of different software. The Galaxy framework for bioinformatics provides an attractive option for solving many of these current issues in proteomic informatics. Originally developed as a workbench to enable genomic data analysis, numerous researchers are now turning to Galaxy to implement software for MS-based proteomics applications. Here, we provide an introduction to Galaxy and its features, and describe how software tools are deployed, published and shared via the scalable framework. We also describe some of the existing tools in Galaxy for basic MS-based proteomics data analysis and informatics. Finally, we describe how proteomics tools in Galaxy can be combined with other existing tools for genomic and transcriptomic data analysis to enable powerful multi-omic data analysis applications.

Discovery and functional assessment of gene variants in the vascular endothelial growth factor pathway

Angiogenesis is a host-mediated mechanism in disease pathophysiology. The vascular endothelial growth factor (VEGF) pathway is a major determinant of angiogenesis, and a comprehensive annotation of the functional variation in this pathway is essential to understand the genetic basis of angiogenesis-related diseases. We assessed the allelic heterogeneity of gene expression, population specificity of cis expression quantitative trait loci (eQTLs), and eQTL function in luciferase assays in CEU and Yoruba people of Ibadan, Nigeria (YRI) HapMap lymphoblastoid cell lines in 23 resequenced genes. Among 356 cis-eQTLs, 155 and 174 were unique to CEU and YRI, respectively, and 27 were shared between CEU and YRI. Two cis-eQTLs provided mechanistic evidence for two genome-wide association study findings. Five eQTLs were tested for function in luciferase assays and the effect of two KRAS variants was concordant with the eQTL effect. Two eQTLs found in each of PRKCE, PIK3C2A, and MAP2K6 could predict 44%, 37%, and 45% of the variance in gene expression, respectively. This is the first analysis focusing on the pattern of functional genetic variation of the VEGF pathway genes in CEU and YRI populations and providing mechanistic evidence for genetic association studies of diseases for which angiogenesis plays a pathophysiologic role.

Large-scale genotyping identifies a new locus at 22q13.2 associated with female breast size

BACKGROUND

Individual differences in breast size are a conspicuous feature of variation in human females and have been associated with fecundity and advantage in selection of mates. To identify common variants that are associated with breast size, we conducted a large-scale genotyping association meta-analysis in 7169 women of European descent across three independent sample collections with digital or screen film mammograms.

METHODS

The samples consisted of the Swedish KARMA, LIBRO-1 and SASBAC studies genotyped on iCOGS, a custom illumina iSelect genotyping array comprising of 211 155 single nucleotide polymorphisms (SNPs) designed for replication and fine mapping of common and rare variants with relevance to breast, ovary and prostate cancer. Breast size of each subject was ascertained by measuring total breast area (mm(2)) on a mammogram.

RESULTS

We confirm genome-wide significant associations at 8p11.23 (rs10086016, p=1.3×10(-14)) and report a new locus at 22q13 (rs5995871, p=3.2×10(-8)). The latter region contains the MKL1 gene, which has been shown to impact endogenous oestrogen receptor α transcriptional activity and is recruited on oestradiol sensitive genes. We also replicated previous genome-wide association study findings for breast size at four other loci.

CONCLUSIONS

A new locus at 22q13 may be associated with female breast size.

A guide to the current Web-based resources in pharmacogenomics

Human genomics research has produced vast amounts of data that can be applied to or used to inform pharmacogenomic studies. The Internet is an extremely useful resource for pharmacogenomics as many Web sites provide access to data from genomic and clinical studies or host tools which can be used to interpret findings or generate hypotheses. Human genetic variation can now easily be explored or visualized through genome browsers and Web-based repositories which store the details of millions of human germ-line and somatic genetic variants. Gene expression data from many different tissue and cell types are available through Web-based repositories, and human genetic variants that associate with mRNA expression can be identified using Web data portals. Pharmacogenetic associations can be explored through publically available data repositories and the functionality of genetic variants predicted through Web-based bioinformatic tools. Furthermore, resources relating to currently used genetic tests are available online. Large clinical and population studies, many linked to medical records, can be queried for the availability of biospecimens or data. In the future, as the amount of genomic and associated clinical data increases, there is little doubt that Web-based resources will continue to evolve and overcome barriers hindering their efficient use, leading to systems-based approaches to pharmacogenomics.

