Beyond the HapMap Genotypic Data: Prospects of Deep Resequencing Projects

Nutriepigenomics in Environmental-Associated Oxidative Stress

Complex molecular mechanisms define our responses to environmental stimuli. Beyond the DNA sequence itself, epigenetic machinery orchestrates changes in gene expression induced by diet, physical activity, stress and pollution, among others. Importantly, nutrition has a strong impact on epigenetic players and, consequently, sustains a promising role in the regulation of cellular responses such as oxidative stress. As oxidative stress is a natural physiological process where the presence of reactive oxygen-derived species and nitrogen-derived species overcomes the uptake strategy of antioxidant defenses, it plays an essential role in epigenetic changes induced by environmental pollutants and culminates in signaling the disruption of redox control. In this review, we present an update on epigenetic mechanisms induced by environmental factors that lead to oxidative stress and potentially to pathogenesis and disease progression in humans. In addition, we introduce the microenvironment factors (physical contacts, nutrients, extracellular vesicle-mediated communication) that influence the epigenetic regulation of cellular responses. Understanding the mechanisms by which nutrients influence the epigenome, and thus global transcription, is crucial for future early diagnostic and therapeutic efforts in the field of environmental medicine.

Non-coding RNAs and nuclear architecture during epithelial-mesenchymal transition in lung cancer and idiopathic pulmonary fibrosis

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. On the other hand, idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease showing a prevalence of 20 new cases per 100,000 persons per year. Despite differences in cellular origin and pathological phenotypes, LC and IPF are lung diseases that share common features, including hyperproliferation of specific cell types in the lung, involvement of epithelial-mesenchymal transition (EMT) and enhanced activity of signaling pathways, such as tissue growth factor (TGFB), epidermal growth factor (EGF), fibroblast growth factor (FGF), wingless secreted glycoprotein (WNT) signaling, among others. EMT is a process during which epithelial cells lose their cell polarity and cell-cell adhesion, and acquire migratory and invasive properties to become mesenchymal cells. EMT involves numerous morphological hallmarks of hyperproliferative diseases, like cell plasticity, resistance to apoptosis, dedifferentiation and proliferation, thereby playing a central role during organ fibrosis and cancer progression. EMT was considered as an "all-or-none" process. In contrast to these outdated dichotomist interpretations, recent reports suggest that EMT occurs gradually involving different epithelial cell intermediate states with mesenchyme-like characteristics. These cell intermediate states of EMT differ from each other in their cell plasticity, invasiveness and metastatic potential, which in turn are induced by signals from their microenvironment. EMT is regulated by several transcription factors (TFs), which are members of prominent families of master regulators of transcription. In addition, there is increasing evidence for the important contribution of noncoding RNAs (ncRNAs) to EMT. In our review we highlight articles dissecting the function of different ncRNAs subtypes and nuclear architecture in cell intermediate states of EMT, as well as their involvement in LC and IPF.

Pharmacomicrobiomics: the impact of human microbiome variations on systems pharmacology and personalized therapeutics

The Human Microbiome Project (HMP) is a global initiative undertaken to identify and characterize the collection of human-associated microorganisms at multiple anatomic sites (skin, mouth, nose, colon, vagina), and to determine how intra-individual and inter-individual alterations in the microbiome influence human health, immunity, and different disease states. In this review article, we summarize the key findings and applications of the HMP that may impact pharmacology and personalized therapeutics. We propose a microbiome cloud model, reflecting the temporal and spatial uncertainty of defining an individual's microbiome composition, with examples of how intra-individual variations (such as age and mode of delivery) shape the microbiome structure. Additionally, we discuss how this microbiome cloud concept explains the difficulty to define a core human microbiome and to classify individuals according to their biome types. Detailed examples are presented on microbiome changes related to colorectal cancer, antibiotic administration, and pharmacomicrobiomics, or drug-microbiome interactions, highlighting how an improved understanding of the human microbiome, and alterations thereof, may lead to the development of novel therapeutic agents, the modification of antibiotic policies and implementation, and improved health outcomes. Finally, the prospects of a collaborative computational microbiome research initiative in Africa are discussed.

