MutationDistiller: user-driven identification of pathogenic DNA variants

MutationDistiller is a freely available online tool for user-driven analyses of Whole Exome Sequencing data. It offers a user-friendly interface aimed at clinicians and researchers, who are not necessarily bioinformaticians. MutationDistiller combines Mutation- Taster’s pathogenicity predictions with a phenotypebased approach. Phenotypic information is not limited to symptoms included in the Human Phenotype Ontology (HPO), but may also comprise clinical diagnoses and the suspected mode of inheritance. The search can be restricted to lists of candidate genes (e.g. virtual gene panels) and by tissue-specific gene expression. The inclusion of GeneOntology (GO) and metabolic pathways facilitates the discovery of hitherto unknown disease genes. In a novel approach, we trained MutationDistiller’s HPO-based prioritization on authentic genotype–phenotype sets obtained from ClinVar and found it to match or outcompete current prioritization tools in terms of accuracy. In the output, the program provides a list of potential disease mutations ordered by the likelihood of the affected genes to cause the phenotype. MutationDistiller provides links to gene-related information from various resources. It has been extensively tested by clinicians and their suggestions have been valued in many iterative cycles of revisions. The tool, a comprehensive documentation and examples are freely available at https://www.mutationdistiller.org

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

GEneSTATION 1.0: A Synthetic Resource of Diverse Evolutionary and Functional Genomic Data for Studying The Evolution of Pregnancy-Associated Tissues and Phenotypes

Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy

Trisomy 21 alters DNA methylation in parent-of-origin-dependent and independent manners

The supernumerary chromosome 21 in Down syndrome differentially affects the methylation statuses at CpG dinucleotide sites and creates genome-wide transcriptional dysregulation of parental alleles, ultimately causing diverse pathologies. At present, it is unknown whether those effects are dependent or independent of the parental origin of the nondis-joined chromosome 21. Linkage analysis is a standard method for the determination of the parental origin of this aneuploidy, although it is inadequate in cases with deficiency of samples from the progenitors. Here, we assessed the reliability of the epigenetic 5(m)CpG imprints resulting in the maternally (oocyte)-derived allele methylation at a differentially methylated region (DMR) of the candidate imprinted WRB gene for asserting the parental origin of chromosome 21. We developed a methylation-sensitive restriction enzyme-specific PCR assay, based on the WRB DMR, across single nucleotide polymorphisms (SNPs) to examine the methylation statuses in the parental alleles. In genomic DNA from blood cells of either disomic or trisomic subjects, the maternal alleles were consistently methylated, while the paternal alleles were unmethylated. However, the supernumerary chromosome 21 did alter the methylation patterns at the RUNX1 (chromosome 21) and TMEM131 (chromosome 2) CpG sites in a parent-of-origin-independent manner. To evaluate the 5(m)CpG imprints, we conducted a computational comparative epigenomic analysis of transcriptome RNA sequencing (RNA-Seq) and histone modification expression patterns. We found allele fractions consistent with the transcriptional biallelic expression of WRB and ten neighboring genes, despite the similarities in the confluence of both a 17-histone modification activation backbone module and a 5-histone modification repressive module between the WRB DMR and the DMRs of six imprinted genes. We concluded that the maternally inherited 5(m)CpG imprints at the WRB DMR are uncoupled from the parental allele expression of WRB and ten neighboring genes in several tissues and that trisomy 21 alters DNA methylation in parent-of-origin-dependent and -independent manners

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

2D association and integrative omics analysis in rice provides systems biology view in trait analysis.

The interactions among genes and between genes and environment contribute significantly to the phenotypic variation of complex traits and may be possible explanations for missing heritability. However, to our knowledge no existing tool can address the two kinds of interactions. Here we propose a novel linear mixed model that considers not only the additive effects of biological markers but also the interaction effects of marker pairs. Interaction effect is demonstrated as a 2D association. Based on this linear mixed model, we developed a pipeline, namely PATOWAS. PATOWAS can be used to study transcriptome-wide and metabolome-wide associations in addition to genome-wide associations. Our case analysis with real rice recombinant inbred lines (RILs) at three omics levels demonstrates that 2D association mapping and integrative omics are able to provide a systems biology view into the analyzed traits, leading toward an answer about how genes, transcripts, proteins, and metabolites work together to produce an observable phenotype

Digital Music Notation Data Model and Prototype Delivery System

The U.Va. Library requests $44,164 in outright funds from NEH to collaborate with the University of Paderborn in Detmold, Germany, in conducting two workshops, one to be held in summer 2009 and one in spring 2010, which will promote an international collaboration to create a music notation data model and prototype delivery system. We intend to engage a select group of international scholars and technologists with a broad range of expertise in discussing the features and functions required in a scholarly XML music notation model, critically evaluate the existing data models, discuss optimum solutions for achieving the desired features, and plan for future implementation of the solutions. Our long-term plans include applying for further grant funding to continue to develop this project after this basic collaboration is complete

Support systems to guide clinical decision-making in precision oncology: The Cancer Core Europe Molecular Tumor Board Portal.

To the editor: the optimal management of cancer patients is increasingly dependent on individualized treatments guided by tumor sequencing data. As comprehensive genomic tests become routine in many disease settings and academic centers promote omics-guided clinical trial recruitment, accurate and scalable data interpretation represents a major challenge. The meticulous task of matching tumor alterations with approved or experimental therapies relies heavily on the expertise of each center