Cancer pharmacogenomics: strategies and challenges

Genetic variation influences the response of an individual to drug treatments. Understanding this variation has the potential to make therapy safer and more effective by determining selection and dosing of drugs for an individual patient. In the context of cancer, tumours may have specific disease-defining mutations, but a patient's germline genetic variation will also affect drug response (both efficacy and toxicity), and here we focus on how to study this variation. Advances in sequencing technologies, statistical genetics analysis methods and clinical trial designs have shown promise for the discovery of variants associated with drug response. We discuss the application of germline genetics analysis methods to cancer pharmacogenomics with a focus on the special considerations for study design.

Next-generation sequencing and large genome assemblies

The next-generation sequencing (NGS) revolution has drastically reduced time and cost requirements for sequencing of large genomes, and also qualitatively changed the problem of assembly. This article reviews the state of the art in de novo genome assembly, paying particular attention to mammalian-sized genomes. The strengths and weaknesses of the main sequencing platforms are highlighted, leading to a discussion of assembly and the new challenges associated with NGS data. Current approaches to assembly are outlined and the various software packages available are introduced and compared. The question of whether quality assemblies can be produced using short-read NGS data alone, or whether it must be combined with more expensive sequencing techniques, is considered. Prospects for future assemblers and tests of assembly performance are also discussed.

Nutrigenomics and personalized diets: What will they mean for food?

The modern food system feeds six billion people with remarkable diversity, safety, and nutrition. Yet, the current rise in diet-related diseases is compromising health and devaluing many aspects of modern agriculture. Steps to increase the nutritional quality of individual foods will assist in personalizing health and in guiding individuals to achieve superior health. Nutrigenomics is the scientific field of the genetic basis for varying susceptibilities to disease and the diverse responses to foods. Although some of these genetic determinants will be simple and amenable to personal genotyping as the means to predict health, in practice most will not. As a result, genotyping will not be the secret to personalizing diet and health. Human assessment technologies from imaging to proteomics and metabolomics are providing tools to both understand and accurately assess the nutritional phenotype of individuals. The business models are also emerging to bring these assessment capabilities to industrial practice, in which consumers will know more about their personal health and seek personal solutions.

Sequencing by ligation variation with endonuclease V digestion and deoxyinosine-containing query oligonucleotides

Background

Sequencing-by-ligation (SBL) is one of several next-generation sequencing methods that has been developed for massive sequencing of DNA immobilized on arrayed beads (or other clonal amplicons). SBL has the advantage of being easy to implement and accessible to all because it can be performed with off-the-shelf reagents. However, SBL has the limitation of very short read lengths.

Results

To overcome the read length limitation, research groups have developed complex library preparation processes, which can be time-consuming, difficult, and result in low complexity libraries. Herein we describe a variation on traditional SBL protocols that extends the number of sequential bases that can be sequenced by using Endonuclease V to nick a query primer, thus leaving a ligatable end extended into the unknown sequence for further SBL cycles. To demonstrate the protocol, we constructed a known DNA sequence and utilized our SBL variation, cyclic SBL (cSBL), to resequence this region. Using our method, we were able to read thirteen contiguous bases in the 3' - 5' direction.

Conclusions

Combining this read length with sequencing in the 5' - 3' direction would allow a read length of over twenty bases on a single tage. Implementing mate-paired tags and this SBL variation could enable > 95% coverage of the genome.