Marketed marine natural products in the pharmaceutical and cosmeceutical industries: tips for success

The marine environment harbors a number of macro and micro organisms that have developed unique metabolic abilities to ensure their survival in diverse and hostile habitats, resulting in the biosynthesis of an array of secondary metabolites with specific activities. Several of these metabolites are high-value commercial products for the pharmaceutical and cosmeceutical industries. The aim of this review is to outline the paths of marine natural products discovery and development, with a special focus on the compounds that successfully reached the market and particularly looking at the approaches tackled by the pharmaceutical and cosmetic companies that succeeded in marketing those products. The main challenges faced during marine bioactives discovery and development programs were analyzed and grouped in three categories: biodiversity (accessibility to marine resources and efficient screening), supply and technical (sustainable production of the bioactives and knowledge of the mechanism of action) and market (processes, costs, partnerships and marketing). Tips to surpass these challenges are given in order to improve the market entry success rates of highly promising marine bioactives in the current pipelines, highlighting what can be learned from the successful and unsuccessful stories that can be applied to novel and/or ongoing marine natural products discovery and development programs.

SEED servers: high-performance access to the SEED genomes, annotations, and metabolic models

The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Yet, genome annotation, comparison, and modeling remain a major bottleneck to the translation of sequence information into biological knowledge, hence computational analysis tools are continuously being developed for rapid genome annotation and interpretation. Among the earliest, most comprehensive resources for prokaryotic genome analysis, the SEED project, initiated in 2003 as an integration of genomic data and analysis tools, now contains >5,000 complete genomes, a constantly updated set of curated annotations embodied in a large and growing collection of encoded subsystems, a derived set of protein families, and hundreds of genome-scale metabolic models. Until recently, however, maintaining current copies of the SEED code and data at remote locations has been a pressing issue. To allow high-performance remote access to the SEED database, we developed the SEED Servers (http://www.theseed.org/servers): four network-based servers intended to expose the data in the underlying relational database, support basic annotation services, offer programmatic access to the capabilities of the RAST annotation server, and provide access to a growing collection of metabolic models that support flux balance analysis. The SEED servers offer open access to regularly updated data, the ability to annotate prokaryotic genomes, the ability to create metabolic reconstructions and detailed models of metabolism, and access to hundreds of existing metabolic models. This work offers and supports a framework upon which other groups can build independent research efforts. Large integrations of genomic data represent one of the major intellectual resources driving research in biology, and programmatic access to the SEED data will provide significant utility to a broad collection of potential users.

Next-generation sequencing entering the clinical arena

Over the last decade the genetic etiology of many heritable diseases could be resolved. For heart muscle diseases, so called cardiomyopathies, mutations in more than 40 different genes have been identified. Due to this large genetic heterogeneity and missing of adequate gene-diagnostic tools, most patients are not genetically characterized, which would be important for individualized patient care. Currently, next-generation sequencing technologies are revolutionizing genetic and epigenetic research, since they are capable to produce billions of bases of sequence information in a single experiment. Accordingly, this powerful technology can now also open avenues for genetic diagnostics. The scope of this article is to illustrate technical approaches, clinical applications, and yet unsolved problems of next-generation sequencing entering the clinical arena.

