Dataset Information

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

ABSTRACT: One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research.

SUBMITTER: Wang J

PROVIDER: S-EPMC5670038 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

Wang Julia J Al-Ouran Rami R Hu Yanhui Y Kim Seon-Young SY Wan Ying-Wooi YW Wangler Michael F MF Yamamoto Shinya S Chao Hsiao-Tuan HT Comjean Aram A Mohr Stephanie E SE Perrimon Norbert N Liu Zhandong Z Bellen Hugo J HJ

American journal of human genetics 20170511 6

One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid ...[more]

PMID: 28502612

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Project description:BackgroundIdentifying the biologic functions of groups of genes identified in high-throughput studies currently requires considerable time and/or bioinformatics experience. This is due in part to each resource housed within separate databases, requiring users to know about them, and integrate across them. Time consuming and often repeated for each study, integrating across resources and merging with data under study is an increasingly common bioinformatics task.MethodsWe developed an open-source R software package for assisting researchers in annotating their genesets with functions, pathways, and their interconnectivity across a diversity of network resources.ResultsWe present rapid integration of term annotation and network resources (RITAN) for the rapid and comprehensive annotation of a list of genes using functional term and pathway resources and their relationships among each other using multiple network biology resources. Currently, and to comply with data redistribution policies, RITAN allows rapid access to 16 term annotations spanning gene ontology, biologic pathways, and immunologic modules, and nine network biology resources, with support for user-supplied resources; we provide recommendations for additional resources and scripts to facilitate their addition to RITAN. Having the resources together in the same system allows users to derive novel combinations. RITAN has a growing set of tools to explore the relationships within resources themselves. These tools allow users to merge resources together such that the merged annotations have a minimal overlap with one another. Because we index both function annotation and network interactions, the combination allows users to expand small groups of genes using links from biologic networks-either by adding all neighboring genes or by identifying genes that efficiently connect among input genes-followed by term enrichment to identify functions. That is, users can start from a core set of genes, identify interacting genes from biologic networks, and then identify the functions to which the expanded list of genes contribute.ConclusionWe believe RITAN fills the important niche of bridging the results of high-throughput experiments with the ever-growing corpus of functional annotations and network biology resources.AvailabilityRapid integration of term annotation and network resources is available as an R package at github.com/MTZimmer/RITAN and BioConductor.org.

Project description:In order to generate an atlas of the functional elements driving genome expression in domestic animals, the Functional Annotation of Animal Genome (FAANG) strategy was to sample many tissues from a few animals of different species, sexes, ages, and production stages. This article presents the collection of tissue samples for four species produced by two pilot projects, at INRAE (National Research Institute for Agriculture, Food and Environment) and the University of California, Davis. There were three mammals (cattle, goat, and pig) and one bird (chicken). It describes the metadata characterizing these reference sets (1) for animals with origin and selection history, physiological status, and environmental conditions; (2) for samples with collection site and tissue/cell processing; (3) for quality control; and (4) for storage and further distribution. Three sets are identified: set 1 comprises tissues for which collection can be standardized and for which representative aliquots can be easily distributed (liver, spleen, lung, heart, fat depot, skin, muscle, and peripheral blood mononuclear cells); set 2 comprises tissues requiring special protocols because of their cellular heterogeneity (brain, digestive tract, secretory organs, gonads and gametes, reproductive tract, immune tissues, cartilage); set 3 comprises specific cell preparations (immune cells, tracheal epithelial cells). Dedicated sampling protocols were established and uploaded in https://data.faang.org/protocol/samples. Specificities between mammals and chicken are described when relevant. A total of 73 different tissues or tissue sections were collected, and 21 are common to the four species. Having a common set of tissues will facilitate the transfer of knowledge within and between species and will contribute to decrease animal experimentation. Combining data on the same samples will facilitate data integration. Quality control was performed on some tissues with RNA extraction and RNA quality control. More than 5,000 samples have been stored with unique identifiers, and more than 4,000 were uploaded onto the Biosamples database, provided that standard ontologies were available to describe the sample. Many tissues have already been used to implement FAANG assays, with published results. All samples are available without restriction for further assays. The requesting procedure is described. Members of FAANG are encouraged to apply a range of molecular assays to characterize the functional status of collected samples and share their results, in line with the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles.

Dataset Information

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

Publications

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

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