A variant in MCF2L is associated with osteoarthritis

Osteoarthritis (OA) is a prevalent, heritable degenerative joint disease with a substantial public health impact. We used a 1000-Genomes-Project-based imputation in a genome-wide association scan for osteoarthritis (3177 OA cases and 4894 controls) to detect a previously unidentified risk locus. We discovered a small disease-associated set of variants on chromosome 13. Through large-scale replication, we establish a robust association with SNPs in MCF2L (rs11842874, combined odds ratio [95% confidence interval] 1.17 [1.11-1.23], p = 2.1 × 10(-8)) across a total of 19,041 OA cases and 24,504 controls of European descent. This risk locus represents the third established signal for OA overall. MCF2L regulates a nerve growth factor (NGF), and treatment with a humanized monoclonal antibody against NGF is associated with reduction in pain and improvement in function for knee OA patients.

Pharmacogenomic technologies: a necessary "luxury" for better global public health?

BACKGROUND

Pharmacogenomic technologies aim to redirect drug development to increase safety and efficacy of individual care. There is much hope that their implementation in the drug development process will help respond to population health needs, particularly in developing countries. However, there is also fear that novel pharmacogenomic drugs will remain too costly, be designed for the needs of the wealthy nations, and so constitute an unnecessary "luxury" for most populations. In this paper, we analyse the promise that pharmacogenomic technologies hold for improving global public health and identify strategies and challenges associated with their implementation.

DISCUSSION

This paper evaluates the capacity of pharmacogenomic technologies to meet six criteria described by the University of Toronto Joint Centre for Bioethics group: 1) impact of the technology, 2) technology appropriateness, 3) capacity to address local burdens, 4) feasibility to be implemented in reasonable time, 5) capacity to reduce the knowledge gap, and 6) capacity for indirect benefits. We argue that the implementation of pharmacogenomic technologies in the drug development process can positively impact population health. However, this positive impact depends on how and for which purposes the technologies are used. We discuss the potential of these technologies to stimulate drug discovery in the case of rare (orphan diseases) or neglected diseases, but also to reduce acute adverse drug reactions in infectious disease treatment and prevention, which promises to improve global public health.

CONCLUSIONS

The implementation of pharmacogenomic technologies may lead to the development of drugs that appear to be a "luxury" for populations in need of numerous interventions that are known to have a demonstrable impact on population health (e.g., secure access to potable water, reduction of social inequities, health education). However, our analysis shows that pharmacogenomic technologies do have the potential to redirect drug development and distribution so as to improve the health of vulnerable populations. Strategies should thus be developed to better direct their implementation towards meeting the needs and responding to the realities of populations of the developing world (i.e., social, cultural and political acceptability, and local health burdens), making pharmacogenomic technologies a necessary "luxury" for global public health.

Improving oncology outcomes through targeted therapeutics will require electronic delivery systems

Typically, chemotherapy selection takes into account patient demographic data, including disease symptoms, family history, environmental factors and concurrent medications. Although validated and approved genomics tests are available for targeted therapeutics, a major challenge facing healthcare is the ability to process the genomic data in the patient’s context and to return clinically interpretable dosing guidance to the physician in a realistic time frame. Delivery of these targeted therapeutics, made possible by clinical decision support systems connected to an electronic health record may help drive both the acceptance and adaptation of an electronic health record system, as well as provide personalized information at point-of-care, as part of the routine workflow. The realization of targeted therapeutics will depend on the concerted efforts of stakeholder groups as they address political, ethical, socioeconomical and technical challenges to achieve personalized medicine adoption through real-world implementation.

The impact of next-generation sequencing on genomics

This article reviews basic concepts, general applications, and the potential impact of next-generation sequencing (NGS) technologies on genomics, with particular reference to currently available and possible future platforms and bioinformatics. NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed, thereby enabling previously unimaginable scientific achievements and novel biological applications. But, the massive data produced by NGS also presents a significant challenge for data storage, analyses, and management solutions. Advanced bioinformatic tools are essential for the successful application of NGS technology. As evidenced throughout this review, NGS technologies will have a striking impact on genomic research and the entire biological field. With its ability to tackle the unsolved challenges unconquered by previous genomic technologies, NGS is likely to unravel the complexity of the human genome in terms of genetic variations, some of which may be confined to susceptible loci for some common human conditions. The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.