Population differences in microRNA expression and biological implications

Population differences observed for complex traits may be attributed to the combined effect of socioeconomic, environmental, genetic and epigenetic factors. To better understand population differences in complex traits, genome-wide genetic and gene expression differences among ethnic populations have been studied. Here we set out to evaluate population differences in small non-coding RNAs through an evaluation of microRNA (miRNA) baseline expression in HapMap lymphoblastoid cell lines (LCLs) derived from 53 CEU (Utah residents with northern and western European ancestry) and 54 YRI (African from Ibadan, Nigeria). Using the Exiqon miRCURYTM LNA arrays, we found that 16% of all miRNAs evaluated in our study differ significantly between these 2 ethnic groups (pBonferroni corrected< 0.05). Furthermore, we explored the potential biological function of these observed differentially expressed miRNAs by comprehensively examining their effect on the transcriptome and their relationship with cellular sensitivity drug phenotypes. After multiple testing adjustment (false discovery rate (FDR)< 0.1), we found that 55% and 88% of the differentially expressed miRNAs were significantly and inversely correlated with an mRNA expression phenotype in the CEU and YRI samples, respectively. Interestingly, a substantial proportion (64%) of these miRNAs correlated with cellular sensitivity to chemotherapeutic agents (FDR< 0.05). Lastly, upon performing a genome-wide association study between SNPs and miRNA expression, we identified a large number of SNPs exhibiting different allele frequencies that affect the expression of these differentially expressed miRNAs, suggesting the role of genetic variants in mediating the observed population differences.

Targeted next-generation sequencing for the molecular genetic diagnostics of cardiomyopathies

BACKGROUND

Today, mutations in more than 30 different genes have been found to cause inherited cardiomyopathies, some associated with very poor prognosis. However, because of the genetic heterogeneity and limitations in throughput and scalability of current diagnostic tools up until now, it is hardly possible to genetically characterize patients with cardiomyopathy in a fast, comprehensive, and cost-efficient manner.

METHODS AND RESULTS

We established an array-based subgenomic enrichment followed by next-generation sequencing to detect mutations in patients with hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM). With this approach, we show that the genomic region of interest can be enriched by a mean factor of 2169 compared with the coverage of the whole genome, resulting in high sequence coverage of selected disease genes and allowing us to define the genetic pathogenesis of cardiomyopathies in a single sequencing run. In 6 patients, we detected disease-causing mutations, 2 microdeletions, and 4 point mutations. Furthermore, we identified several novel nonsynonymous variants, which are predicted to be harmful, and hence, might be potential disease mutations or modifiers for DCM or HCM.

CONCLUSIONS

The approach presented here allows for the first time a comprehensive genetic screening in patients with hereditary DCM or HCM in a fast and cost-efficient manner.

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.

A pharmacogene database enhanced by the 1000 Genomes Project

Human genetic variation is likely to be responsible for a substantial fraction of the variability in complex traits including drug response. Single nucleotide polymorphisms have been implicated in drug response using genome-wide association studies as well as candidate-gene approaches. A more comprehensive catalogue of human genetic variation should complement the current large-scale genotypic dataset from the International HapMap Project, which focuses on common genetic variants. The 1000 Genomes Project is an international research effort that aims to provide the most comprehensive map of human genetic variation using next-generation sequencing platforms. Owing to the lack of convenient tools, however, it is a challenge for the pharmacogenetic research community to take advantage of these data. Here, we present a new database of some pharmacogenes of particular interest to pharmacogenetic researchers. Our database provides a convenient portal for immediate utilization of the newly released 1000 Genomes Project data in pharmacogenetic studies.

SCAN: SNP and copy number annotation

MOTIVATION

Genome-wide association studies (GWAS) generate relationships between hundreds of thousands of single nucleotide polymorphisms (SNPs) and complex phenotypes. The contribution of the traditionally overlooked copy number variations (CNVs) to complex traits is also being actively studied. To facilitate the interpretation of the data and the designing of follow-up experimental validations, we have developed a database that enables the sensible prioritization of these variants by combining several approaches, involving not only publicly available physical and functional annotations but also multilocus linkage disequilibrium (LD) annotations as well as annotations of expression quantitative trait loci (eQTLs).

RESULTS

For each SNP, the SCAN database provides: (i) summary information from eQTL mapping of HapMap SNPs to gene expression (evaluated by the Affymetrix exon array) in the full set of HapMap CEU (Caucasians from UT, USA) and YRI (Yoruba people from Ibadan, Nigeria) samples; (ii) LD information, in the case of a HapMap SNP, including what genes have variation in strong LD (pairwise or multilocus LD) with the variant and how well the SNP is covered by different high-throughput platforms; (iii) summary information available from public databases (e.g. physical and functional annotations); and (iv) summary information from other GWAS. For each gene, SCAN provides annotations on: (i) eQTLs for the gene (both local and distant SNPs) and (ii) the coverage of all variants in the HapMap at that gene on each high-throughput platform. For each genomic region, SCAN provides annotations on: (i) physical and functional annotations of all SNPs, genes and known CNVs within the region and (ii) all genes regulated by the eQTLs within the region.

