Cross species integration of functional genomics experiments

Automated gene data integration with Databio

Objective

Although sequencing and other high-throughput data production technologies are increasingly affordable, data analysis and interpretation remains a significant factor in the cost of -omics studies. Despite the broad acceptance of findable, accessible, interoperable, and reusable (FAIR) data principles which focus on data discoverability and annotation, data integration remains a significant bottleneck in linking prior work in order to better understand novel research. Relevant and timely information discovery is difficult for increasingly multi-disciplinary projects when scientists cannot easily keep up with work across multiple fields. Computational tools are necessary to accurately describe data contents, and empower linkage to existing resources without prior knowledge of the various database resources.

Results

We developed the Databio tool, accessible at https://datab.io/, to automate data parsing, identifier detection, and streamline common tasks to provide a point-and-click approach to data manipulation and integration in life sciences research and translational medicine. Databio uses fast real-time data structures and a data warehouse of 137 million identifiers, with automated heuristics to describe data provenance without highly specialized knowledge or bioinformatics training.

The Genetics of Externalizing Problems

Externalizing problems generally refer to a constellation of behaviors and/or disorders characterized by impulsive action and behavioral disinhibition. Phenotypes on the externalizing spectrum include psychiatric disorders, nonclinical behaviors, and personality characteristics (e.g. alcohol use disorders, other illicit substance use, antisocial behaviors, risky sex, sensation seeking, among others). Research using genetic designs including latent designs from twin and family data and more recent designs using genome-wide data reveal that these behaviors and problems are genetically influenced and largely share a common genetic etiology. Large-scale gene-identification efforts have started to identify robust associations between genetic variants and these phenotypes. However, there is still considerable work to be done. This chapter provides an overview of the current state of research into the genetics of behaviors and disorders on the externalizing spectrum.

Integrative Functional Genomics for Systems Genetics in GeneWeaver.org

The abundance of existing functional genomics studies permits an integrative approach to interpreting and resolving the results of diverse systems genetics studies. However, a major challenge lies in assembling and harmonizing heterogeneous data sets across species for facile comparison to the positional candidate genes and coexpression networks that come from systems genetic studies. GeneWeaver is an online database and suite of tools at www.geneweaver.org that allows for fast aggregation and analysis of gene set-centric data. GeneWeaver contains curated experimental data together with resource-level data such as GO annotations, MP annotations, and KEGG pathways, along with persistent stores of user entered data sets. These can be entered directly into GeneWeaver or transferred from widely used resources such as GeneNetwork.org. Data are analyzed using statistical tools and advanced graph algorithms to discover new relations, prioritize candidate genes, and generate function hypotheses. Here we use GeneWeaver to find genes common to multiple gene sets, prioritize candidate genes from a quantitative trait locus, and characterize a set of differentially expressed genes. Coupling a large multispecies repository curated and empirical functional genomics data to fast computational tools allows for the rapid integrative analysis of heterogeneous data for interpreting and extrapolating systems genetics results.

GeneWeaver: finding consilience in heterogeneous cross-species functional genomics data

A persistent challenge lies in the interpretation of consensus and discord from functional genomics experimentation. Harmonizing and analyzing this data will enable investigators to discover relations of many genes to many diseases, and from many phenotypes and experimental paradigms to many diseases through their genomic substrates. The GeneWeaver.org system provides a platform for cross-species integration and interrogation of heterogeneous curated and experimentally derived functional genomics data. GeneWeaver enables researchers to store, share, analyze, and compare results of their own genome-wide functional genomics experiments in an environment containing rich companion data obtained from major curated repositories, including the Mouse Genome Database and other model organism databases, along with derived data from highly specialized resources, publications, and user submissions. The data, largely consisting of gene sets and putative biological networks, are mapped onto one another through gene identifiers and homology across species. A versatile suite of interactive tools enables investigators to perform a variety of set analysis operations to find consilience among these often noisy experimental results. Fast algorithms enable real-time analysis of large queries. Specific applications include prioritizing candidate genes for quantitative trait loci, identifying biologically valid mouse models and phenotypic assays for human disease, finding the common biological substrates of related diseases, classifying experiments and the biological concepts they represent from empirical data, and applying patterns of genomic evidence to implicate novel genes in disease. These results illustrate an alternative to strict emphasis on replicability, whereby researchers classify experimental results to identify the conditions that lead to their similarity.