Population differences in the rate of proliferation of international HapMap cell lines

The International HapMap Project is a resource for researchers containing genotype, sequencing, and expression information for EBV-transformed lymphoblastoid cell lines derived from populations across the world. The expansion of the HapMap beyond the four initial populations of Phase 2, referred to as Phase 3, has increased the sample number and ethnic diversity available for investigation. However, differences in the rate of cellular proliferation between the populations can serve as confounders in phenotype-genotype studies using these cell lines. Within the Phase 2 populations, the JPT and CHB cell lines grow faster (p < 0.0001) than the CEU or YRI cell lines. Phase 3 YRI cell lines grow significantly slower than Phase 2 YRI lines (p < 0.0001), with no widespread genetic differences based on common SNPs. In addition, we found significant growth differences between the cell lines in the Phase 2 ASN populations and the Han Chinese from the Denver metropolitan area panel in Phase 3 (p < 0.0001). Therefore, studies that separate HapMap panels into discovery and replication sets must take this into consideration.

SAHG, a comprehensive database of predicted structures of all human proteins

Most proteins from higher organisms are known to be multi-domain proteins and contain substantial numbers of intrinsically disordered (ID) regions. To analyse such protein sequences, those from human for instance, we developed a special protein-structure-prediction pipeline and accumulated the products in the Structure Atlas of Human Genome (SAHG) database at http://bird.cbrc.jp/sahg. With the pipeline, human proteins were examined by local alignment methods (BLAST, PSI-BLAST and Smith–Waterman profile–profile alignment), global–local alignment methods (FORTE) and prediction tools for ID regions (POODLE-S) and homology modeling (MODELLER). Conformational changes of protein models upon ligand-binding were predicted by simultaneous modeling using templates of apo and holo forms. When there were no suitable templates for holo forms and the apo models were accurate, we prepared holo models using prediction methods for ligand-binding (eF-seek) and conformational change (the elastic network model and the linear response theory). Models are displayed as animated images. As of July 2010, SAHG contains 42 581 protein-domain models in approximately 24 900 unique human protein sequences from the RefSeq database. Annotation of models with functional information and links to other databases such as EzCatDB, InterPro or HPRD are also provided to facilitate understanding the protein structure-function relationships.

Opal web services for biomedical applications

Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal’s programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239 814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net.

Comprehensive survey of SNPs in the Affymetrix exon array using the 1000 Genomes dataset

Microarray gene expression data has been used in genome-wide association studies to allow researchers to study gene regulation as well as other complex phenotypes including disease risks and drug response. To reach scientifically sound conclusions from these studies, however, it is necessary to get reliable summarization of gene expression intensities. Among various factors that could affect expression profiling using a microarray platform, single nucleotide polymorphisms (SNPs) in target mRNA may lead to reduced signal intensity measurements and result in spurious results. The recently released 1000 Genomes Project dataset provides an opportunity to evaluate the distribution of both known and novel SNPs in the International HapMap Project lymphoblastoid cell lines (LCLs). We mapped the 1000 Genomes Project genotypic data to the Affymetrix GeneChip Human Exon 1.0ST array (exon array), which had been used in our previous studies and for which gene expression data had been made publicly available. We also evaluated the potential impact of these SNPs on the differentially spliced probesets we had identified previously. Though the 1000 Genomes Project data allowed a comprehensive survey of the SNPs in this particular array, the same approach can certainly be applied to other microarray platforms. Furthermore, we present a detailed catalogue of SNP-containing probesets (exon-level) and transcript clusters (gene-level), which can be considered in evaluating findings using the exon array as well as benefit the design of follow-up experiments and data re-analysis.