AVAILABILITY

http://www.scandb.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A survey of the population genetic variation in the human kinome

Protein kinases are key regulators of various biological processes, such as control of cell growth, metabolism, differentiation and apoptosis. Therefore, protein kinases have been an important class of targets for anticancer drugs. Health-related disparities such as differential drug response have been observed between human populations. A survey of the human kinases and their ligand genes for those containing population-specific genetic variants could provide new insights into the mechanisms of these health disparities and suggest novel targets for ethnicity-specific personalized medicine. Using the International HapMap Project genotypic data on single-nucleotide polymorphisms (SNPs), the protein kinase complement of the human genome (kinome) and some experimentally verified ligand genes were scanned for the existence of population-specific SNPs (eSNPs). In general, protein kinases were found to contain a much higher proportion of eSNPs than the whole genome background, indicating a stronger pressure for adaptation in individual populations. In contrast, the proportion of ligand genes containing eSNPs was not different from that of the whole genome background. Although with some important limitations, our results suggest that human kinases are more likely to be under recent positive selection than ligands. Our findings suggest that the health-related disparities associated with kinase signaling pathways are more likely to be driven by the genetic variation in the kinase genes than their cognate ligands. Illustrating the role of molecular evolution in the genetic variation of the human kinome could provide a promising route to understand the ethnic differences in cancer and facilitate the realization of ethnicity-based individualized medicine.

Identification of common genetic variants that account for transcript isoform variation between human populations

In addition to the differences between populations in transcriptional and translational regulation of genes, alternative pre-mRNA splicing (AS) is also likely to play an important role in regulating gene expression and generating variation in mRNA and protein isoforms. Recently, the genetic contribution to transcript isoform variation has been reported in individuals of recent European descent. We report here results of an investigation of the differences in AS patterns between human populations. AS patterns in 176 HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry were evaluated using the Affymetrix GeneChip Human Exon 1.0 ST Array. A variety of biological processes such as response to stimulus and transcription were found to be enriched among the differentially spliced genes. The differentially spliced genes also include some involved in human diseases that have different prevalence or susceptibility between populations. The genetic contribution to the population differences in transcript isoform variation was then evaluated by a genome-wide association using the HapMap genotypic data on single nucleotide polymorphisms (SNPs). The results suggest that local and distant genetic variants account for a substantial fraction of the observed transcript isoform variation between human populations. Our findings provide new insights into the complexity of the human genome as well as the health disparities between the two populations.

Exploring the evolutionary history of the differentially expressed genes between human populations: action of recent positive selection

Though debates exist on the early human evolutionary models such as the “Out of Africa” theory, which hypothesizes that modern humans migrated from Africa to Europe about 50,000 to 100,000 years ago, Africans and Europeans were geographically separated with minimal gene flow for tens of thousands of years. The variations between the current European and African populations, therefore, should have evolved during this timeframe. To gain more insights into the evolutionary history of human phenotypes including gene expression, it is critical to tell how recent positive selection has played a role in the variations observed in the current populations. Using the list of differentially expressed genes we previously identified between the HapMap samples derived from individuals of African (from Ibadan, Nigeria) and European (from Utah, USA) ancestry, we searched for evidence of selection among these differential genes. We found that 27 differentially expressed genes (out of 356 tested) between these two European and African populations have been under recent positive selection. Our findings suggest that the variation between these two populations appears to be affected primarily by neutral genetic drift and/or stabilizing selection and to a lesser degree by positive selection. Further annotation enrichment analyses showed that these 27 genes under selection were overrepresented in certain Gene Ontology biological processes, molecular functions and cellular components such as transcription, lipid binding and lysosome. Our results can provide unique insights into the evolutionary history of the variation in the gene expression phenotype between these two human populations.